From 29b14ee9b629b1a681f7d5d22388e3e7aa38f035 Mon Sep 17 00:00:00 2001 From: Dario Coscia <93731561+dario-coscia@users.noreply.github.com> Date: Wed, 23 Apr 2025 16:19:07 +0200 Subject: [PATCH] Update Tutorials (#544) * update tutorials * tutorial guidelines * doc --- docs/source/_tutorial.rst | 40 +- tutorials/README.md | 43 +- tutorials/TUTORIAL_GUIDELINES.md | 128 ++++ tutorials/static/API_color.png | Bin 0 -> 124005 bytes tutorials/static/deep_ensemble.png | Bin 0 -> 130702 bytes tutorials/static/logging.png | Bin 0 -> 236447 bytes tutorials/static/neural_operator.png | Bin 0 -> 35744 bytes tutorials/static/pina_logo.png | Bin 0 -> 52492 bytes tutorials/static/pina_wokflow.png | Bin 0 -> 452666 bytes tutorials/tutorial1/tutorial.ipynb | 547 ++++++----------- tutorials/tutorial1/tutorial.py | 340 ----------- tutorials/tutorial10/tutorial.ipynb | 151 +++-- tutorials/tutorial10/tutorial.py | 314 ---------- tutorials/tutorial11/logging.png | Bin 208727 -> 0 bytes tutorials/tutorial11/tutorial.ipynb | 493 +++++++--------- tutorials/tutorial11/tutorial.py | 388 ------------ tutorials/tutorial12/tutorial.ipynb | 149 ++--- tutorials/tutorial12/tutorial.py | 188 ------ tutorials/tutorial13/tutorial.ipynb | 199 +++---- tutorials/tutorial13/tutorial.py | 283 --------- tutorials/tutorial14/tutorial.ipynb | 685 +++++++++------------- tutorials/tutorial14/tutorial.py | 338 ----------- tutorials/tutorial15/tutorial.ipynb | 602 +++++++++++++++++++ tutorials/tutorial16/tutorial.ipynb | 574 ++++++++++++++++++ tutorials/tutorial17/tutorial.ipynb | 841 +++++++++++++++++++++++++++ tutorials/tutorial18/tutorial.ipynb | 443 ++++++++++++++ tutorials/tutorial19/tutorial.ipynb | 604 +++++++++++++++++++ tutorials/tutorial2/tutorial.ipynb | 213 ++++--- tutorials/tutorial2/tutorial.py | 360 ------------ tutorials/tutorial20/tutorial.ipynb | 463 +++++++++++++++ tutorials/tutorial21/tutorial.ipynb | 459 +++++++++++++++ tutorials/tutorial3/tutorial.ipynb | 153 +++-- tutorials/tutorial3/tutorial.py | 336 ----------- tutorials/tutorial4/tutorial.ipynb | 367 +++++------- tutorials/tutorial4/tutorial.py | 676 --------------------- tutorials/tutorial5/tutorial.ipynb | 132 +++-- tutorials/tutorial5/tutorial.py | 209 ------- tutorials/tutorial6/tutorial.ipynb | 117 ++-- tutorials/tutorial6/tutorial.py | 293 ---------- tutorials/tutorial7/tutorial.ipynb | 163 +++--- tutorials/tutorial7/tutorial.py | 255 -------- tutorials/tutorial8/tutorial.ipynb | 685 ++++++++++++++++++---- tutorials/tutorial8/tutorial.py | 315 ---------- tutorials/tutorial9/tutorial.ipynb | 213 ++++--- tutorials/tutorial9/tutorial.py | 246 -------- 45 files changed, 6279 insertions(+), 6726 deletions(-) create mode 100644 tutorials/TUTORIAL_GUIDELINES.md create mode 100644 tutorials/static/API_color.png create mode 100644 tutorials/static/deep_ensemble.png create mode 100644 tutorials/static/logging.png create mode 100644 tutorials/static/neural_operator.png create mode 100644 tutorials/static/pina_logo.png create mode 100644 tutorials/static/pina_wokflow.png delete mode 100644 tutorials/tutorial1/tutorial.py delete mode 100644 tutorials/tutorial10/tutorial.py delete mode 100644 tutorials/tutorial11/logging.png delete mode 100644 tutorials/tutorial11/tutorial.py delete mode 100644 tutorials/tutorial12/tutorial.py delete mode 100644 tutorials/tutorial13/tutorial.py delete mode 100644 tutorials/tutorial14/tutorial.py create mode 100644 tutorials/tutorial15/tutorial.ipynb create mode 100644 tutorials/tutorial16/tutorial.ipynb create mode 100644 tutorials/tutorial17/tutorial.ipynb create mode 100644 tutorials/tutorial18/tutorial.ipynb create mode 100644 tutorials/tutorial19/tutorial.ipynb delete mode 100644 tutorials/tutorial2/tutorial.py create mode 100644 tutorials/tutorial20/tutorial.ipynb create mode 100644 tutorials/tutorial21/tutorial.ipynb delete mode 100644 tutorials/tutorial3/tutorial.py delete mode 100644 tutorials/tutorial4/tutorial.py delete mode 100644 tutorials/tutorial5/tutorial.py delete mode 100644 tutorials/tutorial6/tutorial.py delete mode 100644 tutorials/tutorial7/tutorial.py delete mode 100644 tutorials/tutorial8/tutorial.py delete mode 100644 tutorials/tutorial9/tutorial.py diff --git a/docs/source/_tutorial.rst b/docs/source/_tutorial.rst index 745e575..612320a 100644 --- a/docs/source/_tutorial.rst +++ b/docs/source/_tutorial.rst @@ -1,35 +1,43 @@ -PINA Tutorials -====================== +🚀 Welcome to the PINA Tutorials! +================================== -In this folder we collect useful tutorials in order to understand the principles and the potential of **PINA**. +In this folder we collect useful tutorials in order to understand the principles and the potential of **PINA**. +Whether you're just getting started or looking to deepen your understanding, these resources are here to guide you. Getting started with PINA ------------------------- -- `Introduction to PINA for Physics Informed Neural Networks training `_ +- `Introductory Tutorial: A Beginner's Guide to PINA `_ +- `How to build a Problem in PINA `_ +- `Introduction to Solver classes `_ +- `Introduction to Trainer class `_ +- `Data structure for SciML: Tensor, LabelTensor, Data and Graph `_ +- `Building geometries with DomainInterface class `_ - `Introduction to PINA Equation class `_ -- `PINA and PyTorch Lightning, training tips and visualizations `_ -- `Building custom geometries with PINA Location class `_ - Physics Informed Neural Networks -------------------------------- -- `Two dimensional Poisson problem using Extra Features Learning `_ -- `Two dimensional Wave problem with hard constraint `_ -- `Resolution of a 2D Poisson inverse problem `_ -- `Periodic Boundary Conditions for Helmotz Equation `_ -- `Multiscale PDE learning with Fourier Feature Network `_ +- `Introductory Tutorial: Physics Informed Neural Networks with PINA `_ +- `Enhancing PINNs with Extra Features to solve the Poisson Problem `_ +- `Applying Hard Constraints in PINNs to solve the Wave Problem `_ +- `Applying Periodic Boundary Conditions in PINNs to solve the Helmotz Problem `_ +- `Inverse Problem Solving with Physics-Informed Neural Network `_ +- `Learning Multiscale PDEs Using Fourier Feature Networks `_ +- `Learning Bifurcating PDE Solutions with Physics-Informed Deep Ensembles `_ Neural Operator Learning ------------------------ -- `Two dimensional Darcy flow using the Fourier Neural Operator `_ -- `Time dependent Kuramoto Sivashinsky equation using the Averaging Neural Operator `_ +- `Introductory Tutorial: Neural Operator Learning with PINA `_ +- `Modeling 2D Darcy Flow with the Fourier Neural Operator `_ +- `Solving the Kuramoto-Sivashinsky Equation with Averaging Neural Operator `_ Supervised Learning ------------------- -- `Unstructured convolutional autoencoder via continuous convolution `_ -- `POD-RBF and POD-NN for reduced order modeling `_ +- `Introductory Tutorial: Supervised Learning with PINA `_ +- `Chemical Properties Prediction with Graph Neural Networks `_ +- `Unstructured Convolutional Autoencoders with Continuous Convolution `_ +- `Reduced Order Modeling with POD-RBF and POD-NN Approaches for Fluid Dynamics `_ diff --git a/tutorials/README.md b/tutorials/README.md index 3129dd9..f2a6322 100644 --- a/tutorials/README.md +++ b/tutorials/README.md @@ -1,36 +1,47 @@ -# PINA Tutorials +# 🚀 Welcome to the PINA Tutorials! + +In this folder we collect useful tutorials in order to understand the principles and the potential of **PINA**. Whether you're just getting started or looking to deepen your understanding, these resources are here to guide you. + +The table below provides an overview of each tutorial. All tutorials are also available in HTML in the official [PINA documentation](http://mathlab.github.io/PINA/). -In this folder we collect useful tutorials in order to understand the principles and the potential of **PINA**. Please read the following table for details about the tutorials. The HTML version of all the tutorials is available also within the [documentation](http://mathlab.github.io/PINA/). ## Getting started with PINA | Description | Tutorial | |---------------|-----------| -Introduction to PINA for Physics Informed Neural Networks training|[[.ipynb](tutorial1/tutorial.ipynb), [.py](tutorial1/tutorial.py), [.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial1/tutorial.html)]| -Introduction to PINA `Equation` class|[[.ipynb](tutorial12/tutorial.ipynb), [.py](tutorial12/tutorial.py), [.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial12/tutorial.html)]| -PINA and PyTorch Lightning, training tips and visualizations|[[.ipynb](tutorial11/tutorial.ipynb), [.py](tutorial11/tutorial.py), [.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial11/tutorial.html)]| -Building custom geometries with PINA `Location` class|[[.ipynb](tutorial6/tutorial.ipynb), [.py](tutorial6/tutorial.py), [.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial6/tutorial.html)]| +Introductory Tutorial: A Beginner’s Guide to PINA|[[.ipynb](tutorial17/tutorial.ipynb),[.py](tutorial17/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial17/tutorial.html)]| +How to build a `Problem` in PINA|[[.ipynb](tutorial16/tutorial.ipynb),[.py](tutorial16/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial16/tutorial.html)]| +Introduction to Solver classes|[[.ipynb](tutorial18/tutorial.ipynb),[.py](tutorial18/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial18/tutorial.html)]| +Introduction to `Trainer` class|[[.ipynb](tutorial11/tutorial.ipynb),[.py](tutorial11/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial11/tutorial.html)]| +Data structure for SciML: `Tensor`, `LabelTensor`, `Data` and `Graph` |[[.ipynb](tutorial19/tutorial.ipynb),[.py](tutorial19/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial19/tutorial.html)]| +Building geometries with `DomainInterface` class|[[.ipynb](tutorial6/tutorial.ipynb),[.py](tutorial6/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial6/tutorial.html)]| +Introduction to PINA `Equation` class|[[.ipynb](tutorial12/tutorial.ipynb),[.py](tutorial12/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial12/tutorial.html)]| ## Physics Informed Neural Networks | Description | Tutorial | |---------------|-----------| -Two dimensional Poisson problem using Extra Features Learning     |[[.ipynb](tutorial2/tutorial.ipynb), [.py](tutorial2/tutorial.py), [.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial2/tutorial.html)]| -Two dimensional Wave problem with hard constraint |[[.ipynb](tutorial3/tutorial.ipynb), [.py](tutorial3/tutorial.py), [.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial3/tutorial.html)]| -Resolution of a 2D Poisson inverse problem |[[.ipynb](tutorial7/tutorial.ipynb), [.py](tutorial7/tutorial.py), [.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial7/tutorial.html)]| -Periodic Boundary Conditions for Helmotz Equation |[[.ipynb](tutorial9/tutorial.ipynb), [.py](tutorial9/tutorial.py), [.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial9/tutorial.html)]| -Multiscale PDE learning with Fourier Feature Network |[[.ipynb](tutorial13/tutorial.ipynb), [.py](tutorial13/tutorial.py), [.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial13/tutorial.html)]| +Introductory Tutorial: Physics Informed Neural Networks with PINA |[[.ipynb](tutorial1/tutorial.ipynb),[.py](tutorial1/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial1/tutorial.html)]| +Enhancing PINNs with Extra Features to solve the Poisson Problem |[[.ipynb](tutorial2/tutorial.ipynb),[.py](tutorial2/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial2/tutorial.html)]| +Applying Hard Constraints in PINNs to solve the Wave Problem |[[.ipynb](tutorial3/tutorial.ipynb),[.py](tutorial3/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial3/tutorial.html)]| +Applying Periodic Boundary Conditions in PINNs to solve the Helmotz Problem |[[.ipynb](tutorial9/tutorial.ipynb),[.py](tutorial9/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial9/tutorial.html)]| +Inverse Problem Solving with Physics-Informed Neural Network |[[.ipynb](tutorial7/tutorial.ipynb),[.py](tutorial7/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial7/tutorial.html)]| +Learning Multiscale PDEs Using Fourier Feature Networks|[[.ipynb](tutorial13/tutorial.ipynb),[.py](tutorial13/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial13/tutorial.html)]| +Learning Bifurcating PDE Solutions with Physics-Informed Deep Ensembles|[[.ipynb](tutorial14/tutorial.ipynb),[.py](tutorial14/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial14/tutorial.html)]| ## Neural Operator Learning | Description | Tutorial | |---------------|-----------| -Two dimensional Darcy flow using the Fourier Neural Operator         |[[.ipynb](tutorial5/tutorial.ipynb), [.py](tutorial5/tutorial.py), [.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial5/tutorial.html)]| -Time dependent Kuramoto Sivashinsky equation using the Averaging Neural Operator         |[[.ipynb](tutorial10/tutorial.ipynb), [.py](tutorial10/tutorial.py), [.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial10/tutorial.html)]| +Introductory Tutorial: Neural Operator Learning with PINA |[[.ipynb](tutorial21/tutorial.ipynb),[.py](tutorial21/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial21/tutorial.html)]| +Modeling 2D Darcy Flow with the Fourier Neural Operator |[[.ipynb](tutorial5/tutorial.ipynb),[.py](tutorial5/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial5/tutorial.html)]| +Solving the Kuramoto–Sivashinsky Equation with Averaging Neural Operator |[[.ipynb](tutorial10/tutorial.ipynb),[.py](tutorial10/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial10/tutorial.html)]| ## Supervised Learning | Description | Tutorial | |---------------|-----------| -Unstructured convolutional autoencoder via continuous convolution |[[.ipynb](tutorial4/tutorial.ipynb), [.py](tutorial4/tutorial.py), [.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial4/tutorial.html)]| -POD-RBF and POD-NN for reduced order modeling| [[.ipynb](tutorial8/tutorial.ipynb), [.py](tutorial8/tutorial.py), [.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial8/tutorial.html)]| -POD-RBF for modelling Lid Cavity| [[.ipynb](tutorial14/tutorial.ipynb), [.py](tutorial14/tutorial.py), [.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial14/tutorial.html)]| +Introductory Tutorial: Supervised Learning with PINA |[[.ipynb](tutorial20/tutorial.ipynb),[.py](tutorial20/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial20/tutorial.html)]| +Chemical Properties Prediction with Graph Neural Networks |[[.ipynb](tutorial15/tutorial.ipynb),[.py](tutorial15/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial15/tutorial.html)]| +Unstructured Convolutional Autoencoders with Continuous Convolution |[[.ipynb](tutorial4/tutorial.ipynb),[.py](tutorial4/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial4/tutorial.html)]| +Reduced Order Modeling with POD-RBF and POD-NN Approaches for Fluid Dynamics| [[.ipynb](tutorial8/tutorial.ipynb),[.py](tutorial8/tutorial.py),[.html](http://mathlab.github.io/PINA/_rst/tutorials/tutorial8/tutorial.html)]| + diff --git a/tutorials/TUTORIAL_GUIDELINES.md b/tutorials/TUTORIAL_GUIDELINES.md new file mode 100644 index 0000000..0475cb5 --- /dev/null +++ b/tutorials/TUTORIAL_GUIDELINES.md @@ -0,0 +1,128 @@ +# PINA Tutorial Guidelines + +Welcome to the **PINA Tutorial Guidelines** — a guiding document that defines the structure, style, and pedagogical philosophy for all tutorials in the **PINA** package. The goal of this guideline is to ensure that all learning materials are **clear, consistent, pedagogically sound, and beginner-friendly**, while remaining powerful enough to support advanced use cases. + + +## Purpose + +The purpose of the PINA tutorials is to help users: + +- Gaining a solid understanding of the PINA library and its core functionalities. +- Learning how to work with the PINA modules. +- Explore practical and advanced applications using consistent, hands-on code examples. + + +## Guiding Principles + +1. **Clarity Over Cleverness** + Tutorials should aim to teach, not impress. Prioritize readable and understandable code and explanations. + +2. **Progressive Disclosure of Complexity** + Start simple and gradually introduce complexity. Avoid overwhelming users early on. + +3. **Consistency is Key** + All tutorials should follow a common structure (see below), use the same markdown and code formatting, and have a predictable flow. + +4. **Real Applications, Real Problems** + Ground tutorials in real Scientific Applications or datasets, wherever possible. Bridge theory and implementation. + + +## Tutorial Structure + +To ensure clarity, consistency, and accessibility, all PINA tutorials should follow the same standardized format. + +### 1. Title + +Each tutorial must begin with a clear and descriptive title in the following format: **Tutorial: TUTORIAL_TITLE**. The title should succinctly communicate the focus and objective of the tutorial. + +### 2. Introducing the Topic + +Immediately after the title, include a short introduction that outlines the tutorial's purpose and scope. + +- Briefly explain what the tutorial covers and why it’s useful. +- Link to relevant research papers, publications, or external resources if applicable. +- List the core PINA components or modules that will be utilized. + +### 3. Imports and Setup + +Include a Python code cell with the necessary setup. This ensures that the tutorial runs both locally and on platforms like Google Colab. + +```python +## Routine needed to run the notebook on Google Colab +try: + import google.colab + IN_COLAB = True +except: + IN_COLAB = False + +if IN_COLAB: + !pip install "pina-mathlab[tutorial]" + +import torch # if used +import matplotlib.pyplot as plt # if used +import warnings # if needed + +warnings.filterwarnings("ignore") + +# Additional PINA and problem-specific imports +... +``` + +### 3. Data Generation or Loading +* Describe how the data is generated or loaded. +* Include commentary on data structure, format, and content. +* If applicable, visualize key features of the dataset or simulation domain. + +### 4. Main Body +The core section of the tutorial should present the problem-solving process in a clear, structured, and pedagogical way. This is where the tutorial delivers the key learning objectives. + +- Guide the user step-by-step through the PINA workflow. +- Introduce relevant PINA components as they are used. +- Provide context and explain the rationale behind modeling decisions. +- Break down complex sections with inline comments and markdown explanations. +- Emphasize the relevance of each step to the broader goal of the tutorial. + +### 5. Results, Visualization and Error Analysis +- Show relevant plots of results (e.g., predicted vs. ground truth). +- Quantify performance using metrics like loss or relative error. +- Discuss the outcomes: strengths, limitations, and any unexpected behavior + +### 6. What's Next? +All the tutorials are concluded with the **What's Next?** section,giving suggestions for further exploration. For this use the following format: +```markdown +## What's Next? + +Congratulations on completing the ..., here are a few directions you can explore: + +1. **Direction 1** — Suggestion .... + +2. **Direction 2** — Suggestion .... + +3. **...and many more!** — Other suggestions .... + +For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/). +``` + +## Writing Style + +- Use **clear markdown headers** to segment sections. +- Include **inline math** with `$...$` and display math with `$$...$$`. +- Keep paragraphs short and focused. +- Use **bold** and *italic* for emphasis and structure. +- Include comments in code for clarity. + + +## Testing Tutorials + +Every tutorial should: +- Be executable from top to bottom. +- Use the `tutorial` requirements in the [`pyproject.toml`](https://github.com/mathLab/PINA/blob/6ed3ca04fee3ae3673d53ea384437ce270f008da/pyproject.toml#L40) file. + + +## Contributing Checklist + +We welcome contributions! If you’re writing a tutorial: +1. The tutorial follows this guidelines for structure and tone. +2. The tutorial is simple and modular — one tutorial per concept. +3. 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zdM~?RPq0eHnYjwk;IlwAEt=VuAdI#+u`@TR>AN+*J<-APw-V&1BWrEKpbo{u?GpNh z{!(Io7gRv~npf#O3{P2mr`vCeT6C=bsV@3?%RrX|b#CyvHdz>UJ#YR)z!(`J5YK2^ zmVFy=4=e0Gc(A33PBWdbZf!fNopnD^35a3jFg=9U$*97T1DznWP{rpKd9*&6yb#1@ zLh7zx{q}Q0$kG_-FY=APHFBWKlp*u{Eut3(uXYPNM820_0aU!8smlWh$m4|~YA~8}YXdBrrmk%* zzndWpv>KWjxh@zMjKR+eWrV#tkmqK zUB9VHEr))kNwr8hVpo|!NaGoXwzMg{hehZJx|zJZRajd8&5V+4a{R+bY7LR_Zx4RY z9>R1>S9ug#7J8e00b_p=$vm+z76I_ohm;~|Zt{+*m@Sp1?}s1VG?}y4+wpdlQq&{=%&PtZ|+w8tS$BIyuyRXzx84-~;(DKjgpVpFZ>d zar#HpSZU{#8j}~f!bC^yMR$%BRn4#i@x?CCm)Qv0y@fPSg ##### ⚠️ ***Before starting:***\n", + "> We assume you are already familiar with the concepts covered in the [Getting started with PINA](https://mathlab.github.io/PINA/_tutorial.html#getting-started-with-pina) tutorials. If not, we strongly recommend reviewing them before exploring this advanced topic.\n" ] }, { @@ -17,71 +19,15 @@ "id": "ef4949c9", "metadata": {}, "source": [ - "In this tutorial, we will demonstrate a typical use case of **PINA** on a toy problem, following the standard API procedure. \n", + "In this tutorial, we will demonstrate a typical use case of **PINA** for Physics Informed Neural Network (PINN) training. We will cover the basics of training a PINN with PINA, if you want to go further into PINNs look at our dedicated [tutorials](https://mathlab.github.io/PINA/_tutorial.html#physics-informed-neural-networks) on the topic.\n", "\n", - "

\n", - " \"PINA\n", - "

\n", - "\n", - "Specifically, the tutorial aims to introduce the following topics:\n", - "\n", - "* Explaining how to build **PINA** Problems,\n", - "* Showing how to generate data for `PINN` training\n", - "\n", - "These are the two main steps needed **before** starting the modelling optimization (choose model and solver, and train). We will show each step in detail, and at the end, we will solve a simple Ordinary Differential Equation (ODE) problem using the `PINN` solver." - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "cf9c96e3", - "metadata": {}, - "source": [ - "## Build a PINA problem" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "8a819659", - "metadata": {}, - "source": [ - "Problem definition in the **PINA** framework is done by building a python `class`, which inherits from one or more problem classes (`SpatialProblem`, `TimeDependentProblem`, `ParametricProblem`, ...) depending on the nature of the problem. Below is an example:\n", - "### Simple Ordinary Differential Equation\n", - "Consider the following:\n", - "\n", - "$$\n", - "\\begin{equation}\n", - "\\begin{cases}\n", - "\\frac{d}{dx}u(x) &= u(x) \\quad x\\in(0,1)\\\\\n", - "u(x=0) &= 1 \\\\\n", - "\\end{cases}\n", - "\\end{equation}\n", - "$$\n", - "\n", - "with the analytical solution $u(x) = e^x$. In this case, our ODE depends only on the spatial variable $x\\in(0,1)$ , meaning that our `Problem` class is going to be inherited from the `SpatialProblem` class:\n", - "\n", - "```python\n", - "from pina.problem import SpatialProblem\n", - "from pina.domain import CartesianProblem\n", - "\n", - "class SimpleODE(SpatialProblem):\n", - " \n", - " output_variables = ['u']\n", - " spatial_domain = CartesianProblem({'x': [0, 1]})\n", - "\n", - " # other stuff ...\n", - "```\n", - "\n", - "Notice that we define `output_variables` as a list of symbols, indicating the output variables of our equation (in this case only $u$), this is done because in **PINA** the `torch.Tensor`s are labelled, allowing the user maximal flexibility for the manipulation of the tensor. The `spatial_domain` variable indicates where the sample points are going to be sampled in the domain, in this case $x\\in[0,1]$.\n", - "\n", - "What if our equation is also time-dependent? In this case, our `class` will inherit from both `SpatialProblem` and `TimeDependentProblem`:\n" + "Let's start by importing the useful modules:" ] }, { "cell_type": "code", "execution_count": null, - "id": "2373a925", + "id": "86478a84", "metadata": {}, "outputs": [], "source": [ @@ -93,78 +39,59 @@ "except:\n", " IN_COLAB = False\n", "if IN_COLAB:\n", - " !pip install \"pina-mathlab\"\n", + " !pip install \"pina-mathlab[tutorial]\"\n", "\n", "import warnings\n", + "import torch\n", + "import matplotlib.pyplot as plt\n", "\n", - "from pina.problem import SpatialProblem, TimeDependentProblem\n", + "from pina import Trainer, Condition\n", + "from pina.problem import SpatialProblem\n", + "from pina.operator import grad\n", + "from pina.solver import PINN\n", + "from pina.model import FeedForward\n", + "from pina.optim import TorchOptimizer\n", "from pina.domain import CartesianDomain\n", + "from pina.callback import MetricTracker\n", + "from pina.equation import Equation, FixedValue\n", "\n", - "warnings.filterwarnings(\"ignore\")\n", - "\n", - "\n", - "class TimeSpaceODE(SpatialProblem, TimeDependentProblem):\n", - "\n", - " output_variables = [\"u\"]\n", - " spatial_domain = CartesianDomain({\"x\": [0, 1]})\n", - " temporal_domain = CartesianDomain({\"t\": [0, 1]})\n", - "\n", - " # other stuff ..." + "warnings.filterwarnings(\"ignore\")" ] }, { "attachments": {}, "cell_type": "markdown", - "id": "ad8566b8", + "id": "8a819659", "metadata": {}, "source": [ - "where we have included the `temporal_domain` variable, indicating the time domain wanted for the solution.\n", + "## Build the problem\n", "\n", - "In summary, using **PINA**, we can initialize a problem with a class which inherits from different base classes: `SpatialProblem`, `TimeDependentProblem`, `ParametricProblem`, and so on depending on the type of problem we are considering. Here are some examples (more on the official documentation):\n", - "* ``SpatialProblem`` $\\rightarrow$ a differential equation with spatial variable(s) ``spatial_domain``\n", - "* ``TimeDependentProblem`` $\\rightarrow$ a time-dependent differential equation with temporal variable(s) ``temporal_domain``\n", - "* ``ParametricProblem`` $\\rightarrow$ a parametrized differential equation with parametric variable(s) ``parameter_domain``\n", - "* ``AbstractProblem`` $\\rightarrow$ any **PINA** problem inherits from here" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "592a4c43", - "metadata": {}, - "source": [ - "### Write the problem class\n", + "We will use a simple Ordinary Differential Equation as pedagogical example:\n", "\n", - "Once the `Problem` class is initialized, we need to represent the differential equation in **PINA**. In order to do this, we need to load the **PINA** operators from `pina.operator` module. Again, we'll consider Equation (1) and represent it in **PINA**:" + "$$\n", + "\\begin{equation}\n", + "\\begin{cases}\n", + "\\frac{d}{dx}u(x) &= u(x) \\quad x\\in(0,1)\\\\\n", + "u(x=0) &= 1 \\\\\n", + "\\end{cases}\n", + "\\end{equation}\n", + "$$\n", + "\n", + "with the analytical solution $u(x) = e^x$. \n", + "\n", + "The PINA problem is easly written as:" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "f2608e2e", "metadata": {}, "outputs": [], "source": [ - "import torch\n", - "import matplotlib.pyplot as plt\n", - "\n", - "from pina.problem import SpatialProblem\n", - "from pina.operator import grad\n", - "from pina import Condition\n", - "from pina.domain import CartesianDomain\n", - "from pina.equation import Equation, FixedValue\n", - "\n", - "\n", - "# defining the ode equation\n", "def ode_equation(input_, output_):\n", - "\n", - " # computing the derivative\n", " u_x = grad(output_, input_, components=[\"u\"], d=[\"x\"])\n", - "\n", - " # extracting the u input variable\n", " u = output_.extract([\"u\"])\n", - "\n", - " # calculate the residual and return it\n", " return u_x - u\n", "\n", "\n", @@ -178,13 +105,11 @@ " \"D\": CartesianDomain({\"x\": [0, 1]}),\n", " }\n", "\n", - " # conditions to hold\n", " conditions = {\n", " \"bound_cond\": Condition(domain=\"x0\", equation=FixedValue(1.0)),\n", " \"phys_cond\": Condition(domain=\"D\", equation=Equation(ode_equation)),\n", " }\n", "\n", - " # defining the true solution\n", " def solution(self, pts):\n", " return torch.exp(pts.extract([\"x\"]))\n", "\n", @@ -198,11 +123,19 @@ "id": "7cf64d01", "metadata": {}, "source": [ - "After we define the `Problem` class, we need to write different class methods, where each method is a function returning a residual. These functions are the ones minimized during PINN optimization, given the initial conditions. For example, in the domain $[0,1]$, the ODE equation (`ode_equation`) must be satisfied. We represent this by returning the difference between subtracting the variable `u` from its gradient (the residual), which we hope to minimize to 0. This is done for all conditions. Notice that we do not pass directly a `python` function, but an `Equation` object, which is initialized with the `python` function. This is done so that all the computations and internal checks are done inside **PINA**.\n", - "\n", - "Once we have defined the function, we need to tell the neural network where these methods are to be applied. To do so, we use the `Condition` class. In the `Condition` class, we pass the location points and the equation we want minimized on those points (other possibilities are allowed, see the documentation for reference).\n", - "\n", - "Finally, it's possible to define a `solution` function, which can be useful if we want to plot the results and see how the real solution compares to the expected (true) solution. Notice that the `solution` function is a method of the `PINN` class, but it is not mandatory for problem definition.\n" + "We are going to use latin hypercube points for sampling. We need to sample in all the conditions domains. In our case we sample in domain `D` and `x0`:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "622f705c", + "metadata": {}, + "outputs": [], + "source": [ + "# sampling for training\n", + "problem.discretise_domain(1, \"lh\", domains=[\"x0\"])\n", + "problem.discretise_domain(20, \"lh\", domains=[\"D\"])" ] }, { @@ -218,7 +151,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "09ce5c3a", "metadata": {}, "outputs": [], @@ -244,7 +177,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "329962b6", "metadata": {}, "outputs": [], @@ -254,53 +187,6 @@ "problem.discretise_domain(20, \"lh\", domains=[\"D\"])" ] }, - { - "cell_type": "markdown", - "id": "ca2ac5c2", - "metadata": {}, - "source": [ - "The points are saved in a python `dict`, and can be accessed by calling the attribute `input_pts` of the problem " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d6ed9aaf", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Input points: {'x0': LabelTensor([[0.]]), 'D': LabelTensor([[0.3097],\n", - " [0.9524],\n", - " [0.6227],\n", - " [0.9200],\n", - " [0.1549],\n", - " [0.8729],\n", - " [0.8064],\n", - " [0.3929],\n", - " [0.1100],\n", - " [0.4493],\n", - " [0.2909],\n", - " [0.6947],\n", - " [0.0141],\n", - " [0.4516],\n", - " [0.5632],\n", - " [0.5328],\n", - " [0.7851],\n", - " [0.0829],\n", - " [0.7144],\n", - " [0.2229]])}\n", - "Input points labels: ['x']\n" - ] - } - ], - "source": [ - "print(\"Input points:\", problem.discretised_domains)\n", - "print(\"Input points labels:\", problem.discretised_domains[\"D\"].labels)" - ] - }, { "cell_type": "markdown", "id": "669e8534", @@ -311,23 +197,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "3802e22a", "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", 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" ] @@ -342,7 +218,7 @@ " problem.input_pts[location].extract(problem.spatial_variables).flatten()\n", " )\n", " plt.scatter(coords, torch.zeros_like(coords), s=10, label=location)\n", - "plt.legend()" + "_=plt.legend()" ] }, { @@ -351,7 +227,7 @@ "id": "22e502dd", "metadata": {}, "source": [ - "## Perform a small training" + "## Easily solve a Physics Problem with three step pipeline" ] }, { @@ -360,14 +236,77 @@ "id": "075f43f5", "metadata": {}, "source": [ - "Once we have defined the problem and generated the data we can start the modelling. Here we will choose a `FeedForward` neural network available in `pina.model`, and we will train using the `PINN` solver from `pina.solver`. We highlight that this training is fairly simple, for more advanced stuff consider the tutorials in the ***Physics Informed Neural Networks*** section of ***Tutorials***. For training we use the `Trainer` class from `pina.trainer`. Here we show a very short training and some method for plotting the results. Notice that by default all relevant metrics (e.g. MSE error during training) are going to be tracked using a `lightning` logger, by default `CSVLogger`. If you want to track the metric by yourself without a logger, use `pina.callback.MetricTracker`." + "Once the problem is defined and the data is generated, we can move on to modeling. This process consists of three key steps:\n", + "\n", + "**Choosing a Model**\n", + "- Select a neural network architecture. You can use the model we provide in the `pina.model` module (see [here](https://mathlab.github.io/PINA/_rst/_code.html#models) for a full list), or define a custom PyTorch module (more on this [here](https://pytorch.org/docs/stable/notes/modules.html)).\n", + "\n", + "**Choosing a PINN Solver & Defining the Trainer**\n", + "* Use a Physics Informed solver from `pina.solver` module to solve the problem using the specified model. We have already implemented most State-Of-The-Arte solvers for you, [have a look](https://mathlab.github.io/PINA/_rst/_code.html#solvers) if interested. Today we will use the standard `PINN` solver.\n", + "\n", + "**Training**\n", + "* Train the model with the [`Trainer`](https://mathlab.github.io/PINA/_rst/trainer.html) class. The Trainer class provides powerful features to enhance model accuracy, optimize training time and memory, and simplify logging and visualization, thanks to PyTorch Lightning's excellent work, see [our dedicated tutorial](https://mathlab.github.io/PINA/tutorial11/tutorial.html) for further details. By default, training metrics (e.g., MSE error) are logged using a lightning logger (CSVLogger). If you prefer manual tracking, use `pina.callback.MetricTracker`.\n", + "\n", + "Let's cover all steps one by one!\n", + "\n", + "First we build the model, in this case a FeedForward neural network, with two layers of size 10 and hyperbolic tangent activation:" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "3bb4dc9b", "metadata": {}, + "outputs": [], + "source": [ + "# build the model\n", + "model = FeedForward(\n", + " layers=[10, 10],\n", + " func=torch.nn.Tanh,\n", + " output_dimensions=len(problem.output_variables),\n", + " input_dimensions=len(problem.input_variables),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "c3b92328", + "metadata": {}, + "source": [ + "Then we build the solver. The Physics-Informed Neural Network (`PINN`) solver class needs to be initialised with a `model` and a specific `problem` to be solved. They also take extra arguments, as the optimizer, scheduler, loss type and weighting for the different conditions which are all set to their defualt values.\n", + "\n", + ">##### 💡***Bonus tip:***\n", + "> All physics solvers in PINA can handle both forward and inverse problems without requiring any changes to the model or solver structure! See [our tutorial](https://mathlab.github.io/PINA/tutorial7/tutorial.html) of inverse problems for more infos." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "f5127744", + "metadata": {}, + "outputs": [], + "source": [ + "# create the PINN object with RAdam Optimizer, notice that Optimizer need to\n", + "# be wrapped with the pina.optim.TorchOptimizer class\n", + "pinn = PINN(problem, model, TorchOptimizer(torch.optim.RAdam, lr=0.005))" + ] + }, + { + "cell_type": "markdown", + "id": "c5d877cc", + "metadata": {}, + "source": [ + "Finally, we train the model using the Trainer API. The trainer offers various options to customize your training, refer to the official documentation for details. Here, we highlight the `MetricTracker` from `pina.callback`, which helps track metrics during training. In order to train just call the `.train()` method.\n", + "\n", + "> ##### ⚠️ ***Important Note:***\n", + "> In PINA you can log metrics in different ways. The simplest approach is to use the `MetricTraker` class from `pina.callbacks` as we will see today. However, expecially when we need to train multiple times to get an average of the loss across multiple runs, we suggest to use `lightning.pytorch.loggers` (see [here](https://lightning.ai/docs/pytorch/stable/extensions/logging.html) for reference).\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "582a843e", + "metadata": {}, "outputs": [ { "name": "stderr", @@ -379,11 +318,18 @@ ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1499: 100%|██████████| 1/1 [00:00<00:00, 149.92it/s, v_num=0, bound_cond_loss=1.52e-8, phys_cond_loss=7.68e-6, train_loss=7.69e-6] " - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "80c2ef11b8534949abcc7a01b36f1094", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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4u8rvnWJvr63zpm6PKCR3RwuqmzJhLP1mrltrWk3T9zdv3qw8efLol19+Ub169RQcHKwFCxZk2PL45JNPqnXr1uf209LSNHDgQPua6aGhoYqKitI333xz2Vo+//xzVaxY0b7GetGiRXXPPfeceywxMVGPP/64ihQpYj/evHlzLV++/JKvZVp+a9eufcF9H3/8scqUKXPu8bFjx+r7778/11pshglk1MU/b948NWzY0H7/kZGReuGFF5SSknLucfO+TW3PP/+8ChQoYH/vvLnlGQCAi1nJZ5U4tb+9PTO4nW5pf688gfc2uV2OZUnJZ5z52oFhpv8+S17KBLJBgwapXLlyyp8//xU9x4TT8ePHa+jQoXbonD9/vh566CEVLlxYrVq1+tvxK1assEPel19+qaZNm+rEiRP6448/zj1uwt+3335rh8rSpUvrvffeU7t27bR9+3Y7FGbWs88+q02bNik2NlajR4+27zOvc/DgwQuOO3DggG655RY7lI8bN84O7Y888ogdks8Poaaup59+WkuXLtXixYvt45s1a6Ybbrgh07UBAOBpdnzzmiok79cRK5/K3P+BAvw9o23SNwOqCafvFHPma794UArKlSUv9eabb2YqaJnWznfeeUe//fabmjRpYt9nwq1pff3iiy8yDKh79+5Vrly5dNttt9mttiaE1qlTx34sPj5eQ4YM0ZgxY3TzzTfb9w0fPlyzZs3SyJEj9dxzz2X6PZmhC6Zl19R6uS5906prxqV+9tlndstqlSpV7BD7r3/9yx4O4ef31y9grVq19Nprr9nbJpCb42fPnk1ABQB4vdhdf6rMlhH29pKqA3R7mZLyFL4ZUL1E/fr1M3W8adU8c+bM38JZUlLSudB5MXOsCaUmyN5000327c4771RYWJh27Nih5ORku0UyXWBgoN3tblpBs5N5fROyz1+/zdQRFxen/fv3q1SpUucC6vnMUIAjR45ka20AADguNUWnJvdWuFL1R0AT3XRPL3kS3wyoppvdtGQ69bWziGnZPJ9pNTQTps5nAmQ6E96Mn3/+WcWLF7/gODOOMyOm1fTPP/+0x4H++uuvduuk6UK/3DjTy/mnGrOaCcznM4HWjMMFAMCbbf/xfVVI2KJYK0z57/lEQQGe0bXv2wHVtLplUTe7OzHjSNevX3/BfWZSUXpIq1atmh1ETbd9Rt35l2JWB2jbtq19M93l+fLl05w5c+yxpkFBQVq4cKHdypoeNk14NZOzLlVjdHS0HVLTWz8vXtvUvKZZleByqlatao99Pf91TB0mUJcoUeKK3xsAAN4mLnqbSqz+0N6eX+YJ3ValsjyNbwZUL3Xdddfp/ffftycNme5vMxnKBNb07nsT3swkpKeeespuRTQz7mNiYuxgFx4erq5du/7tNX/66Sft3LlTLVu2tCdiTZ8+3X5u5cqV7RbcPn362GNNzUQm061uJkmZYQQ9evTIsEYzs/7o0aP2cWY1gBkzZtirEZivn87M6J85c6a9rFbBggXtVQwu1rdvX3v2/2OPPab+/fvbx5rwbCZEpY8/BQDA51iWosf3VgUlaZVfDV3/wF+L83sa/pJ7EdOi+corr9gz6xs0aKDTp0+rS5cuFxzz1ltv2ceY2fymFdKMKTVd/mbZqYyY1tLvvvvODr/meDP7f+LEiapevbr9+Lvvvqu7775bnTt3Vt26de1xriZcXmpVAfMaZoLT4MGD7SWuli1bZofm85nZ+CYAmzG2psXVBOiLmSEKJiyb55vX6d27tx2KX3755Wv4DgIA4Nm2zxqmCnErlGAFSu0/UWiwZ7ZFuqyLBwR6ILMkkWllM62B57fEGQkJCdq1a5cdwMwSRACyHr9nAOC8sycOKOXTBsqjeM2I7K2bHv2PPCWvXYwWVAAAAE9nWdoztrcdTje7yqlpZ8++MA0BFQAAwMPtmPulqsTMV7Llr9PtPlF4WKg8GQEVAADAgyWcOqyC816yt38v0lkNGreUpyOgAgAAeLAd4/opn2K13VVKjbq+I2/gMwHVC+aCAW6L3y8AcMbOPyap+olZSrVcOtH2I+XN7R3rvHt9QE1fpN6szQkge6T/fl185S4AQPZJiD2uvHNesLfnFrpfDZu1lbfwzMWxMsHf399eyzP9+uvmGvLnX78dwLW1nJpwan6/zO+Z+X0DAOSMbV8+pprWSe1WMdXr8q68idcHVCMiIsL+Nz2kAshaJpym/54BALLfzsXTVPPoz0qzXDp83SCVyeCqi57MJwKqaTGNjIxUkSJF7GvFA8g6plufllMAyDmJ8SeV+9dn7O15Be5Sm1a3ytv4REBNZ/6I8ocUAAB4ss3jnlaUdUz7VVRRXT6QN/L6SVIAAADeYtfyXxR1+Dt7e3+L/6hA/vzyRgRUAAAAD5B05rRCfnnS3p6ft70aX3+nvBUBFQAAwANsGP+cItOidUgFVb3Lx/JmBFQAAAA3t3vVHEUdmPTXdpN3VLBgIXkzAioAAIAbS048I/8fH5Ofy9LC3O3U+MaO8nYEVAAAADe2dvwAlUzbr6PKp0pdPvWJCw4RUAEAANzUnnULFLV3nL29vcFbKlzENy6KQkAFAABwQylJCbKm9VOAK01Lc7VR41s6y1cQUAEAANzQqgmvqkzqbh1XuMp0HuwTXfvpCKgAAABuZu/Gpaq9a4S9vaXuqyoaUVy+hIAKAADgZl37Kd/2VqArVStCm6nJbT3kawioAAAAbmTVVy+rXOpOnVAelewyVC4/34trvveOAQAA3NSudQtVZ/dIe3tLvTdUNLKUfBEBFQAAwA0kJ56Va1ofe9b+8lyt1Pi27vJVBFQAAAA3sPrLASqTukfHlVdlugzxqVn7FyOgAgAAOGzHqnmqu2/MX9sN31Lhor41a/9iBFQAAAAHJSWcUeCPfeXvsrQs9/VqcHMX+ToCKgAAgIPWjHtOpdL266jyqXxX31qQ/1IIqAAAAA7ZtuI31Tvwlb29p8k7Klg40umS3AIBFQAAwAEJZ04rdPpj8nNZWhreTvXbPeh0SW6DgAoAAOCAteOeVYm0gzqiAqrc9TOny3ErBFQAAIActmXpTNU/NNne3t/8XeUrWMTpktwKARUAACAHnY2LVe4Zj9td+0vy3qq6bTs6XZLbIaACAADkoHXjnlZxK1rRKqSq3f7rdDluiYAKAACQQzYtnq6GR6bY29Gt31fe/AWdLsktEVABAABywJm4U8r36xP29pL8t6t267ucLsltEVABAABywIYxTyjSOqJDKqxq3T5xuhy3RkAFAADIZhv+mKYGx6bZ20ev/1DheQs4XZJbI6ACAABko7jYEyo4+xl7e0nBu1Srxe1Ol+T2CKgAAADZaPPoforQMR1wFVWNbh85XY5HIKACAABkkzW/faX6J6crzXLp1I2fKHeefE6X5BEIqAAAANng5JEDKrngBXt7ScQDqt7kZqdL8hgEVAAAgCxmpaVp99heKqBY7fIrrbrdBjldkkchoAIAAGSxP38cqjrxC5Rk+Su1w1CFhIY5XZJHIaACAABkocP7tqnSqjft7RVle6tCraZOl+RxCKgAAABZJC01VcfG91AendXmgKpq+ODrTpfkkQioAAAAWWTFlHdVPXGNzljBCus4TAGBQU6X5JEIqAAAAFlg35ZVqrXpr3VO11Z7VqUq1nK6JI9FQAUAALhGKUmJSpjyiEJcyVobXF8N73nW6ZI8GgEVAADgGq386mVVTNmmGOVSkc7D5edPxLoWmfruDRw4UA0aNFCePHlUpEgRdejQQVu2bLnsc8aMGSOXy3XBLSQk5IJjLMvSq6++qsjISIWGhqpt27batm3b1b0jAACAHLR99XzV2z3C3t5S73VFlCjndEm+FVDnzZunfv36acmSJZo1a5aSk5N14403Kj4+/rLPCw8P16FDh87d9uzZc8Hj7733nj799FMNHTpUS5cuVa5cudSuXTslJCRc3bsCAADIAQln4hT0Qx8FuNK0IncbNbjtEadL8goBmTl4xowZf2sdNS2pK1euVMuWLS/5PNNqGhERkeFjpvX0448/1ssvv6w77rjDvm/cuHEqWrSopk2bpk6dOv3tOYmJifYtXWxsbGbeBgAAQJZYO/ZpNUzbr6PKr3Jdh9iZB9fumgZIxMTE2P8WKFDgssfFxcWpdOnSKlmypB1CN2zYcO6xXbt2KTo62u7WT5c3b141atRIixcvvuRQA3NM+s28LgAAQE7atPBHNTw82d7e3+I9FSgc6XRJXuOqA2paWpqefPJJNWvWTDVq1LjkcZUrV9aoUaP0/fffa/z48fbzmjZtqv3799uPm3BqmBbT85n99McuNmDAADscp9/27dt3tW8DAAAg0+JiTqjAb0/a24sL3KE619/ndEm+28V/PjMWdf369VqwYMFlj2vSpIl9S2fCadWqVfXFF1/orbfeuqqvHRwcbN8AAACcsGV0H9Wzjmm/K0I1un3idDle56paUPv376+ffvpJv//+u0qUKJGp5wYGBqpOnTravn27vZ8+NvXw4cMXHGf2LzVuFQAAwClrZ32peqdmKNVy6VS7T5UnPL/TJfl2QDUTmkw4nTp1qubMmaOyZctm+gumpqZq3bp19pJShnkNE0Rnz559waQnM5v//JZXAAAAp508ckAlFr5oby+JfEg1GrdzuiSvFJDZbv0JEybY40nNWqjpY0TNRCWzfqnRpUsXFS9e3J7IZLz55ptq3LixKlSooFOnTun999+3l5nq2bOn/biZ7WbGsr799tuqWLGiHVhfeeUVFStWzF5nFQAAwB1YaWnaO6aHohSrHX5lVK/re06X5LUyFVCHDBli/9u6desL7h89erS6detmb+/du1d+fv/fMHvy5Ek98sgjdpjNnz+/6tWrp0WLFqlatWrnjnn++efttVR79eplh9jmzZvbS1pdvKA/AACAU/6c+pHqnVmsJCtAaR2+UEhomNMleS2XZfrtPZwZEmBacc2MfnNRAAAAgKx0cPta5f/yeoW6krSw/NNq1vk1p0vy6rzGhWIBAAAuIyUpUWcmdbfD6dqg2mr8wMtOl+T1CKgAAACXserLF1QhZZtirFwq/NBI+fv7O12S1yOgAgAAXMK25bNUd+9oe3tLw7cVWaqC0yX5BAIqAABABs7EnlDu6X3l77K0NLydGtzysNMl+QwCKgAAQAY2j+6jSOuIDqioqjw81F4aEzmDgAoAAHCRtTNHq+7Jv64WdeLGT5U3fwGnS/IpBFQAAIDzHD+4S6UX/zVTf3GxrqrZ9CanS/I5BFQAAID/sdJSdXjcw8qrOG3xr6gG3f7jdEk+iYAKAADwP39OfkfVElbpjBWsgHtHKDiYq1o6gYAKAAAgad+mpaq5+WN7+8+qz6l8ldpOl+SzCKgAAMDnJSeeUdo3jyjIlaKVIU3U9N5nnC7JpxFQAQCAz1sz5imVTt2jY8qrEl1HyM+fiOQkvvsAAMCnbVk4TfUPTbK3dzV9T0UjSzhdks8joAIAAJ91+uRhFZz1pL29MH8HNbixk9MlgYAKAAB8lmVp16ieKqST2u0qrlrdP3W6IvwPARUAAPikNT8OVq3T85Vs+Sv+tqHKkyev0yXhfwioAADA5xzetUEV/3zT3l5cureq12vpdEk4DwEVAAD4lNTkRMVN6KowJWpdYE016fyG0yXhIgRUAADgU1aPfVblk7fplJVb+R4crcDAQKdLwkUIqAAAwGdsW/yj6u0fZ29vavBvlSxT0emSkAECKgAA8AlxJw6pwMzH7O0Fedur8a1dnS4Jl0BABQAA3s+ytGfUwyqok9rlKqlaPQfL5XI5XRUugYAKAAC83prv3lP1uMVKtAJ19vYvFM6SUm6NgAoAALzawS3LVWXt+/b24vJPqFqdZk6XhH9AQAUAAF4rOSFOKV93V7ArWSuDG6rFgy85XRKuAAEVAAB4rQ2jH1ep1L06qnwq1nWU/P2JPp6AswQAALzSlrkTVfvwt/b2jmaDFFmspNMl4QoRUAEAgNeJObxbEXOftbfnFeqkxjfc63RJyAQCKgAA8CpWaooOje6qvIrTVr/yqt/9I6dLQiYRUAEAgFdZO/lNVUlYrXgrWNbdI5UrLMzpkpBJBFQAAOA19q2br+pb/mtvL6/6gipXr+N0SbgKBFQAAOAVEuNPKmBqTwW40rQ4tJVa3vuk0yXhKhFQAQCAV9g6srci0w7roAqrwsPD5ceSUh6LMwcAADzeppnDVfPEDKVaLh247lMVLlLU6ZJwDQioAADAox3fu0klF79ib8+L7K4GLW9xuiRcIwIqAADwWGlJCYr98iHl1lmt86+upg8PdLokZAECKgAA8Fjrxz6pssnbdcrKrdwPjFZIcLDTJSELEFABAIBH2v7H16p1YKK9va7BQJUtX9npkpBFCKgAAMDjxEbvVuHZT9nbv+e/V81v7ex0SchCBFQAAOBRrNRkHRnzoH0p081+FVS/5ydyuVxOl4UsREAFAAAeZf1XA1QhYb3irFDpnlHKkyuX0yUhixFQAQCAx9iz7GdV3zHC3l5W8zVVqRbldEnIBgRUAADgEeJPHFSeX/rKz2VpXu5b1Obu3k6XhGxCQAUAAO4vLU37R3ZRAeuUdrhKqmbPIYw79WIEVAAA4PbWT3lDleOX66wVpPj2I1QgXz6nS0I2IqACAAC3dmDt76qy8VN7e2HF51WrbmOnS0I2I6ACAAC3lXj6mAKnPaIAV5oWhrZWm/ufcbok5AACKgAAcE+WpZ0jHlaRtKPapwhV7D5C/v5EF1/AWQYAAG5p0w8fqGrMfCVZ/opuN0RFChd2uiTkEAIqAABwO0e2LlP5VQPt7bmlH1eDJtc5XRJyEAEVAAC4lZQzMUqZ3E1BStGSoMZq3fkVp0tCDiOgAgAA92FZ2jKql4qlHtAhq6BKdB2loEB/p6tCDiOgAgAAt7Ft5lBVPzZDKZafdrb+VCWKF3e6JDiAgAoAANzC8R1/quSSV+3t2ZE91azNbU6XBIcQUAEAgFuMO02Y0FkhStLygHpq1f0dp0uCgwioAADAWZalbSN7qHjqfkVbBVWk6xiFBAU6XRUcREAFAACO2vLzJ6p6fJaSLX/taP1flS5ZyumS4DACKgAAcMzRrUtVdsVb9vZvxfuoWZtbnS4JboCACgAAHJEcf1Kpk7v8td5pYCNd9/AbTpcEN0FABQAAOc+ytGPEw4pIjdZ+FVbxbmMUHBjgdFVwEwRUAACQ47Z8P0hVTv6uJMtfe6/7XCWLF3O6JLgRAioAAMhRhzctVLnVA+3t2aUeV9OWNzpdEtwMARUAAOSYpNPHpSndFKhULQxqruu7vOJ0SXBDBFQAAJAzLEu7RnRR0bQj2quiKv3wSAUF+jtdFdwQARUAAOSIzd+9o8oxC5RoBerQDV+oRGSE0yXBTRFQAQBAtoteN1cV1g2yt+eUfVqNmrVxuiS4MQIqAADIVokxhxUwtbsClKb5Ia3V9qF/OV0S3BwBFQAAZJ+0NO0d0VmF0o5rl4qpYveRCgxg3Ckuj4AKAACyzeZv3lDF00t11grS0ZuHKbJIIadLggcgoAIAgGxxaM1vqrjhE3v79/LPq2GjFk6XBG8MqAMHDlSDBg2UJ08eFSlSRB06dNCWLVsu+5zhw4erRYsWyp8/v31r27atli1bdsEx3bp1k8vluuB20003Xd07AgAAjjt74oCCp/WQv8vS76E36MYHn3G6JHhrQJ03b5769eunJUuWaNasWUpOTtaNN96o+Pj4Sz5n7ty5uv/++/X7779r8eLFKlmypP2cAwcOXHCcCaSHDh06d5s4ceLVvysAAOAYKyVJh4Z3VAHrlLaplKr1HKYAfzptceVclmVZukpHjx61W1JNcG3ZsuUVPSc1NdVuSf3ss8/UpUuXcy2op06d0rRp066qjtjYWOXNm1cxMTEKDw+/qtcAAABZY9OYx1R19zidtkK1vcNPqlOnvtMlwQ1kJq9d08cZ8wWMAgUKXPFzzpw5Y7e8Xvwc09Jqwm7lypXVp08fHT9+/JKvkZiYaL/J828AAMB5e/74yg6nxsKabxNOkbMtqGlpabr99tvtls8FCxZc8fP69u2rmTNnasOGDQoJCbHvmzRpksLCwlS2bFnt2LFDL774onLnzm0PCfD3//tSFK+//rreeOONv91PCyoAAM6J2bdRgSPbKEwJmpG3o9o9+YU9rwTIbAvqVQdU08r5yy+/2OG0RIkSV/Scd999V++9957dWlqrVq1LHrdz506VL19ev/32m66//voMW1DN7fw3bMa2ElABAHBGWsJpHfqgmYon79Fqv+oq9+xshYeFOl0WfKmLv3///vrpp5/siU9XGk4HDRpkB9Rff/31suHUKFeunAoVKqTt27dn+HhwcLD9xs6/AQAAh1iWto3sYYfTI1Z+hT04jnCKa5KpgGoaW004nTp1qubMmWN3yV8J02r61ltvacaMGapf/5/Houzfv98egxoZGZmZ8gAAgAO2/fyRKh+dqWTLXxubfaJK5Ss4XRJ8KaCaJabGjx+vCRMm2GuhRkdH27ezZ8+eO8bMzB8wYMC5/f/85z965ZVXNGrUKJUpU+bcc+Li4uzHzb/PPfecvXTV7t27NXv2bN1xxx2qUKGC2rVrl5XvFQAAZLEjG/9QmRVv29szi/dT6xvvcLok+FpAHTJkiD1uoHXr1nbrZvpt8uTJ547Zu3evvY7p+c9JSkrSPffcc8FzTJe/YSZBrV271p5wValSJfXo0UP16tXTH3/8YXflAwAA95QYc1h+33RToFK1IKi52nZ7zemS4CWuaR1Ud8E6qAAA5LC0VO348AaVj1upXSqmwN7zVCKiiNNVwY3l2DqoAADAN22e+IIdTuOtYB29ZQThFFmKgAoAADJl39LvVGXbMHt7XuVX1LBhM6dLgpchoAIAgCt2Onqb8v3S397+NXcHtev01zaQlQioAADgilhJZ3RyVCflUbzWuSqrfq/B8vfjSlHIegRUAABwRbaM7qNSSdt13AqXf8exKhCe2+mS4KUIqAAA4B/tmPm5qhyaplTLpVUNB6lalapOlwQvRkAFAACXdWzLEpVY/Kq9PaNIT11/y31OlwQvR0AFAACXlBgTLWvyQwpWshYHNNJ1PQfK5WLcKbIXARUAAGQsNUX7h3VS4bSj2q1IFe8+VqHBgU5XBR9AQAUAABnaPP4plY9fpTgrREduGaVSxSKdLgk+goAKAAD+Zvfcsaqya5y9Pb/6m2rYsKnTJcGHEFABAMAFTu76UxFzn7W3p+e7Xzfd08vpkuBjCKgAAOCc5LjjShz/gEKUpGX+ddSi18fyYzF+5DACKgAA+EtaqvYMe0ARqYe0zyqiQl3HKU9YiNNVwQcRUAEAgG3LpAGqELtEZ60g7b1huMqVKuV0SfBRBFQAAKC9i75W5a1f2NuzK76kZs1bO10SfBgBFQAAHxe7b4MK/vq4vT0zz526+YEnnC4JPo6ACgCAD0s9G6O4sR2VS2e1yq+6GvUaLH8mRcFhBFQAAHxVWpp2DuusYin7FG0VUNgDXypfnlxOVwUQUAEA8FVbv31TFU/OU6IVoC2tP1flCuWdLgmwEVABAPBBB1f8oArrP7a3fy3znFq1udnpkoBzCKgAAPiYuOhtyv1TH/m5LP0WdrNu6vK80yUBFyCgAgDgQ9IS4nRy1H0KV5zWuSqpdq9hCvQnDsC98BMJAICvsCxtH9FVJZN26piVV34dv1ShfOFOVwX8DQEVAAAfsfXbN1Tp2G9Ksvy1tul/Vb1KFadLAjJEQAUAwAfsXzpVFdb9NSlqZulndF27O5wuCbgkAioAAF4udt965f/lr0lRs3Ldppu6DnC6JOCyCKgAAHixlPiTih97n32lqNV+1VT/0S+YFAW3x08oAADeKi1Vu7/opMiUAzpoFVTYQ18pf3hup6sC/hEBFQAAL7VlwnOqELtEZ60g7bp+mCqVK+d0ScAVIaACAOCFds8dq8rbR9rbcyq/qmYt2zpdEnDFCKgAAHiZE9uWKmLus/b29Lz36+ZO/Z0uCcgUAioAAF4kMSZaqRMfVIiStCygnlo8+rH8/FxOlwVkCgEVAAAvYaUk6sAX96lw2lHtVqQiHh6vPGEhTpcFZBoBFQAAL7F1TD+VO7NGp61QHb11jEoVL+Z0ScBVIaACAOAFdvzyqSrvn6I0y6WFUf9RgwaNnS4JuGoEVAAAPNzhdXNUaunr9vb0Ij3V7s4uTpcEXBMCKgAAHuzs0d0K/q6bApWq+UEt1faRd+VyMSkKno2ACgCAh7KS4nV0xD3KZ8Voi8qoUq/RCgkKcLos4JoRUAEA8ESWpW3DuqpU4jadsPIo6Z4vFVGokNNVAVmCgAoAgAfaOuVVVTo2S8mWv1Y3+UQ1a9RyuiQgyxBQAQDwMHsXTFSljZ/a2zPKPK/rbrrb6ZKALEVABQDAg5zYvlxFfnvc3p6Z507d3OV5p0sCshwBFQAAD5Fw4oDSJnSyL2O63L+OmvQZogB//pTD+/BTDQCAB7CSzyp62N0qlHZMO1VcRXtMVHhYqNNlAdmCgAoAgLuzLG0d/rDKJGzSKSuXYu4Yp1LFIp2uCsg2BFQAANzc1m/fUOUjv9gz9lc2+kR16tR3uiQgWxFQAQBwY3sWTlGl9R/Z2zNLPa3rb7nX6ZKAbEdABQDATZ3YsVKFZ/W3t2flvl03dXvR6ZKAHEFABQDADSWcPKSUrzoqTAla4R+lhn2GMWMfPoOfdAAA3IyVnKBDw+5RkbSj2qNIFX54ovLmYsY+fAcBFQAAd2JZ2jKih8qeXa8YK5eOtx+n0iWKO10VkKMIqAAAuJGtU/+tKod/Uorlp+UNPlTdeg2dLgnIcQRUAADcxN7F36nCmkH29oyST6jtbZ2cLglwBAEVAAA3cGLXahWa2Ud+Lkuzc92qm7q94nRJgGMIqAAAuMOM/S/vtWfsr/Kvqfq9RyggwN/psgDHEFABAHBQWuIZHfriLhVJO6I9ilC+bhOUN0+Y02UBjiKgAgDglLQ0bR3WRWUTNuqUmbF/x3iVLVnK6aoAxxFQAQBwyKaJL6jK8VlKsvy1qulnqlungdMlAW6BgAoAgAN2zBquqtu+sLdnlX9Rbdrd5XRJgNsgoAIAkMMOrZmtUgv/ZW/PyP+Abn7oGadLAtwKARUAgBwUe2CzwqZ2VaBStTComVr1/lR+fi6nywLcCgEVAIAcknT6uOJG3aW8Oq0Nroqq2PsrhQYHOl0W4HYIqAAA5AArJVF7h96tYqkHdNAqpKDOk1SkQH6nywLcEgEVAIDsZlnaPOIRVYhfpdNWqPbfMkYVy1VwuirAbRFQAQDIZpu/fUtVo79XquXS0nqD1LBRC6dLAtwaARUAgGy0a/4EVVn/gb09o9TTanv7Q06XBLg9AioAANnk8KZFipzzhL39W54OuunhV5wuCfAIBFQAALJB3OFdCvj6AYUoScsC6qtx3y/kz3JSwBUhoAIAkMVSzpzSyRF3qqB1UttUSiV7TVLu0BCnywI8BgEVAIAsZKUma8fQTiqZvEtHrbxK6TRJkUUKO10W4L0BdeDAgWrQoIHy5MmjIkWKqEOHDtqyZcs/Pm/KlCmqUqWKQkJCVLNmTU2fPv2Cxy3L0quvvqrIyEiFhoaqbdu22rZtW+bfDQAATrIsbRrVW5VjF+usFaRt149Q1SrVna4K8O6AOm/ePPXr109LlizRrFmzlJycrBtvvFHx8fGXfM6iRYt0//33q0ePHlq1apUdas1t/fr1545577339Omnn2ro0KFaunSpcuXKpXbt2ikhIeHa3h0AADlo87dvq9qBb5RmubQg6l01bXmj0yUBHsllmebLq3T06FG7JdUE15YtW2Z4TMeOHe0A+9NPP527r3Hjxqpdu7YdSM2XL1asmJ555hk9++yz9uMxMTEqWrSoxowZo06dOv3tNRMTE+1butjYWJUsWdJ+Xnh4+NW+HQAArtrO38ep3LzH7O1fij+hm3q+IZeLSVHA+Xktb968V5TXrmkMqvkCRoECBS55zOLFi+0u+/OZ1lFzv7Fr1y5FR0dfcIwpvlGjRueOyWiogTkm/WbCKQAATjm4do5KzHvK3p4Vfpdu7EE4Ba7FVQfUtLQ0Pfnkk2rWrJlq1KhxyeNM+DStoecz++b+9MfT77vUMRcbMGCAHY7Tb/v27bvatwEAwDU5uXeDcn3XRUFK0eKgJmrWdyjLSQHXKOBqn2jGoppxpAsWLFBOCw4Otm8AADgp4VS0EsfcpQid1ka/iqrQe6LCQvj7BDjSgtq/f397TOnvv/+uEiVKXPbYiIgIHT58+IL7zL65P/3x9PsudQwAAO4mNfGMDg7poIi0aO1XEYV2+UaFC+R3uizA9wKqmdBkwunUqVM1Z84clS1b9h+f06RJE82ePfuC+8wKAOZ+w7yGCaLnH2MG0ZrZ/OnHAADgVtJStXXI/SqXuEmnrFw6fscElS1TxumqAN/s4jfd+hMmTND3339vr4WaPkbUTFQy65caXbp0UfHixe2JTMYTTzyhVq1a6YMPPtCtt96qSZMmacWKFRo2bJj9uBlEbsayvv3226pYsaIdWF955RV7Zr9ZjgoAAHezYczjqn5qrhKtAK1rMUQt6jRwuiTAdwPqkCFD7H9bt259wf2jR49Wt27d7O29e/fKz+//G2abNm1qh9qXX35ZL774oh1Cp02bdsHEqueff95eiqpXr146deqUmjdvrhkzZtgL+wMA4E42TXtf1feOt7fnVXtTN7a9w+mSAK9zTeugeuK6WgAAXK2dC75WmVm95OeyNCPiUbV79D8sJwW42zqoAAD4iugNC1Xst352OP09961q23Mg4RTIJgRUAAD+QcyBbQr65n6FKEkrAuupQb9RCgjwd7oswGsRUAEAuIyE2GOKG9VBBawYbXWVValHv1buUOZIANmJgAoAwCWkJSVo35A7VTx1v6KtgvJ7aIqKFCrkdFmA1yOgAgCQkbQ0bR7ygCqeXavTVqiib/tSFcpXdLoqwCcQUAEAuJhlad3o/qp2craSLH+tbvqZajdo5nRVgM8goAIAcJEN376jmvu+srfnV3tTLdrd43RJgE8hoAIAcJ6tv41S9fXv2dszi/XT9ff1c7okwOcQUAEA+J89K35R2T+etbfn5LtLbXu8zVqngAMIqAAASDq8bYUK/tRdga5ULQ5poaZ9h8nfnz+TgBP4zQMA+LyYQzvkP+Fe5dYZrfGvoWp9JyokKNDpsgCfRUAFAMjXF+I/PeIOFbJOaIerpIo88q3yhudxuizApxFQAQA+KzXxjPZ/fodKpO5TtApKD36ryIgIp8sCfB4BFQDgk6zUFG35vKMqJKxXrBWmw+3Hq3yFyk6XBYCACgDwSZal9SN7q1rMfCVaAdrQcqii6jV1uioA/0NABQD4nHWTX1fNg1OUZrm0KOodNbn+DqdLAnAeAioAwKds+mWoam7+2N6eXfpJtbnrUadLAnARAioAwGfsXPK9Kix50d6eXaCTru/2mtMlAcgAARUA4BMObVqsiBm97IX4F4a2UYs+g+Xnx1WiAHdEQAUAeL3jezcqZHJHhSlBqwKiVKv/VwoKDHC6LACXQEAFAHi100f3KnlMB+VXjLa4yqnEo98qT65cTpcF4DIIqAAAr5UQe1wnv2iviLTD2qsIhXWfqsKFCztdFoB/QEAFAHillIR47fv8dpVK2a2jVj6d7fiNSpYs43RZAK4AARUA4HWs1GRtHXyvKv7vKlEH23+lylVrOl0WgCtEQAUAeN9VooZ2VbXTC5VgBWpT6+GKqt/c6aoAZAIBFQDgVdaMeVI1j/6sFMtPy+p/oEZtbnO6JACZREAFAHiNdVPeVtSeMfb2/Movq2X7rk6XBOAqEFABAF5h4y9fqOaG9+3t34r3VZv7n3a6JABXiYAKAPB42xZ8q0pLXrC3f89/n67r/m+5XFwlCvBUBFQAgEfbu+Z3lfittwJcaVqU63o17zdEfv78eQM8Gb/BAACPFb19lfJOfUihStLKoPqq3f8rBQZwCVPA0xFQAQAe6eSB7fL/6m7lVZw2+ldW+b7fKCw01OmyAGQBAioAwOPEnYxW/KjbVdg6rl2ukirQa5ry5cvvdFkAsggBFQDgURLiTurw5+1VIvWADqmQXF2+U0TRYk6XBSALEVABAB4jJSFeez67Q+WTt+qklUcxd09WmbKVnC4LQBYjoAIAPEJacpI2f3aPKiesUZwVqr23fKkqNes7XRaAbEBABQC4PSstVes/f1A14hYpwQrUpjbDFNWojdNlAcgmBFQAgHuzLK0Z1ku1Tv6qZMtffzb+RA1a3+50VQCyEQEVAODWVo19VrWjv1Ga5dLiqH+r6c0POl0SgGxGQAUAuK01k95Und0j7O15Ff+llnf1cbokADmAgAoAcEvrfvhUUZs/sLd/L95brR98wemSAOQQAioAwO1s/G2sqq981d6eW+h+te4xUC6Xy+myAOQQAioAwK1sWzhVFf54Sn4uSwvCb1WLPp/L5cefK8CX8BsPAHAbu/6crRKzeinIlaolYa3VsP9Y+fvzpwrwNfzWAwDcwv6NS1Toh4cUqiT9GVRfUY9NUlBQoNNlAXAAARUA4LjDu9Yr19f3Ko/OaH1ANZXv/51CQ0OdLguAQwioAABHnTi4Uxp3h/IrVtv8yiqy9/fKG57X6bIAOIiACgBwTOyxA4of0V5FrWPa4yqm3D1/UMFCRZwuC4DDCKgAAEfEnTqqE0NuUcm0/YpWIanzNEUWK+V0WQDcAAEVAJDjEuJOKnrwLSqTultHlU9xnb5T6XKVnS4LgJsgoAIAclTimVjt+e9tqpC8VSetPDp+1xRVqBLldFkA3AgBFQCQY1ISz2jHf+9Q5cT1irXCdPD2CapSq6HTZQFwMwRUAECOSE1O0qb/3q1qZ/9UvBWsXe3Gqnq9lk6XBcANEVABANnOSk3R+s86qmbcIiVYgdrSZriimt7odFkA3BQBFQCQray0VK0Z3FlRMXOUZPlrbbPBqtv6DqfLAuDGCKgAgGxjpaVp1RePqPaJ6Uqx/LSiwQdqeGNHp8sC4OYIqACA7GFZWjXycdU9/K3SLJeWRP1bTW972OmqAHgAAioAIFusHPeC6h740t5eWPVlNb+rr9MlAfAQBFQAQJb7c+IbqrdrqL09r9wzatHpWadLAuBBCKgAgCy1+tv3VXfLh/b2vBJ91LLzK06XBMDDEFABAFlmzY+DVXvd2/b2/KJd1LLHQLlcLqfLAuBhCKgAgCyxbsZI1Vjxkr39R8F71LzXJ4RTAFeFgAoAuGbrZ41V1cXPyt9laWHe29S073D5+fMnBsDV4f8eAIBrsmH2BFVe8JQCXGlanOcmNXpsrPwJpwCuAf8HAQBctU1zv1bF+f0V6ErVktxtVf/x8QoICHC6LAAejoAKALgqm//4TuV/76MgV6qW5mqjuo9PVGBgoNNlAfACBFQAQKZtWfSDyv7WS0GuFC0PbaHaj09SUFCQ02UB8BIEVABApmxdOl2lZvZQsCtZK0OaqOYTUxQcHOJ0WQC8CAEVAHDFtq+YpRLTuynUlaRVwQ1V7fHvFBIS6nRZALwMARUAcEV2/DlHkT89pDBXolYH1VXlJ6YqNCzM6bIAeKFMB9T58+erffv2KlasmL0A87Rp0y57fLdu3ezjLr5Vr1793DGvv/763x6vUqXK1b0jAECW27Vmnor88IByKUFrg6JU4fEfFBaW2+myAHipTAfU+Ph4RUVFafDgwVd0/CeffKJDhw6du+3bt08FChTQvffee8FxJrCef9yCBQsyWxoAIBvsWb9IBaferzw6q/WBNVS2/w/KnTuP02UB8GKZXqzu5ptvtm9XKm/evPYtnWlxPXnypB5++OELCwkIUERERGbLAQBko70blyrvN/cqXPHaGFBNJfv/pDzh+ZwuC4CXy/ExqCNHjlTbtm1VunTpC+7ftm2bPWygXLlyevDBB7V3795LvkZiYqJiY2MvuAEAstb+LSuV5+t7lE9x2uRfWcX6/aS8efM7XRYAH5CjAfXgwYP65Zdf1LNnzwvub9SokcaMGaMZM2ZoyJAh2rVrl1q0aKHTp09n+DoDBw481zJrbiVLlsyhdwAAvuHAttUKm3in8itWW/wrKKLvz8qXv6DTZQHwES7LsqyrfrLLpalTp6pDhw5XdLwJlh988IEdVC+3oPOpU6fsFtYPP/xQPXr0yLAF1dzSmRZUE1JjYmIUHh5+le8GAGAc2LpKIRM6qKBOabtfWeXvM0MFCzMEC8C1MXnNNCxeSV7LsQsmmxw8atQode7c+R+vNpIvXz5VqlRJ27dvz/Dx4OBg+wYAyN5wmrf3dMIpAO/t4p83b54dODNqEb1YXFycduzYocjIyBypDQDwVzgNnXDHBeG0cJFiTpcFwAdlOqCa8Lh69Wr7ZpjxomY7fVLTgAED1KVLlwwnR5mxpjVq1PjbY88++6wdYHfv3q1FixbpzjvvlL+/v+6///6re1cAgEzZv+VPO5wWUIwdTvP1/oVwCsAxme7iX7Fihdq0aXNu/+mnn7b/7dq1qz3RyaxhevEMfDPW4Ntvv7XXRM3I/v377TB6/PhxFS5cWM2bN9eSJUvsbQBA9ofTsIkmnMZqm1855e89XYWK0IMFwEMnSXnioFsAwP/bt3mlck3qcF44/UWFijDmFICPTJICALiXfZtXKNekO8+F0wJ9fmFCFADfXKgfAOBu4bQ84RSAWyGgAoCP2bd5uXJfEE5ZSgqAe6GLHwB8LpzeZV8haqt/BRXqM10FChV1uiwAuAAtqADgI/ZuXEY4BeARaEEFAB8Jp+Ff36V8Ok04BeD2CKgA4GPhtHDfGcpfkHWmAbgvuvgBwIvtXrdI4V/fSTgF4FEIqADgpXaunqcC396jfIrTFv9KhFMAHoOACgBeaPuKWSoyraPCFa+NAdVUtD/hFIDnIKACgJfZsvQXFfvxQeXWWa0LrKUSj09XvvwFnS4LAK4Yk6QAwItsXviDSv/aQ6GuJK0Jqqvyj3+v3Lkvf81rAHA3tKACgJfYOO8blf21ux1OVwU3VMUnfyScAvBIBFQA8ALr50xUhTmPKtiVrJWhTVX1ye8VFpbb6bIA4KoQUAHAw639dZwqz+unIFeKVoS1VI0npyokNMzpsgDgqhFQAcCDrZk+QtUWPqFAV6qW5b5etZ78VsHBIU6XBQDXhIAKAB5q9Y+fq8bSZxXgStOS8JtU54nJCgoKcrosALhmBFQA8EB/TvtYtVa8KH+XpcX52qvBExMUGBjodFkAkCVYZgoAPMzKKe+r3oa3JZe0sMBdatxvpPz9aW8A4D0IqADgQVZMelv1N79vby8o3ElNew+RH+EUgJchoAKAh1j+5UtqsOMze/uPiK5q3utjufwIpwC8DwEVANyclZamFaOeUoP9Y+z9P0o8oubd3yOcAvBaBFQAcGNWWqpWDu2lBke+sfcXlHtKLbq87nRZAJCtCKgA4KbSUpK1anAX1T85XWmWS4urvqTmnZ5zuiwAyHYEVABwQylJCVr/346qd3quUiw/rajzbzXr0NfpsgAgRxBQAcDNJJ2N15b/3qXaZ5Yo0QrQmkYfqvEtXZ0uCwByDAEVANxIQnyMdn56u2omrtZZK0gbW36uhtff63RZAJCjCKgA4CbiYo7rwGe3qlryJsVZodpxw0jVa36r02UBQI4joAKAG4g5dlDHh96qyik7FWPl0oH2XymqfhunywIARxBQAcBhxw/uVtyI21QubZ+OK69O3PW1qkU1drosAHAMARUAHHRk7xaljL5dpa1oHVZBxXeaqopVopwuCwAcRUAFAIcc2L5GgePvVDEd135FyOryvcqVq+J0WQDgOAIqADhgz4YlyjPlPhVQjHa5Siqkx4+KLFHW6bIAwC0QUAEgh21bPksRP3dRHp3RNr9yytfrRxWOKOF0WQDgNgioAJCDNs6borJz+irUlaQNgdVVrM8Pyl+gkNNlAYBbIaACQA5Z88sIVVvyvAJdqVoV0lCV+n+rXLnDnS4LANwOARUAcsDKb95XnXX/lp/L0rLc1yvqsQkKDg5xuiwAcEsEVADITpal5eNfVoMdn0kuaVH+DmrYb6QCAvjfLwBcCv+HBIBsYqWlaeWI/mpw8Ct7f0FkNzV75CO5/PycLg0A3BoBFQCyQVpKslZ93k31T/xk7y8o/7SaPfSqXC6X06UBgNsjoAJAFktOPKuN/71P9eLmK9VyaWnNN9T8niecLgsAPAYBFQCy0NnTp7RrcAdFJaxSkhWg1Y0/VNObuzpdFgB4FAIqAGSR0ycPK/rz9qqWvEXxVrC2tRmmhq07OF0WAHgcAioAZIETh3br9PD2qpi2V6eUWwdv+1K1G1zndFkA4JEIqABwjaJ3b5Q19g6Vto7oiAoo9t6vVa16A6fLAgCPRUAFgGuwe90ihX/bSQUUo32uSKnzNFUoV8XpsgDAoxFQAeAqbV70o0r+2lO5lKDtfmWVp+f3KlqstNNlAYDHI6ACwFVYO3O0qix6VkGuFK0LjFLJvlOVL39Bp8sCAK9AQAWATPpzynuqvf4d+bksrQhrqer9Jyk0LJfTZQGA1yCgAkAmLl26YsyzarB3pOSSFuXvoIZ9RyggMNDp0gDAqxBQAeBKL106tLsaHPvB3v+jxCNq3v09ufz8nC4NALwOARUA/kFSwhlt+uxe1YtbYF+6dHHVl9Si03NOlwUAXouACgCXERdzXPs/v0NRieuUaAVqTaNBan5LN6fLAgCvRkAFgEs4Eb1HscNvV5XU3TpthWpn2xFq2OI2p8sCAK9HQAWADBzasU4af5fKWEd0VPl0/M6Jiqrd1OmyAMAnEFAB4CK71sxXvqkPKr9i7atDpT30naqUr+Z0WQDgMwioAHCezQumqdRvvRSmRG31r6B8j0xTkYiSTpcFAD6F9VEA4H9W/zhE5Wd1t8Pp2qA6KvrYLMIpADiAFlQAsCytGP+y6u/4zF6Af2mu6xTV/yuFhIY5XRkA+CQCKgCflpaSolVfPKL6R7+z9xcUeUBNHv1M/v7+TpcGAD6LgArAZyWePa0tgzuqXtxCpVkuLaz4nJo/+KJcLpfTpQGATyOgAvBJscejFT30DtVK3mwvwL+64XtqcWt3p8sCABBQAfiiw7s3KXncXaqUdlAxVi7tvnGUGjW7yemyAAD/Q0AF4FN2r/1D4d89qKKK0UEVVvx9kxRVvb7TZQEAzkNABeAzNs7/RmVm91WYK1Hb/coqrPtUVSxR1umyAAAXIaAC8Amrv/9UNf58TQGuNK0JqqvSfb5RvvwFnS4LAJABAioAr2alpenPcS+o3u4v7DVOl+S5UbX7jVNISKjTpQEALoGACsBrpaYka82Qh1Xv+I/2/vyiXdSs1yfy9+ciegDgzgioALxSQnyMtg++V3XPLFWq5dLiKgPUotPzrHEKAB6AgArA65yI3qNTI+5UjZQdOmsFaW2Tj9T8poecLgsAcIUIqAC8yr7NyxU8uaPKWcd1QuE6cPMYNWp8vdNlAQAyIdMDsebPn6/27durWLFidlfZtGnTLnv83Llz7eMuvkVHR19w3ODBg1WmTBmFhISoUaNGWrZsWWZLA+DjNi+YpvyT2quIdVx7XMUV++Avqkk4BQDvD6jx8fGKioqyA2VmbNmyRYcOHTp3K1KkyLnHJk+erKefflqvvfaa/vzzT/v127VrpyNHjmS2PAA+atW0T1Rh1sPKrbNaF1hTufrMUZmKNZwuCwCQE138N998s33LLBNI8+XLl+FjH374oR555BE9/PDD9v7QoUP1888/a9SoUXrhhRf+dnxiYqJ9SxcbG5vpegB4BystVX+Ofkb19o3+axmp3G0V1fdLhYaFOV0aAOAq5dhaK7Vr11ZkZKRuuOEGLVy48Nz9SUlJWrlypdq2bfv/Rfn52fuLFy/O8LUGDhyovHnznruVLFkyR94DAPeSnHhGaz+5569waoYgRXZXg6emEE4BwMNle0A1odS0iH777bf2zYTJ1q1b2135xrFjx5SamqqiRYte8Dyzf/E41XQDBgxQTEzMudu+ffuy+20AcDOnTx7Wzg/aKipmjpItfy2o/qZaPvoRa5wCgBfI9ln8lStXtm/pmjZtqh07duijjz7Sl19+eVWvGRwcbN8A+KbDuzcqedzdqpx2ULFWmLa1/lzN29zpdFkAgCziSFNDw4YNtX37dnu7UKFC8vf31+HDhy84xuxHREQ4UR4AN7bjz9kKHnOjSqQd1CEVUvQ936se4RQAvIojAXX16tV2178RFBSkevXqafbs2eceT0tLs/ebNGniRHkA3NT6X8eoxPcdlU+ntcW/gqyes1WpZkOnywIAON3FHxcXd67109i1a5cdOAsUKKBSpUrZ40MPHDigcePG2Y9//PHHKlu2rKpXr66EhASNGDFCc+bM0a+//nruNcwSU127dlX9+vXt1lXzHLOcVfqsfgA+zrK0cuLrqrf1Y3um/sqQxqrYd7LCwzNeGQQA4GMBdcWKFWrTps0F4dIwAXPMmDH2Gqd79+69YJb+M888Y4fWsLAw1apVS7/99tsFr9GxY0cdPXpUr776qj0xysz4nzFjxt8mTgHwPanJiVr7RU/VO/aDvf9HgbvVqPcXCgoKdLo0AEA2cVmWZcnDmXVQzXJTZkZ/eHi40+UAyCLxp45p79C7VTVhtVItlxaWf1otOr9iX40OAOC9eS3bZ/EDwNU4vGuDkr+8V1XTDijeCtH6ph+pZbsHnC4LAJADCKgA3M72ZTNUaHoPFVWcolVIJ+/8Uo1qN3W6LABADiGgAnAra3/8TFVWvKogV6o2+1dS+MNTVLVEGafLAgDkIAIqALdgpaXqz9FPqd6+sfZM/WVhrVS1z3jlycO4cgDwNQRUAI5LPBOrLUMeUL3Tf9j78yO6qWnPDxQQwP+iAMAX8X9/AI46eXivTg6/U7VStivRCtDyqDfV8q5+TpcFAHAQARWAY/ZtWKzgbx5UOeu4Tlh5tOfGEWre7CanywIAOIyACsARm36foDLznlSoErXLVVJ6cJLqVKzhdFkAADdAQAWQsyxLqya9qajNH8nPZWl1UF2VevRrFShY2OnKAABugoAKIMekJJ7VumE9Vef4T/ZM/QX5O6h+72EKCQ52ujQAgBshoALIEbHHDip6+D2qk7jBvmzpgvLPqOVDL8nl5+d0aQAAN0NABZDtDmxepoDJD6iSdVSxVpg2N/9ErW64z+myAABuioAKIFttnPOVys5/yp4MtdcVqYR7J6hh9bpOlwUAcGMEVADZwkpL0+oJL6vO9sH2/urA2irea7JKFY5wujQAgJsjoALIckln47RpaBfViZlt788vcLcaPjqEyVAAgCtCQAWQpU5G79GJkXcrKnmbki1/La4yQC06PSuXy+V0aQAAD0FABZBl9qyZp9xTu6q8TtpXhtp13VC1bHWb02UBADwMARVAllj/y3BVXDJAwa5k7XSVsq8MVa9idafLAgB4IAIqgGtipaVq1ZhnVHfvaHvx/RXBjVS+9yTlz1/A6dIAAB6KgArgqiXEndL2oferbtwie39ukc5q1utjBQbwvxYAwNXjrwiAq3JszybFj+uoGql7lGgFanmtN9T67n5OlwUA8AIEVACZtnXR94r4tY8KKV5HlF+Hbh6p5o2vd7osAICXIKACuHKWpdWT31LNTR/K32Vpo39lhXeZqKjS5Z2uDADgRQioAK5IckKcNn7RTbVPzrInQy3Mc7Nq9x6pXLlyOV0aAMDLEFAB/KMTB7br1Oj7FJWyw158f2GFZ9TygQHy8/dzujQAgBcioAK4rJ3LZyr/zz1VTrH24vs72wxR69btnS4LAODFCKgAMmZZWvPdIFVbO1CBrlRt8yunwAcnqX75yk5XBgDwcgRUAH+TknhW64f3VO1jP9njTZeEtVHV3mOVNzyv06UBAHwAARXABWIO79WRkfepdtImpVou/VGmv1p0eVP+jDcFAOQQAiqAc/asmatc07qponVSMVYubW7+sVrfcJ/TZQEAfAwBFYBt3Y+fqfKK1xTkStFOV0mldfpKjapEOV0WAMAHEVABH5ealKC1I/qozpHv7PGmy0OaqcKj45U/fwGnSwMA+CgCKuDDTkXv0dFRHVUnaZPSLJfmF++p5t3fVUAA/2sAADiHv0KAj9q5Yqby/fSIKirGHm+6qemHat2uk9NlAQBAQAV8jmVp9TcDVWP9+wpwpWm7Xxm5On6pxpVrOV0ZAAA2AirgQ5LOnNbmYQ+r9qlZ9njTxbmuV7VHR7O+KQDArRBQAR9xbM8mxY3rpFqpu5Vs+WtB+afU6sGX5Mf6pgAAN0NABXzAlj++UbHZj6mQzuio8mnP9Z+rTctbnS4LAIAMEVABL2alpWr1+BdVZ+dQe3+Df1WFd/5K9cuUd7o0AAAuiYAKeKmzsSe084v7VSd+ib0/P18H1X90iMJCw5wuDQCAyyKgAl7o0JaVsiY/qOpph5RgBWpp9VfU8t7H5XK5nC4NAIB/REAFvMyGGSNUbsmLClWiDqiIjt82Uq0atHS6LAAArhgBFfCiS5auG9lXtQ9/a++vCqyryB7jVSuiuNOlAQCQKQRUwAucPLBdJ8bcr9rJW+393yMeVtPu7yk4KMjp0gAAyDQCKuDhti38TkVmPabyitMpK7c2NR2kNu3ud7osAACuGgEV8FBWaopWjx+gqJ3D5eeytNmvgoIeGK8mFao6XRoAANeEgAp4oLiT0do3/EHVObPCvmTp/Ly3q26vocqdK5fTpQEAcM0IqICH2btmrkKmdVdV67jOWMFaXvNVtby7H0tIAQC8BgEV8BSWpbXf/kdV172nQFeqdqu44u8cpVa1GztdGQAAWYqACniAxPhT2jr8YdU6Ncfu0l8a2lIVHhmjMgUKOl0aAABZjoAKuLno7auUPPEh1Uzdr2TLXwvKPqGWnV+Rv7+f06UBAJAtCKiAG9s4c7jKLn7JvirUEeXXvhuGqk3zm5wuCwCAbEVABdxQSkK81o/qo9pHvrf3VwdGqXDX8apXopTTpQEAkO0IqICbObJrnc5+9ZBqp+xWmuXSvMhuXBUKAOBTCKiAG9k4c4TKLH5JRZSg41ZebWvxkdq0vdvpsgAAyFEEVMBNuvQ3jOqjqP916a8NqKn8ncepcelyTpcGAECOI6ACDju6a73iv3pIUSm7znXpN3n4PYUE06UPAPBNBFTAQRtnjlTpxS+qsN2lH67tzT9SmxvucbosAAAcRUAFHJul31e1j0yz99cG1FD+h8apUZnyTpcGAIDjCKhADju6e4Pixz+o2uld+hFd1aS76dIPdro0AADcAgEVcLBLf1vzD9XmhnudLgsAALdCQAVyqkt/dD/VPjz1gi79xnTpAwDwNwRUIEe69M3C+zvp0gcA4AoQUIFstHHGcJVe8jJd+gAAZAIBFcgGifGntHlUb0Ud/+Vcl34+uvQBALgiBFQgi+3fsEiub3soKu2gUi2X5hfroSbdBrLwPgAAV4iACmQVy9KaKe+o2oYPFOhK1SEV1IHrPlWbVrc5XRkAAB6FgApkgbiT0do7oqui4pdILmlZcFOV7j5K9YtGOl0aAAAeh4AKXKOdy6Yr/Je+qmadVKIVqEUVnlbLB16Qv7+f06UBAOCRCKjAVUpLTtLar15QrV2j5OeytMtVQvG3D1Obus2cLg0AAI+W6Sae+fPnq3379ipWrJhcLpemTfvrWuKX8t133+mGG25Q4cKFFR4eriZNmmjmzJkXHPP666/br3X+rUqVKpl/N0AOOXFgm3YMaqXau0fa4fSPPLcq/xMLVINwCgBAzgfU+Ph4RUVFafDgwVccaE1AnT59ulauXKk2bdrYAXfVqlUXHFe9enUdOnTo3G3BggWZLQ3IEZtnj1Pg8JaqmLhRp61QzY96X82f/kr58uV3ujQAAHyzi//mm2+2b1fq448/vmD/nXfe0ffff68ff/xRderU+f9CAgIUERGR2XKAHJOcEKcNo/qp9pG/eg02+ldWcMdRalmphtOlAQDgVXJ8DGpaWppOnz6tAgUKXHD/tm3b7GEDISEh9jCAgQMHqlSpUhm+RmJion1LFxsbm+11w7dFb12ppMndVDt171+XKy3ykBp3H6TQ0BCnSwMAwOvk+DTjQYMGKS4uTvfdd9+5+xo1aqQxY8ZoxowZGjJkiHbt2qUWLVrYQTYjJrzmzZv33K1kyZI5+A7gUyxLa6cOUr4J7VQqda+OKp+WtRilNv0+I5wCAJBNXJZlWVf9ZJdLU6dOVYcOHa7o+AkTJuiRRx6xu/jbtm17yeNOnTql0qVL68MPP1SPHj2uqAXVhNSYmBh7IhaQFeKOH9Se0d1VPW6xvb8yqL4iuoxW8RIZt+wDAIBLM3nNNCxeSV7LsS7+SZMmqWfPnpoyZcplw6mRL18+VapUSdu3b8/w8eDgYPsGZJdtC79TwVlPqrpi/lrbtOxjav7QSwoMYGU2AACyW478tZ04caK6d+9uh9Rbb731H483QwB27Nihzp0750R5wDkpCfFaN/Yp1Tk02d7f4Sqls3d8oTZ1mjpdGgAAPiPTAdWEx/NbNs140dWrV9uTnsykpgEDBujAgQMaN27cuW79rl276pNPPrHHmkZHR9v3h4aG2s28xrPPPmsvPWW69Q8ePKjXXntN/v7+uv/++7PunQL/4NDm5Uqe0kN1UvfY+/Py36063T9WeB6GjQAA4NaTpFasWGEvD5W+RNTTTz9tb7/66qv2vlnDdO/eveeOHzZsmFJSUtSvXz9FRkaeuz3xxBPnjtm/f78dRitXrmxPnipYsKCWLFliL+4PZDcrLVVrvv63Ck68SaVS9+iYlVeLm3yhVk+MIpwCAOBpk6Q8cdAtcL7Yw3t1YOzDqnpmhb2/IriRIjuPYCIUAAC+MEkKcDebf5+oiHnPqapO66wVpCUVn1bL+/8lf/8cX30NAACch4AKn5N05rQ2jul/7opQW/3KKfXOYWpTs4HTpQEAAAIqfM2+DYvk+ranaqcdsK8INb/w/WrQ/QPlCgtzujQAAPA/BFT4BCs1RWu+flPVN3+mQFeqDquAdrf8UK2vv9Pp0gAAwEUIqPB6Jw5s19Evu6t2whrJJS0Lba7S3UaoUdFIp0sDAAAZIKDCe1mW1k8fqjLL31BlnVW8FawVVQeoxb1PyI+JUAAAuC0CKrxS3IlD2jXmEdWM/cPe3+BfVUH3fKFWVaOcLg0AAPwDAiq8ztb5X6vQnGdVUzFKsvy1sGQvNen8pkKCg5wuDQAAXAECKrxGYvwpbTLLRx390d7f6Sqp+NuGqE39Fk6XBgAAMoGACq+we+UsBf/cT7XTDtvLR/1RuKPqdhukcrnzOF0aAADIJAIqPFpqUoLWfvm8ovaOk5/L0kEV1oE2H6pV69udLg0AAFwlAio81qEtK5Q4pafqpOyyl49akPsmVX14sBoULOR0aQAA4BoQUOGhi+6/peqb/2svun/cCtfmBm+r2a1d5HK5nC4PAABcIwIqPMqxfZt1YnwP1U5cb7eaLg9urGKdh6tZiVJOlwYAALIIARWes+j+T/9V2ZX/ViUlKM4K0cqqL7DoPgAAXoiACrcXe3iv9n3ZSzXiFtv76wJqKNd9w9SqUnWnSwMAANmAgAr3ZVnaMHO4Si55XdUVr0QrQItL91bTh15XUFCg09UBAIBsQkCFW4o9ul97xz2qGqcX2Pub/SrIumOIWkc1dLo0AACQzQiocC+WpY2zxqj4opdVQ3H2pUoXlXxEje1LlQY7XR0AAMgBBFS4jbgTh7Rr7KOqGTPP3t/qV07Jt32m1nWbOV0aAADIQQRUuIVNs8cr4o8BqqlYJVv+WljsYTXq8m+FhoY4XRoAAMhhBFQ4Kv7kEe0Y21u1Ts2293e4SuvMrZ+pdYOWTpcGAAAcQkCFYzbPnaTCc/+lWjqlFMtPCyM6q0G3dxUWGuZ0aQAAwEEEVOS4MzHHtG1sP0WdmGHv73KVVOwtn6pVw+ucLg0AALgBAipy1JY/vlHBOc8qyjqpVMulBUUfVL2u/1HZXLmdLg0AALgJAipyxNmY49oy7jHVPv6zvb/HVVwn232iVk1ucLo0AADgZgioyHab5k5U4XkDVNs6qTTLpT8Kd1Sdru+rdJ5wp0sDAABuiICKbF3XdOe4fudm6JtW0+NtP1Sr5jc5XRoAAHBjBFRkPcvShlmjVWzRa6ql2L9m6Bd9QHW7vKvSufM4XR0AAHBzBFRkqZjDe7Xvy96qEbfQ3t/uV0ZnbvpErRq2dro0AADgIQioyBqWpXU/DVaZlf9WDZ1RkuWvxSW6q+FDbyk0NNTp6gAAgAchoOKaHd+/TUcmPKqaZ1ba+5v9Kirtjs/UKqqx06UBAAAPREDFVbPSUrV26iBVXPeBqipRCVaglpbpo8YPvqzgoGCnywMAAB6KgIqrcnjXesVMelRRievt/fUB1RV812C1qlbH6dIAAICHI6AiU9JSkrVmytuqunmwirqSFW8Fa0XFJ9W00/MKDODHCQAAXDsSBa7YwS3LdfabvqqTvFVySasD6yhfx8/VqkI1p0sDAABehICKf5ScEK91E15SzT3jFOhKVawVptXVn1ezu5+Qv7+f0+UBAAAvQ0DFZe1YNl0hM55W3bRDdqvp8pBmirz/v2pZurzTpQEAAC9FQEWG4k8d1dbxT6rOsZ/s/SPKrx31X1fjW7vK5XI5XR4AAPBiBFRkcJnSMYpc9JrqKMa+a0G+O1St8wdqUrCw09UBAAAfQEDFOScO7tDBr/qqRvwSe3+Xq4ROXj9IzZvf7HRpAADAhxBQISs1Rau/fU+VN36sGkr86zKlxR9Wg4feVNmwXE6XBwAAfAwB1ccd2LxCZ781S0dtsfc3BFRT4B3/Vaua9Z0uDQAA+CgCqo9KTjyjtV+9pFp7xtpLR522QrWq8lNqet8zCmDBfQAA4CCSiA/avnS6QmY+o3ppB+2lo5aFNlexTp+oZekKTpcGAABAQPUlcSePaNv4p1Tn+PlLR72hxrd2YekoAADgNgioPsBKS9O6n4eo1MqBqqPT9n0sHQUAANwVAdXLHdq+WjFTHlOtxLX2/k5XKcW2HaTmzdo5XRoAAECGCKheKjkhXmsnvKKae8Yo0pWqs1aQlpfppYb3v6JyISFOlwcAAHBJBFQvtGXhVOWZ/YLqpUXbk6BWBjdSwXs/UcsKVZ0uDQAA4B8RUL3IqcN7tWfCE4qKmWPvH1YB7az/mhrf0kUuPz+nywMAALgiBFRvuRLU1A9VYf1HitIZpVouLSp0r2o+9B81yV/A6fIAAAAyhYDq4fZtWKTEaU+oTvJWe3+zfyWl3vKhWtRr4XRpAAAAV4WA6qES4k5p/Vf/Up2Dk+XvsuwrQa2u/IQa3/usAgMDnS4PAADgqhFQPY1lacPs8Sq88DXVt47bk6CW5mqjEp0+UouSZZ2uDgAA4JoRUD3IkT0bdXTyk6p+Zqm9v08Rim7+thpefw9XggIAAF6DgOoBks7Ga+2k11Rr92gVcaUo0QrQ0siHVPeht1Uydx6nywMAAMhSBFQ3t2nuZOWb97LqW0fs7vzVQXWVu8NHalmtttOlAQAAZAsCqps6umezor9+UjXjF9v70SqoXfVeVqNbusnPnzVNAQCA9yKgupnkxDNaM+kN1dg5UoVdyUqy/LU04n7VeuDfapI3n9PlAQAAZDsCqhvZNP8b5f39JdW3/rpE6ZrA2grt8KFaVK/ndGkAAAA5hoDqBo7t26qDk59UrbiF9v4RFdD2ui+q8a096M4HAAA+h4DqoJTEs1o9+S1V3zFctVxJSrb8taTIfar5wDtqyiVKAQCAjyKgOmTzH1OV+/cXVT/toN2dvy6wloJv/0AtajZ0ujQAAABHEVBz2FHTnf/1M4o6Pf+vfeXXttovqHH7XnTnAwAAEFBzTuLZ01pnZufvHqMoV7JSLD8tKXyvqj8wUE0LFHS6PAAAALdBQM1ulqX1v41ToUVvqb511O7OX2u6828bpOZRjZyuDgAAwO0QULPR/s0rdHraM6qRsNreP6RC2l3vJRbbBwAAuAwCajaIO3VMmycOUO3ob1TClaYEK1DLi3dR7ftfU5M8eZ0uDwAAwK0RULOQlZqi1T98qrJrPlR9nba785eHtlCRe95Xi/JVnS4PAADAI2S6n3n+/Plq3769ihUrJpfLpWnTpv3jc+bOnau6desqODhYFSpU0JgxY/52zODBg1WmTBmFhISoUaNGWrZsmTzJjhW/adfAhqqz5g3l02ntdJXSn63HqP7zP6o04RQAACD7Amp8fLyioqLsQHkldu3apVtvvVVt2rTR6tWr9eSTT6pnz56aOXPmuWMmT56sp59+Wq+99pr+/PNP+/XbtWunI0eOyN2dPLRbqz6+R+V/ulvlUnYo1grTHxWeVfEXlqtu6zvtEA8AAIAr57Isy7rqJ7tcmjp1qjp06HDJY/71r3/p559/1vr168/d16lTJ506dUozZsyw902LaYMGDfTZZ5/Z+2lpaSpZsqQee+wxvfDCC/9YR2xsrPLmzauYmBiFh4crx64CNWWgqm0fqjAlKs1yaUm+W1W+039UNLJEjtQAAADgKTKT17J9DOrixYvVtm3bC+4zraOmJdVISkrSypUrNWDAgHOP+/n52c8xz81IYmKifTv/DeekTQumKXzOC6qfdsje3+hfRdbN76lp/VY5WgcAAIA3yva1jqKjo1W0aNEL7jP7JlSePXtWx44dU2pqaobHmOdmZODAgXYCT7+Z1tacdPLANhVPO2RfBWphrXdU+cXFqk44BQAAyBIeuRinaW01zcPpt3379uXo129415P6o+yTCnziTzW7q5/8WdMUAAAgy2R7F39ERIQOHz58wX1m34w9CA0Nlb+/v33L6Bjz3IyY1QDMzSkBgYFq0fUNx74+AACAN8v2pr8mTZpo9uzZF9w3a9Ys+34jKChI9erVu+AYM0nK7KcfAwAAAN+R6YAaFxdnLxdlbunLSJntvXv3nut+79Kly7nje/furZ07d+r555/X5s2b9fnnn+vrr7/WU089de4Ys8TU8OHDNXbsWG3atEl9+vSxl7N6+OGHs+ZdAgAAwHu7+FesWGGvaXp+uDS6du1qL8B/6NChc2HVKFu2rL3MlAmkn3zyiUqUKKERI0bYM/nTdezYUUePHtWrr75qT4yqXbu2vQTVxROnAAAA4P2uaR1Ud+HEOqgAAADInrzG9HMAAAC4FQIqAAAA3AoBFQAAAG6FgAoAAAC3QkAFAACAWyGgAgAAwK0QUAEAAOBWCKgAAABwKwRUAAAAuBUCKgAAANwKARUAAABuhYAKAAAAt0JABQAAgFshoAIAAMCtEFABAADgVgioAAAAcCsEVAAAALgVAioAAADcCgEVAAAAboWACgAAALcSIC9gWZb9b2xsrNOlAAAAIAPpOS09t3l9QD19+rT9b8mSJZ0uBQAAAP+Q2/LmzXu5Q+SyriTGurm0tDQdPHhQefLkkcvlyrFPASYQ79u3T+Hh4TnyNZF1OH+ej3Po+TiHno9z6Nlic/j8mchpwmmxYsXk5+fn/S2o5k2WKFHCka9tTii/lJ6L8+f5OIeej3Po+TiHni08B8/fP7WcpmOSFAAAANwKARUAAABuhYB6lYKDg/Xaa6/Z/8LzcP48H+fQ83EOPR/n0LMFu/H584pJUgAAAPAetKACAADArRBQAQAA4FYIqAAAAHArBFQAAAC4FQIqAAAA3AoB9TIGDx6sMmXKKCQkRI0aNdKyZcsue/yUKVNUpUoV+/iaNWtq+vTpOVYrru38DR8+XC1atFD+/PntW9u2bf/xfMP9fgfTTZo0yb7scYcOHbK9RmTtOTx16pT69eunyMhIe+mbSpUq8f9SDzp/H3/8sSpXrqzQ0FD7EppPPfWUEhIScqxeXGj+/Plq3769fWlR8//EadOm6Z/MnTtXdevWtX//KlSooDFjxsgRZpkp/N2kSZOsoKAga9SoUdaGDRusRx55xMqXL591+PDhDI9fuHCh5e/vb7333nvWxo0brZdfftkKDAy01q1bl+O1I/Pn74EHHrAGDx5srVq1ytq0aZPVrVs3K2/evNb+/ftzvHZc3TlMt2vXLqt48eJWixYtrDvuuCPH6sW1n8PExESrfv361i233GItWLDAPpdz5861Vq9eneO1I/Pn76uvvrKCg4Ptf825mzlzphUZGWk99dRTOV47/jJ9+nTrpZdesr777juzpKg1depU63J27txphYWFWU8//bSdZf773//a2WbGjBlWTiOgXkLDhg2tfv36ndtPTU21ihUrZg0cODDD4++77z7r1ltvveC+Ro0aWY8++mi214prP38XS0lJsfLkyWONHTs2G6tEVp9Dc96aNm1qjRgxwuratSsB1cPO4ZAhQ6xy5cpZSUlJOVglsur8mWOvu+66C+4zQadZs2bZXiv+2ZUE1Oeff96qXr36Bfd17NjRateunZXT6OLPQFJSklauXGl386bz8/Oz9xcvXpzhc8z95x9vtGvX7pLHw73O38XOnDmj5ORkFShQIBsrRVafwzfffFNFihRRjx49cqhSZOU5/OGHH9SkSRO7i79o0aKqUaOG3nnnHaWmpuZg5bja89e0aVP7OenDAHbu3GkPz7jllltyrG5cG3fKMgE5/hU9wLFjx+z/IZr/QZ7P7G/evDnD50RHR2d4vLkf7n/+Lvavf/3LHrNz8S8q3PccLliwQCNHjtTq1atzqEpk9Tk0gWbOnDl68MEH7WCzfft29e3b1/6waC7HCPc+fw888ID9vObNm5veWaWkpKh379568cUXc6hqXKtLZZnY2FidPXvWHlucU2hBBS7y7rvv2pNspk6dak8MgPs7ffq0OnfubE92K1SokNPl4CqlpaXZLeDDhg1TvXr11LFjR7300ksaOnSo06XhCpjJNabF+/PPP9eff/6p7777Tj///LPeeustp0uDB6IFNQPmD5y/v78OHz58wf1mPyIiIsPnmPszczzc6/ylGzRokB1Qf/vtN9WqVSubK0VWncMdO3Zo9+7d9mzV88OOERAQoC1btqh8+fI5UDmu5ffQzNwPDAy0n5euatWqdquO6XIOCgrK9rpx9efvlVdesT8o9uzZ0943q9nEx8erV69e9gcNM0QA7i3iElkmPDw8R1tPDX5aMmD+J2g+vc+ePfuCP3Zm34yPyoi5//zjjVmzZl3yeLjX+TPee+89+5P+jBkzVL9+/RyqFllxDs3ybuvWrbO799Nvt99+u9q0aWNvm+Vu4P6/h82aNbO79dM/XBhbt261gyvh1P3Pnxm7f3EITf+w8dccHbi7Ju6UZXJ8WpYHLa9hlssYM2aMvdRCr1697OU1oqOj7cc7d+5svfDCCxcsMxUQEGANGjTIXqbotddeY5kpDzp/7777rr2cyjfffGMdOnTo3O306dMOvgvfltlzeDFm8XveOdy7d6+9ekb//v2tLVu2WD/99JNVpEgR6+2333bwXfiuzJ4/83fPnL+JEyfayxX9+uuvVvny5e1VbuCM06dP28snmpuJfB9++KG9vWfPHvtxc/7Mebx4mannnnvOzjJm+UWWmXJDZv2vUqVK2cHFLLexZMmSc4+1atXK/gN4vq+//tqqVKmSfbxZpuHnn392oGpczfkrXbq0/ct78c38Dxee8zt4PgKqZ57DRYsW2Uv0mWBklpz697//bS8fBvc/f8nJydbrr79uh9KQkBCrZMmSVt++fa2TJ086VD1+//33DP+2pZ838685jxc/p3bt2vY5N7+Do0ePdqR2l/lPzrfbAgAAABljDCoAAADcCgEVAAAAboWACgAAALdCQAUAAIBbIaACAADArRBQAQAA4FYIqAAAAHArBFQAAAC4FQIqAAAA3AoBFQAAAG6FgAoAAAC5k/8DM2iGZydAHzYAAAAASUVORK5CYII=", - "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -506,10 +418,10 @@ "pts = pinn.problem.spatial_domain.sample(256, \"grid\", variables=\"x\")\n", "predicted_output = pinn.forward(pts).extract(\"u\").tensor.detach()\n", "true_output = pinn.problem.solution(pts).detach()\n", - "fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(8, 8))\n", + "fig, ax = plt.subplots(nrows=1, ncols=1)\n", "ax.plot(pts.extract([\"x\"]), predicted_output, label=\"Neural Network solution\")\n", "ax.plot(pts.extract([\"x\"]), true_output, label=\"True solution\")\n", - "plt.legend()" + "_=plt.legend()" ] }, { @@ -517,120 +429,18 @@ "id": "bf47b98a", "metadata": {}, "source": [ - "The solution is overlapped with the actual one, and they are barely indistinguishable. We can also take a look at the loss using `TensorBoard`:" + "The solution is overlapped with the actual one, and they are barely indistinguishable. We can also visualize the loss during training using the `MetricTracker`:" ] }, { "cell_type": "code", - "execution_count": null, - "id": "fcac93e4", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "To load TensorBoard run load_ext tensorboard on your terminal\n", - "To visualize the loss you can run tensorboard --logdir 'tutorial_logs' on your terminal\n", - "\n", - "The tensorboard extension is already loaded. To reload it, use:\n", - " %reload_ext tensorboard\n" - ] - }, - { - "data": { - "text/plain": [ - "Reusing TensorBoard on port 6007 (pid 55149), started 0:00:03 ago. (Use '!kill 55149' to kill it.)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - " \n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "print(\"\\nTo load TensorBoard run load_ext tensorboard on your terminal\")\n", - "print(\n", - " \"To visualize the loss you can run tensorboard --logdir 'tutorial_logs' on your terminal\\n\"\n", - ")\n", - "# # uncomment for running tensorboard\n", - "# %load_ext tensorboard\n", - "# %tensorboard --logdir=tutorial_logs" - ] - }, - { - "cell_type": "markdown", - "id": "58172899", - "metadata": {}, - "source": [ - "As we can see the loss has not reached a minimum, suggesting that we could train for longer! Alternatively, we can also take look at the loss using callbacks. Here we use `MetricTracker` from `pina.callback`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "03398692", "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "GPU available: True (mps), used: False\n", - "TPU available: False, using: 0 TPU cores\n", - "HPU available: False, using: 0 HPUs\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1499: 100%|██████████| 1/1 [00:00<00:00, 211.36it/s, v_num=0, bound_cond_loss=3.6e-8, phys_cond_loss=2.13e-5, train_loss=2.13e-5] " - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "`Trainer.fit` stopped: `max_epochs=1500` reached.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1499: 100%|██████████| 1/1 [00:00<00:00, 134.97it/s, v_num=0, bound_cond_loss=3.6e-8, phys_cond_loss=2.13e-5, train_loss=2.13e-5]\n" - ] - }, { "data": { - "image/png": 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", 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", 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" ] @@ -640,39 +450,8 @@ } ], "source": [ - "from pina.callback import MetricTracker\n", - "\n", - "# create the model\n", - "newmodel = FeedForward(\n", - " layers=[10, 10],\n", - " func=torch.nn.Tanh,\n", - " output_dimensions=len(problem.output_variables),\n", - " input_dimensions=len(problem.input_variables),\n", - ")\n", - "\n", - "# create the PINN object\n", - "newpinn = PINN(\n", - " problem, newmodel, optimizer=TorchOptimizer(torch.optim.Adam, lr=0.005)\n", - ")\n", - "\n", - "# create the trainer\n", - "newtrainer = Trainer(\n", - " solver=newpinn,\n", - " max_epochs=1500,\n", - " logger=True, # enable parameter logging\n", - " callbacks=[MetricTracker()],\n", - " accelerator=\"cpu\",\n", - " train_size=1.0,\n", - " test_size=0.0,\n", - " val_size=0.0,\n", - " enable_model_summary=False,\n", - ") # we train on CPU and avoid model summary at beginning of training (optional)\n", - "\n", - "# train\n", - "newtrainer.train()\n", - "\n", "# plot loss\n", - "trainer_metrics = newtrainer.callbacks[0].metrics\n", + "trainer_metrics = trainer.callbacks[0].metrics\n", "loss = trainer_metrics[\"train_loss\"]\n", "epochs = range(len(loss))\n", "plt.plot(epochs, loss.cpu())\n", @@ -687,17 +466,21 @@ "id": "33e672da", "metadata": {}, "source": [ - "## What's next?\n", + "## What's Next?\n", "\n", - "Congratulations on completing the introductory tutorial of **PINA**! There are several directions you can go now:\n", + "Congratulations on completing the introductory tutorial on Physics-Informed Training! Now that you have a solid foundation, here are several exciting directions you can explore:\n", "\n", - "1. Train the network for longer or with different layer sizes and assert the finaly accuracy\n", + "1. **Experiment with Training Duration & Network Architecture**: Try different training durations and tweak the network architecture to optimize performance.\n", "\n", - "2. Train the network using other types of models (see `pina.model`)\n", + "2. **Explore Other Models in `pina.model`**: Check out other models available in `pina.model` or design your own custom PyTorch module to suit your needs.\n", "\n", - "3. GPU training and speed benchmarking\n", + "3. **Run Training on a GPU**: Speed up your training by running on a GPU and compare the performance improvements.\n", "\n", - "4. Many more..." + "4. **Test Various Solvers**: Explore and evaluate different solvers to assess their performance on various types of problems.\n", + "\n", + "5. **... and many more!**: The possibilities are vast! Continue experimenting with advanced configurations, solvers, and other features in PINA.\n", + "\n", + "For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/)." ] } ], diff --git a/tutorials/tutorial1/tutorial.py b/tutorials/tutorial1/tutorial.py deleted file mode 100644 index 42b5483..0000000 --- a/tutorials/tutorial1/tutorial.py +++ /dev/null @@ -1,340 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# # Tutorial: Physics Informed Neural Networks on PINA -# -# [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial1/tutorial.ipynb) -# - -# In this tutorial, we will demonstrate a typical use case of **PINA** on a toy problem, following the standard API procedure. -# -#

-# PINA API -#

-# -# Specifically, the tutorial aims to introduce the following topics: -# -# * Explaining how to build **PINA** Problems, -# * Showing how to generate data for `PINN` training -# -# These are the two main steps needed **before** starting the modelling optimization (choose model and solver, and train). We will show each step in detail, and at the end, we will solve a simple Ordinary Differential Equation (ODE) problem using the `PINN` solver. - -# ## Build a PINA problem - -# Problem definition in the **PINA** framework is done by building a python `class`, which inherits from one or more problem classes (`SpatialProblem`, `TimeDependentProblem`, `ParametricProblem`, ...) depending on the nature of the problem. Below is an example: -# ### Simple Ordinary Differential Equation -# Consider the following: -# -# $$ -# \begin{equation} -# \begin{cases} -# \frac{d}{dx}u(x) &= u(x) \quad x\in(0,1)\\ -# u(x=0) &= 1 \\ -# \end{cases} -# \end{equation} -# $$ -# -# with the analytical solution $u(x) = e^x$. In this case, our ODE depends only on the spatial variable $x\in(0,1)$ , meaning that our `Problem` class is going to be inherited from the `SpatialProblem` class: -# -# ```python -# from pina.problem import SpatialProblem -# from pina.domain import CartesianProblem -# -# class SimpleODE(SpatialProblem): -# -# output_variables = ['u'] -# spatial_domain = CartesianProblem({'x': [0, 1]}) -# -# # other stuff ... -# ``` -# -# Notice that we define `output_variables` as a list of symbols, indicating the output variables of our equation (in this case only $u$), this is done because in **PINA** the `torch.Tensor`s are labelled, allowing the user maximal flexibility for the manipulation of the tensor. The `spatial_domain` variable indicates where the sample points are going to be sampled in the domain, in this case $x\in[0,1]$. -# -# What if our equation is also time-dependent? In this case, our `class` will inherit from both `SpatialProblem` and `TimeDependentProblem`: -# - -# In[ ]: - - -## routine needed to run the notebook on Google Colab -try: - import google.colab - - IN_COLAB = True -except: - IN_COLAB = False -if IN_COLAB: - get_ipython().system('pip install "pina-mathlab"') - -import warnings - -from pina.problem import SpatialProblem, TimeDependentProblem -from pina.domain import CartesianDomain - -warnings.filterwarnings("ignore") - - -class TimeSpaceODE(SpatialProblem, TimeDependentProblem): - - output_variables = ["u"] - spatial_domain = CartesianDomain({"x": [0, 1]}) - temporal_domain = CartesianDomain({"t": [0, 1]}) - - # other stuff ... - - -# where we have included the `temporal_domain` variable, indicating the time domain wanted for the solution. -# -# In summary, using **PINA**, we can initialize a problem with a class which inherits from different base classes: `SpatialProblem`, `TimeDependentProblem`, `ParametricProblem`, and so on depending on the type of problem we are considering. Here are some examples (more on the official documentation): -# * ``SpatialProblem`` $\rightarrow$ a differential equation with spatial variable(s) ``spatial_domain`` -# * ``TimeDependentProblem`` $\rightarrow$ a time-dependent differential equation with temporal variable(s) ``temporal_domain`` -# * ``ParametricProblem`` $\rightarrow$ a parametrized differential equation with parametric variable(s) ``parameter_domain`` -# * ``AbstractProblem`` $\rightarrow$ any **PINA** problem inherits from here - -# ### Write the problem class -# -# Once the `Problem` class is initialized, we need to represent the differential equation in **PINA**. In order to do this, we need to load the **PINA** operators from `pina.operator` module. Again, we'll consider Equation (1) and represent it in **PINA**: - -# In[ ]: - - -import torch -import matplotlib.pyplot as plt - -from pina.problem import SpatialProblem -from pina.operator import grad -from pina import Condition -from pina.domain import CartesianDomain -from pina.equation import Equation, FixedValue - - -# defining the ode equation -def ode_equation(input_, output_): - - # computing the derivative - u_x = grad(output_, input_, components=["u"], d=["x"]) - - # extracting the u input variable - u = output_.extract(["u"]) - - # calculate the residual and return it - return u_x - u - - -class SimpleODE(SpatialProblem): - - output_variables = ["u"] - spatial_domain = CartesianDomain({"x": [0, 1]}) - - domains = { - "x0": CartesianDomain({"x": 0.0}), - "D": CartesianDomain({"x": [0, 1]}), - } - - # conditions to hold - conditions = { - "bound_cond": Condition(domain="x0", equation=FixedValue(1.0)), - "phys_cond": Condition(domain="D", equation=Equation(ode_equation)), - } - - # defining the true solution - def solution(self, pts): - return torch.exp(pts.extract(["x"])) - - -problem = SimpleODE() - - -# After we define the `Problem` class, we need to write different class methods, where each method is a function returning a residual. These functions are the ones minimized during PINN optimization, given the initial conditions. For example, in the domain $[0,1]$, the ODE equation (`ode_equation`) must be satisfied. We represent this by returning the difference between subtracting the variable `u` from its gradient (the residual), which we hope to minimize to 0. This is done for all conditions. Notice that we do not pass directly a `python` function, but an `Equation` object, which is initialized with the `python` function. This is done so that all the computations and internal checks are done inside **PINA**. -# -# Once we have defined the function, we need to tell the neural network where these methods are to be applied. To do so, we use the `Condition` class. In the `Condition` class, we pass the location points and the equation we want minimized on those points (other possibilities are allowed, see the documentation for reference). -# -# Finally, it's possible to define a `solution` function, which can be useful if we want to plot the results and see how the real solution compares to the expected (true) solution. Notice that the `solution` function is a method of the `PINN` class, but it is not mandatory for problem definition. -# - -# ## Generate data -# -# Data for training can come in form of direct numerical simulation results, or points in the domains. In case we perform unsupervised learning, we just need the collocation points for training, i.e. points where we want to evaluate the neural network. Sampling point in **PINA** is very easy, here we show three examples using the `.discretise_domain` method of the `AbstractProblem` class. - -# In[ ]: - - -# sampling 20 points in [0, 1] through discretization in all locations -problem.discretise_domain(n=20, mode="grid", domains="all") - -# sampling 20 points in (0, 1) through latin hypercube sampling in D, and 1 point in x0 -problem.discretise_domain(n=20, mode="latin", domains=["D"]) -problem.discretise_domain(n=1, mode="random", domains=["x0"]) - -# sampling 20 points in (0, 1) randomly -problem.discretise_domain(n=20, mode="random") - - -# We are going to use latin hypercube points for sampling. We need to sample in all the conditions domains. In our case we sample in `D` and `x0`. - -# In[ ]: - - -# sampling for training -problem.discretise_domain(1, "random", domains=["x0"]) -problem.discretise_domain(20, "lh", domains=["D"]) - - -# The points are saved in a python `dict`, and can be accessed by calling the attribute `input_pts` of the problem - -# In[ ]: - - -print("Input points:", problem.discretised_domains) -print("Input points labels:", problem.discretised_domains["D"].labels) - - -# To visualize the sampled points we can use `matplotlib.pyplot`: - -# In[ ]: - - -for location in problem.input_pts: - coords = ( - problem.input_pts[location].extract(problem.spatial_variables).flatten() - ) - plt.scatter(coords, torch.zeros_like(coords), s=10, label=location) -plt.legend() - - -# ## Perform a small training - -# Once we have defined the problem and generated the data we can start the modelling. Here we will choose a `FeedForward` neural network available in `pina.model`, and we will train using the `PINN` solver from `pina.solver`. We highlight that this training is fairly simple, for more advanced stuff consider the tutorials in the ***Physics Informed Neural Networks*** section of ***Tutorials***. For training we use the `Trainer` class from `pina.trainer`. Here we show a very short training and some method for plotting the results. Notice that by default all relevant metrics (e.g. MSE error during training) are going to be tracked using a `lightning` logger, by default `CSVLogger`. If you want to track the metric by yourself without a logger, use `pina.callback.MetricTracker`. - -# In[ ]: - - -from pina import Trainer -from pina.solver import PINN -from pina.model import FeedForward -from lightning.pytorch.loggers import TensorBoardLogger -from pina.optim import TorchOptimizer - - -# build the model -model = FeedForward( - layers=[10, 10], - func=torch.nn.Tanh, - output_dimensions=len(problem.output_variables), - input_dimensions=len(problem.input_variables), -) - -# create the PINN object -pinn = PINN(problem, model, TorchOptimizer(torch.optim.Adam, lr=0.005)) - -# create the trainer -trainer = Trainer( - solver=pinn, - max_epochs=1500, - logger=TensorBoardLogger("tutorial_logs"), - accelerator="cpu", - train_size=1.0, - test_size=0.0, - val_size=0.0, - enable_model_summary=False, -) # we train on CPU and avoid model summary at beginning of training (optional) - -# train -trainer.train() - - -# After the training we can inspect trainer logged metrics (by default **PINA** logs mean square error residual loss). The logged metrics can be accessed online using one of the `Lightning` loggers. The final loss can be accessed by `trainer.logged_metrics` - -# In[27]: - - -# inspecting final loss -trainer.logged_metrics - - -# By using `matplotlib` we can also do some qualitative plots of the solution. - -# In[ ]: - - -pts = pinn.problem.spatial_domain.sample(256, "grid", variables="x") -predicted_output = pinn.forward(pts).extract("u").tensor.detach() -true_output = pinn.problem.solution(pts).detach() -fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(8, 8)) -ax.plot(pts.extract(["x"]), predicted_output, label="Neural Network solution") -ax.plot(pts.extract(["x"]), true_output, label="True solution") -plt.legend() - - -# The solution is overlapped with the actual one, and they are barely indistinguishable. We can also take a look at the loss using `TensorBoard`: - -# In[ ]: - - -print("\nTo load TensorBoard run load_ext tensorboard on your terminal") -print( - "To visualize the loss you can run tensorboard --logdir 'tutorial_logs' on your terminal\n" -) -# # uncomment for running tensorboard -# %load_ext tensorboard -# %tensorboard --logdir=tutorial_logs - - -# As we can see the loss has not reached a minimum, suggesting that we could train for longer! Alternatively, we can also take look at the loss using callbacks. Here we use `MetricTracker` from `pina.callback`: - -# In[ ]: - - -from pina.callback import MetricTracker - -# create the model -newmodel = FeedForward( - layers=[10, 10], - func=torch.nn.Tanh, - output_dimensions=len(problem.output_variables), - input_dimensions=len(problem.input_variables), -) - -# create the PINN object -newpinn = PINN( - problem, newmodel, optimizer=TorchOptimizer(torch.optim.Adam, lr=0.005) -) - -# create the trainer -newtrainer = Trainer( - solver=newpinn, - max_epochs=1500, - logger=True, # enable parameter logging - callbacks=[MetricTracker()], - accelerator="cpu", - train_size=1.0, - test_size=0.0, - val_size=0.0, - enable_model_summary=False, -) # we train on CPU and avoid model summary at beginning of training (optional) - -# train -newtrainer.train() - -# plot loss -trainer_metrics = newtrainer.callbacks[0].metrics -loss = trainer_metrics["train_loss"] -epochs = range(len(loss)) -plt.plot(epochs, loss.cpu()) -# plotting -plt.xlabel("epoch") -plt.ylabel("loss") -plt.yscale("log") - - -# ## What's next? -# -# Congratulations on completing the introductory tutorial of **PINA**! There are several directions you can go now: -# -# 1. Train the network for longer or with different layer sizes and assert the finaly accuracy -# -# 2. Train the network using other types of models (see `pina.model`) -# -# 3. GPU training and speed benchmarking -# -# 4. Many more... diff --git a/tutorials/tutorial10/tutorial.ipynb b/tutorials/tutorial10/tutorial.ipynb index fa0642d..9355927 100644 --- a/tutorials/tutorial10/tutorial.ipynb +++ b/tutorials/tutorial10/tutorial.ipynb @@ -4,17 +4,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Tutorial: Averaging Neural Operator for solving Kuramoto Sivashinsky equation\n", + "# Tutorial: Solving the Kuramoto–Sivashinsky Equation with Averaging Neural Operator\n", "\n", "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial10/tutorial.ipynb)\n", "\n", - "In this tutorial we will build a Neural Operator using the\n", - "`AveragingNeuralOperator` model and the `SupervisedSolver`. At the end of the\n", - "tutorial you will be able to train a Neural Operator for learning\n", - "the operator of time dependent PDEs.\n", "\n", + "In this tutorial, we will build a Neural Operator using the **`AveragingNeuralOperator`** model and the **`SupervisedSolver`**. By the end of this tutorial, you will be able to train a Neural Operator to learn the operator for time-dependent PDEs.\n", "\n", - "First of all, some useful imports. Note we use `scipy` for i/o operations.\n" + "Let's start by importing the necessary modules." ] }, { @@ -31,7 +28,7 @@ "except:\n", " IN_COLAB = False\n", "if IN_COLAB:\n", - " !pip install \"pina-mathlab\"\n", + " !pip install \"pina-mathlab[tutorial]\"\n", " # get the data\n", " !mkdir \"data\"\n", " !wget \"https://github.com/mathLab/PINA/raw/refs/heads/master/tutorials/tutorial10/data/Data_KS.mat\" -O \"data/Data_KS.mat\"\n", @@ -42,7 +39,7 @@ "import warnings\n", "\n", "from scipy import io\n", - "from pina import Condition, Trainer, LabelTensor\n", + "from pina import Trainer, LabelTensor\n", "from pina.model import AveragingNeuralOperator\n", "from pina.solver import SupervisedSolver\n", "from pina.problem.zoo import SupervisedProblem\n", @@ -56,43 +53,42 @@ "source": [ "## Data Generation\n", "\n", - "We will focus on solving a specific PDE, the **Kuramoto Sivashinsky** (KS) equation.\n", - "The KS PDE is a fourth-order nonlinear PDE with the following form:\n", + "In this tutorial, we will focus on solving the **Kuramoto-Sivashinsky (KS)** equation, a fourth-order nonlinear PDE. The equation is given by:\n", "\n", "$$\n", - "\\frac{\\partial u}{\\partial t}(x,t) = -u(x,t)\\frac{\\partial u}{\\partial x}(x,t)- \\frac{\\partial^{4}u}{\\partial x^{4}}(x,t) - \\frac{\\partial^{2}u}{\\partial x^{2}}(x,t).\n", + "\\frac{\\partial u}{\\partial t}(x,t) = -u(x,t)\\frac{\\partial u}{\\partial x}(x,t) - \\frac{\\partial^{4}u}{\\partial x^{4}}(x,t) - \\frac{\\partial^{2}u}{\\partial x^{2}}(x,t).\n", "$$\n", "\n", - "In the above $x\\in \\Omega=[0, 64]$ represents a spatial location, $t\\in\\mathbb{T}=[0,50]$ the time and $u(x, t)$ is the value of the function $u:\\Omega \\times\\mathbb{T}\\in\\mathbb{R}$. We indicate with $\\mathbb{U}$ a suitable space for $u$, i.e. we have that the solution $u\\in\\mathbb{U}$.\n", + "In this equation, $x \\in \\Omega = [0, 64]$ represents a spatial location, and $t \\in \\mathbb{T} = [0, 50]$ represents time. The function $u(x, t)$ is the value of the function at each point in space and time, with $u(x, t) \\in \\mathbb{R}$. We denote the solution space as $\\mathbb{U}$, where $u \\in \\mathbb{U}$.\n", "\n", + "We impose Dirichlet boundary conditions on the derivative of $u$ at the boundary of the domain $\\partial \\Omega$:\n", "\n", - "We impose Dirichlet boundary conditions on the derivative of $u$ on the border of the domain $\\partial \\Omega$\n", "$$\n", - "\\frac{\\partial u}{\\partial x}(x,t)=0 \\quad \\forall (x,t)\\in \\partial \\Omega\\times\\mathbb{T}.\n", - " $$\n", - "\n", - "Initial conditions are sampled from a distribution over truncated Fourier series with random coefficients \n", - "$\\{A_k, \\ell_k, \\phi_k\\}_k$ as\n", - "$$\n", - " u(x,0) = \\sum_{k=1}^N A_k \\sin(2 \\pi \\ell_k x / L + \\phi_k) \\ ,\n", + "\\frac{\\partial u}{\\partial x}(x,t) = 0 \\quad \\forall (x,t) \\in \\partial \\Omega \\times \\mathbb{T}.\n", "$$\n", "\n", - "where $A_k \\in [-0.4, -0.3]$, $\\ell_k = 2$, $\\phi_k = 2\\pi \\quad \\forall k=1,\\dots,N$. \n", + "The initial conditions are sampled from a distribution over truncated Fourier series with random coefficients $\\{A_k, \\ell_k, \\phi_k\\}_k$, as follows:\n", "\n", + "$$\n", + "u(x,0) = \\sum_{k=1}^N A_k \\sin\\left(2 \\pi \\frac{\\ell_k x}{L} + \\phi_k\\right),\n", + "$$\n", "\n", - "We have already generated some data for differenti initial conditions, and our objective will\n", - "be to build a Neural Operator that, given $u(x, t)$ will output $u(x, t+\\delta)$, where\n", - "$\\delta$ is a fixed time step. We will come back on the Neural Operator architecture, for now\n", - "we first need to import the data.\n", + "where:\n", + "- $A_k \\in [-0.4, -0.3]$,\n", + "- $\\ell_k = 2$,\n", + "- $\\phi_k = 2\\pi \\quad \\forall k=1,\\dots,N$.\n", + "\n", + "We have already generated data for different initial conditions. The goal is to build a Neural Operator that, given $u(x,t)$, outputs $u(x,t+\\delta)$, where $\\delta$ is a fixed time step. \n", + "\n", + "We will cover the Neural Operator architecture later, but for now, let’s start by importing the data.\n", "\n", "**Note:**\n", - "*The numerical integration is obtained by using pseudospectral method for spatial derivative discratization and\n", - "implicit Runge Kutta 5 for temporal dynamics.*\n" + "The numerical integration is obtained using a pseudospectral method for spatial derivative discretization and implicit Runge-Kutta 5 for temporal dynamics." ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -131,17 +127,17 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The data are saved in the form `B \\times N \\times D`, where `B` is the batch_size\n", - "(basically how many initial conditions we sample), `N` the number of points in the mesh\n", - "(which is the product of the discretization in `x` timese the one in `t`), and \n", - "`D` the dimension of the problem (in this case we have three variables `[u, t, x]`).\n", + "The data is saved in the form `[B, N, D]`, where:\n", + "- `B` is the batch size (i.e., how many initial conditions we sample),\n", + "- `N` is the number of points in the mesh (which is the product of the discretization in $x$ times the one in $t$),\n", + "- `D` is the dimension of the problem (in this case, we have three variables: $[u, t, x]$).\n", "\n", "We are now going to plot some trajectories!" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -217,27 +213,23 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "As we can see, as the time progresses the solution becomes chaotic, which makes\n", - "it really hard to learn! We will now focus on building a Neural Operator using the\n", - "`SupervisedSolver` class to tackle the problem.\n", + "As we can see, as time progresses, the solution becomes chaotic, making it very difficult to learn! We will now focus on building a Neural Operator using the `SupervisedSolver` class to tackle this problem.\n", "\n", "## Averaging Neural Operator\n", "\n", - "We will build a neural operator $\\texttt{NO}$ which takes the solution at time $t=0$ for any $x\\in\\Omega$,\n", - "the time $(t)$ at which we want to compute the solution, and gives back the solution to the KS equation $u(x, t)$, mathematically:\n", + "We will build a neural operator $\\texttt{NO}$, which takes the solution at time $t=0$ for any $x\\in\\Omega$, the time $t$ at which we want to compute the solution, and gives back the solution to the KS equation $u(x, t)$. Mathematically:\n", + "\n", "$$\n", "\\texttt{NO}_\\theta : \\mathbb{U} \\rightarrow \\mathbb{U},\n", "$$\n", + "\n", "such that\n", + "\n", "$$\n", "\\texttt{NO}_\\theta[u(t=0)](x, t) \\rightarrow u(x, t).\n", "$$\n", "\n", - "There are many ways on approximating the following operator, e.g. by 2D [FNO](https://mathlab.github.io/PINA/_rst/models/fno.html) (for regular meshes),\n", - "a [DeepOnet](https://mathlab.github.io/PINA/_rst/models/deeponet.html), [Continuous Convolutional Neural Operator](https://mathlab.github.io/PINA/_rst/layers/convolution.html),\n", - "[MIONet](https://mathlab.github.io/PINA/_rst/models/mionet.html). \n", - "In this tutorial we will use the *Averaging Neural Operator* presented in [*The Nonlocal Neural Operator: Universal Approximation*](https://arxiv.org/abs/2304.13221)\n", - "which is a [Kernel Neural Operator](https://mathlab.github.io/PINA/_rst/models/base_no.html) with integral kernel:\n", + "There are many ways to approximate the following operator, for example, by using a 2D [FNO](https://mathlab.github.io/PINA/_rst/model/fourier_neural_operator.html) (for regular meshes), a [DeepOnet](https://mathlab.github.io/PINA/_rst/model/deeponet.html), [Continuous Convolutional Neural Operator](https://mathlab.github.io/PINA/_rst/model/block/convolution.html), or [MIONet](https://mathlab.github.io/PINA/_rst/model/mionet.html). In this tutorial, we will use the *Averaging Neural Operator* presented in [*The Nonlocal Neural Operator: Universal Approximation*](https://arxiv.org/abs/2304.13221), which is a [Kernel Neural Operator](https://mathlab.github.io/PINA/_rst/model/kernel_neural_operator.html) with an integral kernel:\n", "\n", "$$\n", "K(v) = \\sigma\\left(Wv(x) + b + \\frac{1}{|\\Omega|}\\int_\\Omega v(y)dy\\right)\n", @@ -245,19 +237,19 @@ "\n", "where:\n", "\n", - "* $v(x)\\in\\mathbb{R}^{\\rm{emb}}$ is the update for a function $v$ with $\\mathbb{R}^{\\rm{emb}}$ the embedding (hidden) size\n", - "* $\\sigma$ is a non-linear activation\n", - "* $W\\in\\mathbb{R}^{\\rm{emb}\\times\\rm{emb}}$ is a tunable matrix.\n", - "* $b\\in\\mathbb{R}^{\\rm{emb}}$ is a tunable bias.\n", + "* $v(x) \\in \\mathbb{R}^{\\rm{emb}}$ is the update for a function $v$, with $\\mathbb{R}^{\\rm{emb}}$ being the embedding (hidden) size.\n", + "* $\\sigma$ is a non-linear activation function.\n", + "* $W \\in \\mathbb{R}^{\\rm{emb} \\times \\rm{emb}}$ is a tunable matrix.\n", + "* $b \\in \\mathbb{R}^{\\rm{emb}}$ is a tunable bias.\n", "\n", - "If PINA many Kernel Neural Operators are already implemented, and the modular componets of the [Kernel Neural Operator](https://mathlab.github.io/PINA/_rst/models/base_no.html) class permits to create new ones by composing base kernel layers.\n", + "In PINA, many Kernel Neural Operators are already implemented. The modular components of the [Kernel Neural Operator](https://mathlab.github.io/PINA/_rst/model/kernel_neural_operator.html) class allow you to create new ones by composing base kernel layers.\n", "\n", - "**Note:*** We will use the already built class* `AveragingNeuralOperator`, *as constructive excercise try to use the* [KernelNeuralOperator](https://mathlab.github.io/PINA/_rst/models/base_no.html) *class for building a kernel neural operator from scratch. You might employ the different layers that we have in pina, e.g.* [FeedForward](https://mathlab.github.io/PINA/_rst/models/fnn.html), *and* [AveragingNeuralOperator](https://mathlab.github.io/PINA/_rst/layers/avno_layer.html) *layers*." + "**Note:** We will use the already built class `AveragingNeuralOperator`. As a constructive exercise, try to use the [KernelNeuralOperator](https://mathlab.github.io/PINA/_rst/model/kernel_neural_operator.html) class to build a kernel neural operator from scratch. You might employ the different layers that we have in PINA, such as [FeedForward](https://mathlab.github.io/PINA/_rst/model/feed_forward.html) and [AveragingNeuralOperator](https://mathlab.github.io/PINA/_rst/model/average_neural_operator.html) layers." ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -285,17 +277,16 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Super easy! Notice that we use the `SIREN` activation function, more on [Implicit Neural Representations with Periodic Activation Functions](https://arxiv.org/abs/2006.09661).\n", + "Super easy! Notice that we use the `SIREN` activation function, which is discussed in more detail in the paper [Implicit Neural Representations with Periodic Activation Functions](https://arxiv.org/abs/2006.09661).\n", "\n", "## Solving the KS problem\n", "\n", - "We will now focus on solving the KS equation using the `SupervisedSolver` class\n", - "and the `AveragingNeuralOperator` model. As done in the [FNO tutorial](https://github.com/mathLab/PINA/blob/master/tutorials/tutorial5/tutorial.ipynb) we now create the Neural Operator problem class with `SupervisedProblem`." + "We will now focus on solving the KS equation using the `SupervisedSolver` class and the `AveragingNeuralOperator` model. As done in the [FNO tutorial](https://github.com/mathLab/PINA/blob/master/tutorials/tutorial5/tutorial.ipynb), we now create the Neural Operator problem class with `SupervisedProblem`." ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -308,11 +299,18 @@ ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 39: 100%|██████████| 20/20 [00:01<00:00, 18.75it/s, v_num=9, data_loss_step=0.0809, train_loss_step=0.0809, data_loss_epoch=0.108, train_loss_epoch=0.108]" - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "38a4c0eac050435283e8250fadec6764", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" ] @@ -390,21 +381,21 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "As we can see we can obtain nice result considering the small training time and the difficulty of the problem!\n", + "As we can see, we can obtain nice results considering the small training time and the difficulty of the problem! \n", "Let's take a look at the training and testing error:" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Training error: 0.107\n", - "Testing error: 0.097\n" + "Training error: 0.114\n", + "Testing error: 0.106\n" ] } ], @@ -430,22 +421,24 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "As we can see the error is pretty small, which agrees with what we can see from the previous plots." + "As we can see, the error is pretty small, which aligns with the observations from the previous plots." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## What's next?\n", + "## What's Next?\n", "\n", - "Now you know how to solve a time dependent neural operator problem in **PINA**! There are multiple directions you can go now:\n", + "You have completed the tutorial on solving time-dependent PDEs using Neural Operators in **PINA**. Great job! Here are some potential next steps you can explore:\n", "\n", - "1. Train the network for longer or with different layer sizes and assert the final accuracy\n", + "1. **Train the network for longer or with different layer sizes**: Experiment with various configurations, such as adjusting the number of layers or hidden dimensions, to further improve accuracy and observe the impact on performance.\n", "\n", - "2. We left a more challenging dataset [Data_KS2.mat](dat/Data_KS2.mat) where $A_k \\in [-0.5, 0.5]$, $\\ell_k \\in [1, 2, 3]$, $\\phi_k \\in [0, 2\\pi]$ for longer training\n", + "2. **Use a more challenging dataset**: Try using the more complex dataset [Data_KS2.mat](dat/Data_KS2.mat) where $A_k \\in [-0.5, 0.5]$, $\\ell_k \\in [1, 2, 3]$, and $\\phi_k \\in [0, 2\\pi]$ for a more difficult task. This dataset may require longer training and testing.\n", "\n", - "3. Compare the performance between the different neural operators (you can even try to implement your favourite one!)" + "3. **... and many more...**: Explore other models, such as the [FNO](https://mathlab.github.io/PINA/_rst/models/fno.html), [DeepOnet](https://mathlab.github.io/PINA/_rst/models/deeponet.html), or implement your own operator using the [KernelNeuralOperator](https://mathlab.github.io/PINA/_rst/models/base_no.html) class to compare performance and find the best model for your task.\n", + "\n", + "For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/)." ] } ], diff --git a/tutorials/tutorial10/tutorial.py b/tutorials/tutorial10/tutorial.py deleted file mode 100644 index 564617d..0000000 --- a/tutorials/tutorial10/tutorial.py +++ /dev/null @@ -1,314 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# # Tutorial: Averaging Neural Operator for solving Kuramoto Sivashinsky equation -# -# [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial10/tutorial.ipynb) -# -# In this tutorial we will build a Neural Operator using the -# `AveragingNeuralOperator` model and the `SupervisedSolver`. At the end of the -# tutorial you will be able to train a Neural Operator for learning -# the operator of time dependent PDEs. -# -# -# First of all, some useful imports. Note we use `scipy` for i/o operations. -# - -# In[ ]: - - -## routine needed to run the notebook on Google Colab -try: - import google.colab - - IN_COLAB = True -except: - IN_COLAB = False -if IN_COLAB: - get_ipython().system('pip install "pina-mathlab"') - # get the data - get_ipython().system('mkdir "data"') - get_ipython().system('wget "https://github.com/mathLab/PINA/raw/refs/heads/master/tutorials/tutorial10/data/Data_KS.mat" -O "data/Data_KS.mat"') - get_ipython().system('wget "https://github.com/mathLab/PINA/raw/refs/heads/master/tutorials/tutorial10/data/Data_KS2.mat" -O "data/Data_KS2.mat"') - -import torch -import matplotlib.pyplot as plt -import warnings - -from scipy import io -from pina import Condition, Trainer, LabelTensor -from pina.model import AveragingNeuralOperator -from pina.solver import SupervisedSolver -from pina.problem.zoo import SupervisedProblem - -warnings.filterwarnings("ignore") - - -# ## Data Generation -# -# We will focus on solving a specific PDE, the **Kuramoto Sivashinsky** (KS) equation. -# The KS PDE is a fourth-order nonlinear PDE with the following form: -# -# $$ -# \frac{\partial u}{\partial t}(x,t) = -u(x,t)\frac{\partial u}{\partial x}(x,t)- \frac{\partial^{4}u}{\partial x^{4}}(x,t) - \frac{\partial^{2}u}{\partial x^{2}}(x,t). -# $$ -# -# In the above $x\in \Omega=[0, 64]$ represents a spatial location, $t\in\mathbb{T}=[0,50]$ the time and $u(x, t)$ is the value of the function $u:\Omega \times\mathbb{T}\in\mathbb{R}$. We indicate with $\mathbb{U}$ a suitable space for $u$, i.e. we have that the solution $u\in\mathbb{U}$. -# -# -# We impose Dirichlet boundary conditions on the derivative of $u$ on the border of the domain $\partial \Omega$ -# $$ -# \frac{\partial u}{\partial x}(x,t)=0 \quad \forall (x,t)\in \partial \Omega\times\mathbb{T}. -# $$ -# -# Initial conditions are sampled from a distribution over truncated Fourier series with random coefficients -# $\{A_k, \ell_k, \phi_k\}_k$ as -# $$ -# u(x,0) = \sum_{k=1}^N A_k \sin(2 \pi \ell_k x / L + \phi_k) \ , -# $$ -# -# where $A_k \in [-0.4, -0.3]$, $\ell_k = 2$, $\phi_k = 2\pi \quad \forall k=1,\dots,N$. -# -# -# We have already generated some data for differenti initial conditions, and our objective will -# be to build a Neural Operator that, given $u(x, t)$ will output $u(x, t+\delta)$, where -# $\delta$ is a fixed time step. We will come back on the Neural Operator architecture, for now -# we first need to import the data. -# -# **Note:** -# *The numerical integration is obtained by using pseudospectral method for spatial derivative discratization and -# implicit Runge Kutta 5 for temporal dynamics.* -# - -# In[2]: - - -# load data -data = io.loadmat("data/Data_KS.mat") - -# converting to label tensor -initial_cond_train = LabelTensor( - torch.tensor(data["initial_cond_train"], dtype=torch.float), - ["t", "x", "u0"], -) -initial_cond_test = LabelTensor( - torch.tensor(data["initial_cond_test"], dtype=torch.float), ["t", "x", "u0"] -) -sol_train = LabelTensor( - torch.tensor(data["sol_train"], dtype=torch.float), ["u"] -) -sol_test = LabelTensor(torch.tensor(data["sol_test"], dtype=torch.float), ["u"]) - -print("Data Loaded") -print(f" shape initial condition: {initial_cond_train.shape}") -print(f" shape solution: {sol_train.shape}") - - -# The data are saved in the form `B \times N \times D`, where `B` is the batch_size -# (basically how many initial conditions we sample), `N` the number of points in the mesh -# (which is the product of the discretization in `x` timese the one in `t`), and -# `D` the dimension of the problem (in this case we have three variables `[u, t, x]`). -# -# We are now going to plot some trajectories! - -# In[3]: - - -# helper function -def plot_trajectory(coords, real, no_sol=None): - # find the x-t shapes - dim_x = len(torch.unique(coords.extract("x"))) - dim_t = len(torch.unique(coords.extract("t"))) - # if we don't have the Neural Operator solution we simply plot the real one - if no_sol is None: - fig, axs = plt.subplots(1, 1, figsize=(15, 5), sharex=True, sharey=True) - c = axs.imshow( - real.reshape(dim_t, dim_x).T.detach(), - extent=[0, 50, 0, 64], - cmap="PuOr_r", - aspect="auto", - ) - axs.set_title("Real solution") - fig.colorbar(c, ax=axs) - axs.set_xlabel("t") - axs.set_ylabel("x") - # otherwise we plot the real one, the Neural Operator one, and their difference - else: - fig, axs = plt.subplots(1, 3, figsize=(15, 5), sharex=True, sharey=True) - axs[0].imshow( - real.reshape(dim_t, dim_x).T.detach(), - extent=[0, 50, 0, 64], - cmap="PuOr_r", - aspect="auto", - ) - axs[0].set_title("Real solution") - axs[1].imshow( - no_sol.reshape(dim_t, dim_x).T.detach(), - extent=[0, 50, 0, 64], - cmap="PuOr_r", - aspect="auto", - ) - axs[1].set_title("NO solution") - c = axs[2].imshow( - (real - no_sol).abs().reshape(dim_t, dim_x).T.detach(), - extent=[0, 50, 0, 64], - cmap="PuOr_r", - aspect="auto", - ) - axs[2].set_title("Absolute difference") - fig.colorbar(c, ax=axs.ravel().tolist()) - for ax in axs: - ax.set_xlabel("t") - ax.set_ylabel("x") - plt.show() - - -# a sample trajectory (we use the sample 5, feel free to change) -sample_number = 20 -plot_trajectory( - coords=initial_cond_train[sample_number].extract(["x", "t"]), - real=sol_train[sample_number].extract("u"), -) - - -# As we can see, as the time progresses the solution becomes chaotic, which makes -# it really hard to learn! We will now focus on building a Neural Operator using the -# `SupervisedSolver` class to tackle the problem. -# -# ## Averaging Neural Operator -# -# We will build a neural operator $\texttt{NO}$ which takes the solution at time $t=0$ for any $x\in\Omega$, -# the time $(t)$ at which we want to compute the solution, and gives back the solution to the KS equation $u(x, t)$, mathematically: -# $$ -# \texttt{NO}_\theta : \mathbb{U} \rightarrow \mathbb{U}, -# $$ -# such that -# $$ -# \texttt{NO}_\theta[u(t=0)](x, t) \rightarrow u(x, t). -# $$ -# -# There are many ways on approximating the following operator, e.g. by 2D [FNO](https://mathlab.github.io/PINA/_rst/models/fno.html) (for regular meshes), -# a [DeepOnet](https://mathlab.github.io/PINA/_rst/models/deeponet.html), [Continuous Convolutional Neural Operator](https://mathlab.github.io/PINA/_rst/layers/convolution.html), -# [MIONet](https://mathlab.github.io/PINA/_rst/models/mionet.html). -# In this tutorial we will use the *Averaging Neural Operator* presented in [*The Nonlocal Neural Operator: Universal Approximation*](https://arxiv.org/abs/2304.13221) -# which is a [Kernel Neural Operator](https://mathlab.github.io/PINA/_rst/models/base_no.html) with integral kernel: -# -# $$ -# K(v) = \sigma\left(Wv(x) + b + \frac{1}{|\Omega|}\int_\Omega v(y)dy\right) -# $$ -# -# where: -# -# * $v(x)\in\mathbb{R}^{\rm{emb}}$ is the update for a function $v$ with $\mathbb{R}^{\rm{emb}}$ the embedding (hidden) size -# * $\sigma$ is a non-linear activation -# * $W\in\mathbb{R}^{\rm{emb}\times\rm{emb}}$ is a tunable matrix. -# * $b\in\mathbb{R}^{\rm{emb}}$ is a tunable bias. -# -# If PINA many Kernel Neural Operators are already implemented, and the modular componets of the [Kernel Neural Operator](https://mathlab.github.io/PINA/_rst/models/base_no.html) class permits to create new ones by composing base kernel layers. -# -# **Note:*** We will use the already built class* `AveragingNeuralOperator`, *as constructive excercise try to use the* [KernelNeuralOperator](https://mathlab.github.io/PINA/_rst/models/base_no.html) *class for building a kernel neural operator from scratch. You might employ the different layers that we have in pina, e.g.* [FeedForward](https://mathlab.github.io/PINA/_rst/models/fnn.html), *and* [AveragingNeuralOperator](https://mathlab.github.io/PINA/_rst/layers/avno_layer.html) *layers*. - -# In[4]: - - -class SIREN(torch.nn.Module): - def forward(self, x): - return torch.sin(x) - - -embedding_dimesion = 40 # hyperparameter embedding dimension -input_dimension = 3 # ['u', 'x', 't'] -number_of_coordinates = 2 # ['x', 't'] -lifting_net = torch.nn.Linear(input_dimension, embedding_dimesion) -projecting_net = torch.nn.Linear(embedding_dimesion + number_of_coordinates, 1) -model = AveragingNeuralOperator( - lifting_net=lifting_net, - projecting_net=projecting_net, - coordinates_indices=["x", "t"], - field_indices=["u0"], - n_layers=4, - func=SIREN, -) - - -# Super easy! Notice that we use the `SIREN` activation function, more on [Implicit Neural Representations with Periodic Activation Functions](https://arxiv.org/abs/2006.09661). -# -# ## Solving the KS problem -# -# We will now focus on solving the KS equation using the `SupervisedSolver` class -# and the `AveragingNeuralOperator` model. As done in the [FNO tutorial](https://github.com/mathLab/PINA/blob/master/tutorials/tutorial5/tutorial.ipynb) we now create the Neural Operator problem class with `SupervisedProblem`. - -# In[5]: - - -# initialize problem -problem = SupervisedProblem( - initial_cond_train, - sol_train, - input_variables=initial_cond_train.labels, - output_variables=sol_train.labels, -) -# initialize solver -solver = SupervisedSolver(problem=problem, model=model) -# train, only CPU and avoid model summary at beginning of training (optional) -trainer = Trainer( - solver=solver, - max_epochs=40, - accelerator="cpu", - enable_model_summary=False, - batch_size=5, # we train on CPU and avoid model summary at beginning of training (optional) - train_size=1.0, - val_size=0.0, - test_size=0.0, -) -trainer.train() - - -# We can now see some plots for the solutions - -# In[6]: - - -sample_number = 2 -no_sol = solver(initial_cond_test) -plot_trajectory( - coords=initial_cond_test[sample_number].extract(["x", "t"]), - real=sol_test[sample_number].extract("u"), - no_sol=no_sol[5], -) - - -# As we can see we can obtain nice result considering the small training time and the difficulty of the problem! -# Let's take a look at the training and testing error: - -# In[7]: - - -from pina.loss import PowerLoss - -error_metric = PowerLoss(p=2) # we use the MSE loss - -with torch.no_grad(): - no_sol_train = solver(initial_cond_train) - err_train = error_metric( - sol_train.extract("u"), no_sol_train - ).mean() # we average the error over trajectories - no_sol_test = solver(initial_cond_test) - err_test = error_metric( - sol_test.extract("u"), no_sol_test - ).mean() # we average the error over trajectories - print(f"Training error: {float(err_train):.3f}") - print(f"Testing error: {float(err_test):.3f}") - - -# As we can see the error is pretty small, which agrees with what we can see from the previous plots. - -# ## What's next? -# -# Now you know how to solve a time dependent neural operator problem in **PINA**! There are multiple directions you can go now: -# -# 1. Train the network for longer or with different layer sizes and assert the final accuracy -# -# 2. We left a more challenging dataset [Data_KS2.mat](dat/Data_KS2.mat) where $A_k \in [-0.5, 0.5]$, $\ell_k \in [1, 2, 3]$, $\phi_k \in [0, 2\pi]$ for longer training -# -# 3. 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zUDHquAlWH1oxk*!PP4EHS@xbui%pVacGmrGCC=eAH@|`-1B>^o>4c2jLZ73RDLi>Zanci-*Jt&m;7!LzPTEp{_}55fU)HtYD=S z8PZ$FE80T;i}$hkk?m)?uFvIH&pg(RM?!V_D<#_Dd=lB(_1JUH%n_jVU40a&2v?kF zu-|xBY$-AAW?A?8w5H>Gntdh>eA@gmCj0j)R=R{V8^^!DM9NX@(Wd42|8awhJy_9S zYZ&dNm=o)M6>|Px-9!Ow;Gi}iTq{o5cL8x?EjUB*pp=Ac-<$TIf5|es$7nz@Dc7oQ zqUp8%S>k|HR0-4j%B;@P+$2ko4DMS&7@VEP;W}}e0ntC}f>t~NNS+?r$o0>qY5t&H z4#4U0>}YW8KbNNY1Jxc_ORBHz3Yt*Uf1myON5BDv<>jns5bXZv4W|;QQ7TX9UyB*X z|NP{?zxV%r{r~%V*8T76`TzU$L>o3M{Pr8&?}ra6>i=hlg8qL`(w6`K4Bd}~-)2)X W1^<4x<*(oH-(h9VgPBUlFa95#e!*}6 diff --git a/tutorials/tutorial11/tutorial.ipynb b/tutorials/tutorial11/tutorial.ipynb index b9acb6d..ba74768 100644 --- a/tutorials/tutorial11/tutorial.ipynb +++ b/tutorials/tutorial11/tutorial.ipynb @@ -4,17 +4,18 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Tutorial: PINA and PyTorch Lightning, training tips and visualizations \n", - "\n", + "# Tutorial: Introduction to `Trainer` class\n", "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial11/tutorial.ipynb)\n", "\n", "In this tutorial, we will delve deeper into the functionality of the `Trainer` class, which serves as the cornerstone for training **PINA** [Solvers](https://mathlab.github.io/PINA/_rst/_code.html#solvers). \n", "\n", "The `Trainer` class offers a plethora of features aimed at improving model accuracy, reducing training time and memory usage, facilitating logging visualization, and more thanks to the amazing job done by the PyTorch Lightning team!\n", "\n", - "Our leading example will revolve around solving the `SimpleODE` problem, as outlined in the [*Introduction to PINA for Physics Informed Neural Networks training*](https://github.com/mathLab/PINA/blob/master/tutorials/tutorial1/tutorial.ipynb). If you haven't already explored it, we highly recommend doing so before diving into this tutorial.\n", + "Our leading example will revolve around solving a simple regression problem where we want to approximate the following function with a Neural Net model $\\mathcal{M}_{\\theta}$:\n", + "$$y = x^3$$\n", + "by having only a set of $20$ observations $\\{x_i, y_i\\}_{i=1}^{20}$, with $x_i \\sim\\mathcal{U}[-3, 3]\\;\\;\\forall i\\in(1,\\dots,20)$.\n", "\n", - "Let's start by importing useful modules, define the `SimpleODE` problem and the `PINN` solver." + "Let's start by importing useful modules!" ] }, { @@ -30,18 +31,15 @@ "except:\n", " IN_COLAB = False\n", "if IN_COLAB:\n", - " !pip install \"pina-mathlab\"\n", + " !pip install \"pina-mathlab[tutorial]\"\n", "\n", "import torch\n", "import warnings\n", "\n", - "from pina import Condition, Trainer\n", - "from pina.solver import PINN\n", + "from pina import Trainer\n", + "from pina.solver import SupervisedSolver\n", "from pina.model import FeedForward\n", - "from pina.problem import SpatialProblem\n", - "from pina.operator import grad\n", - "from pina.domain import CartesianDomain\n", - "from pina.equation import Equation, FixedValue\n", + "from pina.problem.zoo import SupervisedProblem\n", "\n", "warnings.filterwarnings(\"ignore\")" ] @@ -59,55 +57,22 @@ "metadata": {}, "outputs": [], "source": [ - "# defining the ode equation\n", - "def ode_equation(input_, output_):\n", + "# defining the problem\n", + "x_train = torch.empty((20, 1)).uniform_(-3, 3)\n", + "y_train = x_train.pow(3) + 3 * torch.randn_like(x_train)\n", "\n", - " # computing the derivative\n", - " u_x = grad(output_, input_, components=[\"u\"], d=[\"x\"])\n", - "\n", - " # extracting the u input variable\n", - " u = output_.extract([\"u\"])\n", - "\n", - " # calculate the residual and return it\n", - " return u_x - u\n", - "\n", - "\n", - "class SimpleODE(SpatialProblem):\n", - "\n", - " output_variables = [\"u\"]\n", - " spatial_domain = CartesianDomain({\"x\": [0, 1]})\n", - "\n", - " domains = {\n", - " \"x0\": CartesianDomain({\"x\": 0.0}),\n", - " \"D\": CartesianDomain({\"x\": [0, 1]}),\n", - " }\n", - "\n", - " # conditions to hold\n", - " conditions = {\n", - " \"bound_cond\": Condition(domain=\"x0\", equation=FixedValue(1.0)),\n", - " \"phys_cond\": Condition(domain=\"D\", equation=Equation(ode_equation)),\n", - " }\n", - "\n", - " # defining the true solution\n", - " def solution(self, pts):\n", - " return torch.exp(pts.extract([\"x\"]))\n", - "\n", - "\n", - "# sampling for training\n", - "problem = SimpleODE()\n", - "problem.discretise_domain(1, \"random\", domains=[\"x0\"])\n", - "problem.discretise_domain(20, \"lh\", domains=[\"D\"])\n", + "problem = SupervisedProblem(x_train, y_train)\n", "\n", "# build the model\n", "model = FeedForward(\n", " layers=[10, 10],\n", " func=torch.nn.Tanh,\n", - " output_dimensions=len(problem.output_variables),\n", - " input_dimensions=len(problem.input_variables),\n", + " output_dimensions=1,\n", + " input_dimensions=1,\n", ")\n", "\n", - "# create the PINN object\n", - "pinn = PINN(problem, model)" + "# create the SupervisedSolver object\n", + "solver = SupervisedSolver(problem, model, use_lt=False)" ] }, { @@ -115,7 +80,7 @@ "metadata": {}, "source": [ "Till now we just followed the extact step of the previous tutorials. The `Trainer` object\n", - "can be initialized by simiply passing the `PINN` solver" + "can be initialized by simiply passing the `SupervisedSolver` solver" ] }, { @@ -134,7 +99,7 @@ } ], "source": [ - "trainer = Trainer(solver=pinn)" + "trainer = Trainer(solver=solver)" ] }, { @@ -143,18 +108,13 @@ "source": [ "## Trainer Accelerator\n", "\n", - "When creating the trainer, **by defualt** the `Trainer` will choose the most performing `accelerator` for training which is available in your system, ranked as follow:\n", + "When creating the `Trainer`, **by default** the most performing `accelerator` for training which is available in your system will be chosen, ranked as follows:\n", "1. [TPU](https://cloud.google.com/tpu/docs/intro-to-tpu)\n", "2. [IPU](https://www.graphcore.ai/products/ipu)\n", "3. [HPU](https://habana.ai/)\n", "4. [GPU](https://www.intel.com/content/www/us/en/products/docs/processors/what-is-a-gpu.html#:~:text=What%20does%20GPU%20stand%20for,video%20editing%2C%20and%20gaming%20applications) or [MPS](https://developer.apple.com/metal/pytorch/)\n", - "5. CPU" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ + "5. CPU\n", + "\n", "For setting manually the `accelerator` run:\n", "\n", "* `accelerator = {'gpu', 'cpu', 'hpu', 'mps', 'cpu', 'ipu'}` sets the accelerator to a specific one" @@ -162,7 +122,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -176,14 +136,14 @@ } ], "source": [ - "trainer = Trainer(solver=pinn, accelerator=\"cpu\")" + "trainer = Trainer(solver=solver, accelerator=\"cpu\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "as you can see, even if in the used system `GPU` is available, it is not used since we set `accelerator='cpu'`." + "As you can see, even if a `GPU` is available on the system, it is not used since we set `accelerator='cpu'`." ] }, { @@ -192,16 +152,16 @@ "source": [ "## Trainer Logging\n", "\n", - "In **PINA** you can log metrics in different ways. The simplest approach is to use the `MetricTraker` class from `pina.callbacks` as seen in the [*Introduction to PINA for Physics Informed Neural Networks training*](https://github.com/mathLab/PINA/blob/master/tutorials/tutorial1/tutorial.ipynb) tutorial.\n", + "In **PINA** you can log metrics in different ways. The simplest approach is to use the `MetricTracker` class from `pina.callbacks`, as seen in the [*Introduction to Physics Informed Neural Networks training*](https://github.com/mathLab/PINA/blob/master/tutorials/tutorial1/tutorial.ipynb) tutorial.\n", "\n", - "However, expecially when we need to train multiple times to get an average of the loss across multiple runs, `pytorch_lightning.loggers` might be useful. Here we will use `TensorBoardLogger` (more on [logging](https://lightning.ai/docs/pytorch/stable/extensions/logging.html) here), but you can choose the one you prefer (or make your own one).\n", + "However, especially when we need to train multiple times to get an average of the loss across multiple runs, `lightning.pytorch.loggers` might be useful. Here we will use `TensorBoardLogger` (more on [logging](https://lightning.ai/docs/pytorch/stable/extensions/logging.html) here), but you can choose the one you prefer (or make your own one).\n", "\n", - "We will now import `TensorBoardLogger`, do three runs of training and then visualize the results. Notice we set `enable_model_summary=False` to avoid model summary specifications (e.g. number of parameters), set it to true if needed.\n" + "We will now import `TensorBoardLogger`, do three runs of training, and then visualize the results. Notice we set `enable_model_summary=False` to avoid model summary specifications (e.g. number of parameters); set it to `True` if needed." ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -209,113 +169,108 @@ "output_type": "stream", "text": [ "GPU available: True (mps), used: False\n", - "TPU available: False, using: 0 TPU cores\n", + "TPU available: False, using: 0 TPU cores\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ "HPU available: False, using: 0 HPUs\n" ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 233.15it/s, v_num=0, bound_cond_loss=1.22e-5, phys_cond_loss=0.000517, train_loss=0.000529]" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "`Trainer.fit` stopped: `max_epochs=1000` reached.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 137.95it/s, v_num=0, bound_cond_loss=1.22e-5, phys_cond_loss=0.000517, train_loss=0.000529]\n" - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "775a2d088e304b2589631b176c9e99e2", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00\n", - "\\\"Logging\n", + "\\\"Logging\n", "

" ] }, @@ -340,39 +295,28 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "as you can see, by default, **PINA** logs the losses which are shown in the progress bar, as well as the number of epochs. You can always insert more loggings by either defining a **callback** ([more on callbacks](https://lightning.ai/docs/pytorch/stable/extensions/callbacks.html)), or inheriting the solver and modify the programs with different **hooks** ([more on hooks](https://lightning.ai/docs/pytorch/stable/common/lightning_module.html#hooks))." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Trainer Callbacks" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Whenever we need to access certain steps of the training for logging, do static modifications (i.e. not changing the `Solver`) or updating `Problem` hyperparameters (static variables), we can use `Callabacks`. Notice that `Callbacks` allow you to add arbitrary self-contained programs to your training. At specific points during the flow of execution (hooks), the Callback interface allows you to design programs that encapsulate a full set of functionality. It de-couples functionality that does not need to be in **PINA** `Solver`s.\n", - "Lightning has a callback system to execute them when needed. Callbacks should capture NON-ESSENTIAL logic that is NOT required for your lightning module to run.\n", + "As you can see, by default, **PINA** logs the losses which are shown in the progress bar, as well as the number of epochs. You can always insert more loggings by either defining a **callback** ([more on callbacks](https://lightning.ai/docs/pytorch/stable/extensions/callbacks.html)), or inheriting the solver and modifying the programs with different **hooks** ([more on hooks](https://lightning.ai/docs/pytorch/stable/common/lightning_module.html#hooks)).\n", "\n", - "The following are best practices when using/designing callbacks.\n", + "## Trainer Callbacks\n", + "\n", + "Whenever we need to access certain steps of the training for logging, perform static modifications (i.e. not changing the `Solver`), or update `Problem` hyperparameters (static variables), we can use **Callbacks**. Notice that **Callbacks** allow you to add arbitrary self-contained programs to your training. At specific points during the flow of execution (hooks), the Callback interface allows you to design programs that encapsulate a full set of functionality. It de-couples functionality that does not need to be in **PINA** `Solver`s.\n", + "\n", + "Lightning has a callback system to execute them when needed. **Callbacks** should capture NON-ESSENTIAL logic that is NOT required for your lightning module to run.\n", + "\n", + "The following are best practices when using/designing callbacks:\n", "\n", "* Callbacks should be isolated in their functionality.\n", "* Your callback should not rely on the behavior of other callbacks in order to work properly.\n", "* Do not manually call methods from the callback.\n", - "* Directly calling methods (eg. on_validation_end) is strongly discouraged.\n", + "* Directly calling methods (e.g., on_validation_end) is strongly discouraged.\n", "* Whenever possible, your callbacks should not depend on the order in which they are executed.\n", "\n", - "We will try now to implement a naive version of `MetricTraker` to show how callbacks work. Notice that this is a very easy application of callbacks, fortunately in **PINA** we already provide more advanced callbacks in `pina.callbacks`.\n", - "\n", - "" + "We will try now to implement a naive version of `MetricTraker` to show how callbacks work. Notice that this is a very easy application of callbacks, fortunately in **PINA** we already provide more advanced callbacks in `pina.callbacks`." ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -398,12 +342,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Let's see the results when applyed to the `SimpleODE` problem. You can define callbacks when initializing the `Trainer` by the `callbacks` argument, which expects a list of callbacks. " + "Let's see the results when applied to the problem. You can define **callbacks** when initializing the `Trainer` by using the `callbacks` argument, which expects a list of callbacks.\n" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -416,24 +360,24 @@ ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 278.93it/s, v_num=0, bound_cond_loss=6.94e-5, phys_cond_loss=0.00116, train_loss=0.00123] " - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "f38442d749ad4702a0c99715ecf08c59", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00 -# \"Logging -#

- -# as you can see, by default, **PINA** logs the losses which are shown in the progress bar, as well as the number of epochs. You can always insert more loggings by either defining a **callback** ([more on callbacks](https://lightning.ai/docs/pytorch/stable/extensions/callbacks.html)), or inheriting the solver and modify the programs with different **hooks** ([more on hooks](https://lightning.ai/docs/pytorch/stable/common/lightning_module.html#hooks)). - -# ## Trainer Callbacks - -# Whenever we need to access certain steps of the training for logging, do static modifications (i.e. not changing the `Solver`) or updating `Problem` hyperparameters (static variables), we can use `Callabacks`. Notice that `Callbacks` allow you to add arbitrary self-contained programs to your training. At specific points during the flow of execution (hooks), the Callback interface allows you to design programs that encapsulate a full set of functionality. It de-couples functionality that does not need to be in **PINA** `Solver`s. -# Lightning has a callback system to execute them when needed. Callbacks should capture NON-ESSENTIAL logic that is NOT required for your lightning module to run. -# -# The following are best practices when using/designing callbacks. -# -# * Callbacks should be isolated in their functionality. -# * Your callback should not rely on the behavior of other callbacks in order to work properly. -# * Do not manually call methods from the callback. -# * Directly calling methods (eg. on_validation_end) is strongly discouraged. -# * Whenever possible, your callbacks should not depend on the order in which they are executed. -# -# We will try now to implement a naive version of `MetricTraker` to show how callbacks work. Notice that this is a very easy application of callbacks, fortunately in **PINA** we already provide more advanced callbacks in `pina.callbacks`. -# -# - -# In[6]: - - -from lightning.pytorch.callbacks import Callback -from lightning.pytorch.callbacks import EarlyStopping -import torch - - -# define a simple callback -class NaiveMetricTracker(Callback): - def __init__(self): - self.saved_metrics = [] - - def on_train_epoch_end( - self, trainer, __ - ): # function called at the end of each epoch - self.saved_metrics.append( - {key: value for key, value in trainer.logged_metrics.items()} - ) - - -# Let's see the results when applyed to the `SimpleODE` problem. You can define callbacks when initializing the `Trainer` by the `callbacks` argument, which expects a list of callbacks. - -# In[7]: - - -model = FeedForward( - layers=[10, 10], - func=torch.nn.Tanh, - output_dimensions=len(problem.output_variables), - input_dimensions=len(problem.input_variables), -) -pinn = PINN(problem, model) -trainer = Trainer( - solver=pinn, - accelerator="cpu", - logger=True, - callbacks=[NaiveMetricTracker()], # adding a callbacks - enable_model_summary=False, - train_size=1.0, - val_size=0.0, - test_size=0.0, -) -trainer.train() - - -# We can easily access the data by calling `trainer.callbacks[0].saved_metrics` (notice the zero representing the first callback in the list given at initialization). - -# In[8]: - - -trainer.callbacks[0].saved_metrics[:3] # only the first three epochs - - -# PyTorch Lightning also has some built in `Callbacks` which can be used in **PINA**, [here an extensive list](https://lightning.ai/docs/pytorch/stable/extensions/callbacks.html#built-in-callbacks). -# -# We can for example try the `EarlyStopping` routine, which automatically stops the training when a specific metric converged (here the `train_loss`). In order to let the training keep going forever set `max_epochs=-1`. - -# In[ ]: - - -model = FeedForward( - layers=[10, 10], - func=torch.nn.Tanh, - output_dimensions=len(problem.output_variables), - input_dimensions=len(problem.input_variables), -) -pinn = PINN(problem, model) -trainer = Trainer( - solver=pinn, - accelerator="cpu", - max_epochs=-1, - enable_model_summary=False, - enable_progress_bar=False, - val_size=0.2, - train_size=0.8, - test_size=0.0, - callbacks=[EarlyStopping("val_loss")], -) # adding a callbacks -trainer.train() - - -# As we can see the model automatically stop when the logging metric stopped improving! - -# ## Trainer Tips to Boost Accuracy, Save Memory and Speed Up Training -# -# Untill now we have seen how to choose the right `accelerator`, how to log and visualize the results, and how to interface with the program in order to add specific parts of code at specific points by `callbacks`. -# Now, we well focus on how boost your training by saving memory and speeding it up, while mantaining the same or even better degree of accuracy! -# -# -# There are several built in methods developed in PyTorch Lightning which can be applied straight forward in **PINA**, here we report some: -# -# * [Stochastic Weight Averaging](https://pytorch.org/blog/pytorch-1.6-now-includes-stochastic-weight-averaging/) to boost accuracy -# * [Gradient Clippling](https://deepgram.com/ai-glossary/gradient-clipping) to reduce computational time (and improve accuracy) -# * [Gradient Accumulation](https://lightning.ai/docs/pytorch/stable/common/optimization.html#id3) to save memory consumption -# * [Mixed Precision Training](https://lightning.ai/docs/pytorch/stable/common/optimization.html#id3) to save memory consumption -# -# We will just demonstrate how to use the first two, and see the results compared to a standard training. -# We use the [`Timer`](https://lightning.ai/docs/pytorch/stable/api/lightning.pytorch.callbacks.Timer.html#lightning.pytorch.callbacks.Timer) callback from `pytorch_lightning.callbacks` to take the times. Let's start by training a simple model without any optimization (train for 2000 epochs). - -# In[10]: - - -from lightning.pytorch.callbacks import Timer -from lightning.pytorch import seed_everything - -# setting the seed for reproducibility -seed_everything(42, workers=True) - -model = FeedForward( - layers=[10, 10], - func=torch.nn.Tanh, - output_dimensions=len(problem.output_variables), - input_dimensions=len(problem.input_variables), -) - -pinn = PINN(problem, model) -trainer = Trainer( - solver=pinn, - accelerator="cpu", - deterministic=True, # setting deterministic=True ensure reproducibility when a seed is imposed - max_epochs=2000, - enable_model_summary=False, - callbacks=[Timer()], -) # adding a callbacks -trainer.train() -print(f'Total training time {trainer.callbacks[0].time_elapsed("train"):.5f} s') - - -# Now we do the same but with StochasticWeightAveraging - -# In[11]: - - -from lightning.pytorch.callbacks import StochasticWeightAveraging - -# setting the seed for reproducibility -seed_everything(42, workers=True) - -model = FeedForward( - layers=[10, 10], - func=torch.nn.Tanh, - output_dimensions=len(problem.output_variables), - input_dimensions=len(problem.input_variables), -) -pinn = PINN(problem, model) -trainer = Trainer( - solver=pinn, - accelerator="cpu", - deterministic=True, - max_epochs=2000, - enable_model_summary=False, - callbacks=[Timer(), StochasticWeightAveraging(swa_lrs=0.005)], -) # adding StochasticWeightAveraging callbacks -trainer.train() -print(f'Total training time {trainer.callbacks[0].time_elapsed("train"):.5f} s') - - -# As you can see, the training time does not change at all! Notice that around epoch `1600` -# the scheduler is switched from the defalut one `ConstantLR` to the Stochastic Weight Average Learning Rate (`SWALR`). -# This is because by default `StochasticWeightAveraging` will be activated after `int(swa_epoch_start * max_epochs)` with `swa_epoch_start=0.7` by default. Finally, the final `mean_loss` is lower when `StochasticWeightAveraging` is used. -# -# We will now now do the same but clippling the gradient to be relatively small. - -# In[12]: - - -# setting the seed for reproducibility -seed_everything(42, workers=True) - -model = FeedForward( - layers=[10, 10], - func=torch.nn.Tanh, - output_dimensions=len(problem.output_variables), - input_dimensions=len(problem.input_variables), -) -pinn = PINN(problem, model) -trainer = Trainer( - solver=pinn, - accelerator="cpu", - max_epochs=2000, - enable_model_summary=False, - gradient_clip_val=0.1, # clipping the gradient - callbacks=[Timer(), StochasticWeightAveraging(swa_lrs=0.005)], -) -trainer.train() -print(f'Total training time {trainer.callbacks[0].time_elapsed("train"):.5f} s') - - -# As we can see we by applying gradient clipping we were able to even obtain lower error! -# -# ## What's next? -# -# Now you know how to use efficiently the `Trainer` class **PINA**! There are multiple directions you can go now: -# -# 1. Explore training times on different devices (e.g.) `TPU` -# -# 2. Try to reduce memory cost by mixed precision training and gradient accumulation (especially useful when training Neural Operators) -# -# 3. Benchmark `Trainer` speed for different precisions. diff --git a/tutorials/tutorial12/tutorial.ipynb b/tutorials/tutorial12/tutorial.ipynb index 0223da5..7c9cb79 100644 --- a/tutorials/tutorial12/tutorial.ipynb +++ b/tutorials/tutorial12/tutorial.ipynb @@ -4,50 +4,37 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Tutorial: The `Equation` Class\n", + "# Tutorial: Introduction to PINA `Equation` class\n", "\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial12/tutorial.ipynb)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In this tutorial, we will show how to use the `Equation` Class in PINA. Specifically, we will see how use the Class and its inherited classes to enforce residuals minimization in PINNs." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Example: The Burgers 1D equation" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial12/tutorial.ipynb)\n", + "\n", + "\n", + "In this tutorial, we will explore how to use the `Equation` class in **PINA**. We will focus on how to leverage this class, along with its inherited subclasses, to enforce residual minimization in **Physics-Informed Neural Networks (PINNs)**.\n", + "\n", + "By the end of this guide, you'll understand how to integrate physical laws and constraints directly into your model training, ensuring that the solution adheres to the underlying differential equations.\n", + "\n", + "\n", + "## Example: The Burgers 1D equation\n", "We will start implementing the viscous Burgers 1D problem Class, described as follows:\n", "\n", - "\n", "$$\n", "\\begin{equation}\n", "\\begin{cases}\n", "\\frac{\\partial u}{\\partial t} + u \\frac{\\partial u}{\\partial x} &= \\nu \\frac{\\partial^2 u}{ \\partial x^2}, \\quad x\\in(0,1), \\quad t>0\\\\\n", - "u(x,0) &= -\\sin (\\pi x)\\\\\n", - "u(x,t) &= 0 \\quad x = \\pm 1\\\\\n", + "u(x,0) &= -\\sin (\\pi x), \\quad x\\in(0,1)\\\\\n", + "u(x,t) &= 0, \\quad x = \\pm 1, \\quad t>0\\\\\n", "\\end{cases}\n", "\\end{equation}\n", "$$\n", "\n", "where we set $ \\nu = \\frac{0.01}{\\pi}$.\n", "\n", - "In the class that models this problem we will see in action the `Equation` class and one of its inherited classes, the `FixedValue` class. " + "In the class that models this problem we will see in action the `Equation` class and one of its inherited classes, the `FixedValue` class." ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -59,7 +46,7 @@ "except:\n", " IN_COLAB = False\n", "if IN_COLAB:\n", - " !pip install \"pina-mathlab\"\n", + " !pip install \"pina-mathlab[tutorial]\"\n", "\n", "import torch\n", "\n", @@ -68,7 +55,14 @@ "from pina.problem import SpatialProblem, TimeDependentProblem\n", "from pina.equation import Equation, FixedValue\n", "from pina.domain import CartesianDomain\n", - "from pina.operator import grad, laplacian" + "from pina.operator import grad, fast_grad, laplacian" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's begin by defining the Burgers equation and its initial condition as Python functions. These functions will take the model's `input` (spatial and temporal coordinates) and `output` (predicted solution) as arguments. The goal is to compute the residuals for the Burgers equation, which we will minimize during training." ] }, { @@ -79,7 +73,7 @@ "source": [ "# define the burger equation\n", "def burger_equation(input_, output_):\n", - " du = grad(output_, input_)\n", + " du = fast_grad(output_, input_, components=[\"u\"], d=[\"x\"])\n", " ddu = grad(du, input_, components=[\"dudx\"])\n", " return (\n", " du.extract([\"dudt\"])\n", @@ -91,9 +85,32 @@ "# define initial condition\n", "def initial_condition(input_, output_):\n", " u_expected = -torch.sin(torch.pi * input_.extract([\"x\"]))\n", - " return output_.extract([\"u\"]) - u_expected\n", + " return output_.extract([\"u\"]) - u_expected" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Above we use the `grad` operator from `pina.operator` to compute the gradient. In PINA each differential operator takes the following inputs:\n", + "- `output_`: A tensor on which the operator is applied.\n", + "- `input_`: A tensor with respect to which the operator is computed.\n", + "- `components`: The names of the output variables for which the operator is evaluated.\n", + "- `d`: The names of the variables with respect to which the operator is computed.\n", "\n", + "Each differential operator has its **fast** version, which performs no internal checks on input and output tensors. For these methods, the user is always required to specify both ``components`` and ``d`` as lists of strings.\n", "\n", + "Let's define now the problem!\n", + "\n", + "> **👉 Do you want to learn more on Problems? Check the dedicated [tutorial](https://mathlab.github.io/PINA/tutorial16/tutorial.html) to learn how to build a Problem from scratch.**" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ "class Burgers1D(TimeDependentProblem, SpatialProblem):\n", "\n", " # assign output/ spatial and temporal variables\n", @@ -128,36 +145,29 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "\n", "The `Equation` class takes as input a function (in this case it happens twice, with `initial_condition` and `burger_equation`) which computes a residual of an equation, such as a PDE. In a problem class such as the one above, the `Equation` class with such a given input is passed as a parameter in the specified `Condition`. \n", "\n", - "The `FixedValue` class takes as input a value of same dimensions of the output functions; this class can be used to enforce a fixed value for a specific condition, e.g. Dirichlet boundary conditions, as it happens for instance in our example.\n", + "The `FixedValue` class takes as input a value of the same dimensions as the output functions. This class can be used to enforce a fixed value for a specific condition, such as Dirichlet boundary conditions, as demonstrated in our example.\n", "\n", - "Once the equations are set as above in the problem conditions, the PINN solver will aim to minimize the residuals described in each equation in the training phase. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Available classes of equations include also:\n", - "- `FixedGradient` and `FixedFlux`: they work analogously to `FixedValue` class, where we can require a constant value to be enforced, respectively, on the gradient of the solution or the divergence of the solution;\n", - "- `Laplace`: it can be used to enforce the laplacian of the solution to be zero;\n", - "- `SystemEquation`: we can enforce multiple conditions on the same subdomain through this class, passing a list of residual equations defined in the problem.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Defining a new Equation class" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "`Equation` classes can be also inherited to define a new class. As example, we can see how to rewrite the above problem introducing a new class `Burgers1D`; during the class call, we can pass the viscosity parameter $\\nu$:" + "Once the equations are set as above in the problem conditions, the PINN solver will aim to minimize the residuals described in each equation during the training phase. \n", + "\n", + "### Available classes of equations:\n", + "- `FixedGradient` and `FixedFlux`: These work analogously to the `FixedValue` class, where we can enforce a constant value on the gradient or the divergence of the solution, respectively.\n", + "- `Laplace`: This class can be used to enforce that the Laplacian of the solution is zero.\n", + "- `SystemEquation`: This class allows you to enforce multiple conditions on the same subdomain by passing a list of residual equations defined in the problem.\n", + "\n", + "## Defining a new Equation class\n", + "`Equation` classes can also be inherited to define a new class. For example, we can define a new class `Burgers1D` to represent the Burgers equation. During the class call, we can pass the viscosity parameter $\\nu$:\n", + "\n", + "```python\n", + "class Burgers1D(Equation):\n", + " def __init__(self, nu):\n", + " self.nu = nu\n", + "\n", + " def equation(self, input_, output_):\n", + " ...\n", + "```\n", + "In this case, the `Burgers1D` class will inherit from the `Equation` class and compute the residual of the Burgers equation. The viscosity parameter $\\nu$ is passed when instantiating the class and used in the residual calculation. Let's see it in more details:" ] }, { @@ -239,17 +249,18 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# What's next?" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Congratulations on completing the `Equation` class tutorial of **PINA**! As we have seen, you can build new classes that inherit `Equation` to store more complex equations, as the Burgers 1D equation, only requiring to pass the characteristic coefficients of the problem. \n", - "From now on, you can:\n", - "- define additional complex equation classes (e.g. `SchrodingerEquation`, `NavierStokeEquation`..)\n", - "- define more `FixedOperator` (e.g. `FixedCurl`)" + "## What's Next?\n", + "\n", + "Congratulations on completing the `Equation` class tutorial of **PINA**! As we've seen, you can build new classes that inherit from `Equation` to store more complex equations, such as the 1D Burgers equation, by simply passing the characteristic coefficients of the problem.\n", + "\n", + "From here, you can:\n", + "\n", + "- **Define Additional Complex Equation Classes**: Create your own equation classes, such as `SchrodingerEquation`, `NavierStokesEquation`, etc.\n", + "- **Define More `FixedOperator` Classes**: Implement operators like `FixedCurl`, `FixedDivergence`, and others for more advanced simulations.\n", + "- **Integrate Custom Equations and Operators**: Combine your custom equations and operators into larger systems for more complex simulations.\n", + "- **and many more!**: Explore for example different residual minimization techniques to improve the performance and accuracy of your models.\n", + "\n", + "For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/)." ] } ], diff --git a/tutorials/tutorial12/tutorial.py b/tutorials/tutorial12/tutorial.py deleted file mode 100644 index 213e207..0000000 --- a/tutorials/tutorial12/tutorial.py +++ /dev/null @@ -1,188 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# # Tutorial: The `Equation` Class -# -# [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial12/tutorial.ipynb) - -# In this tutorial, we will show how to use the `Equation` Class in PINA. Specifically, we will see how use the Class and its inherited classes to enforce residuals minimization in PINNs. - -# # Example: The Burgers 1D equation - -# We will start implementing the viscous Burgers 1D problem Class, described as follows: -# -# -# $$ -# \begin{equation} -# \begin{cases} -# \frac{\partial u}{\partial t} + u \frac{\partial u}{\partial x} &= \nu \frac{\partial^2 u}{ \partial x^2}, \quad x\in(0,1), \quad t>0\\ -# u(x,0) &= -\sin (\pi x)\\ -# u(x,t) &= 0 \quad x = \pm 1\\ -# \end{cases} -# \end{equation} -# $$ -# -# where we set $ \nu = \frac{0.01}{\pi}$. -# -# In the class that models this problem we will see in action the `Equation` class and one of its inherited classes, the `FixedValue` class. - -# In[1]: - - -## routine needed to run the notebook on Google Colab -try: - import google.colab - - IN_COLAB = True -except: - IN_COLAB = False -if IN_COLAB: - get_ipython().system('pip install "pina-mathlab"') - -import torch - -# useful imports -from pina import Condition -from pina.problem import SpatialProblem, TimeDependentProblem -from pina.equation import Equation, FixedValue -from pina.domain import CartesianDomain -from pina.operator import grad, laplacian - - -# In[2]: - - -# define the burger equation -def burger_equation(input_, output_): - du = grad(output_, input_) - ddu = grad(du, input_, components=["dudx"]) - return ( - du.extract(["dudt"]) - + output_.extract(["u"]) * du.extract(["dudx"]) - - (0.01 / torch.pi) * ddu.extract(["ddudxdx"]) - ) - - -# define initial condition -def initial_condition(input_, output_): - u_expected = -torch.sin(torch.pi * input_.extract(["x"])) - return output_.extract(["u"]) - u_expected - - -class Burgers1D(TimeDependentProblem, SpatialProblem): - - # assign output/ spatial and temporal variables - output_variables = ["u"] - spatial_domain = CartesianDomain({"x": [-1, 1]}) - temporal_domain = CartesianDomain({"t": [0, 1]}) - - domains = { - "bound_cond1": CartesianDomain({"x": -1, "t": [0, 1]}), - "bound_cond2": CartesianDomain({"x": 1, "t": [0, 1]}), - "time_cond": CartesianDomain({"x": [-1, 1], "t": 0}), - "phys_cond": CartesianDomain({"x": [-1, 1], "t": [0, 1]}), - } - # problem condition statement - conditions = { - "bound_cond1": Condition( - domain="bound_cond1", equation=FixedValue(0.0) - ), - "bound_cond2": Condition( - domain="bound_cond2", equation=FixedValue(0.0) - ), - "time_cond": Condition( - domain="time_cond", equation=Equation(initial_condition) - ), - "phys_cond": Condition( - domain="phys_cond", equation=Equation(burger_equation) - ), - } - - -# -# The `Equation` class takes as input a function (in this case it happens twice, with `initial_condition` and `burger_equation`) which computes a residual of an equation, such as a PDE. In a problem class such as the one above, the `Equation` class with such a given input is passed as a parameter in the specified `Condition`. -# -# The `FixedValue` class takes as input a value of same dimensions of the output functions; this class can be used to enforce a fixed value for a specific condition, e.g. Dirichlet boundary conditions, as it happens for instance in our example. -# -# Once the equations are set as above in the problem conditions, the PINN solver will aim to minimize the residuals described in each equation in the training phase. - -# Available classes of equations include also: -# - `FixedGradient` and `FixedFlux`: they work analogously to `FixedValue` class, where we can require a constant value to be enforced, respectively, on the gradient of the solution or the divergence of the solution; -# - `Laplace`: it can be used to enforce the laplacian of the solution to be zero; -# - `SystemEquation`: we can enforce multiple conditions on the same subdomain through this class, passing a list of residual equations defined in the problem. -# - -# # Defining a new Equation class - -# `Equation` classes can be also inherited to define a new class. As example, we can see how to rewrite the above problem introducing a new class `Burgers1D`; during the class call, we can pass the viscosity parameter $\nu$: - -# In[3]: - - -class Burgers1DEquation(Equation): - - def __init__(self, nu=0.0): - """ - Burgers1D class. This class can be - used to enforce the solution u to solve the viscous Burgers 1D Equation. - - :param torch.float32 nu: the viscosity coefficient. Default value is set to 0. - """ - self.nu = nu - - def equation(input_, output_): - return ( - grad(output_, input_, d="t") - + output_ * grad(output_, input_, d="x") - - self.nu * laplacian(output_, input_, d="x") - ) - - super().__init__(equation) - - -# Now we can just pass the above class as input for the last condition, setting $\nu= \frac{0.01}{\pi}$: - -# In[4]: - - -class Burgers1D(TimeDependentProblem, SpatialProblem): - - # define initial condition - def initial_condition(input_, output_): - u_expected = -torch.sin(torch.pi * input_.extract(["x"])) - return output_.extract(["u"]) - u_expected - - # assign output/ spatial and temporal variables - output_variables = ["u"] - spatial_domain = CartesianDomain({"x": [-1, 1]}) - temporal_domain = CartesianDomain({"t": [0, 1]}) - - domains = { - "bound_cond1": CartesianDomain({"x": -1, "t": [0, 1]}), - "bound_cond2": CartesianDomain({"x": 1, "t": [0, 1]}), - "time_cond": CartesianDomain({"x": [-1, 1], "t": 0}), - "phys_cond": CartesianDomain({"x": [-1, 1], "t": [0, 1]}), - } - # problem condition statement - conditions = { - "bound_cond1": Condition( - domain="bound_cond1", equation=FixedValue(0.0) - ), - "bound_cond2": Condition( - domain="bound_cond2", equation=FixedValue(0.0) - ), - "time_cond": Condition( - domain="time_cond", equation=Equation(initial_condition) - ), - "phys_cond": Condition( - domain="phys_cond", equation=Burgers1DEquation(nu=0.01 / torch.pi) - ), - } - - -# # What's next? - -# Congratulations on completing the `Equation` class tutorial of **PINA**! As we have seen, you can build new classes that inherit `Equation` to store more complex equations, as the Burgers 1D equation, only requiring to pass the characteristic coefficients of the problem. -# From now on, you can: -# - define additional complex equation classes (e.g. `SchrodingerEquation`, `NavierStokeEquation`..) -# - define more `FixedOperator` (e.g. `FixedCurl`) diff --git a/tutorials/tutorial13/tutorial.ipynb b/tutorials/tutorial13/tutorial.ipynb index 765ca47..b814070 100644 --- a/tutorials/tutorial13/tutorial.ipynb +++ b/tutorials/tutorial13/tutorial.ipynb @@ -4,17 +4,13 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Tutorial: Multiscale PDE learning with Fourier Feature Network\n", + "# Tutorial: Learning Multiscale PDEs Using Fourier Feature Networks\n", "\n", "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial13/tutorial.ipynb)\n", "\n", - "This tutorial presents how to solve with Physics-Informed Neural Networks (PINNs)\n", - "a PDE characterized by multiscale behaviour, as\n", - "presented in [*On the eigenvector bias of Fourier feature networks: From regression to solving\n", - "multi-scale PDEs with physics-informed neural networks*](\n", - "https://doi.org/10.1016/j.cma.2021.113938). \n", + "This tutorial demonstrates how to solve a PDE with multiscale behavior using Physics-Informed Neural Networks (PINNs), as discussed in [*On the Eigenvector Bias of Fourier Feature Networks: From Regression to Solving Multi-Scale PDEs with Physics-Informed Neural Networks*](https://doi.org/10.1016/j.cma.2021.113938).\n", "\n", - "First of all, some useful imports." + "Let’s begin by importing the necessary libraries.\n" ] }, { @@ -31,7 +27,7 @@ "except:\n", " IN_COLAB = False\n", "if IN_COLAB:\n", - " !pip install \"pina-mathlab\"\n", + " !pip install \"pina-mathlab[tutorial]\"\n", "\n", "import torch\n", "import matplotlib.pyplot as plt\n", @@ -56,24 +52,31 @@ "source": [ "## Multiscale Problem\n", "\n", - "We begin by presenting the problem which also can be found in Section 2 of [*On the eigenvector bias of Fourier feature networks: From regression to solving\n", - "multi-scale PDEs with physics-informed neural networks*](\n", - "https://doi.org/10.1016/j.cma.2021.113938). The one-dimensional Poisson problem we aim to solve is mathematically written as:\n", + "We begin by presenting the problem, which is also discussed in Section 2 of [*On the Eigenvector Bias of Fourier Feature Networks: From Regression to Solving Multi-Scale PDEs with Physics-Informed Neural Networks*](https://doi.org/10.1016/j.cma.2021.113938). The one-dimensional Poisson problem we aim to solve is mathematically defined as:\n", "\n", "\\begin{equation}\n", "\\begin{cases}\n", - "\\Delta u (x) + f(x) = 0 \\quad x \\in [0,1], \\\\\n", - "u(x) = 0 \\quad x \\in \\partial[0,1], \\\\\n", + "\\Delta u(x) + f(x) = 0 \\quad x \\in [0,1], \\\\\n", + "u(x) = 0 \\quad x \\in \\partial[0,1],\n", "\\end{cases}\n", "\\end{equation}\n", "\n", - "We impose the solution as $u(x) = \\sin(2\\pi x) + 0.1 \\sin(50\\pi x)$ and obtain the force term $f(x) = (2\\pi)^2 \\sin(2\\pi x) + 0.1 (50 \\pi)^2 \\sin(50\\pi x)$.\n", - "Though this example is simple and pedagogical, it is worth noting that\n", - "the solution exhibits low frequency in the macro-scale and high frequency in the micro-scale, which resembles many\n", - "practical scenarios.\n", + "We define the solution as:\n", "\n", + "$$\n", + "u(x) = \\sin(2\\pi x) + 0.1 \\sin(50\\pi x),\n", + "$$\n", "\n", - "In **PINA** this problem is written, as always, as a class [see here for a tutorial on the Problem class](https://mathlab.github.io/PINA/_rst/tutorials/tutorial1/tutorial.html). Below you can find the `Poisson` problem which is mathmatically described above." + "which leads to the corresponding force term:\n", + "\n", + "$$\n", + "f(x) = (2\\pi)^2 \\sin(2\\pi x) + 0.1 (50 \\pi)^2 \\sin(50\\pi x).\n", + "$$\n", + "\n", + "While this example is simple and pedagogical, it's important to note that the solution exhibits low-frequency behavior in the macro-scale and high-frequency behavior in the micro-scale. This characteristic is common in many practical scenarios.\n", + "\n", + "Below is the implementation of the `Poisson` problem as described mathematically above.\n", + "> **👉 We have a dedicated [tutorial](https://mathlab.github.io/PINA/tutorial16/tutorial.html) to teach how to build a Problem from scratch — have a look if you're interested!**" ] }, { @@ -127,10 +130,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "A standard PINN approach would be to fit this model using a Feed Forward (fully connected) Neural Network. For a conventional fully-connected neural network is easy to\n", - "approximate a function $u$, given sufficient data inside the computational domain. However solving high-frequency or multi-scale problems presents great challenges to PINNs especially when the number of data cannot capture the different scales.\n", + "A standard PINN approach would involve fitting the model using a Feed Forward (fully connected) Neural Network. For a conventional fully-connected neural network, it is relatively easy to approximate a function $u$, given sufficient data inside the computational domain. \n", "\n", - "Below we run a simulation using the `PINN` solver and the self adaptive `SAPINN` solver, using a [`FeedForward`](https://mathlab.github.io/PINA/_modules/pina/model/feed_forward.html#FeedForward) model. " + "However, solving high-frequency or multi-scale problems presents significant challenges to PINNs, especially when the number of data points is insufficient to capture the different scales effectively.\n", + "\n", + "Below, we run a simulation using both the `PINN` solver and the self-adaptive `SAPINN` solver, employing a [`FeedForward`](https://mathlab.github.io/PINA/_modules/pina/model/feed_forward.html#FeedForward) model.\n" ] }, { @@ -148,42 +152,42 @@ ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1499: 100%|██████████| 1/1 [00:00<00:00, 161.89it/s, v_num=2, bound_cond0_loss=3.12e+3, bound_cond1_loss=3.12e+3, phys_cond_loss=1.21e+3, train_loss=7.46e+3]" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "`Trainer.fit` stopped: `max_epochs=1500` reached.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1499: 100%|██████████| 1/1 [00:00<00:00, 104.39it/s, v_num=2, bound_cond0_loss=3.12e+3, bound_cond1_loss=3.12e+3, phys_cond_loss=1.21e+3, train_loss=7.46e+3]" - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "b9db39fafd844f7fa5e3cb0b39307330", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" ] @@ -256,7 +253,7 @@ }, { "data": { - "image/png": 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Q0XX3SEhhUCEiIjIvTxu2wcG0REREZLIYVIiIiMhkMagQERGRyTL7MSpERM87RTIxMRFJSUnGbgqRRbGzs4O9vf1zLx3CoEJEVis+Ph7Xr1/H/fv3jd0UIovk6uqKgIAAODo6PvN9MKgQkVWSxSLPnz+vvvXJglPyQcpFI4lyrlIpXwRu3ryp/s5Kly6d6aJumWFQISKrJB+iElZkHQf51kdEOcvFxQUODg64ePGi+ntzdnZ+pvvhYFoismrP+i2PiHLn74t/oURERGSyGFSIiIjIZDGoEBGRQTRt2hRDhw6FpRszZgyqVauWa4+3YMECeHl5Pff9bNu2TQ0gv3fvHkwZgwoRkZnp1auX2sF89913qS5fs2aNWc1ckh2utLdVq1apLpcdp1wuO9LsbJMOHToYoJWWGxrr16+vpud7enrClDGoZOD8rVh0/3kvTkVEG7spRERPkBkU33//Pe7evZvrj52QkJBj9yULgv3zzz/YunUrzHWxQHPl6OgIf39/kw+3DCoZGLf+JHaevoXWU3Zi3IaTiI0z3zcjEWV9x3M/PtEoJ3ns7GjevLnayYwbNy7T2+3atQuNGjVSU0VlKvZ7772H2NjYlOtlJyWVGH3SrSDVDnHhwgV1m99++w1NmjRRAWnx4sW4ffs23njjDRQsWFBN765cuTKWLl2K7HJzc0Pv3r0xYsSITG93+fJlvPbaa6ptefPmRfv27VXbdF0vCxcuxNq1a1VbddWYzp07Y/DgwSn3IRUFuS40NFSdlymz8vgSlERcXJzaPr6+vup5NmzYEPv373+iq2TDhg2oWbMmnJyc1PZN6+zZsyhRooR67PReV7lM2lykSBF1H7KOjzyujoTPHj16wNvbW23bl19+GadPn85WNUmeq1RRdNdv374dU6ZMSdk+su3S6/pZtWoVKlasqNpVrFgx/O9//0t1v3LZt99+q14zd3d39Rzmzp0LQ+I6Khn4vG0FyNtr84kIzNl+Dn8euobRr1REy4r+xm4aERnIg4QkVPhik1Ee+8RXLeHqmPWPZFmoTnYYb775ptrJFSpUKN0dpnSrfPPNN5g3b55afEt2nnKaP39+ttonQUJ2WtWrV1c78YcPH6qd9fDhw+Hh4YF169ahe/fuKFmyJOrUqZOt+5addqlSpbBy5UoVLtKr4LRs2RKBgYHYuXOnqsLIc5LnduTIEXz00Uc4efIkoqKiUp6XhJmjR49izpw5KfcjO2sfHx+1gy5XrpwKIXLf0gUiPvnkE7WjltBTtGhRjB8/Xj3umTNn1P3pb4sffvhBhREJE/pdVNIe+Z0+ffqoNqZHHmPSpElYtmyZCgXh4eE4fPhwyvUSLCSY/PHHH2rbyjZu3bo1Tpw4odYlyS4JKKdOnUKlSpXw1Vdfqcvy58+fEvR0QkJCVBiU16Nr164ICgrCwIEDkS9fPtUmHXkffP311/j000/VazZgwAAVYsuWLQtDYEUlA4XzuuLHHrXwU49aKOTtgmuRD9Hv1xB8svIwqytEZBJeffVVNYhz9OjR6V4v1ZZu3bqpb9eyMqjskKdOnYpffvlFBY3skPvo2LEjihcvrpZEl0qKBAR5fNlhDxkyRAWH5cuXZ/t5SEXh/fffx6hRo9LtSpFqjizO99NPP6nKTfny5VUguXTpkgoJefLkURUjqQJIlUlO0q0hFQXZuUtAkyqF/CyPowsW8n/t2rVV1UKqTLNmzcKECRNUBaNChQr48ccf1f3+/PPPqdojO/uXXnpJhTL9ACM7dnlM2S4ZhRQh7ZY2SlVMKhIS7Pr27auu0wUUea5SCatataqqYF29evWJyldWyRgU2R7yPHXbR4JuWhMnTsSLL76Izz//HGXKlFHhREKtbBN9EpokwEi4lBAl4c+QXXesqDxF8wp+aFDKB1O2nMacHWex/L8rOHjpHub1qq3CDBFZDhcHO1XZMNZjPwsZp/LCCy+onWNa8i1dvuHLjk6/20F3+ADZ4WdVrVq1Up2XgzhKRUeCiexEpRtFuk6edZVf2eFJ9UMqP/KtPu3zkKqGdDXok7AlVaOMSAVBgoRUUmRHLdWgtm3bYsaMGep6uVzXPSL3I9WVBg0apPy+VC8kREi1JrNtoQsfEl7Gjh371JlOXbp0weTJk1XAk3AnO/527dqpSpE8lvxft27dlNvny5dPVSvStiOnyf1Ll5o+2R7SVnm9deGmSpUqKddL15EEnxs3bhisXQwqWeDiaIcRL5dDkzL58f6ygzh9IwYdZuzG3B41UbPo4zRNROZNPnSz0/1iCho3bqy6GkaOHJmqPC9iYmLQr1+/VOMfdOSbvO45px1Hkd5gWRnLoU++ZUuXguzEpMoh18sOWgLLs5CxJ/IcvvzySxUm0j4P6WbSD1w60oWREXlusn2kciLVFgklspOVQHXs2DFVAUkv4D1N2m2ha4dUhmScjozfkC6bjMhYobCwMDU2ZvPmzao6IdtTgtOzrv6qycJrmFPSdj/Jdpbwayjs+smGwJL58MfghqhYwAO3Y+Pxxty9WHPwqrGbRURWTqYp//nnnwgODk51eY0aNVR3h5To0550R7OVHaxMUdWRroesHE169+7d6tv3W2+9pbonpDog4yCeh3QfyU5XAlDa5yHtkkGuaZ+HbmqtPB/51p+WjJ2QoCInCSpy/xJeJBhIYNFVUKQbR+5Dnpf+zl7GsUg30NNIF9Fff/2lxu9IcIyOjn7q7aWKIl1x0jZ57WRMjVS5pPtr7969Kbe9ffu2CjYZtSPtaygOHTqU6nxG20efPLb+8xdyXrqB0usqyi0MKtnk7+mMFf0D0aKCH+KTkjH0t0OYuPlUtkfsExHlFKloyFgU2eml7U6RqoGMM5Adl+zsZWaM/kwY6TaaPn06Dh48iP/++w/9+/fP0oBNGfMi1QC5f+kykMpNRETEcz0P2clLRSXt85DnJuMgJBjJYFrptpKdu1SKrly5kjIbRbq5ZId+69atlIqCbpzK8ePH1Swe3WVSnZEuHF11RP6XQaEff/wxNm7cqH5Hxo1IaJOBsVkh9yGDiqXrRsa5SCUoPTKjSsa9SFXn3LlzWLRokQouMoBXtqs8T3lsmVF0+PBhFQZlTFDabhn911BeOxl7JK+xjFmS+9Yn20fCjwygle2TXgVk2LBh2LJlixooK6FTBhXLe+NZqk45iUHlGUhpePZbNdGvSQl1fuqW0/jgt0OIS8w8rRIRGYoM8Ey785FuDulOkJ2ODMyUMRpffPGF6qLQn8EhXRFyvcwgkp1SVsaZfPbZZ6rSIdUD2fHLOIWcWHCtZ8+eqjqjT9qzY8cO1V0lA3rlm7+EBxmjoutikR27jOOQ8CEVBl1lQEKcdCvJoF8ZdCukvVJd0I1P0a9MderUSc1ekucm42I2bdqkZvZklTyGTF+WL69t2rRJNRVcR9ojA3WlmiOvkXQBSUVMxqIIGSgsXV3SBRYYGKjua/369RkGSHkNZACszFqSwcFSzZHpzfrkdZWqiFRlZPvImJq05DnLmCOZjSTje+S9Iu+rtF2Kuc1GY+alAJmOJqW/yMjITPsEDWXZvkv4bM0xJCZrULuYN+Z0r4W8btqSKhGZLtnJyTdzmcXyrIefJ6Jn/zvL6v6bFZXn9HqdIljwdh24O9tj/4W7eGX6Lhy+bNrHTSAiIjIXDCo5oGFpH/w+oD4K53XBlbsP0Hl2EGZsPYOEJMONgiYiIrIGDCo5pLSfO/4a0ggvV/JHQpIGEzaFoc3Unfjvwh1jN42IiMhsMajkIE8XB8zsVgP/61JVjVM5FRGDzrODMWLVEdyNfba1BYiIiKwZg0oOk4VvOtUshC0fNkHXWoXVZcv2X0az/23D0n2XkJxs1mOXiYiIchWDioF4uzni+85VsLxfIMr6uePe/QSM/P0oXp0VhOPXIo3dPCIiIrPAoGJgdYrnxV/vNVRHY87jZK9mBMny+3O2n2V1hYiI6CkYVHKBg50t+jQsjn+HNUHLin5qsO24DaF499cQHomZiIgoEwwqucjXw1mtaPtdx8pwtLfFPycj1GDbq/ceGLtpREREJolBxQiDbWWRuGXv1oNPHiecvB6F9tN34+Clu8ZuGhFRrpFj9cjn4b17z7dAphy7Ru4n7UH4yHIwqBhJjSLeWDu4Acr5u+NWTBxen7sHG46mPvolEVFaslPO7DRmzBhYKjnmTNrjCclxiuTIwXJsGrJMDCpGVNDLBSsH1MeL5XwRl5iMgUsO4Ked53gkZiLKkOyUdafJkyerY6ToX6Z/pFv5LElMtOxxcHKgPTkgohyxmCwTg4qRyUyguT1qoXu9opB88s26k/jyzxNI4owgotwnf4TxscY5ZfELiuyUdSc5oJtUUXTnQ0ND4e7uro7eK0ffdXJywq5du9KtRAwdOjTV0YPlyMvjxo1TB49zcXFB1apVsXLlykzbMnPmTJQuXVodbM7Pzw+dO3dOuS4uLg7vvfcefH191fUNGzbE/v37M7wvqQTJEY71SRArVqxYyvULFy7E2rVrU6pH0n2UXtePHDG6Tp066vkHBARgxIgRqQKbPG9pmxxtOG/evGrbWXIlytwxgpoAO1sbfNW+ojpW0LfrQ7Eg6ALO34rF5K7V1HosRJRLEu4D3xYwzmN/eg1wdMuRu5Id8w8//IASJUrA29s7S78jIWXRokWYPXu2Ch87duzAW2+9hfz586NJkyZP3P6///5TO/tff/0V9evXx507d7Bz586U6yUErFq1SoWLokWLYvz48WjZsiXOnDmjwkF2SaXo5MmT6oi78+fPV5fJ/Vy7di3V7a5evYrWrVurcPbLL7+o8Na3b18VlvTDiLTrww8/xN69exEcHKxu36BBA7z00kvZbhsZFoOKiZBvBO82LokCXi4Ytvwwtp+6ibbTdmFClyqoX9LH2M0jIjPy1VdfZWuHK9WPb7/9Fv/88w8CAwPVZRJypBozZ86cdIPKpUuX4ObmhrZt26oqjoSR6tWrq+tiY2Mxa9YsLFiwAC+//LK67Mcff8TmzZvx888/4+OPP872c8qTJ4+q9EhbpQKSWZVHxq1Mnz5dfa6WK1dOhZnhw4fjiy++gK2ttiOhSpUqGD16tPpZgpncfsuWLQwq1hZU5I0qJynNiYoVK6o3iu6N+/DhQwwbNgzLli1Tbz5J2/ImkxKitWpbpQBK5s+DAYtCcOH2fbz54168UacwRrxcXh1LiIgMyMFVW9kw1mPnkFq1amXr9lLluH///hM76fj4+JTwkZbcVsKJBJpWrVqp06uvvgpXV1ecPXsWCQkJqkKh4+DgoLpjpCpiSHL/ErYkpOhIO2JiYnDlyhUUKVIkJajoky6iGzduGLRtZIJBpVChQvjuu+9UWpVBXVJqa9++PQ4ePKhCywcffIB169ZhxYoVqq918ODB6NixI3bv3g1rVj7AA38OaYjvNoRi8d5LWLrvMracvIGv2ldSC8bp/wESUQ6Sv60c6n4xJql06JMqQtpB+hIkdGQnLuTzuGDBgqluJ+M80iNVlAMHDqhxIn///bf6EipdK5mNQ8nM09qY0yQ46ZPPVRmnQ1Y2mLZdu3aqr1CCSpkyZTB27FhVvtuzZw8iIyNVCXDixIl44YUX1MAv6XcMCgpS11s7d2cHjH21slpvpbiPG25Ex6H/ohD0WfgfLt2+b+zmEZEZkXEmMiNIn/7g0woVKqhAIt05pUqVSnWSbpSMyEyb5s2bq/EnR44cUdXzf//9FyVLloSjo2OqL50SOiTEyGNl1Mbw8PBUYSXt2ihyn0lJSZk+1/Lly6sxJ/r3I+2QYCVfnsn85NqsH3lzSReP9F1KWS4kJES9ceVNriN9iVKWkzdZRqSLSAZT6Z8sWb0S+bDh/UYY2LQkHOxs8G/oDbw0aTumbTmN+ESmfyJ6OvkyKINfZXDp6dOn1diMY8eOpVwvO3EZrCpVbql8S9eNVEumTZumzqfnr7/+wtSpU1WYuHjxorpvqUiULVtWVXQGDBigxqJs3LgRJ06cUANapXupT58+6d6fzMS5efOmCj3y+DNmzFCzl/TJDCAJRGFhYbh161a6FZeBAwfi8uXLGDJkiBpIK7OE5PnKwFnd+BQyLwZ/1Y4ePaqqKJLW+/fvj9WrV6tELclZ0rGXl1eq28v4FLkus5Hp0k2kO2WW9i2Fs4MdPmlVDhveb4z6JfOpNVf+t/kUXp25G2duRBu7eURk4mT83+eff65m4tSuXRvR0dHo0aNHqtt8/fXX6jbyGStVCRlzIl1BMl05PfLZ/fvvv6sQJLeX2UJLly5V3fpCuv07deqE7t27o0aNGmoczKZNmzKchST3IWMUJaDI1Oh9+/alWhNGSNiRICRjcKQCk94wAem6Wr9+vfp9uR/Z70g4+uyzz55jC5Ix2WgMvLqYDMaScqJ09cic/J9++knNcZcU/vbbb6sKiT4ZbNWsWTN8//336d6f3F7/d6SiImFF7l8WPrJ08nL9cfgaxvxxHHfvJ8DZwRY/dKmqBuESUdbJYP7z58+rHbFMXSWi3P07k/23FByetv82+PRkqZpIP6eQcSjSRzllyhR07dpVhRg5zoN+VSUiIiLTqWdSmclocJc1kAFf7asVRGCJfBi24jB2nr6FwUsO4tzNWAx5oRQH2hIRkUXJ9Q476cOUioiEFhl1LfPWdaTfUaovunn8lPmRmBe8XQd9GmrLshM3n8LQ3w7hYULmA82IiIjMiUErKiNHjlRrpsgAWekTXbJkiZrKJv2UUu6RfkMZ4CSrC0rZRwY/SUipV6+eIZtlUSvaft62Akr55sHna45h7aFruHL3AX7uWQterlzRloiIzJ9Bg4osniMDtmRanAQTWWBHQopuUaFJkyapUdgy4Ep/wTfKnjfqFEHRfK7o/2sIQi7eRadZQVjYuw4KeefcAlJEREQWOZjW0LI6GMcanIqIRs95+3A98iH8PJxU15AsHkdEGQ/ykymvsjQ7EeW8Bw8eqPV1nmcwLSeVW5Ayfu5YNaA+yvjlQURUHF6bHYytYVwSmiizlUllbQ8iMgzd31falYCzgxUVCxR5PwF9f/kP+y7cUSuCf9SiLPo3KanGtBDRY9ItLTMPfX191TFqOGuOKGdItJCQIkNAZGavHEvpWfffDCoWKi4xSa21IscJErWLeav1VormM//jmBDlFPn4kwUmJawQUc6TkCJLjqT3JYBBhZTl+y/jyz+PIzY+CS4OdhjZuhzeqlsUtqyuEKU6xIchD4BHZI0cHBxgZ2eX4fUMKpTi8p37+GTlEQSfu63O1ymWF2NfrYTSfu7GbhoREVmpKA6mJZ3CeV2x+J26GNOugqqqyNiV1lN3YsKmUC4QR0REJo1BxUpIV0+vBsWx+cPGaF7eFwlJGszYehYtJ+9Qa68QERGZIgYVKyOLwP3YoxZmv1UT/h7OuHj7PrrMDsLkf04hOdmsewGJiMgCMahYIRl93aqSP/7+sDFerV4Qkk8m/3NaTWmOesgBhUREZDoYVKyYh7MDJnWthv91qQpHe1tsCb2BzrOCcD3ygbGbRkREpDCoEDrVLIRV/evD190JpyJi0HFmEMLCo43dLCIiIgYV0qpcyBO/D6yvjsQsxwqScSt7H01nJiIiMhYGFUo10HZl/0DUKuqNqIeJ6P7zPqw/et3YzSIiIivGoEKpeLk6YtE7ddGigh/ik5IxaMkBLNh93tjNIiIiK8WgQk9wdrDDrLdq4q16RSDrFo/58wS+2xDK6ctERJTrGFQoXXKk5a/bV8LHLcuq87O3n8WQpQcRzenLRESUixhUKNP1VgY1K4UJnavA3tYG645eR7tpu3D4Mo80S0REuYNBhZ6qS63CWN4/EAW9XHDh9n28OnM3vt/I4wQREZHhMahQltQo4o117zVE+2oF1Eq2s7adRdtpu3DwEo8TREREhsOgQtmaETTl9eqY270m8rs74cyNGHSaFYRx60+yukJERAbBoELZ1qKiPzZ/8Pg4QXN2nEPrqTt5FGYiIspxDCr0zNUVOU7QTz1qqaX3z92MRefZQZi0mUdhJiKinMOgQs+leQU/bP6gCTrWKKjWXJmy5TTe/TUEMXGJxm4aERFZAAYVem6erg6Y+Fo1/PDoKMz/nIxAtx/34E5svLGbRkREZo5BhXJM55qFsLxfILxdHXD4SqQ6sOHVew+M3SwiIjJjDCqUo6oV9sKK/vUR4OmMszJuZVYQztyINnaziIjITDGoUI4r5ZsHqwbUR8n8brge+RBdZgfjEFezJSKiZ8CgQgZRwMtFVVaqFvLE3fsJePPHPdhx6qaxm0VERGaGQYUMJq+bI5b0rYdGpX1wPz4JfRbux9pDV43dLCIiMiMMKmRQbk72+LlnbbSrWgAJSRq8v+wQZmw9A43MZSYiInoKBhUyOJmyPKVrNfSqX0ydn7ApDP1+DcFdTl8mIqKnYFChXGFra4Mxr1TEdx0rw9HOFn+fiECLyTuwNfSGsZtGREQmjEGFctXrdYqkzAi6GR2Htxfsx8jfj3AlWyIiSheDCuW6yoU8se69RujTsDhsbICl+y6j1eQd2HvutrGbRkREJoZBhYzC2cEOn7etgCXv1ENBLxdcufsAr/+4B9+uP4mHCUnGbh4REVlDUBk3bhxq164Nd3d3+Pr6okOHDggLC0t1m4cPH2LQoEHIly8f8uTJg06dOiEiIsKQzSITElgyHzYObYTXahVSBzWcu+Mc2k/fjbM3Y4zdNCIisvSgsn37dhVC9uzZg82bNyMhIQEtWrRAbGxsym0++OAD/Pnnn1ixYoW6/bVr19CxY0dDNotMjLuzA8Z3roofe9SCTx5HhEVEo8P03dhykoGViMja2WhycUGLmzdvqsqKBJLGjRsjMjIS+fPnx5IlS9C5c2d1m9DQUJQvXx7BwcGoV6/eE/cRFxenTjpRUVEoXLiwui8PD4/ceipkIDLAduDiEOy/cBe2NsB3HavgtdqFjd0sIiLKYbL/9vT0fOr+O1fHqEhjRN68edX/ISEhqsrSvHnzlNuUK1cORYoUUUElo+4keWK6k4QUshz53Z2w+J16qisoWQN8suoIftxxztjNIiIiI8m1oJKcnIyhQ4eiQYMGqFSpkrosPDwcjo6O8PLySnVbPz8/dV16Ro4cqQKP7nT58uVcaT/l7gJx33eqgn6NS6jzY9efxIRNoVzNlojICtnn1gPJWJVjx45h165dz3U/Tk5O6kSWzcbGBiNbl4enqwPGbwzDjK1nEfkgAV+9UkktHkdERNYhVyoqgwcPxl9//YWtW7eiUKFCKZf7+/sjPj4e9+7dS3V7mfUj1xENbFoKY1+tpNZbWbTnEj5acRiJScnGbhYREVlCUJFSvYSU1atX499//0Xx4sVTXV+zZk04ODhgy5YtKZfJ9OVLly4hMDDQkE0jM9KtblFM7loNdrY2+P3gVQxacgBxiVxrhYjIGhh01s/AgQPVjJ61a9eibNmyKZfLIFgXFxf184ABA7B+/XosWLBAjfodMmSIujwoKChHRw2T+dt8IkKFlPjEZDQq7YOZ3Wqoqc1ERGR+srr/NmhQkXEG6Zk/fz569eqVsuDbsGHDsHTpUjXtuGXLlpg5c2aWu34YVKzL7jO30PeX/3A/PgmlffPg5561USSfq7GbRURE5hhUcgODivU5cuWeCisRUXFwd7bHt69WRruqBYzdLCIiMvd1VIhyQpVCXlg7qCGqF/FC9MNEDFl6EMOWH+YRmImILBCDCpklf09nLO8XiCEvlFIzglYduII2U3fiwKW7xm4aERHlIAYVMlsOdrYY1qIslvWthwKezrh4+z66zA7GpM2nOIWZiMhCMKiQ2atbIh82vN8Yr1QtgKRkDaZsOY1Os4Nx/tbjg18SEZF5YlAhiyAr2E59ozqmvF5NDbA9fPke2k3bpaY0ExGR+WJQIYvSvlpBbBraGHWK5VWDa2V20KxtZ3mcICIiM8WgQhangJcLFveti56BRdX57zeG4ruNPKghEZE5YlAhix1o+2X7ShjVurw6P2f7OXy6+pgaw0JEROaDQYUsWt/GJfBdx8pqCvPSfZcw9LdDSOCMICIis8GgQhbv9TpFMO2N6nCws8Gfh69h0GIe1JCIyFwwqJBVaFulAOZ2rwVHe1v8fSIC/X8NwcMEhhUiIlPHoEJWo1k5X8zrWRvODrbYGnZTzQh6EM+wQkRkyhhUyKo0LO2DBW/XgaujHXaevoUe8/bibmy8sZtFREQZYFAhq1OvRD782qeOWhhu/4W76DQriKvYEhGZKAYVsko1i+bFqgH1UdDLBeduxapVbP84fM3YzSIiojQYVMhqlfFzx+qB9VGnuHYV2/eWHsTI349ykC0RkQlhUCGr5uvhjCXv1MXgZqVS1lrpMGM3TkVEG7tpRETEoEIE2NvZ4qOWZfFL7zrwyeOI0PBo1RW0MOgCl90nIjIyBhWiRxqVzo/17zdCkzL5EZeYjNF/HEfvBftxKybO2E0jIrJaDCpEenzdnbHg7doY066CWhxO1luR6sqRK/eM3TQiIqvEoEKUho2NDXo1KI4/BzdEifxuuB75EJ1nB2PjsevGbhoRkdVhUCHKQFl/d6wZ1ADNy/siPjEZAxcfwMqQK8ZuFhGRVWFQIcqEh7MD5nSvha61CiNZA3y04jDm7z5v7GYREVkNBhWip7CztcF3nSqjT8Pi6vyXf57AtC2njd0sIiKrwKBClMVxK5+1KY8PmpdR5/+3+RQmbT5l7GYREVk8BhWibISV95uXxqety6nzU7acxsTNp7jWChGRATGoEGXTu41LYlTr8urnqVtOq8oKwwoRkWEwqBA9g76NS6iuIDH13zP4dv1JJMtoWyIiylEMKkTP6J1GJfBF2wrq5x93nsewFYcRl8gDGhIR5SQGFaLn0LthcfyvS1U1M2j1wavoMjsYV+7eN3aziIgsBoMK0XPqVLMQ5veqDS9XBxy5Eom203Zh+6mbxm4WEZFFYFAhygGNy+THX0MaokohT9y7n4Be8/dh4t9hSExKNnbTiIjMGoMKUQ4p5O2KFf0D0a1uEcgkIBlk23XuHly+w64gIqJnxaBClIOc7O0w9tXKmPpGdbg72SPk4l20nrITaw9dNXbTiIjMkkGDyo4dO9CuXTsUKFBALZa1Zs2aVNfL2hNffPEFAgIC4OLigubNm+P0aS5NTubvlaoFsP79RqhZ1BvRcYl4f9khfLbmqDq4IRERmUhQiY2NRdWqVTFjxox0rx8/fjymTp2K2bNnY+/evXBzc0PLli3x8OFDQzaLKFcUzuuK396th/deLA0bG2DRnkvo9tMe3I2NN3bTiIjMho0ml5bUlIrK6tWr0aFDB3VeHlYqLcOGDcNHH32kLouMjISfnx8WLFiA119/PUv3GxUVBU9PT/W7Hh4eBn0ORM9qy8kIDF12SFVXSuR3w8K366ggQ0RkraKyuP822hiV8+fPIzw8XHX36EiD69ati+Dg4Ax/Ly4uTj05/RORqXuxvB9WDayPAE9nnLsZq9ZbOX8r1tjNIiIyeUYLKhJShFRQ9Ml53XXpGTdunAo0ulPhwoUN3lainFDGzx2/D6yP0r55EB71EF3nBOPszRhjN4uIyKSZ3ayfkSNHqjKR7nT58mVjN4koywI8XbD03Xoo6+eOG9Fx6DpnD05HRBu7WUREJstoQcXf31/9HxERkepyOa+7Lj1OTk6qL0v/RGROfPI4qbBSPsADt2Li8PrcPQgLZ1ghIjKpoFK8eHEVSLZs2ZJymYw3kdk/gYGBxmoWUa7I6+aIpX3rolJBD9yOjcfrc4Nx4hrHWxER5WpQiYmJwaFDh9RJN4BWfr506ZKaBTR06FB88803+OOPP3D06FH06NFDzQTSzQwismRero5Y3KeeWnb/7v0EvPnTHhy7GmnsZhERWc/05G3btqFZs2ZPXN6zZ081BVkeevTo0Zg7dy7u3buHhg0bYubMmShTpkyWH4PTk8ncRT5IQM95+3Do8j14ONvj1z51UbWwl7GbRURkUFndf+faOiqGwqBCliD6oRzIcL9act/V0Q4TOldFmyoBxm4WEZH1rqNCRI+5OztgYe86aFjKB/fjkzBoyQF8tyEUSclm/T2CiOi5MagQmYg8TvZY8HZt9GtcQp2fvf0ses3fhztccp+IrBiDCpEJsbezxcjW5dXRl50dbLHz9C28PGUHgs7eMnbTiIiMgkGFyESPvrx6YAOUzO+GiKg4dPtpL8ZvDEVCEo++TETWhUGFyETJgnB/DmmIN+oUhgx5n7ntrDpG0PXIB8ZuGhFRrmFQITJhro72GNexCmZ2q6GmLssU5rZTd2HPudvGbhoRUa5gUCEyA60rB+CvIY1QIUC7km2Pn/dh7aGrxm4WEZHBMagQmYki+VyxakB9tK7sj/ikZLy/7BDm7Tpv7GYRERkUgwqRGXFxtMP0N2qgT8Pi6vxXf53ATzvPGbtZREQGw6BCZGZsbW3wWZvyGPJCKXX+m3UnGVaIyGIxqBCZITmo54cvlcF7emHlxx0MK0RkeRhUiMw5rLQoi/dfLK3Oj11/Uq1mS0RkSRhUiMzcBy+VwdDm2rAixweasfWMsZtERJRjGFSILMDQ5mUw7KUy6ucJm8Iw5Z/Txm4SEVGOYFAhshBDXiyNT1qVVT9P+ucUxq0/iWQefZmIzByDCpEFGdi0FEa1Lq9+nrPjHAYvPYD78YnGbhYR0TNjUCGyMH0bl8CkrlXhYGeD9UfD0X76bpyOiDZ2s4iIngmDCpEFerV6ISzqUxf53Z1w+kYMXpm+Gyv+u2zsZhERZRuDCpGFqlsiH9a/1wiNSvvgQUISPl55BMOWH2ZXEBGZFQYVIgsmFZWFb9fBRy3KwNYGWHXgiqqunGJXEBGZCQYVIitYcn/wC6WxtG89+Hk44YzqCtqF5f9dhkbDWUFEZNoYVIisrCuocZn8eJiQjE9WHsHna48hMSnZ2E0jIsoQgwqRFcmXxwkLetXGxy3LwsYGWLTnEvr+8h8exCcZu2lEROliUCGywq6gQc1KYVa3mnB2sMXWsJt4e8E+xMZxkC0RmR4GFSIr1aqSPxa/Uxd5nOyx59wdvD1/P2IYVojIxDCoEFmxmkXzYtE7deHubI99F+6g57x9iH6YYOxmERGlYFAhsnLVCnthyTv14OnigJCLd/HWz/sQ+YBhhYhMA4MKEaFyIU/VDeTl6oDDl++hx897GVaIyCQwqBCRUqmgp6qseEtYuRKJ7hJW7jOsEJFxMagQUYoKBTywpG895HVzxJErkej28x7cjokzdrOIyIoxqBBRKuUDJKzUVWHl2NUodJoVhAu3Yo3dLCKyUgwqRPSEcv4eWN6vHgp5u+DC7fvoMHM3tobdMHaziMgK2WjM/GAfUVFR8PT0RGRkJDw8PIzdHHoeSQnAvUtAdDiQnADYuwDu/tqTvVPW7uNhJHDnPHD3AhAXpb1PRzfANR/gVRTwLpq1+0pOBmJvAJFXgIT7QHIS4OwJ5PEF3AvIqmmwBjeiH6Lvwv/UmBUxoGlJDHupDOztrOP5E5Hx998MKtZOdshRV4CHUQA0gIs34OYL2Dtm/Dvylom9CdwMBW6cBG6cAO5dBmIigMQ4wMZWu0PP46cNGfK/nHfLr73/5ETg/h3gzlngzjng9lng7nntfWgyWMrdJS/gWejxSYKHuH8biLwKRF7Wnh7cfcoTtgE8CwP5SgDexbX3I8FFwoi0Se5DwpK0JSmDsRl2jtrQk7c44F1Mez/yszxPCTRxkUDMTe32kO0Uc0MbeuQyee4SeLwKA/nLA76PTnI/tnaZvE5J2vuSIJb4ELB3Bpy9tNtV1sI3oLjEJHy77iQWBl9U52sX88bUN6ojwNPFoI9LRJaNQcWSJSVqKwbR17VVAyE7W9lxyclF/vcE7BxS7+jkdyRc3Ax7dAoFbp3S7qTTkkChAoaf9v5kxyi3i72l/d0Hdwzz3KSK4lFA+3ziY7XVlYwCQ0YkEMmOX0KIrb32fmQnL88/Pibr9yOBS6onTnm0P0tIkPAhYcMQzztfSe1zd3LXBioJXbqQI9s9vRDn5AHkL/c48MjPcpKAqB9gJJDKe0XuU3eS7eLgCrjlA3zKaCtPmVh/9DqGrzyC6LhENY15QueqeKmCX85vCyKyClHmFFRmzJiBCRMmIDw8HFWrVsW0adNQp04dywsqsqmjrml3vrpv/hImXPNqd6pSNXBwTv07UumQMHH9MBB+BLh+BIg4nrWdt4ObNmTovo1nVK2wddAGEyHtkm6Xp7LRhgHdDjJviUddNC7aHbnsYGWnHhOu97NUBO5pw4MEKfkd3Ul20lKZSLuDlW0mbZLtFiWVkyvaqoeEBrlOnp9UWDweVVqka0ft6DPY/rIdpIqjTucfVyhkh63uqzDgVUR7ktCgH/aEbEtpg1SAdF1Mup+luiNVEQkPEpZ0VST9ipLc34N72mrSDQmNJ7XBT9rw1E1uq71vBxcg4YE2eGgyOPKxo7v2NZX2yHOU7Z7RbVNez6KAbwXtyb8S4FdZWynSq/TIoNphS/bg6rWr8LaJwesV3fBGTT84Okvg8dVuN0fXpz8XIrJ6UeYSVH777Tf06NEDs2fPRt26dTF58mSsWLECYWFh8PX1NZ2gIlUM2RHJB76N7IzyaHeIsoNLr/QuO7R7F7UBQ07XDmn/f1olQoULb+1ORb796yomT9zOVbsjlQqKPL7s6B482iFl9DsSInxKP/rWXfbx/xIQ7OxTBwMJFhKo5P+46Ec7cxft4+Ur9egbOHdIOUJX7ZKwE31NW+mQy1RVy/dRyHn0v373UGI8cPuMtutNuuB01TIJYRmFUnnfqKqbt7aCkvhA+zpLgEuPhEoJ0FJRS4rXvrfSq8Dpk/dTgWpAQFUg4NH/EsbTI2OIdBUeee9Jl6MEu6dUd4jI/JlNUJFwUrt2bUyfPl2dT05ORuHChTFkyBCMGDHCeEEl/BhwMQiIOAqEH9XuCNL71ivfcqU6oE5e2nEesmOXb93ywZ7eB797gPbbu/yujOmQsRESYDLqUnD1efShXwXwr6L9WXYGGQ3olJ2c7lu0fHvXHzOS2TgIsgzynlKDiaO170F5X0pQkP/TVux0pGtJN94o4pi2ahdxQhtk0mNrjzhHL1x56Iz7yfZws01EEYdI2CdEZ/welvefdOlJiJL3pYSTjEK13F4qdX5S2amoPUmwzko4lo80OVnJgGeibJEvByJttTg9sm+SzwPZH5Zoov07zEFZ3X8/+hptHPHx8QgJCcHIkSNTLrO1tUXz5s0RHByc7u/ExcWpk/4TNYgDvwD75qS50EYbSKTaITsBCSXys+4bYXqDLuWF1X2rlJOU1dPbWcgHq3xoS9VG7kuqNqpqEpBxV0ZGJIyo7qQMvsWSZZMwIJWy7HDzAYo30p70A6+Mg5L3o1RvpOomXU/yvnLygJONDVzuPcB7v/yH49ei4JRoi3mvFUcDt+vA9UOPq4jSNXb/lvaULvm78tC+5+XLgBrYfAu4sFN7SrmZLZC3pLaaJ9U93d9hqlPU479NCTvSFSV/g/6VHwce+RsmsmQajfbLivqSfeJx1fXuxcfDBnRDA+TvQfYxjo96CaRCL3/zt85oJ1roNP8yx4NKVhk1qNy6dQtJSUnw80s9IE/Oh4aGpvs748aNw5dffmn4xhUN1HbdyDc66a+XSob+zAwZnCgfqPLBKONI9KsX0i3kUVA7ZiKrFQx5c+gqM0SmQN67ullWGSjg5YIV/QMxZMlBbAm9gV6/ncP0N2ugZcNmj28kfxcyrki6EaULVf5G5ANSupSkC0p+1v87UVPMz2krOqqy86jCI+Hl9mntKSvUIOQbwNX/Ul/u+Si8yPgb6dKScKSqmvKF4462uqSmtidqQ58EMwlIatzOowpPZhVNouchXb/SjSvvf1XlPK4NDQmx2nAu48/UvsLjUch49L98AZb3sIQRGcsosw8zI/cnJxn7lxmZ4ShBX8YSGolRu36uXbuGggULIigoCIGBgSmXf/LJJ9i+fTv27t2bpYqKdBWZxWBaIguVkJSMocsOYd3R67CztcHE16qifbWCOfsgMihbQouEGKnwSLiXb4ApJ4/HP0sYkmAkU991QUfK1/rfEJ+HVDulsiMVUulWlQqPVHL0Z1XpTvJFRqqrsmOR8V1qfJicZCB6uccD2TMr1eumpsvzkm++0o2mG1dGOUc3Rk9VEeO0QVVVEfNlHkzli6sK10cfv9fkvARluR+pGsq4KwkUuiqGmqX5KHDIe0cmDKiqxwVtRfB52Tk+6j6t/HjSg7z/5PHkecqXa3lPyRcJNR5SKpIx2jAkbdRVIw345dksun58fHxgZ2eHiIiIVJfLeX9//3R/x8nJSZ2IyHQ42NliyuvV4ORgi98PXMXQ3w4hIUmDzjUzrsZkmxpn9QJQ8oWs3V5mkEl3a6WOjy+THZCq1BzTdmslyJo0TtqwIJUT9b/Po+n9jtoxOmrNoDDtzkd2RDJbS6qp0r0lp6yQ+5FvuFJZOrc1TTsLAPnLPB60rAbGP5qaLrPmpDs4LQkssiPRX4tHN/tON8Bfuu7kPnQz5nQn2SHJeDgJPGohxCKP1wPKyro88fe1207uV9qm1vR5tDaQjL/LahVZtr1uJp8uhOlm8ck2yWwtp5Q1oK4+Xo9JBqOr55bweD0o3WD0PI8WjpTL5flJtUy2rfyebvadql6c1O7An9jedqnvSxcupfImbbh1+umDzKV6IcElK6Tt6jWtAPhV0I7PUoHB5lGgiHxUyY98XNWXx5ftJ9tOKiDyO5ltQzMaGmASg2llKrJMSdYNpi1SpAgGDx5s3MG0RJRtyckafLb2GJbsvaT2B993rILXaheGRZEAIDtFNbU8FLh/V7uTkEqO6sryTt21Jd9gdbMGZakBNTtLFksMzXqFRzelXx5bvv1mtpaPBCzZoWV3/SEhIUeFlmLaACP3Ex+tnRmmAs+19Hfk+u2Ubm/dFH85yfgn3RIJutlt0q2e0UwzxebRKtAB2pOM1ZO2SXVCgo0EDLmv7D5HWYpBApGa6JDJrk+6VyTAyuPJ888KmVUp4UI3tV/Cp1S+pN26WZy6CoZusoP6P1IbGiVISZVOqhiyzaxAlDlNT+7ZsyfmzJmjAotMT16+fLkao5J27Ep6GFSITIt8pIz+4zh+ebSS7XcdK+P1OrLToyfITkoCi0wzl2/GatVhWQbAE3D301t0Me/jrgfd4R0k9DytGqAWLZQdfUHtcgbyv25MkJT55X5kTIOcJDRlutaOHtn5yv3KDlW6piSESWUhu4shyoBOqaDolmRQK01fyXoAkWAkoUrGEEk1Sa0dZKsNj2o1aN1Jb+0q/d+Vx9Z1wUn1QqoQarC285Ndb2otqEdrQsmYJtUN56bdrvL4shYUZ1VaXteP6Nq1K27evIkvvvhCLfhWrVo1bNy4MUshhYhMj42NDb58pSJsbWywIOgCRvx+FInJGrxVr6ixm2Z6JJAUqas9ZZXsiHXHwCre+PHl8p1TvrXLN3YhXTKy487qWBYZ9yNdU2ohw/PawCA7YxVK/LVVDelWUOs3eT7ZRaSbJXbv0WEoIuVQFJe0O3WZCitjMlIOO1FMu7iirivmiYUZbz0egK1bJFPCi1REpB26hSJloccsP7+4x1UcO6enjzvRkbarkFcga49DOc7oFZXnxYoKkWmSj5av/zqJebvPq/Pvv1gaQ5uXVkGGiCgqi/tvzq8jIoOQQPJ52/IY1KykOj9ly2l88NshxMYZ4FhJRGSxGFSIyKBh5eOW5TD21UqwtQHWHLqG9jN243REFgcoEpHVY1AhIoPrVrcolvatB193J5y5EYNXpu/GqpAcWtOEiCwagwoR5Yq6JfJh/fuN0LCUDx4kJGHYisOqKyj6YVaO1k1E1opBhYhyjU8eJyzsXQcfNC+juoJWH7yK1lN3IuRiOsfKIiJiUCGi3CZL7L/fvDSW9wtEQS8XXL7zAK/NCcaMrWfUgnFERPoYVIjIKGoVy4sNQxuhfbUCSErWYMKmMAxcfICzgogoFQYVIjIaD2cHTHm9OsZ1rAwHOxtsPB6ON3/cg7uxssQ5ERGDChGZgDfqFMGyd+vB29UBh69Eqq6giKiHxm4WEZkABhUiMgk1i+ZV41b8PJxw+kYMOs8OwqXbTzkiLRFZPAYVIjIZpf3csbJ/fRTN56oG2UpYkXVXiMh6MagQkUkpnNcVK/oHopy/O25Ex+H1uXu4ki2RFWNQISKT4+vujCV966FCgAduxWjDSlg4wwqRNWJQISKTlNfNEUv61kWlgh64HRuPN37cgxPXoozdLCLKZQwqRGSyvFwdsbhPPVQp5Ik7sfHoOicYQWdvGbtZRJSLGFSIyKR5ujrg1z51Uad4XkTHJaLnvH1YsvcSNBquYktkDRhUiMjkebo44JfeddCmcgASkjT4dPVRdUBDrmJLZPkYVIjILDg72GHaG9Ux4uVy6nhBaw5dwyvTd3GQLZGFY1AhIrNha2uD/k1KqlVs/T2ccfZmLNpN34Wfd53nAQ2JLBSDChGZndrF8mLdew3RtGx+xCcm4+u/TuCtn/fi6r0Hxm4aEeUwBhUiMkv58jhhfq/a+KZDJbg42CHo7G20mrwD649eN3bTiCgHMagQkdmysbHBW/WKYv37jVCtsBeiHyZi4OID+OrPE0hMSjZ284goBzCoEJHZK+7jhpX9A9GvSQl1ft7u8+i/6AAexCcZu2lE9JwYVIjIItjb2WLky+Uxq1sNONnb4p+TEWrcyr378cZuGhE9BwYVIrIoL1cOwKJ36sLD2R4hF++iy+xgXOMgWyKzxaBCRBY5K2hF//pqCvPpGzEqrFy8HWvsZhHRM2BQISKLVNbfHasG1kcJHzc1bbnrnD04ezPG2M0iomxiUCEii1XQywXL+tVDad88CI96qMLK6QiuZEtkThhUiMii+bo7q5Vsywd44FZMHLrO3YOjVyKN3SwiyiIGFSKyisXhlvati8oFPXEnNh6vzw3G9lM3jd0sIsoCBhUisgpero5Y0rcuGpTKh9j4JPResB8/7TwHjYbHCCIyZQwqRGQ13J0dML9XHXSqUQhJyRp8s+4kBi89yLVWiEwYgwoRWRVHe1v80KUKRrerADtbG6w7ch0tJ+9gVxCRiWJQISKrPEbQ2w2Kq2X3ZfpyRFQces7bh8/WHMX9+ERjN4+IciOojB07FvXr14erqyu8vLzSvc2lS5fQpk0bdRtfX198/PHHSEzkhwQR5Y7qRbyx7r1G6FW/mDq/aM8ltJm6C4cv3zN204jI0EElPj4eXbp0wYABA9K9PikpSYUUuV1QUBAWLlyIBQsW4IsvvjBUk4iInuDiaIcxr1TEoj511Uq252/FotOsIEzbcppHYCYyATYaAw95l/AxdOhQ3LuX+hvKhg0b0LZtW1y7dg1+fn7qstmzZ2P48OG4efMmHB0ds3T/UVFR8PT0RGRkJDw8PAzyHIjIOsig2lFrjqlxK6JOsbyY+VYN+ORxMnbTiCxOVvffRhujEhwcjMqVK6eEFNGyZUvV8OPHj2f4e3Fxceo2+iciopyawjz9jeqY1LUq8jjZY9+FO2g/fTdOXOPnDJGxGC2ohIeHpwopQndersvIuHHjVALTnQoXLmzwthKRdQ20fbV6IawZ1EDvOEHB2Hf+jrGbRmSVshVURowYof6IMzuFhoYarrUARo4cqcpEutPly5cN+nhEZJ1K+ebB6kENUKd4XkTHJaL7z3uxNfSGsZtFZHXss3PjYcOGoVevXpnepkSJElm6L39/f+zbty/VZRERESnXZcTJyUmdiIgMzdPFAb/0roNBiw9gS+gN9P3lP0zsWg2vVC1g7KYRWY1sBZX8+fOrU04IDAxUU5hv3LihpiaLzZs3qwE1FSpUyJHHICJ6Xs4OdpjdvSY+WnEYaw9dw/vLDiLyfjy6B2qnNBORmY5RkTVSDh06pP6Xqcjys5xiYmLU9S1atFCBpHv37jh8+DA2bdqEzz77DIMGDWLFhIhMioOdLSa9Vg09AotC5kl+vvY4Jv9ziscJIjLn6cnSRSRro6S1detWNG3aVP188eJFtc7Ktm3b4Obmhp49e+K7776DvX3WCz2cnkxEuUU+LqdsOY3J/5xW53sGFsXodhVha2tj7KYRmZ2s7r8Nvo6KoTGoEFFu+yX4Akb/cVxVV16u5I8JXbTTmYnIgtZRISIyVz0Ci2HK69XhYGeDDcfC8eqM3TgdEW3sZhFZJAYVIqJnIDN/lr0bCF93J5y+EYM203ZhzvazSEo26yI1kclhUCEiekY1i3rjr/caomnZ/IhPTMa4DaHoMjsI525qJw0Q0fNjUCEieg6+7s6Y36s2vu9UWY1TOXDpHlpP3Ymfd51HMqsrRM+NQYWI6DnJqtxdaxfBpg8ao2EpHzxMSMbXf51A17nBuHAr1tjNIzJrDCpERDmkoJcLfu1TB2NfrQQ3Rzvsv3AXrabswJK9l7jmCtEzYlAhIsrh6kq3ukWxcWhjNCiVT1VXPl19FB+tOIKHCUnGbh6R2WFQISIygMJ5XbGoT12MeLkcZD24VQeuqAMbRt5PMHbTiMwKgwoRkQGrK/2blMSvferC3cledQV1mROEa/ceGLtpRGaDQYWIyMAalPLB8v6B8PNwwqmIGHSaFYRTXCCOKEsYVIiIckH5AA+sGlAfJfO74XrkQ3SeFYT9F+4Yu1lEJo9BhYgolxTydsXK/vVRo4gXoh4m4q2f9mLT8XBjN4vIpDGoEBHlIm83Ryx+px6al/dFXGIyBiwKUdOXiSh9DCpERLnMxdEOs9+qia61CkMWr5Xpy2PXnUBiUrKxm0ZkchhUiIiMwN7OFt91qoz3Xiilzv+48zy6/bQXVzkjiCgVBhUiIiNOX/6wRVnM6lZDrWS79/wdtJi4HYv2XORxgogeYVAhIjKylysH4K/3GqFWUW/ExifhszXH8OZPe3DxNo8TRMSgQkRkAor7uGF5v0CMblcBLg522HPuDlpM2oGZ284ggWNXyIoxqBARmQhbWxu83aA4Nj06TpDMChq/MQztpu3CgUt3jd08IqNgUCEiMjFF8mmPE/S/LlXh7eqA0PBotZrthE2hrK6Q1WFQISIy0YG2nWoWwpZhTdGxRkFoNMCMrWfx+tw9uBkdZ+zmEeUaBhUiIhOW180RE1+rhulvVoe7sz1CLt5Fhxm7eawgshoMKkREZqBtlQJYO6gBiuVzVWutdJoZhO2nbhq7WUQGx6BCRGQmSuTPg9UDG6BO8byIjktE7wX7sXjvRWM3i8igGFSIiMzsWEG/9qmDTjUKISlZg1Grj2H8xlAuEEcWi0GFiMjMONnb4YcuVTC0eWl1fua2s/hw+SHEJ3JGEFkeBhUiIjOdFTS0eRmM71wF9rY2WHPoGnrM24vbMZwRRJaFQYWIyIy9Vqsw5vWqrY4VJKvZtp22CyEX7xi7WUQ5hkGFiMjMNS6TH78PbIAS+d1wPfIhOs8Oxpg/jiMmLtHYTSN6bgwqREQWoKy/O/4Y3DBlcbgFQRfUkZi3nIwwdtOInguDChGRhcjjZK8Wh/uldx0UzuuCa5EP0Wfhf+j7y3+4dPu+sZtH9EwYVIiILLAr6O+hTdCvcQk10HbziQg0n7Qd//s7DA/ik4zdPKJsYVAhIrJALo52GNm6PDa830gdiVmmLk/79wyaT9yOoDO3jN08oixjUCEismCl/dzVkZhnv1UDBb1c1PL7b/60F9/8dQKJPBIzmQEGFSIiK1hzpVWlAGz6oDG61S2iLvtp13n0mLcPd2Ljjd08IuMElQsXLqBPnz4oXrw4XFxcULJkSYwePRrx8an/KI4cOYJGjRrB2dkZhQsXxvjx4w3VJCIiWPtg27GvVlbVFVdHOwSdvY1203bh2NVIYzeNKPeDSmioHHsiGXPmzMHx48cxadIkzJ49G59++mnKbaKiotCiRQsULVoUISEhmDBhAsaMGYO5c+caqllERFZPqitr9I7E3Hl2ENYfvW7sZhGly0ajkRn3uUOCyKxZs3Du3Dl1Xn4eNWoUwsPD4ejoqC4bMWIE1qxZo4JOVkjY8fT0RGRkJDw8PAzafiIiSxJ5PwHvLTuI7aduqvMftyyLgU1Lqq4iIkPL6v47V8eoSGPy5s2bcj44OBiNGzdOCSmiZcuWCAsLw927d9O9j7i4OPXk9E9ERJR9nq4O+LlnLfSqX0ydn7ApDB+vPMKDG5JJybWgcubMGUybNg39+vVLuUwqKX5+fqlupzsv16Vn3LhxKoHpTjKuhYiIno29nS3GvFIRX7WvCFsbYGXIFbz54x5cj3xg7KYRPVtQka4ZKQtmdkrbbXP16lW0atUKXbp0Qd++ffE8Ro4cqSozutPly5ef6/6IiAjoEVhMHdzQ3cke/128i9ZTdmLT8fS/MBLlJvvs/sKwYcPQq1evTG9TokSJlJ+vXbuGZs2aoX79+k8MkvX390dEROrjUOjOy3XpcXJyUiciIspZTcv64s8hDTF46QEcuxqFfr+GoE2VAHzepgL8PZ2N3TyyUtkOKvnz51enrJBKioSUmjVrYv78+bC1TV3ACQwMVINpExIS4ODgoC7bvHkzypYtC29v7+w2jYiInlMxHzesGlAfU/45jTk7zmHdkev49+QNDGhaEn0blVAr3hJZxKwfCSlNmzZVU48XLlwIO7vHb25dtUS6biSUyBTl4cOH49ixY+jdu7eayvzuu+9m6XE464eIyDBkfZUv1h7DgUv31PkCns4Y/nI5vFK1AGcG0XPL6v7bYEFlwYIFePvtt9O9Tv8hZcG3QYMGYf/+/fDx8cGQIUNUaMkqBhUiIsORz+u/jlzHdxtC1ZoronoRL3zRtgKqF2Hlm8w4qOQWBhUiIsN7mJCEn3aew8xtZ3H/0RGYO1QrgFFtKiC/O8cNkoWso0JERObJ2cEOg18oja0fNUWXmoUgPT9rDl1Dq8k7sOVk6kkRRDmJQYWIiLLMz8MZE7pUxR+DGqKcvztux8ajz8L/MG7DSR6NmQyCQYWIiLKtciFPdbyg3g2Kq/Nztp9TR2O+HRNn7KaRhWFQISKiZ+4O+qJdBUx/s3rK0ZjbTtuFQ5e1s4SIcgKDChERPZe2VQpg7aAGKOHjhuuRD/Ha7GAs2Xsp1QxPomfFoEJERM+ttJ871g5ugJYV/RCflIxPVx/F8FVH1GwhoufBoEJERDnC3dkBs9+qiU9alVUHOFz+3xV0nh2EUxHRxm4amTEGFSIiyjGyYu3ApqXwS++68HZ1UMcMajN1J77fGIrIBwnGbh6ZIQYVIiLKcQ1L+2D9+43QvLwfEpI0mLXtLBqP36r+f/BowTiirODKtEREZDCyi9l8IgITNoXh9I0YdZmsZPveC6Xwep0icLDj92VrFcUl9ImIyFQkJWuw9tBVTPrnFC7f0R4zqFg+V3zUsizaVA7gQQ6tUBSDChERmZr4xGQs238JU7ecxq2YeHVZ1cJe+K5jZZQP4Ge4NYliUCEiIlMVE5eoDnL4445ziI1Pgr2tDd57sTQGNSsFO5kyRBYvigclJCIiU5XHyR5Dm5dRBzmUtVcSkzWYuPkUes3nMvyUGoMKEREZja+Hs1p7ZeJrVeHiYIedp2+hzdRdCLl4x9hNIxPBoEJEREYlA2k71iikVrYtkd8N4VEP0XXOHtUtZOajEygHMKgQEZFJKOPnjj8GN0S7qgVUV9DY9SfxzsL/cDdWO+iWrBODChERmdTYlamvV8M3HSrB0d4WW0JvqJVt919gV5C1YlAhIiKT6wp6q15RrB5YH8V93HBNjsg8JxifrTmKyPtcht/aMKgQEZFJqljAE38OaYhONQpBhqos2nMJDcf/i0mbT/G4QVaE66gQEZHJCzp7C1/+cQJhj47E7O5sj94NiquTp6uDsZtHz4ALvhERkUVJTtZgw7FwTNlyCqcitMcNcneyR68GxVRg8XZzNHYTKRsYVIiIyKIDiyzDr6uwuDna4Z1GJTCgaUk4O9gZu4mUBQwqRERk8YHl7xMRKrCcuB6lLiuc1wXfd6yC+qV8jN08egoGFSIisgqyG1t/NBzfrDuB65EPIQdi7te4JIa1KAMHO84ZMVU81g8REVnNdOY2VQLwz4dN8EadImqG0OztZ9F5VhAu3Io1dvPoOTGoEBGRRXBzsse4jpUx+60a8HRxwOErkWqxuN8PXDF20+g5MKgQEZFFaVUpABveb4S6xfMiNj4JHy4/jA9+O4SYuERjN42eAYMKERFZnAJeLljStx4+fKkMbG2A1QevquoKj8psfhhUiIjIItnZ2uC9F0tjeb9AFPRywcXb99FpVjCGrzyC8MiHxm4eZRFn/RARkcWTYwTJrKAVIdrxKo52tuhSqxD6NymJwnldjd08qxTF6clERESp/XfhDsZvDMO+R0djlqpL+2oF1HTmsv7uxm6eVYliUCEiIkrf3nO3MX3rGew8fSvlshfK+aJf4xKoUzyvmvJMhsWgQkRE9BSHLt/DnO1nsfF4uFp/RTQq7YNRbcqjnD/3KYbEoEJERJRF52/FYu6Oc1gZchkJSRrVJTSoWSkMeaEUV7e15JVpX3nlFRQpUgTOzs4ICAhA9+7dce3atVS3OXLkCBo1aqRuU7hwYYwfP96QTSIiInpCcR83tVicrG7bsqIfkpI16hhCHWcG4cwN7YEPyTgMGlSaNWuG5cuXIywsDKtWrcLZs2fRuXPnVGmqRYsWKFq0KEJCQjBhwgSMGTMGc+fONWSziIiI0lU0nxvmdK+FaW9UV6vbHr0qq9vuwvzd59UxhSj35WrXzx9//IEOHTogLi4ODg4OmDVrFkaNGoXw8HA4Ojqq24wYMQJr1qxBaGhouvchvysn/bAjlRh2/RARUU6KiHqIj1cewY5TN9X5ZmXzY0KXqvDJ42TsplkEk+j60Xfnzh0sXrwY9evXVyFFBAcHo3HjxikhRbRs2VJVYO7evZvu/YwbN049Md1JQgoREVFO8/NwxsK3a+PLVyrC0d4WW8NuotXkndj+KLhQ7jB4UBk+fDjc3NyQL18+XLp0CWvXrk25Tiopfn5+qW6vOy/XpWfkyJEqfelOly9fNvAzICIiayXTlHvWL4Y/BzdEWT933IqJQ895+/DxisO4Extv7OZZhWwHFemakRcus5N+t83HH3+MgwcP4u+//4adnR169OjxXP18Tk5OqkSkfyIiIjIkWQxu7eAG6BlYVJ2XFW6bTtiKGVvPIJYHOzStMSo3b97E7du3M71NiRIlUnXn6Fy5ckV11QQFBSEwMFCFFumjkjEpOlu3bsULL7yguoq8vb2f2h5OTyYiotwUcvEuPltzDCevR6nzXq4O6BFYDL3qF0Netyf3ffR8+297ZFP+/PnV6VkkJyer/3WDYSWsyGDahISElHErmzdvRtmyZbMUUoiIiHJbzaLe+GtIQ/x5+Bom/3MKF27fV1OZ5+44i661CuOdRiV4/CBzmPWzd+9e7N+/Hw0bNlShQ6Ymf/7554iIiMDx48dVF46kKAklMkVZxrIcO3YMvXv3xqRJk/Duu+9m6XFYUSEiImOR9VY2HgvH7O1n1VRmIYvFta0SoI4fVKEA90smuzLt0aNH8f777+Pw4cOIjY1VC761atUKn332GQoWLJhqwbdBgwapUOPj44MhQ4ao0JJVDCpERGRssisNOntbBRb94we9VMEPo9tVQCFvVlhMLqjkFgYVIiIyJceuRqrAsv7odSRrABcHO3zcsqwaw2Jry4Md6jCoEBERGdHpiGiMWn0M+y7cUecDS+TDD69VRUEvF2M3zSSY3IJvRERE1qS0nzuWvVsPX3eopKoqweduo9WkHVgZcoXL8WcDgwoREZGBSFdP93pFseH9RqhRxAvRcYn4aMVh9Ps1RC0eR0/HoEJERGRgxXzcsKJ/fXzSqiwc7Gzw94kItJy0A5uOp78KOz3GoEJERJQLZNrywKalsHZQQ5Tzd8ft2HhVWRm0+ADO3YwxdvNMFgfTEhER5bK4xCRM/uc05mw/q2YGSYhpUzkAfRuVQOVCnrAGUZz1Q0REZNpOXIvCxM1h+OfkjZTL6hbPqwLLC+V8LXo6M4MKERGRGa298vOu82pZ/kQpschx83zc0LthcXSqUQgujnawNAwqREREZuZ65AMsCLqAJXsvIfqh9qjM3q4OGNSsFHrWLwYHO8sZWsqgQkREZKZi4hKxfP9lzNt9HlfuPlCXlfbNg+87V0GNIpZx0F4GFSIiIjOXmJSMVQeu4PuNYbgTGw8ZstK/SUm837w0nOzNuzuIK9MSERGZOXs7W3StXQT/DmuCV6sXVDOEZm47i/bTd6uBuNaAQYWIiMjEebk6YlLXapj9Vg3kc3NEaHg02s/Yhen/nlZVF0vGoEJERGQmWlUKwKYPGqNFBT8kJGnww9+n0GlWEM7csNwF4xhUiIiIzIhPHifM6V4Tk7pWhbuzPQ5fiUSbqTsxYVMooh4mwNJwMC0REZEZT2cevuoodpy6qc57ujjg9TqF1YEQC3m7wpRx1g8REZEV0Gg06iCH4zeG4uzNWHWZzA56qYIf3m5QXK10a2NjeivcMqgQERFZkaRkDf4NvYGFQRew68ytlMsrF/TEO42Ko3XlAJNaMI5BhYiIyEqdjojG/KALWBVyBXGJ2llBBb1c8FHLMmhftaBJHEOIQYWIiMjK3YmNx6I9F/FL8AXciolXl9Uo4oUJXaqiZP48Rm0bgwoREREpDxOS1HL8M/49g9j4JDjZ22J4q3LoVb+Y0aorXJmWiIiIFGcHOwxsWgr/DGuCRqV9VHfQV3+dQLef9uLynfswZQwqREREViLA0wW/9K6DrztUgouDHYLP3UaryTuwdN8lNXvIFDGoEBERWREbGxu1zsqG9xuhZlFv1RU08vej6Dl/v1qXxdQwqBAREVmhYj5uWN4vEJ+1KQ9He1u1aNxLE3dgxtYzeBCfBFPBwbRERERW7syNGHy04jAOXb6nzsuBD7vVK4q36hWBr7uzQR6Ts36IiIgoy5KTNfjj8DVM2BSGq/e0XUAOdjZoV7UA+jQsjooFPGGM/bd9jj4qERERmSVbWxt0qF4QbaoEYNPxcMzffQEhF+/i9wNXkdfVMceDSlYxqBAREVEKWWa/bZUC6iRdQfN3n0fP+sVgLAwqRERElK5qhb0w5fXqMCbO+iEiIiKTxaBCREREJotBhYiIiEwWgwoRERFZd1CJi4tDtWrV1LK9hw4dSnXdkSNH0KhRIzg7O6Nw4cIYP358bjSJiIiIzECuBJVPPvkEBQoUSHexlxYtWqBo0aIICQnBhAkTMGbMGMydOzc3mkVEREQmzuDTkzds2IC///4bq1atUj/rW7x4MeLj4zFv3jw4OjqiYsWKquIyceJEvPvuu4ZuGhEREVlzRSUiIgJ9+/bFr7/+CldX1yeuDw4ORuPGjVVI0WnZsiXCwsJw9+7dDLuRpBKjfyIiIiLLZLCgIocQ6tWrF/r3749atWqle5vw8HD4+fmlukx3Xq5Lz7hx49SxAXQnGddCRERElinbQWXEiBFqUGxmp9DQUEybNg3R0dEYOXJkjjZY7k8OYKQ7Xb58OUfvn4iIiMx4jMqwYcNUpSQzJUqUwL///qu6dpycnFJdJ9WVbt26YeHChfD391fdQ/p05+W69Mj9pb1PIiIiskzZDir58+dXp6eZOnUqvvnmm5Tz165dU+NPfvvtN9StW1ddFhgYiFGjRiEhIQEODg7qss2bN6Ns2bLw9vbObtOIiIjIwhhs1k+RIkVSnc+TJ4/6v2TJkihUqJD6+c0338SXX36JPn36YPjw4Th27BimTJmCSZMmGapZREREZEaMevRkGQwrU5cHDRqEmjVrwsfHB1988UW2pibLoF3B2T9ERETmQ7ff1u3HM2KjedotTNyVK1c484eIiMhMyaQYXU+LRQaV5ORkNf7F3d1dzTjK6bQnIUg2ooeHR47eNz3G7Zw7uJ1zB7dz7uB2Nv/tLPFDZgfLyvW2tram2fWTE+TJZZbEcoK8OPxDMDxu59zB7Zw7uJ1zB7ezeW9nGQLyNDx6MhEREZksBhUiIiIyWQwqmZCF5UaPHs0F5gyM2zl3cDvnDm7n3MHtbD3b2ewH0xIREZHlYkWFiIiITBaDChEREZksBhUiIiIyWQwqREREZLIYVIiIiMhkWXVQmTFjBooVKwZnZ2fUrVsX+/bty/T2K1asQLly5dTtK1eujPXr1+daW61pW//4449o1KgRvL291al58+ZPfW3o2d7TOsuWLVOHoOjQoYPB22iN2/nevXvq4KsBAQFqmmeZMmX4+WGA7Tx58mSULVsWLi4uatn3Dz74AA8fPsy19pqjHTt2oF27dmoZe/kMWLNmzVN/Z9u2bahRo4Z6L5cqVQoLFiwwbCM1VmrZsmUaR0dHzbx58zTHjx/X9O3bV+Pl5aWJiIhI9/a7d+/W2NnZacaPH685ceKE5rPPPtM4ODhojh49muttt/Rt/eabb2pmzJihOXjwoObkyZOaXr16aTw9PTVXrlzJ9bZb8nbWOX/+vKZgwYKaRo0aadq3b59r7bWW7RwXF6epVauWpnXr1ppdu3ap7b1t2zbNoUOHcr3tlrydFy9erHFyclL/yzbetGmTJiAgQPPBBx/ketvNyfr16zWjRo3S/P7777JUiWb16tWZ3v7cuXMaV1dXzYcffqj2hdOmTVP7xo0bNxqsjVYbVOrUqaMZNGhQyvmkpCRNgQIFNOPGjUv39q+99pqmTZs2qS6rW7eupl+/fgZvq7Vt67QSExM17u7umoULFxqwlda5nWXb1q9fX/PTTz9pevbsyaBigO08a9YsTYkSJTTx8fG52Err285y2xdeeCHVZbIzbdCggcHbaimQhaDyySefaCpWrJjqsq5du2patmxpsHZZZddPfHw8QkJCVJeC/sEN5XxwcHC6vyOX699etGzZMsPb07Nv67Tu37+PhIQE5M2b14Attc7t/NVXX8HX1xd9+vTJpZZa33b+448/EBgYqLp+/Pz8UKlSJXz77bdISkrKxZZb/nauX7+++h1d99C5c+dU91rr1q1zrd3WINgI+0KzP3rys7h165b6kJAPDX1yPjQ0NN3fCQ8PT/f2cjnl7LZOa/jw4ar/NO0fBz3fdt61axd+/vlnHDp0KJdaaZ3bWXaY//77L7p166Z2nGfOnMHAgQNV+JalySlntvObb76pfq9hw4bSU4DExET0798fn376aS612jqEZ7AvjIqKwoMHD9T4oJxmlRUVMh/fffedGui5evVqNaCOckZ0dDS6d++uBi77+PgYuzkWLTk5WVWt5s6di5o1a6Jr164YNWoUZs+ebeymWRQZ4CmVqpkzZ+LAgQP4/fffsW7dOnz99dfGbho9J6usqMgHs52dHSIiIlJdLuf9/f3T/R25PDu3p2ff1jo//PCDCir//PMPqlSpYuCWWtd2Pnv2LC5cuKBG++vvUIW9vT3CwsJQsmTJXGi55b+fZaaPg4OD+j2d8uXLq2+m0sXh6Oho8HZbw3b+/PPPVfh+55131HmZmRkbG4t3331XBUPpOqLnl9G+0MPDwyDVFGGVr5x8MMg3my1btqT6kJbz0pecHrlc//Zi8+bNGd6enn1bi/Hjx6tvQhs3bkStWrVyqbXWs51lmv3Ro0dVt4/u9Morr6BZs2bqZ5naSTnzfm7QoIHq7tEFQXHq1CkVYBhScm47y1i2tGFEFw557N2cY5R9ocaKp77JVLYFCxaoKVbvvvuumvoWHh6uru/evbtmxIgRqaYn29vba3744Qc1ZXb06NGcnmygbf3dd9+paYkrV67UXL9+PeUUHR1txGdheds5Lc76Mcx2vnTpkpq1NnjwYE1YWJjmr7/+0vj6+mq++eYbIz4Ly9vO8pks23np0qVqCu3ff/+tKVmypJqxSRmTz1VZCkJOEgkmTpyofr548aK6XraxbOu005M//vhjtS+UpSQ4PdmAZP53kSJF1E5RpsLt2bMn5bomTZqoD259y5cv15QpU0bdXqZnrVu3zgittvxtXbRoUfUHk/YkH0SUs+9pfQwqhtvOQUFBajkD2fHKVOWxY8eqqeGUc9s5ISFBM2bMGBVOnJ2dNYULF9YMHDhQc/fuXSO13jxs3bo13c9b3baV/2Vbp/2datWqqddF3s/z5883aBtt5B/D1WuIiIiInp1VjlEhIiIi88CgQkRERCaLQYWIiIhMFoMKERERmSwGFSIiIjJZDCpERERkshhUiIiIyGQxqBAREZHJYlAhIiIik8WgQkRERCaLQYWIiIhgqv4PZIvrRDvOwNcAAAAASUVORK5CYII=", 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", "text/plain": [ "
" ] @@ -269,7 +266,7 @@ "# define the function to plot the solution obtained using matplotlib\n", "def plot_solution(pinn_to_use, title):\n", " pts = pinn_to_use.problem.spatial_domain.sample(256, \"grid\", variables=\"x\")\n", - " predicted_output = pinn_to_use.forward(pts).extract(\"u\").tensor.detach()\n", + " predicted_output = pinn_to_use(pts).extract(\"u\").tensor.detach()\n", " true_output = pinn_to_use.problem.solution(pts).detach()\n", " plt.plot(\n", " pts.extract([\"x\"]), predicted_output, label=\"Neural Network solution\"\n", @@ -289,9 +286,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We can clearly see that the solution has not been learned by the two different solvers. Indeed the big problem is not in the optimization strategy (i.e. the solver), but in the model used to solve the problem. A simple `FeedForward` network can hardly handle multiscales if not enough collocation points are used!\n", + "We can clearly observe that neither of the two solvers has successfully learned the solution. \n", + "The issue is not with the optimization strategy (i.e., the solver), but rather with the model used to solve the problem. \n", + "A simple `FeedForward` network struggles to handle multiscale problems, especially when there are not enough collocation points to capture the different scales effectively.\n", "\n", - "We can also compute the $l_2$ relative error for the `PINN` and `SAPINN` solutions:" + "Next, let's compute the $l_2$ relative error for both the `PINN` and `SAPINN` solutions:" ] }, { @@ -303,8 +302,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "Relative l2 error PINN 2833.18%\n", - "Relative l2 error SAPINN 1921.98%\n" + "Relative l2 error PINN 2593.94%\n", + "Relative l2 error SAPINN 1861.15%\n" ] } ], @@ -326,31 +325,20 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Which is indeed very high!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Fourier Feature Embedding in PINA" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Fourier Feature Embedding is a way to transform the input features, to help the network in learning multiscale variations in the output. It was\n", - "first introduced in [*On the eigenvector bias of Fourier feature networks: From regression to solving\n", - "multi-scale PDEs with physics-informed neural networks*](\n", - "https://doi.org/10.1016/j.cma.2021.113938) showing great results for multiscale problems. The basic idea is to map the input $\\mathbf{x}$ into an embedding $\\tilde{\\mathbf{x}}$ where:\n", + "Which is indeed very high!\n", "\n", - "$$ \\tilde{\\mathbf{x}} =\\left[\\cos\\left( \\mathbf{B} \\mathbf{x} \\right), \\sin\\left( \\mathbf{B} \\mathbf{x} \\right)\\right] $$\n", + "## Fourier Feature Embedding in PINA\n", + "Fourier Feature Embedding is a technique used to transform the input features, aiding the network in learning multiscale variations in the output. It was first introduced in [*On the Eigenvector Bias of Fourier Feature Networks: From Regression to Solving Multi-Scale PDEs with Physics-Informed Neural Networks*](https://doi.org/10.1016/j.cma.2021.113938), where it demonstrated excellent results for multiscale problems.\n", "\n", - "and $\\mathbf{B}_{ij} \\sim \\mathcal{N}(0, \\sigma^2)$. This simple operation allow the network to learn on multiple scales! \n", + "The core idea behind Fourier Feature Embedding is to map the input $\\mathbf{x}$ into an embedding $\\tilde{\\mathbf{x}}$, defined as:\n", "\n", - "In PINA we already have implemented the feature as a `layer` called [`FourierFeatureEmbedding`](https://mathlab.github.io/PINA/_rst/layers/fourier_embedding.html). Below we will build the *Multi-scale Fourier Feature Architecture*. In this architecture multiple Fourier feature embeddings (initialized with different $\\sigma$)\n", - "are applied to input coordinates and then passed through the same fully-connected neural network, before the outputs are finally concatenated with a linear layer." + "$$\n", + "\\tilde{\\mathbf{x}} = \\left[\\cos\\left( \\mathbf{B} \\mathbf{x} \\right), \\sin\\left( \\mathbf{B} \\mathbf{x} \\right)\\right],\n", + "$$\n", + "\n", + "where $\\mathbf{B}_{ij} \\sim \\mathcal{N}(0, \\sigma^2)$. This simple operation allows the network to learn across multiple scales!\n", + "\n", + "In **PINA**, we have already implemented this feature as a `layer` called [`FourierFeatureEmbedding`](https://mathlab.github.io/PINA/_rst/layers/fourier_embedding.html). Below, we will build the *Multi-scale Fourier Feature Architecture*. In this architecture, multiple Fourier feature embeddings (initialized with different $\\sigma$ values) are applied to the input coordinates. These embeddings are then passed through the same fully-connected neural network, and the outputs are concatenated with a final linear layer.\n" ] }, { @@ -383,7 +371,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We will train the `MultiscaleFourierNet` with the `PINN` solver (and feel free to try also with our PINN variants (`SAPINN`, `GPINN`, `CompetitivePINN`, ...)." + "We will train the `MultiscaleFourierNet` using the `PINN` solver. \n", + "Feel free to experiment with other PINN variants as well, such as `SAPINN`, `GPINN`, `CompetitivePINN`, and others, to see how they perform on this multiscale problem." ] }, { @@ -401,11 +390,18 @@ ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1499: 100%|██████████| 1/1 [00:00<00:00, 144.03it/s, v_num=4, bound_cond0_loss=0.00252, bound_cond1_loss=0.00252, phys_cond_loss=0.00678, train_loss=0.0118] " - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "406bab5254d34c1dac9234243b2f3eb4", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" ] @@ -481,19 +470,21 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "It is pretty clear that the network has learned the correct solution, with also a very low error. Obviously a longer training and a more expressive neural network could improve the results!\n", + "It is clear that the network has learned the correct solution, with a very low error. Of course, longer training and a more expressive neural network could further improve the results!\n", "\n", - "## What's next?\n", + "## What's Next?\n", "\n", - "Congratulations on completing the one dimensional Poisson tutorial of **PINA** using `FourierFeatureEmbedding`! There are multiple directions you can go now:\n", + "Congratulations on completing the one-dimensional Poisson tutorial of **PINA** using `FourierFeatureEmbedding`! There are many potential next steps you can explore:\n", "\n", - "1. Train the network for longer or with different layer sizes and assert the finaly accuracy\n", + "1. **Train the network longer or with different layer sizes**: Experiment with different configurations to improve accuracy.\n", "\n", - "2. Understand the role of `sigma` in `FourierFeatureEmbedding` (see original paper for a nice reference)\n", + "2. **Understand the role of `sigma` in `FourierFeatureEmbedding`**: The original paper provides insightful details on the impact of `sigma`. It's a good next step to dive deeper into its effect.\n", "\n", - "3. Code the *Spatio-temporal multi-scale Fourier feature architecture* for a more complex time dependent PDE (section 3 of the original reference)\n", + "3. **Implement the *Spatio-temporal Multi-scale Fourier Feature Architecture***: Code this architecture for a more complex, time-dependent PDE (refer to Section 3 of the original paper).\n", "\n", - "4. Many more..." + "4. **...and many more!**: There are countless directions to further explore, from testing on different problems to refining the model architecture.\n", + "\n", + "For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/)." ] } ], diff --git a/tutorials/tutorial13/tutorial.py b/tutorials/tutorial13/tutorial.py deleted file mode 100644 index 9f33b5b..0000000 --- a/tutorials/tutorial13/tutorial.py +++ /dev/null @@ -1,283 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# # Tutorial: Multiscale PDE learning with Fourier Feature Network -# -# [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial13/tutorial.ipynb) -# -# This tutorial presents how to solve with Physics-Informed Neural Networks (PINNs) -# a PDE characterized by multiscale behaviour, as -# presented in [*On the eigenvector bias of Fourier feature networks: From regression to solving -# multi-scale PDEs with physics-informed neural networks*]( -# https://doi.org/10.1016/j.cma.2021.113938). -# -# First of all, some useful imports. - -# In[ ]: - - -## routine needed to run the notebook on Google Colab -try: - import google.colab - - IN_COLAB = True -except: - IN_COLAB = False -if IN_COLAB: - get_ipython().system('pip install "pina-mathlab"') - -import torch -import matplotlib.pyplot as plt -import warnings - -from pina import Condition, Trainer -from pina.problem import SpatialProblem -from pina.operator import laplacian -from pina.solver import PINN, SelfAdaptivePINN as SAPINN -from pina.loss import LpLoss -from pina.domain import CartesianDomain -from pina.equation import Equation, FixedValue -from pina.model import FeedForward -from pina.model.block import FourierFeatureEmbedding - -warnings.filterwarnings("ignore") - - -# ## Multiscale Problem -# -# We begin by presenting the problem which also can be found in Section 2 of [*On the eigenvector bias of Fourier feature networks: From regression to solving -# multi-scale PDEs with physics-informed neural networks*]( -# https://doi.org/10.1016/j.cma.2021.113938). The one-dimensional Poisson problem we aim to solve is mathematically written as: -# -# \begin{equation} -# \begin{cases} -# \Delta u (x) + f(x) = 0 \quad x \in [0,1], \\ -# u(x) = 0 \quad x \in \partial[0,1], \\ -# \end{cases} -# \end{equation} -# -# We impose the solution as $u(x) = \sin(2\pi x) + 0.1 \sin(50\pi x)$ and obtain the force term $f(x) = (2\pi)^2 \sin(2\pi x) + 0.1 (50 \pi)^2 \sin(50\pi x)$. -# Though this example is simple and pedagogical, it is worth noting that -# the solution exhibits low frequency in the macro-scale and high frequency in the micro-scale, which resembles many -# practical scenarios. -# -# -# In **PINA** this problem is written, as always, as a class [see here for a tutorial on the Problem class](https://mathlab.github.io/PINA/_rst/tutorials/tutorial1/tutorial.html). Below you can find the `Poisson` problem which is mathmatically described above. - -# In[2]: - - -class Poisson(SpatialProblem): - output_variables = ["u"] - spatial_domain = CartesianDomain({"x": [0, 1]}) - - def poisson_equation(input_, output_): - x = input_.extract("x") - u_xx = laplacian(output_, input_, components=["u"], d=["x"]) - f = ((2 * torch.pi) ** 2) * torch.sin(2 * torch.pi * x) + 0.1 * ( - (50 * torch.pi) ** 2 - ) * torch.sin(50 * torch.pi * x) - return u_xx + f - - domains = { - "bound_cond0": CartesianDomain({"x": 0.0}), - "bound_cond1": CartesianDomain({"x": 1.0}), - "phys_cond": spatial_domain, - } - # here we write the problem conditions - conditions = { - "bound_cond0": Condition( - domain="bound_cond0", equation=FixedValue(0.0) - ), - "bound_cond1": Condition( - domain="bound_cond1", equation=FixedValue(0.0) - ), - "phys_cond": Condition( - domain="phys_cond", equation=Equation(poisson_equation) - ), - } - - def solution(self, x): - return torch.sin(2 * torch.pi * x) + 0.1 * torch.sin(50 * torch.pi * x) - - -problem = Poisson() - -# let's discretise the domain -problem.discretise_domain(128, "grid", domains=["phys_cond"]) -problem.discretise_domain(1, "grid", domains=["bound_cond0", "bound_cond1"]) - - -# A standard PINN approach would be to fit this model using a Feed Forward (fully connected) Neural Network. For a conventional fully-connected neural network is easy to -# approximate a function $u$, given sufficient data inside the computational domain. However solving high-frequency or multi-scale problems presents great challenges to PINNs especially when the number of data cannot capture the different scales. -# -# Below we run a simulation using the `PINN` solver and the self adaptive `SAPINN` solver, using a [`FeedForward`](https://mathlab.github.io/PINA/_modules/pina/model/feed_forward.html#FeedForward) model. - -# In[3]: - - -# training with PINN and visualize results -pinn = PINN( - problem=problem, - model=FeedForward( - input_dimensions=1, output_dimensions=1, layers=[100, 100, 100] - ), -) - -trainer = Trainer( - pinn, - max_epochs=1500, - accelerator="cpu", - enable_model_summary=False, - val_size=0.0, - train_size=1.0, - test_size=0.0, -) -trainer.train() - -# training with PINN and visualize results -sapinn = SAPINN( - problem=problem, - model=FeedForward( - input_dimensions=1, output_dimensions=1, layers=[100, 100, 100] - ), -) -trainer_sapinn = Trainer( - sapinn, - max_epochs=1500, - accelerator="cpu", - enable_model_summary=False, - val_size=0.0, - train_size=1.0, - test_size=0.0, -) -trainer_sapinn.train() - - -# In[4]: - - -# define the function to plot the solution obtained using matplotlib -def plot_solution(pinn_to_use, title): - pts = pinn_to_use.problem.spatial_domain.sample(256, "grid", variables="x") - predicted_output = pinn_to_use.forward(pts).extract("u").tensor.detach() - true_output = pinn_to_use.problem.solution(pts).detach() - plt.plot( - pts.extract(["x"]), predicted_output, label="Neural Network solution" - ) - plt.plot(pts.extract(["x"]), true_output, label="True solution") - plt.title(title) - plt.legend() - - -# plot the solution of the two PINNs -plot_solution(pinn, "PINN solution") -plt.figure() -plot_solution(sapinn, "Self Adaptive PINN solution") - - -# We can clearly see that the solution has not been learned by the two different solvers. Indeed the big problem is not in the optimization strategy (i.e. the solver), but in the model used to solve the problem. A simple `FeedForward` network can hardly handle multiscales if not enough collocation points are used! -# -# We can also compute the $l_2$ relative error for the `PINN` and `SAPINN` solutions: - -# In[5]: - - -# l2 loss from PINA losses -l2_loss = LpLoss(p=2, relative=False) - -# sample new test points -pts = pts = problem.spatial_domain.sample(100, "grid") -print( - f"Relative l2 error PINN {l2_loss(pinn(pts), problem.solution(pts)).item():.2%}" -) -print( - f"Relative l2 error SAPINN {l2_loss(sapinn(pts), problem.solution(pts)).item():.2%}" -) - - -# Which is indeed very high! - -# ## Fourier Feature Embedding in PINA - -# Fourier Feature Embedding is a way to transform the input features, to help the network in learning multiscale variations in the output. It was -# first introduced in [*On the eigenvector bias of Fourier feature networks: From regression to solving -# multi-scale PDEs with physics-informed neural networks*]( -# https://doi.org/10.1016/j.cma.2021.113938) showing great results for multiscale problems. The basic idea is to map the input $\mathbf{x}$ into an embedding $\tilde{\mathbf{x}}$ where: -# -# $$ \tilde{\mathbf{x}} =\left[\cos\left( \mathbf{B} \mathbf{x} \right), \sin\left( \mathbf{B} \mathbf{x} \right)\right] $$ -# -# and $\mathbf{B}_{ij} \sim \mathcal{N}(0, \sigma^2)$. This simple operation allow the network to learn on multiple scales! -# -# In PINA we already have implemented the feature as a `layer` called [`FourierFeatureEmbedding`](https://mathlab.github.io/PINA/_rst/layers/fourier_embedding.html). Below we will build the *Multi-scale Fourier Feature Architecture*. In this architecture multiple Fourier feature embeddings (initialized with different $\sigma$) -# are applied to input coordinates and then passed through the same fully-connected neural network, before the outputs are finally concatenated with a linear layer. - -# In[6]: - - -class MultiscaleFourierNet(torch.nn.Module): - def __init__(self): - super().__init__() - self.embedding1 = FourierFeatureEmbedding( - input_dimension=1, output_dimension=100, sigma=1 - ) - self.embedding2 = FourierFeatureEmbedding( - input_dimension=1, output_dimension=100, sigma=10 - ) - self.layers = FeedForward( - input_dimensions=100, output_dimensions=100, layers=[100] - ) - self.final_layer = torch.nn.Linear(2 * 100, 1) - - def forward(self, x): - e1 = self.layers(self.embedding1(x)) - e2 = self.layers(self.embedding2(x)) - return self.final_layer(torch.cat([e1, e2], dim=-1)) - - -# We will train the `MultiscaleFourierNet` with the `PINN` solver (and feel free to try also with our PINN variants (`SAPINN`, `GPINN`, `CompetitivePINN`, ...). - -# In[7]: - - -multiscale_pinn = PINN(problem=problem, model=MultiscaleFourierNet()) -trainer = Trainer( - multiscale_pinn, - max_epochs=1500, - accelerator="cpu", - enable_model_summary=False, - val_size=0.0, - train_size=1.0, - test_size=0.0, -) -trainer.train() - - -# Let us now plot the solution and compute the relative $l_2$ again! - -# In[8]: - - -# plot solution obtained -plot_solution(multiscale_pinn, "Multiscale PINN solution") - -# sample new test points -pts = pts = problem.spatial_domain.sample(100, "grid") -print( - f"Relative l2 error PINN with MultiscaleFourierNet: {l2_loss(multiscale_pinn(pts), problem.solution(pts)).item():.2%}" -) - - -# It is pretty clear that the network has learned the correct solution, with also a very low error. Obviously a longer training and a more expressive neural network could improve the results! -# -# ## What's next? -# -# Congratulations on completing the one dimensional Poisson tutorial of **PINA** using `FourierFeatureEmbedding`! There are multiple directions you can go now: -# -# 1. Train the network for longer or with different layer sizes and assert the finaly accuracy -# -# 2. Understand the role of `sigma` in `FourierFeatureEmbedding` (see original paper for a nice reference) -# -# 3. Code the *Spatio-temporal multi-scale Fourier feature architecture* for a more complex time dependent PDE (section 3 of the original reference) -# -# 4. Many more... diff --git a/tutorials/tutorial14/tutorial.ipynb b/tutorials/tutorial14/tutorial.ipynb index da1c020..27f06cd 100644 --- a/tutorials/tutorial14/tutorial.ipynb +++ b/tutorials/tutorial14/tutorial.ipynb @@ -4,25 +4,13 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Tutorial: Predicting Lid-driven cavity problem parameters with POD-RBF\n", + "# Tutorial: Learning Bifurcating PDE Solutions with Physics-Informed Deep Ensembles\n", "\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial14/tutorial.ipynb)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In this tutorial we will show how to use the **PINA** library to predict the distributions of velocity and pressure the Lid-driven Cavity problem, a benchmark in Computational Fluid Dynamics. The problem consists of a square cavity with a lid on top moving with tangential velocity (by convention to the right), with the addition of no-slip conditions on the walls of the cavity and null static pressure on the lower left angle. \n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial14/tutorial.ipynb)\n", "\n", - "Our goal is to predict the distributions of velocity and pressure of the fluid inside the cavity as the Reynolds number of the inlet fluid varies. To do so we're using a Reduced Order Model (ROM) based on Proper Orthogonal Decomposition (POD). The parametric solution manifold is approximated here with Radial Basis Function (RBF) Interpolation, a common mesh-free interpolation method that doesn't require trainers or solvers as the found radial basis functions are used to interpolate new points." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let's start with the necessary imports. We're particularly interested in the `PODBlock` and `RBFBlock` classes which will allow us to define the POD-RBF model." + "This tutorial demonstrates how to use the Deep Ensemble Physics Informed Network (DeepEnsemblePINN) to learn PDEs exhibiting bifurcating behavior, as discussed in [*Learning and Discovering Multiple Solutions Using Physics-Informed Neural Networks with Random Initialization and Deep Ensemble*](https://arxiv.org/abs/2503.06320).\n", + "\n", + "Let’s begin by importing the necessary libraries." ] }, { @@ -39,17 +27,22 @@ "except:\n", " IN_COLAB = False\n", "if IN_COLAB:\n", - " !pip install \"pina-mathlab\"\n", + " !pip install \"pina-mathlab[tutorial]\"\n", "\n", - "%matplotlib inline\n", - "\n", - "import matplotlib.pyplot as plt\n", "import torch\n", - "import pina\n", + "import matplotlib.pyplot as plt\n", "import warnings\n", "\n", - "from pina.model.block import PODBlock, RBFBlock\n", - "from pina import LabelTensor\n", + "from lightning.pytorch.callbacks import Callback\n", + "\n", + "from pina import Trainer, Condition, LabelTensor\n", + "from pina.solver import DeepEnsemblePINN\n", + "from pina.model import FeedForward\n", + "from pina.operator import laplacian\n", + "from pina.problem import TimeDependentProblem\n", + "from pina.domain import CartesianDomain\n", + "from pina.equation import Equation\n", + "from pina.optim import TorchOptimizer\n", "\n", "warnings.filterwarnings(\"ignore\")" ] @@ -58,366 +51,275 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "In this tutorial we're gonna use the `LidCavity` class from the [Smithers](https://github.com/mathLab/Smithers) library, which contains a set of parametric solutions of the Lid-driven cavity problem in a square domain. The dataset consists of 300 snapshots of the parameter fields, which in this case are the magnitude of velocity and the pressure, and the corresponding parameter values $u$ and $p$. Each snapshot corresponds to a different value of the tangential velocity $\\mu$ of the lid, which has been sampled uniformly between 0.01 m/s and 1 m/s.\n", + "## Deep Ensemble\n", "\n", - "Let's start by importing the dataset:" + "Deep Ensemble methods improve model performance by leveraging the diversity of predictions generated by multiple neural networks trained on the same problem. Each network in the ensemble is trained independently—typically with different weight initializations or even slight variations in the architecture or data sampling. By combining their outputs (e.g., via averaging or majority voting), ensembles reduce overfitting, increase robustness, and improve generalization.\n", + "\n", + "This approach allows the ensemble to capture different perspectives of the problem, leading to more accurate and reliable predictions.\n", + "\n", + "

\n", + " \"PINA\n", + "

\n", + "\n", + "The image above illustrates a Deep Ensemble setup, where multiple models attempt to predict the text from an image. While individual models may make errors (e.g., predicting \"PONY\" instead of \"PINA\"), combining their outputs—such as taking the majority vote—often leads to the correct result. This ensemble effect improves reliability by mitigating the impact of individual model biases.\n", + "\n", + "\n", + "## Deep Ensemble Physics-Informed Networks\n", + "\n", + "In the context of Physics-Informed Neural Networks (PINNs), Deep Ensembles help the network discover different branches or multiple solutions of a PDE that exhibits bifurcating behavior.\n", + "\n", + "By training a diverse set of models with different initializations, Deep Ensemble methods overcome the limitations of single-initialization models, which may converge to only one of the possible solutions. This approach is particularly useful when the solution space of the problem contains multiple valid physical states or behaviors.\n", + "\n", + "\n", + "## The Bratu Problem\n", + "\n", + "In this tutorial, we'll train a `DeepEnsemblePINN` solver to solve a bifurcating ODE known as the **Bratu problem**. The ODE is given by:\n", + "\n", + "$$\n", + "\\frac{d^2u}{dt^2} + \\lambda e^u = 0, \\quad t \\in (0, 1)\n", + "$$\n", + "\n", + "with boundary conditions:\n", + "\n", + "$$\n", + "u(0) = u(1) = 0,\n", + "$$\n", + "\n", + "where $\\lambda > 0$ is a scalar parameter. The analytical solutions to the 1D Bratu problem can be expressed as:\n", + "\n", + "$$\n", + "u(t, \\alpha) = 2 \\log\\left(\\frac{\\cosh(\\alpha)}{\\cosh(\\alpha(1 - 2t))}\\right),\n", + "$$\n", + "\n", + "where $\\alpha$ satisfies:\n", + "\n", + "$$\n", + "\\cosh(\\alpha) - 2\\sqrt{2}\\alpha = 0.\n", + "$$\n", + "\n", + "When $\\lambda < 3.513830719$, the equation admits two solutions $\\alpha_1$ and $\\alpha_2$, which correspond to two distinct solutions of the original ODE: $u_1$ and $u_2$.\n", + "\n", + "In this tutorial, we set $\\lambda = 1$, which leads to:\n", + "\n", + "- $\\alpha_1 \\approx 0.37929$\n", + "- $\\alpha_2 \\approx 2.73468$\n", + "\n", + "We first write the problem class, we do not write the boundary conditions as we will hard impose them.\n", + "\n", + "> **👉 We have a dedicated [tutorial](https://mathlab.github.io/PINA/tutorial16/tutorial.html) to teach how to build a Problem — have a look if you're interested!**\n", + "\n", + "> **👉 We have a dedicated [tutorial](https://mathlab.github.io/PINA/tutorial3/tutorial.html) to teach how to impose hard constraints — have a look if you're interested!**" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 80, "metadata": {}, "outputs": [], "source": [ - "import smithers\n", - "from smithers.dataset import LidCavity\n", + "# define bratu equation\n", + "def bratu_eq(input_, output_):\n", + " u_tt = laplacian(output_=output_, input_=input_, components=[\"u\"], d=[\"t\"])\n", + " return u_tt + torch.exp(output_)\n", "\n", - "dataset = LidCavity()" + "# define true solution\n", + "def true_solution(x):\n", + " alpha1 = torch.tensor([0.37929])\n", + " alpha2 = torch.tensor([2.73468])\n", + " u1 = 2 * torch.log(torch.cosh(alpha1) / torch.cosh(alpha1 * (1 - 2 * x)))\n", + " u2 = 2 * torch.log(torch.cosh(alpha2) / torch.cosh(alpha2 * (1 - 2 * x)))\n", + " return u1, u2\n", + "\n", + "# build problem class\n", + "class BratuProblem(TimeDependentProblem):\n", + " output_variables = [\"u\"]\n", + " temporal_domain = CartesianDomain({\"t\": [0, 1]})\n", + " domains = {\n", + " \"interior\": CartesianDomain({\"t\": [0, 1]}),\n", + " }\n", + " conditions = {\n", + " \"interior\": Condition(domain=\"interior\", equation=Equation(bratu_eq))\n", + " }\n", + "\n", + "# define problem and discretise domain\n", + "problem = BratuProblem()\n", + "problem.discretise_domain(n=101, mode=\"grid\", domains=\"interior\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Let's plot two the data points and the corresponding solution for both parameters at different snapshots, in order to better visualise the data we're using:" + "## Defining the Deep Ensemble Models\n", + "\n", + "Now that the problem setup is complete, we move on to creating an **ensemble of models**. Each ensemble member will be a standard `FeedForward` neural network, wrapped inside a custom `Model` class.\n", + "\n", + "Each model's weights are initialized using a **normal distribution** with mean 0 and standard deviation 2. This random initialization is crucial to promote diversity across the ensemble members, allowing the models to converge to potentially different solutions of the PDE.\n", + "\n", + "The final ensemble is simply a **list of PyTorch models**, which we will later pass to the `DeepEnsemblePINN`" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 81, + "metadata": {}, + "outputs": [], + "source": [ + "# define a single model (ensemble member)\n", + "class Model(torch.nn.Module):\n", + " def __init__(self, *args, **kwargs):\n", + " super().__init__()\n", + " self.model = FeedForward(*args, **kwargs)\n", + " self.init_weights_gaussian()\n", + "\n", + " def forward(self, x):\n", + " return x * (1 - x) * self.model(x)\n", + "\n", + " def init_weights_gaussian(self):\n", + " for param in self.model.parameters():\n", + " if param.requires_grad:\n", + " torch.nn.init.normal_(param, mean=0.0, std=2.0)\n", + "\n", + "# define a list of models with different initializations\n", + "models = [Model(1, 1, inner_size=50, n_layers=2) for _ in range(10)]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's visualize the networks output before strated training" + ] + }, + { + "cell_type": "code", + "execution_count": 82, "metadata": {}, "outputs": [ { "data": { - "image/png": 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aLVu26Ctf+YqGDh2qgoICLViwIO95An464YQTZFmWLr/8cr8XBfAU2Y8oI/sRVWQ/oozsR9TYbhA99thjmjVrlubOnav169drzJgxqq2t1c6dO5NOv3//fp1wwgm6++67VVVV5cg8AQDeIvsBIHrIfgCIFtu/YlZdXa3x48frgQcekCTFYjENGjRIM2fO1C233JL2uUOHDtWNN96oG2+80bF5AgDcR/YDQPSQ/QAQLcV2Jm5ra9O6des0Z86cjscKCwtVU1Oj+vr6nBYgl3m2traqtbW1479jsZh2796tvn37qqCgIKflAIAgsixL//jHPzRgwAAVFrrztXJkPwCYhewn+wFEixe5L9lsEO3atUvt7e2qrKxMeLyyslJvvfVWTguQyzznzZunu+66K6fXA4Aw2r59u4477jhX5k32A4CZyH4AiBY3c1+y2SAyxZw5czRr1qyO/25ubtbgwYM1cP4tKvtkgU6ratCQXh9Kkk4qa3T89U8uaXB8ngDC75225N/HYMdfPqrUe/v7asfecn3wwSdU/NeYts7/to4++mgHltBs6bJ/4AkHNPColo7sTyefukD+A3BStnUhnv2vN1Sp7R+lZD/ZDyDAcsr+/y3S9rnfcT33bTWI+vXrp6KiIjU2JgZsY2Njyi+ic2OepaWlKi0t7fZ4+dZyfVRcoo27+2p9+SGVlrcmeXan1z56X9LHjzuqOe3z/vDxbI/vvSvtdLk6uYwiBATFOx9ln31bW/ul/fvf91Z0/P9d/+idcrrWllIVthSrYluhev51v7ZKrl5mH4TsbyrupyYpq+yXyH8A+cs2/7fuyz77u+pcC8j+RF2zX5Lrx/7JuFUP4qgLgFlsHfunyX+72X9UU5skd3NfstkgKikp0bhx47Ry5UrV1dVJOnwf8MqVK3XdddfltABOzrPvlja1N5ao9ZhCSSVqKy9JOl3bx5/FLh2tgxWxjsdjHxeXHerT7TnJCs5GDUhZaNLJVIQyHUhk4nahAsIs3/0v27DvrLXlyIFvYcvhWO7R3P3e4pKPo+OoFql0T0yle9pU2LQ3j6XNTtiyX5I+qOj+WcTKD9nK/zi7dSBdDch3++uKegDYl89+mKoGJMt/sj+/eXbPfkmyd+wft6O8e/ZLmRtOkvT3o1PX/WQynQd0xXkB4K1c97lk+Z/p2D+e/VLq/I9nf9GutpyWyy7bt5jNmjVL06dP1+mnn64JEyZowYIF2rdvn6688kpJ0rRp0zRw4EDNmzdP0uEvo3vjjTc6/v+OHTu0ceNGHXXUUTrppJOymme2yv66U4Utlkr79JQktR6TfPUOF5LD2hI+iJKEE4i4gxUxHWzpPq9Y+SHtaOk+ohGXqqikuzIgl4ZTV+lOUOPsFicgjLLZVzJJtz9LiScAcYVd8qS0Uw7FTwRKWpLP7/DJwSGV7D6gwg9b1LbzA3sLnKMwZP/hv338Xm8v/Phk4oi2iu4nFqnyX+o0qJCiDuRSAyRn6kBcum2cOgAclk8tyHS1Z1ed879QR04ISjrtjsnyn+zvrmv2S7kc+3/8WJL8l6SDFenzX3K+Bkje1QGJWgBIudUBO/mfzbG/lDz/y//WppLdBxRrarK9jLmw3SCaMmWKmpqadMcdd6ihoUFjx47V8uXLO75sbtu2bQnfqv3+++/rU5/6VMd/33PPPbrnnns0efJkvfjii1nNMxfpThBK98Q+nqaw24dQ0qJuJw0lH3+A3ZpHzUeKSbLRiM4nFZ0LSTpdi0w2Ixe52PWP3o4WHyCIsjlISyXZgX9n8ULQ9TA03eiwlLox1PG6xxRKKlbJ7iwW0kFByf5MHMt/qaMGJMt/KbcaICXWAbdqgHRk+6cWBE8+J3RONMbDJpdakE0NcDL/yf78pMt+KXn+S7mfA0jqNrhgYh2QqAV+CGNTLui1xW4dSFcD7OZ/5mP/Ykk9VexNf0gFlmVZ3ryUe1paWlRRUaGawd9QYf/+auvTM22DSJJK9xzKbpQ5iWQFpONvWewbqQpJOnaKil1uF54woXjm11QxSaaD+1S6jgB0lawAxJWkOB7IVBi6Kt0T09H/+4+OUeQX9i9Rc3OzysvThFMIJct+KfkAQemeIxmaqT4cnsasGiBRB/xA5ufP9JqRSy3IpQ6kyn8p+xpA9h+WKvuzkU3+H54ueQ1Il/9SdjVAMrMOSNSCzsh/75hQJ+zUgnQ1INV5QLIaYCf7S/ccUvHb2/T8tv9wPfcD+StmTul8wtD9b4f/N/mJRvxvSQ4APv6g0xWQtCPSqWQYqc5HmEuB04XOhAALqlwbMm7JdICfTLrmj5T7CUDnkU04r2vWp8v+I9OkPpFwqgZI5tSBgy3Frp94eM2J/CfzveNnjbBTD3KtA3YHAuCObPL/8HT2zwGk7GqAlOO5gORqHZDCd06QTx0g/83hRX1wqg7k0wgyRWgbRJmvECrumC7TfDpPn/i37uEcLxiZNoS28vQnk92m/7iAZDowySRZQcnlRNlJbp6UmNaUgH1ebJ9296tM+242haBrftAcck7X/M8275PNp+s8Ev+e/AA91S0MncVPHvyoA1I0agH5H15ubat29q1860Dpnhi575CS3QdsXUWUrWQ140g9Sd2gyaYGSPbPBSRn64DUvRb4XQckZ2sBdSA6nNx2s9m/nDgXSKbj+NDHppL/KeCz1mOKsxxNTj9NNgXj8HTZNZDicjmJSHh+l5EJpwpKOnZHNUwoRgguJ7dpO/uZnctC4Y1MJwmdmzz5NIsyzztzHbBT+POtAxK1ANHhxLad7b6WywF8NjWhrTz1vNv69FTZhwEbjvZBPnmfTrp5uXUuIDlTByR/aoFkrx5QC+CUfLZvN+pAqoGBTFccei2Ue2D8JCHTVURx2TaJ0snm+YdfJ7uAzKV4xHXeyPItJEnnn+FyWK+KjZfcupTXZEH+HPPd7r1u/jCK7LxsriLNJrdLdh9I+bfOzahsa8Dhad2vAxK1wGlRrAPZMP1zzmfbd7MW5HqSkC6TkJzd4/xs3+OuAxJOnwscnt65OiC5UwukaNUDaoE9Jn32uWz/TtaBIDSHpBA2iAo/bFGsr/13OpeThc6FIf54utHrVPO3c+tC4vPS3/9sh52N063iEmf7fmwPmBRuYeX2dtXxOi6N+B6ZNrvGdFymL0NO/nPH4fquGCfkkv3Z5H5bn54pTxaSPe5UDTg8fe51QAp+LZDMqgfUAe+5uY25XQvSyeYkId1VRDgiVfZ3rsV2a2Y8xzM1ilL9Peh1QLJ/0urVMZwJNYFa4B83trNcfigmF/k2h0p2H5BXrcnQNYi6snOylk0hSXay0Pm/nSwWnZcp+fPsjUKnk+9BiJPdT6+KjF+cLm5hf7/ScergOZewT/8l96m/u6yzXH4lhVvWnJVtk0jKblTZ6RogeVcHJGf2KepB9rw82Qn7e+lXPcj3FxLt7C8MDuSm6+eS7fuYboAgHVPrwOH5eFcLJOevjghbjpnQ8OoqDO+xE9uvk8fb+eS+H0LfIMpFphMGOycLcbkUC8nebQup52FvA8/ldhe3R7lM35HsCEPw5srr0dB8w92pW0+T7aPcVuY+p28zzvVkQcr+VrVk/KgDR+ZrXj2QwlMTolwPJG9rQj71IPtfvkrfLAraSUJY2bnlLJ/c78rtOiC5VwsOz9vMeiAFd1+Keg3oyovtxa1aYOfuAdOFZ03SsHvLR7acKBr5FIu4fEYdks/PuxOJbAX1MmsvC1ZQ3yO7nOzoezEam21zyIRfLQgjk5pEqXhRB+K8qgeHX4uakA2n6kSY3pNsOH01pdv1IN/9gatHu4vt2i198lhJyX+kIF3++9UkSsWJOiC5VwsOz9vMeiCFM/+cqA1hfF+SMeHcIFXeBHFgIFQNos6FIl9+nizE2f1+i1ScGH3O7nXy2znDeEVFVII5F14d7Lp10J/Nz+rmcuVQ/HsnkhUQThCSy3SS4LRcriLNVa5Xn6bi9IBC+tfKf3sNY13oKup1Iui1IJmu+1FQvpg0jJwaJPYy97tyqnnUmVfnBkdejx/1sCuqtcHtmuBWLXCzOeT17cWhahB15sRJgp0mUfw13ZbpNdwsFHFuXULnxUFilAqLU0xtSrjZ+HGCneZQsi8nlaJ7cOAXu79048Wociom1ALJ/UuqvcofakN6ptYBybsD52x+jEQK120GQZPq2N/JOwn8zP1k3KoFknn1QPI+i6gN3VEPsuNcc8j79zsyVSzX4mDaJaiZuFko4kwsGNkyOdTgTbA7tY+6fZVK1+YQ2272up4k2P2xgqA0idLxohZIue+zJtUFif3LNG7Xglz3WaeuGrV7osD2mb+udSCfbczU3E/Gq1og5feemlYT4tj3/GXKeYHd7A96Y9HMvdEhXtxq0JXpRcPp2xWyEZYTCNjnVyff7X3QjVvLOuPKIee59V10kvm5n4wbtyzYQV2IDj9HdL3cL51uDlEHstf5p+7THfs7uS0GMfeT8bsWxIWxuYREYa0F2Wx/dgcF/M7/SO1RXlxFJAWzaHg5wpAtJ4OE4mGPSZdoJmPy/uV2c6h0zyGj199PnU8SkqFJlB0nRtPc4kY2UR+6M70GSGbVAX6pMprClPvJZLtuftWDODfzKqr1IQg1IM7PfdDtL6X26wq2UG716U4S3DxB6CxsRcPOuvhdKJIJUtBFnen7TbrtO8jfzxU2XnwXRVdu5n7hh8k7h+kaYm4Kek3ojPpgFlNrgBPbcS4nCvH8Zzs1k1u5nyrzM/GjJoSpHnTFfucPk+qAnW02LAMDoWwQdebUbWZ2ryKSwtckypbJo8/wTxj2hVyaQ04WCw5UvJFL3sd5nfvpTiL8ah51FZRRaLgryDXAbvbnm/t+314QdF5/xYQbuR/rW55TkyjZc0ypBVK4m0nILMh1oCs3bi2TzMj/0DeIkvHqKiLJnaIRD387xcOk4iDlFhAUCvOEKegzcfPKIROKQZR0bv64UQtMGRwIQvOoM+pCsJiwjXvB66tGO9eDrlePRuU9DyKTmkRdZZqHifVAym97pza4Lwp5lGo78uK2Yj+vHo1kg8hrTheNeMGwUzSymdbUAhEXlF+fCoqwBLsXTdJctxknikWq28ucOGgMu2xGkZMNGDhRjN3KfaeEoSZI7uRYWGtEWDK/Mzv7RC7bs9dXjaYaLOicSWS/uUxuEqUTlnrQmZt5F6QaEcbc78zNGuBnc6grrz/HyDaIvLyKSDJnRDmdMBaIZEz/HHCECQfCufxiGYKlcz0w+VduvDhR6CxoVyA5hRphBie3daebQ0AqQW0SZRLUq5DcQI3whp81wK/8T3dHQeGHLfLqG0kjcWbjx8/dJ+Nk0fCrWFAg4CS/D3gyyac55PTVQ3z/kLvcen+D3iRKJai3N8MMJmzD6eSa/W5cPYTsdP2BGj+P/cPaJEonKoPMyJ/X27GTzSE7Vw/l89P2fv84TSQaRKl4fRWRFI4mUTqcNEAy7+DfjdFjv64cYuQqvUw/de+HsDaJskFNiJagbJfp+JH9yZpDfp8gwDxByv5k3L4lFP4yddu0c1zoxy8VS9ndXuylSDeIpCNvfFBvEwlqsaBIBE8QtzMpuLcWcHLgDFOuIHVaULM/lVzWhdrgvjBsY3a2E7ebQyUtR0aVs71iiKtHg8mtr5YIW/ankus6UhecEaZtzPTmkIlCu7Z2R5GD/MtmYS8WFAlnhXlb6cqt5pDXhYIThOCL4i0Hbst33aNQI6K8fXj9nRPZ3l6WTWMo2QABV4/a5/cAAU0i7/n93WV+YpvozonmUDrpcr/zgEA6XWuCCQPEoW0Q5SJdk8jpEzSaRO7z8/3IFEh8Vu4L6pVDUvbFIdb0octLAifRJDIL7xvsiNoIMswWP8Yhx9zDextcJlw5avc7iLryc3A4MtUu21GEII/Uc6JgDj4Hf7nZHOIkAaYh+4Ejgjw4IGX34wQMDiSX7O6BsF5FFEf+A4mcbA6lk+mq0WyuIMrmitLO+RHbtTubRctb/j+zg5y5UbCCdjkk4LQwnRx0xS0GuTHpfXNrWyP7gfDcVozs0Swj/4E4p/cFt7K/pMXsHyegQeQzmkSAc9xuDvlxkpBsBJnRwvSi+v7E+paT/4isoA8OSKlPDkxqcsM+L7Yzsh9R5/T3zjlxzN+1CZSqMSRld/WoV0I3JBJr+lCF/fv6vRi+45JTRE0YDo5MGTkIokzZ7/dtBp1xywHgrKjcVsx+nRuT8t9NZD+8YOeqPa/Oyb3+UQI7sv3FSpOYU/U8YGqB4FcOgPzk2hxyMw9K98Sy/lUbGkNwGvmPXOR7u44fA3RhuHJI6l4H/B5BRjCR/cgkbLdlmtwcypZp5wGhbhDZ/an7MKJQIM6LguD1yUE++7fdApHLKHI2TaJ0RYEThPBy+yoiifwPOxMP8uPLZOqoMeAXLzI/juwPPhPzPRdu3tkThStH45nh9f5sxtrD1cIRpkIRlsAMKy9v8fSyOZSPdE0iOyMGfAcFoorcDx4vaoEXV456dZJg2uhxGJl6F4FbwnLsT/4jmbBcOSqZefVo5BpEUSsQcUEqFBQDZBK0UeNcDv5NKBBhY1r+cxVRd+Q/smHibcW5SlYfOuc/gwP2cPdAsFEDwsWNgQK3929Trh7yE79iZhC3D1xML5ixpg8pDAHnxdVD+W7HJp4gAG4yPfvjyP/wcPOWAlObQ7kNBHDlENwTlOyPowaEi0nNIY797aFBFDGmFguKQvCFuTnEaELwBOmqGS+Ymv1x1IBwKOzf16jvm8hHrt8758a0CAc/TlJNz/44akB4uFUHwtgcSlcH/Lx6NJINoqhfrhuUYoHgCEJzKEi4vcw9Uc5/k/chP379Cs5y8zMM0pWj2TR++HECf/id/369vsnZH0cNCIegDxDYGRjIt8mf6fZiP0WyQWQyrw5iTCsWFIbgCkpzyOQRhEz8PqhFeJiW/Qg+N68akoLVHIrr/qWjsYR/gNeCkP2cCwSXqVePmnrsb3odyKlBtHDhQg0dOlRlZWWqrq7W2rVr006/dOlSDR8+XGVlZRo9erSeeeaZhL/v3btX1113nY477jj17NlTI0aM0KJFi3JZNNhgWrGgMARPUJpDQZJp9MDPW6fIfudxy8ER1IDgMfWXykyQS0PIlNHjrsKU/X4OuPh9shrk/QnmMvE75yRv9jcnv3vOpPy33SB67LHHNGvWLM2dO1fr16/XmDFjVFtbq507dyadfvXq1Zo6dapmzJihDRs2qK6uTnV1ddq8eXPHNLNmzdLy5cv13//933rzzTd144036rrrrtOTTz6Z+5p9LNXJFCPyh5lWLDhBCAa3R4zjnNo+/T4oC4OgZX865L952R9HDQgGL2pA1K8clRKzyq/BgTBlf1yUa4Cp2R9HDQgOU68aMpnpVw7FFViWZdl5QnV1tcaPH68HHnhAkhSLxTRo0CDNnDlTt9xyS7fpp0yZon379umpp57qeOyMM87Q2LFjO0YLRo0apSlTpuj222/vmGbcuHH6whe+oO985zsZl6mlpUUVFRX6bK9LVVxQ0m1jTbWRmXrg4EfhMu0LXfmyOnN5VbydLA5O7OtefVF1shGEVCcJsaYPdchq0wv7l6i5uVnl5e4V1DBlv2RW/vv6RYSGZX8cNcBcURkc8OPHCbrmP9mfXKbslzJvQ37UAJMaU6Zmf2fUATOFeXAgn9xvPSb9dTeZmkOd8z9V9rft/MCT3Ld1BVFbW5vWrVunmpqaIzMoLFRNTY3q6+uTPqe+vj5hekmqra1NmH7SpEl68skntWPHDlmWpVWrVumdd97Rueeem3Sera2tamlpSfiH/JjWqWUEwTxeXTUkmdcc8opJl5d2FsbsN+lA3U+mZX8cNcA8XDnqLhPzP4zZH0cNMB91wCxcOZpesluKs73V2LT8t9Ug2rVrl9rb21VZWZnweGVlpRoaGpI+p6GhIeP0999/v0aMGKHjjjtOJSUlOu+887Rw4UKdddZZSec5b948VVRUdPwbNGiQndVAQFAYzOBlY0gy94TVLyYcxJL98IPX2YPkgjo4gPyR/eEVlH2NGuC/oA0O+C0MP0hgxK+Y3X///XrllVf05JNPat26dZo/f76uvfZaPf/880mnnzNnjpqbmzv+bd++PafXNeHEyyQm7picIPjHj/fe6W0wSCPIpo0eeMHt7M90Cb0JNcCEZTAx+zujBvgjyIMDQcp+KXr579dxf1de5q8JWd+V6dkfx7mAP4I4OBC07JfMzH9bN9r169dPRUVFamxsTHi8sbFRVVVVSZ9TVVWVdvoDBw7o1ltv1W9/+1udf/75kqTTTjtNGzdu1D333NPtMlVJKi0tVWlpqZ1FR5ZifcuNvC85HlDcj+wNPwpxUA5U3JBLcfByXyD7w8/U7I+jBniH/DdDqoYC2Q8nmZ79nRX270sN8EDQB4fDystt39YVRCUlJRo3bpxWrlzZ8VgsFtPKlSs1ceLEpM+ZOHFiwvSStGLFio7pDx48qIMHD6qwMHFRioqKFIu5f2mWiR19v5m8ozKC4C6/Rmnc2OacHkVwq8Nv4shBV2HM/jhqwBEmZ38cI8nuCUv+O5X9XmWzyTUgzNkf50UNML3OBCH746gB7gn6nQNBvHooGRPywvZXdc+aNUvTp0/X6aefrgkTJmjBggXat2+frrzySknStGnTNHDgQM2bN0+SdMMNN2jy5MmaP3++zj//fC1ZskSvvfaaFi9eLEkqLy/X5MmTNXv2bPXs2VNDhgzRSy+9pJ///Oe69957HVnJwg9bAhV+JjB5RIGRZOf5WWzZN1PrWiT83CeDmP2wz+Ts74yRZOeQ//7JtjlE9rurZPeB0JxcRgXnAs7xqwZEPf8lcwcIbDeIpkyZoqamJt1xxx1qaGjQ2LFjtXz58o4vpNu2bVvCqMCkSZP06KOP6rbbbtOtt96qYcOGadmyZRo1alTHNEuWLNGcOXP0z//8z9q9e7eGDBmi7373u7rmmmscWMXMKAzJmX6iQHHIn9+jMEErDqV7Djn608emFoZkwpj9cX7VABNGiYKMGpAf8h/ZCEL2x5o+zHt7dqsOBCXnTT/mT4U6kDsGB/yVzTmAX/tkgWVZli+v7KCWlhZVVFTos70uVXFBSdINPtOGaFKDyKRiEqRiQXHIjt8nBXFuFwc392knmkTZFIZ0VxDFt/dDVpte2L9Ezc3NKi+PVsF1IvvjaBAlClL2x1EDsmNCDXAr/93Yj50cFOgsXQ0g+9Prmv1S8u06l+3MyW3I5IxPJYjZ3xl1IL2w5r+T+61bmd9VqhrQOTe6Zr9Xue/NOxAAXEWUXJBGFBhFSM+EohAX5OaQdCTUcyki2V41FMQDS7/lM4rsdQ0w/fMNUvbHdf7sqQOJopT/TnP6ytH4PGGmeDbnWw9Mz/iw4lwgOVNqQNDy3y3ZNIf8RIPIMKZsGJ0F7USB4nCEKQWhszAVB7snDpwUeM/Od9B51SQyMeeTCVr2d0YdOMy0GhDU/HejSQSz5dooCkq+pxLk3O+MAQPyP1du530QzgVCWe1yHUXmKqLUglgwolwcTCsKcUEpDnZ0Dfp4UQlCAUB31IFwiWIdIP/d4cRJQy63FsNfnT+PZLUhjJ9XEI/504nSgEEU89+NY7aoDwpEd81T8PPkIIxFxhRROEkwtSjEBf3kIFtONIbIAn9F/ctKOwvTiUKY6wD57833iOVz0sCgQfAFMcNxRFhrAPkfHEGpAzSIkvCjSRSEohOWE4WwFAjTC0JnFIf8hWHfCxKnvoei6/yCKCzZ31nQ6wD57x+730EXlBOCMLJzizEShTH3O+uaoUGqA+S/N7z+5WKTjhMj0yCyWyS8bBKZtEFkEraCEaQCEaSC0FmQiwOQb6MoSPkeVUGoA+S/edxo/CTLizAdcyFYwnbMn46pdSCo2S+FI/+9urXYNJFpEOWC76KIHlMKRJALQmdhKA5eo6FgpkzfQ5Fq2rCI8omC5F0tCEv2S+Q/gOBKlcVu1YIwZb8Urvz34peLk/HzmIsGUQZuNomCehIR9ROFOCeKRNgKQmdhKg4INqdvMwhqdiN3mbI623oQ5szvjPwHwiFKx/zZiEqG5yOs+Z9toyiXppBpx5U0iLLgRpPItA3BLgoGRQJAtJD7qVEPjgjryYHbgn5cCABRyP8g3jJmV6HfCxAUJbsPOFK8nZoPYLIoFAggiti3kQ7bB0xDUzt/7NfIBttJeETqCiInbjOw8z0UyZ4TJowmIxkKRO5SZQX7GQDTkf0AEE3kf+5M7BNEqkHkNBM/UK/RJEJnFIjckScICnIfJgryD4swOADTkftIhWP/8OEWMwCOMKlA0GxBVxzYAu4xKf8BAN4g+/Nj6uAADSLkjXAA20B+aGghaNjnEce2kB/y331+n2wBQJBErkFEkQCigYNuAHCXac0hch9wj2n7O/zF9pAfO/Uq1vShi0vSXeQaRHAHIRFdfPb5yeWExutCERYMEADOIfvzZzf/yX4AJjAp/xkYcB4NIgA5M6lAJGN60TB9+YB0TN//EU1BydWgLCcAdEbtz5/p+U+DCI4hMKIlKJ+36SGcCVe9ADBNUPI/yMh+ezJdXcX7CYRX0I/1TUODCAB8QDFDGNAoiJ4gfOam56vpywekEoT9H+7h889fpvw3oZkdyQaRCW88EGRBKxCmHYybtjxhwigyAMncnDV1uQAgHdOP/YOQrUFYRimiDSK4x/TwQHSZEsqmLAcA2BW0Gm9a3pq2PFHDAAEQbmSsM0LbIOKXHgB3BO0EobOS3Qd8LR52X5uDWQDIjyknDKYsBwDYFaRjf1Oz1tTlSia0DaJMOPEC7AtSgUjH65D2uzEFAPkKcv77nb8MDgAIqiBmv9+Z35Vpy5NJZBtEcE8QgwTR40XThsaQmTj5chaZH35h+Iz9ymJqgFnIfyAaTMleO8thSj4V+70AAOCnzsHd1qen4/MEAJjBjbzP5rUAIIiCPjhQsvuA61mf7rWDKtINosIPWwK/4QNeicK+0jXMsy0qbhQBU0YRwor8B7IT1v0knttOnzwE+aQgKsh/IDrcyvpsXjOoIt0gAoB0gh7wAID0nLiqyMlaweAAABOErYnqRaMon1pgUvbTIAKQUdiKBCAxiuwUkw5qgHwwKBBssaYPVdi/b1bTkv9ANDl9q3EY60bkG0QUCACm4YQbgAk4PjJHrOlDvxcB4PgEoZKsuZOpaeR1Q8iP7I98gwgAgoSThMwYRQYQRJx8e4v8B5KL8n7hxxVBpmU/P3Mv8z4UAAAAAO7iHCB7vFdANIS6QcRIO5C/KI8i+IEDMO/xnueO9w4AACA8Qt0gsoODXOfwXgIAAGSPYyf/8N5nxnsEuMPEfYsGEQAg8kws0KbjPQMQFuRZarw3QLTQIOqEAASA6KIGAEB0UQO64z0BoienBtHChQs1dOhQlZWVqbq6WmvXrk07/dKlSzV8+HCVlZVp9OjReuaZZ7pN8+abb+qCCy5QRUWFevfurfHjx2vbtm25LF5eCML88P4BuTN9/wlz9seZ/hmYgvcJcI7p+1MUsj/O9M/CS7wXgLtM3cdsN4gee+wxzZo1S3PnztX69es1ZswY1dbWaufOnUmnX716taZOnaoZM2Zow4YNqqurU11dnTZv3twxzV//+ledeeaZGj58uF588UW9/vrruv3221VWVpb7muXB1A/LdLxvQO5M33+ikP1xpn8WfuP9AaIjaNnvxA/UkHG8B0CUFViWZdl5QnV1tcaPH68HHnhAkhSLxTRo0CDNnDlTt9xyS7fpp0yZon379umpp57qeOyMM87Q2LFjtWjRIknSpZdeqh49eugXv/hFTivR0tKiiooKfbbXpSouKEn4W2H/vjnNk19uso9iEk7sC97IZv9JduB7yGrTC/uXqLm5WeXl7n1WUcn+ztj2uyPno4V9wH1kv33psl9yJv+l6G7/5Dyiuu17KZfs9yr3bV1B1NbWpnXr1qmmpubIDAoLVVNTo/r6+qTPqa+vT5hekmprazumj8Vievrpp3XyySertrZWn/zkJ1VdXa1ly5bZXBVnEY728H6FF5+t+0x/j4OY/YwiO4/3A4iWIGa/kwo/bIlU7kVtfQEkZ6tBtGvXLrW3t6uysjLh8crKSjU0NCR9TkNDQ9rpd+7cqb179+ruu+/Weeedp+eee04XXnihvvzlL+ull15KOs/W1la1tLQk/Esln5MEQjI7vE9AuAUx+51Cvh3G+wA4z/T9KsrZ31kUGidhXz/Yw/bgLtPf32K/FyAWi0mSvvSlL+mb3/ymJGns2LFavXq1Fi1apMmTJ3d7zrx583TXXXd5snyFH7ZwmV0apm/ggOmiug+Znv2dRbkORHX7xGFR3vbdFtV9K0jZ31UY94eobocAUrN1BVG/fv1UVFSkxsbGhMcbGxtVVVWV9DlVVVVpp+/Xr5+Ki4s1YsSIhGlOPfXUlL9mMGfOHDU3N3f82759u53VsC0KIwe54D2JDj7raItq9ncWtToQtfUF0B3Z3108G4Ocj2FYB7iP7cMdQXhfbTWISkpKNG7cOK1cubLjsVgsppUrV2rixIlJnzNx4sSE6SVpxYoVHdOXlJRo/PjxevvttxOmeeeddzRkyJCk8ywtLVV5eXnCPy8E4QP1AkUlmvjMnReU9zTq2d9Z2PMv7OsH+9genBeU95TsTy9IeUlTCEC2bN9iNmvWLE2fPl2nn366JkyYoAULFmjfvn268sorJUnTpk3TwIEDNW/ePEnSDTfcoMmTJ2v+/Pk6//zztWTJEr322mtavHhxxzxnz56tKVOm6KyzztI555yj5cuX63e/+51efPFFZ9bSQWG8vNQOCgvgjKDtS1HP/q7in19Y6kHQtkd4K+rHPlEWxOyPNX3o2C+ZZaNrfpqyr5DryBfZ76yg7JO2G0RTpkxRU1OT7rjjDjU0NGjs2LFavnx5xxfSbdu2TYWFRy5MmjRpkh599FHddtttuvXWWzVs2DAtW7ZMo0aN6pjmwgsv1KJFizRv3jxdf/31OuWUU/T444/rzDPPdGAVnRe2E4NsBGWDhrsoFM4I4v4UxOz34iQh6PUgiNsiEGR29zknfpExH0HMfr/50TAiy+EWjv2dEaTsL7Asy/Lt1R3S0tKiiooKfbbXpSouKOn2d7dPEMK601BskEpYt3kv5LpfpSoUh6w2vbB/iZqbm4257N4rmbJfcj//kzF5/yDXkQ+Tt+0gyGX/I/u7MzX7nRLrW05Wwyhkf36cyn6vct/3XzHzgtujyJ0/9DDsQBQlZMJoQm7Yt6LBpNsN2ObgJLI/d+yLyBbbCkxD9ucuiPtzJBpEXgrq7QZB3HjhL4oFkJ1U+erk/kOGwytBPc7xE/sngKAj++0LavbTIHKJSSPIqQR1o4U5aBJlh30NybBdIMjI/+ywnwMIE7I/O0HOfhpEHkm2kXi1cwV5A4X5GFFIj/0PQFhxopAa2Q8grMj+9IKe/zSIfJTNxpNp5wv6BojwoFGUiH0TQBSQ/d2R//7z+qfugagh+5NzIv/9/vVKGkSG4yADQUPBcH6/9btQBBknCYA3yP7DnMx/sh+A6cj+w8J0zh6ZBhEnCYC3olgwwlQcACAXZD8ARE8Us18KZ/5HpkEEwB9RKBhhLA4AkI8oZL9E/gNAZ2R/8NEgAuCJzkEahqIR5sIAAE4JW/ZL5H9QcPcA4J+wNoqikP80iAB4LqgnDFEoCgDglqBmv0T+A0Augpz7cVHLfxpEAHzVNXRNKh5RKwhhxSgyYB6Ts1/yP//5gmoAYWN67nfmVw0wIfsj1SDiJAEwX7pAdquQ+H0ikI4JhQIA3JYqh704gTC5BgBAWCXLXr+aRtSBIyLVIAIQbIQ3AEQLuY98MDgMBItbA8XUkuzRIAIAhB4nCQAAAMFFk8cbhX4vAAAAAAAAQFSZ8rUSkWsQmfLGA0Am5BUARA/Z7yzeTwDIXuQaRACAaOIkAQAAAEiNBhEAAAAAAIAPTBrEjGSDyKQPAACSIacAIHrIfnfwvgJAdiLZIAIARBMnCQAAAEByNIgAAAAAAAA8ZtrgZWQbRKZ9EAAQRz4BQPSQ/e7i/QWAzCLbIAIARBMnCQAAAEB3kW4QcZIAAAAARAPH/gBMYmImRbpBBACmMbFQhBHvMwCTkEne4b0GgNQi3yCiSAAAAAAAgKiLfIMIABBNDBAAMAFZ5D3ecwB+MzWHaBDJ3A8HQLSQRd7jPQcAAAAOo0EEAAagUQEA0UP2+4f3HoBfTM4fGkQfM/lDAgC4h/wHgGgi/wF4zfTcoUHUiekfFoBwInsAIHrIfgCAaWgQAQAijxM1AIgm8h+AV4KQNzSIugjChwYgPMgcc/BZAPAKeWMWPg8AOIwGURIUCQBeIGvMw2cCwG3kjJn4XAC4KSgZQ4MohaB8gAAAZ5H/ANxCvpiNzweAG4KULTk1iBYuXKihQ4eqrKxM1dXVWrt2bdrply5dquHDh6usrEyjR4/WM888k3Laa665RgUFBVqwYEEui+aoIH2QAIIliPkSleyXgvn5AIAbopT9EvkPwFlByxTbDaLHHntMs2bN0ty5c7V+/XqNGTNGtbW12rlzZ9LpV69eralTp2rGjBnasGGD6urqVFdXp82bN3eb9re//a1eeeUVDRgwwP6auCRoHygA8wUxV6KW/VIwPycA5gpipkQx+6XDn1UQPy8AZglijthuEN1777266qqrdOWVV2rEiBFatGiRevXqpYceeijp9D/60Y903nnnafbs2Tr11FP17//+7/r0pz+tBx54IGG6HTt2aObMmfrlL3+pHj165LY2LgniBwvATEHNkyhmvxTczwuAWYKaJVHN/rigfm4AkCtbDaK2tjatW7dONTU1R2ZQWKiamhrV19cnfU59fX3C9JJUW1ubMH0sFtMVV1yh2bNna+TIkXYWyTMUCAD5CmqORDn7peB+bgDMENQMiXr2xwX18wPgr6BmR7GdiXft2qX29nZVVlYmPF5ZWam33nor6XMaGhqSTt/Q0NDx39///vdVXFys66+/PqvlaG1tVWt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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# plot solution\n", + "with torch.no_grad():\n", + " pts = problem.input_pts[\"interior\"]\n", + " for model in models:\n", + " plt.plot(pts, model(pts), \"--\")\n", + " plt.plot()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As you can see we get different output since the neural networks are initialized differently.\n", + "\n", + "## Training with `DeepEnsemblePINN`\n", + "\n", + "Now that everything is ready, we can train the models using the `DeepEnsemblePINN` solver! 🎯\n", + "\n", + "This solver is constructed by combining multiple neural network models that all aim to solve the same PDE. Each model $\\mathcal{M}_{i \\in \\{1, \\dots, 10\\}}$ in the ensemble contributes a unique perspective due to different random initializations.\n", + "\n", + "This diversity allows the ensemble to **capture multiple branches or bifurcating solutions** of the problem, making it especially powerful for PDEs like the Bratu problem.\n", + "\n", + "Once the `DeepEnsemblePINN` solver is defined with all the models, we train them using the `Trainer` class, as with any other solver in **PINA**. We also build a callback to store the value of `u(0.5)` during training iterations." + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "GPU available: True (mps), used: False\n", + "TPU available: False, using: 0 TPU cores\n", + "HPU available: False, using: 0 HPUs\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "07f1c3ae122049edabaa0d0f2f5ccb02", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, axs = plt.subplots(1, 3, figsize=(14, 3))\n", - "for ax, par, u in zip(axs, dataset.params[:3], dataset.snapshots[\"mag(v)\"][:3]):\n", - " ax.tricontourf(dataset.triang, u, levels=16)\n", - " ax.set_title(f\"$u$ field for $\\mu$ = {par[0]:.4f}\")\n", - "fig, axs = plt.subplots(1, 3, figsize=(14, 3))\n", - "for ax, par, u in zip(axs, dataset.params[:3], dataset.snapshots[\"p\"][:3]):\n", - " ax.tricontourf(dataset.triang, u, levels=16)\n", - " ax.set_title(f\"$p$ field for $\\mu$ = {par[0]:.4f}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "To train the model we only need the snapshots for the two parameters. In order to be able to work with the snapshots in **PINA** we first need to assure they're in a compatible format, hence why we start by casting them into `LabelTensor` objects:" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "\"\"\"velocity magnitude data, 5041 for each snapshot\"\"\"\n", - "\n", - "u = torch.tensor(dataset.snapshots[\"mag(v)\"]).float()\n", - "u = LabelTensor(u, labels=[f\"s{i}\" for i in range(u.shape[1])])\n", - "\"\"\"pressure data, 5041 for each snapshot\"\"\"\n", - "p = torch.tensor(dataset.snapshots[\"p\"]).float()\n", - "p = LabelTensor(p, labels=[f\"s{i}\" for i in range(p.shape[1])])\n", - "\"\"\"mu corresponding to each snapshot\"\"\"\n", - "mu = torch.tensor(dataset.params).float()\n", - "mu = LabelTensor(mu, labels=[\"mu\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The goal of our training is to be able to predict the solution for new test parameters. The first thing we need to do is validate the accuracy of the model, and in order to do so we split the 300 snapshots in training and testing dataset. In the example we set the training `ratio` to 0.9, which means that 90% of the total snapshots is used for training and the remaining 10% for testing." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "\"\"\"number of snapshots\"\"\"\n", - "\n", - "n = u.shape[0]\n", - "\"\"\"training over total snapshots ratio and number of training snapshots\"\"\"\n", - "ratio = 0.9\n", - "n_train = int(n * ratio)\n", - "\"\"\"split u and p data\"\"\"\n", - "u_train, u_test = u[:n_train], u[n_train:] # for mag(v)\n", - "p_train, p_test = p[:n_train], p[n_train:] # for p\n", - "\"\"\"split snapshots\"\"\"\n", - "mu_train, mu_test = mu[:n_train], mu[n_train:]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We now proceed by defining the model we intend to use. We inherit from the `torch.nn.Module` class, but in addition we require a `pod_rank` for the POD part and a function `rbf_kernel` in order to perform the RBF part:" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "class PODRBF(torch.nn.Module):\n", - " \"\"\"\n", - " Proper orthogonal decomposition with Radial Basis Function interpolation model.\n", - " \"\"\"\n", - "\n", - " def __init__(self, pod_rank, rbf_kernel):\n", - "\n", - " super().__init__()\n", - " self.pod = PODBlock(pod_rank)\n", - " self.rbf = RBFBlock(kernel=rbf_kernel)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We complete our model by adding two crucial methods. The first is `forward`, and it expands the input POD coefficients. After being expanded the POD layer needs to be fit, hence why we add a `fit` method that gives us the POD basis (current **PINA** default is by performing truncated Singular Value Decomposition). The same method then uses the basis to fit the RBF interpolation. Overall, the completed class looks like this:" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "class PODRBF(torch.nn.Module):\n", - " \"\"\"\n", - " Proper orthogonal decomposition with Radial Basis Function interpolation model.\n", - " \"\"\"\n", - "\n", - " def __init__(self, pod_rank, rbf_kernel):\n", - "\n", - " super().__init__()\n", - " self.pod = PODBlock(pod_rank)\n", - " self.rbf = RBFBlock(kernel=rbf_kernel)\n", - "\n", - " def forward(self, x):\n", - " \"\"\"\n", - " Defines the computation performed at every call.\n", - " :param x: The tensor to apply the forward pass.\n", - " :type x: torch.Tensor\n", - " :return: the output computed by the model.\n", - " :rtype: torch.Tensor\n", - " \"\"\"\n", - " coefficients = self.rbf(x)\n", - " return self.pod.expand(coefficients)\n", - "\n", - " def fit(self, p, x):\n", - " \"\"\"\n", - " Call the :meth:`pina.model.layers.PODBlock.fit` method of the\n", - " :attr:`pina.model.layers.PODBlock` attribute to perform the POD,\n", - " and the :meth:`pina.model.layers.RBFBlock.fit` method of the\n", - " :attr:`pina.model.layers.RBFBlock` attribute to fit the interpolation.\n", - " \"\"\"\n", - " self.pod.fit(x)\n", - " self.rbf.fit(p, self.pod.reduce(x))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now that we've built our class, we can fit the model and ask it to predict the parameters for the remaining snapshots. We remember that we don't need to train the model, as it doesn't involve any learnable parameter. The only things we have to set are the rank of the decomposition and the radial basis function (here we use thin plate). Here we focus on predicting the magnitude of velocity:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "\"\"\"create the model\"\"\"\n", - "\n", - "pod_rbfu = PODRBF(pod_rank=20, rbf_kernel=\"thin_plate_spline\")\n", - "\n", - "\"\"\"fit the model to velocity training data\"\"\"\n", - "pod_rbfu.fit(mu_train, u_train)\n", - "\n", - "\"\"\"predict the parameter using the fitted model\"\"\"\n", - "u_train_rbf = pod_rbfu(mu_train)\n", - "u_test_rbf = pod_rbfu(mu_test)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Finally we can calculate the relative error for our model:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Error summary for POD-RBF model:\n", - " Train: 8.186829e-03\n", - " Test: 5.143083e-02\n" + "`Trainer.fit` stopped: `max_epochs=500` reached.\n" ] } ], "source": [ - "relative_u_error_train = torch.norm(u_train_rbf - u_train) / torch.norm(u_train)\n", - "relative_u_error_test = torch.norm(u_test_rbf - u_test) / torch.norm(u_test)\n", + "# define the optimizers, one per model\n", + "optimizers = [TorchOptimizer(torch.optim.Adam, lr=0.006) for _ in range(10)]\n", "\n", - "print(\"Error summary for POD-RBF model:\")\n", - "print(f\" Train: {relative_u_error_train.item():e}\")\n", - "print(f\" Test: {relative_u_error_test.item():e}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The results are promising! Now let's visualise them, comparing four random predicted snapshots to the true ones:" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import numpy as np\n", - "import matplotlib\n", - "import matplotlib.pyplot as plt\n", - "\n", - "idx = torch.randint(0, len(u_test), (4,))\n", - "u_idx_rbf = pod_rbfu(mu_test[idx])\n", - "fig, axs = plt.subplots(3, 4, figsize=(14, 10))\n", - "\n", - "relative_u_error_rbf = np.abs(u_test[idx] - u_idx_rbf.detach())\n", - "relative_u_error_rbf = np.where(\n", - " u_test[idx] < 1e-7, 1e-7, relative_u_error_rbf / u_test[idx]\n", + "# define solver\n", + "solver = DeepEnsemblePINN(\n", + " problem,\n", + " models,\n", + " optimizers=optimizers,\n", ")\n", "\n", - "for i, (idx_, rbf_, rbf_err_) in enumerate(\n", - " zip(idx, u_idx_rbf, relative_u_error_rbf)\n", - "):\n", - " axs[0, i].set_title(\"Prediction for \" f\"$\\mu$ = {mu_test[idx_].item():.4f}\")\n", - " axs[1, i].set_title(\n", - " \"True snapshot for \" f\"$\\mu$ = {mu_test[idx_].item():.4f}\"\n", - " )\n", - " axs[2, i].set_title(\"Error for \" f\"$\\mu$ = {mu_test[idx_].item():.4f}\")\n", + "# callback\n", + "class StoreValue(Callback):\n", + " def on_train_epoch_start(self, trainer, pl_module):\n", + " input = LabelTensor(torch.tensor([[0.5]]), 't')\n", + " output = pl_module(input).tensor.flatten()\n", + " if trainer.current_epoch == 0:\n", + " self.store = [output]\n", + " else:\n", + " self.store.append(output)\n", "\n", - " cm = axs[0, i].tricontourf(\n", - " dataset.triang, rbf_.detach()\n", - " ) # POD-RBF prediction\n", - " plt.colorbar(cm, ax=axs[0, i])\n", + "# define trainer\n", + "trainer = Trainer(\n", + " solver,\n", + " max_epochs=500,\n", + " accelerator=\"cpu\",\n", + " enable_model_summary=False,\n", + " callbacks=[StoreValue()],\n", + ")\n", "\n", - " cm = axs[1, i].tricontourf(dataset.triang, u_test[idx_].flatten()) # Truth\n", - " plt.colorbar(cm, ax=axs[1, i])\n", - "\n", - " cm = axs[2, i].tripcolor(\n", - " dataset.triang, rbf_err_, norm=matplotlib.colors.LogNorm()\n", - " ) # Error for POD-RBF\n", - " plt.colorbar(cm, ax=axs[2, i])\n", - "\n", - "plt.show()" + "# train\n", + "trainer.train()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Overall we have reached a good level of approximation while avoiding time-consuming training procedures. Let's try doing the same to predict the pressure snapshots:" + "The training finished, let's first plot how the value of $u(0.5)$ changed during training" ] }, { "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Error summary for POD-RBF model:\n", - " Train: 5.242423e-02\n", - " Test: 2.334622e+06\n" - ] - } - ], - "source": [ - "\"\"\"create the model\"\"\"\n", - "\n", - "pod_rbfp = PODRBF(pod_rank=20, rbf_kernel=\"thin_plate_spline\")\n", - "\n", - "\"\"\"fit the model to pressure training data\"\"\"\n", - "pod_rbfp.fit(mu_train, p_train)\n", - "\n", - "\"\"\"predict the parameter using the fitted model\"\"\"\n", - "p_train_rbf = pod_rbfp(mu_train)\n", - "p_test_rbf = pod_rbfp(mu_test)\n", - "\n", - "relative_p_error_train = torch.norm(p_train_rbf - p_train) / torch.norm(p_train)\n", - "relative_p_error_test = torch.norm(p_test_rbf - p_test) / torch.norm(p_test)\n", - "\n", - "print(\"Error summary for POD-RBF model:\")\n", - "print(f\" Train: {relative_p_error_train.item():e}\")\n", - "print(f\" Test: {relative_p_error_test.item():e}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Unfortunately here we obtain a very high relative test error, although this is likely due to the nature of the available data. Looking at the plots we can see that the pressure field is subject to high variations between subsequent snapshots, especially here: " - ] - }, - { - "cell_type": "code", - "execution_count": 12, + "execution_count": 84, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ - "
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" ] }, "metadata": {}, @@ -425,34 +327,36 @@ } ], "source": [ - "fig, axs = plt.subplots(2, 3, figsize=(14, 6))\n", - "for ax, par, u in zip(\n", - " axs.ravel(), dataset.params[66:72], dataset.snapshots[\"p\"][66:72]\n", - "):\n", - " cm = ax.tricontourf(dataset.triang, u, levels=16)\n", - " plt.colorbar(cm, ax=ax)\n", - " ax.set_title(f\"$p$ field for $\\mu$ = {par[0]:.4f}\")\n", - "plt.tight_layout()\n", - "plt.show()" + "with torch.no_grad():\n", + " metrics = torch.stack(trainer.callbacks[0].store, dim=0)\n", + " plt.plot(range(metrics.shape[0]), metrics)\n", + " plt.title('Ensemble Convergence')\n", + " plt.ylabel(r'$u(0.5)$')\n", + " plt.xlabel('epochs')\n", + " plt.plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Or here:" + "As you can see, different networks in the ensemble converge to different values pf $u(0.5)$ — this means we can actually **spot the bifurcation** in the solution space!\n", + "\n", + "This is a powerful demonstration of how **Deep Ensemble Physics-Informed Neural Networks** are capable of learning **multiple valid solutions** of a PDE that exhibits bifurcating behavior.\n", + "\n", + "We can also visualize the ensemble predictions to better observe the multiple branches:\n" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 88, "metadata": {}, "outputs": [ { "data": { - "image/png": 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+ "image/png": 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" ] }, "metadata": {}, @@ -460,97 +364,44 @@ } ], "source": [ - "fig, axs = plt.subplots(2, 3, figsize=(14, 6))\n", - "for ax, par, u in zip(\n", - " axs.ravel(), dataset.params[98:104], dataset.snapshots[\"p\"][98:104]\n", - "):\n", - " cm = ax.tricontourf(dataset.triang, u, levels=16)\n", - " plt.colorbar(cm, ax=ax)\n", - " ax.set_title(f\"$p$ field for $\\mu$ = {par[0]:.4f}\")\n", - "plt.tight_layout()\n", - "plt.show()" + "# plot solution\n", + "with torch.no_grad():\n", + " pts = problem.input_pts[\"interior\"]\n", + " u_ensemble = solver(pts)\n", + " u1, u2 = true_solution(pts)\n", + " plt.plot(pts, u1, label=\"Reference solution u1\")\n", + " plt.plot(pts, u2, label=\"Reference solution u2\")\n", + " for idx, sol in enumerate(u_ensemble):\n", + " if idx == 0:\n", + " plt.plot(pts, sol, \"--\", label=\"PINNs\", c='k')\n", + " else:\n", + " plt.plot(pts, sol, \"--\", c=\"k\")\n", + " plt.legend()\n", + " plt.plot()\n", + " plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Scrolling through the velocity snapshots we can observe a more regular behaviour, with no such variations in subsequent snapshots. Moreover, if we decide not to consider the abovementioned \"problematic\" snapshots, we can already observe a huge improvement:" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Error summary for POD-RBF model:\n", - " Train: 3.672517e-02\n", - " Test: 1.686272e-01\n" - ] - } - ], - "source": [ - "\"\"\"excluding problematic snapshots\"\"\"\n", + "## What's Next?\n", "\n", - "data = list(range(300))\n", - "data_to_consider = data[:67] + data[71:100] + data[102:]\n", - "\"\"\"proceed as before\"\"\"\n", - "newp = torch.tensor(dataset.snapshots[\"p\"][data_to_consider]).float()\n", - "newp = LabelTensor(newp, labels=[f\"s{i}\" for i in range(newp.shape[1])])\n", + "You have completed the tutorial on deep ensemble PINNs for bifurcating PDEs, well don! There are many potential next steps you can explore:\n", "\n", - "newmu = torch.tensor(dataset.params[data_to_consider]).float()\n", - "newmu = LabelTensor(newmu, labels=[\"mu\"])\n", + "1. **Train the network longer or with different hyperparameters**: Experiment with different configurations of the single model, you can compose an ensemble by also stacking models with different layers, activation, ... to improve accuracy.\n", "\n", - "newn = newp.shape[0]\n", - "ratio = 0.9\n", - "new_train = int(newn * ratio)\n", + "2. **Solve more complex problems**: The original paper provides very complex problems that can be solved with PINA, we suggest you to try implement and solve them!\n", "\n", - "new_p_train, new_p_test = newp[:new_train], newp[new_train:]\n", + "3. **...and many more!**: There are countless directions to further explore, for example, what does it happen when you vary the network initialization hyperparameters?\n", "\n", - "new_mu_train, new_mu_test = newmu[:new_train], newmu[new_train:]\n", - "\n", - "new_pod_rbfp = PODRBF(pod_rank=20, rbf_kernel=\"thin_plate_spline\")\n", - "\n", - "new_pod_rbfp.fit(new_mu_train, new_p_train)\n", - "\n", - "new_p_train_rbf = new_pod_rbfp(new_mu_train)\n", - "new_p_test_rbf = new_pod_rbfp(new_mu_test)\n", - "\n", - "new_relative_p_error_train = torch.norm(\n", - " new_p_train_rbf - new_p_train\n", - ") / torch.norm(new_p_train)\n", - "new_relative_p_error_test = torch.norm(\n", - " new_p_test_rbf - new_p_test\n", - ") / torch.norm(new_p_test)\n", - "\n", - "print(\"Error summary for POD-RBF model:\")\n", - "print(f\" Train: {new_relative_p_error_train.item():e}\")\n", - "print(f\" Test: {new_relative_p_error_test.item():e}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## What's next?\n", - "\n", - "Congratulations on completing the **PINA** tutorial on building and using a custom POD class! Now you can try:\n", - "\n", - "1. Varying the inputs of the model (for a list of the supported RB functions look at the `rbf_layer.py` file in `pina.layers`)\n", - "\n", - "2. Changing the POD model, for example using Artificial Neural Networks. For a more in depth overview of POD-NN and a comparison with the POD-RBF model already shown, look at [Tutorial: Reduced order model (POD-RBF or POD-NN) for parametric problems](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial9/tutorial.ipynb)\n", - "\n", - "3. Building your own classes or adapt the one shown to other datasets/problems" + "For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/)." ] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "pina", "language": "python", "name": "python3" }, @@ -564,7 +415,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.3" + "version": "3.9.21" } }, "nbformat": 4, diff --git a/tutorials/tutorial14/tutorial.py b/tutorials/tutorial14/tutorial.py deleted file mode 100644 index 835a50b..0000000 --- a/tutorials/tutorial14/tutorial.py +++ /dev/null @@ -1,338 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# # Tutorial: Predicting Lid-driven cavity problem parameters with POD-RBF -# -# [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial14/tutorial.ipynb) - -# In this tutorial we will show how to use the **PINA** library to predict the distributions of velocity and pressure the Lid-driven Cavity problem, a benchmark in Computational Fluid Dynamics. The problem consists of a square cavity with a lid on top moving with tangential velocity (by convention to the right), with the addition of no-slip conditions on the walls of the cavity and null static pressure on the lower left angle. -# -# Our goal is to predict the distributions of velocity and pressure of the fluid inside the cavity as the Reynolds number of the inlet fluid varies. To do so we're using a Reduced Order Model (ROM) based on Proper Orthogonal Decomposition (POD). The parametric solution manifold is approximated here with Radial Basis Function (RBF) Interpolation, a common mesh-free interpolation method that doesn't require trainers or solvers as the found radial basis functions are used to interpolate new points. - -# Let's start with the necessary imports. We're particularly interested in the `PODBlock` and `RBFBlock` classes which will allow us to define the POD-RBF model. - -# In[ ]: - - -## routine needed to run the notebook on Google Colab -try: - import google.colab - - IN_COLAB = True -except: - IN_COLAB = False -if IN_COLAB: - get_ipython().system('pip install "pina-mathlab"') - -get_ipython().run_line_magic('matplotlib', 'inline') - -import matplotlib.pyplot as plt -import torch -import pina -import warnings - -from pina.model.block import PODBlock, RBFBlock -from pina import LabelTensor - -warnings.filterwarnings("ignore") - - -# In this tutorial we're gonna use the `LidCavity` class from the [Smithers](https://github.com/mathLab/Smithers) library, which contains a set of parametric solutions of the Lid-driven cavity problem in a square domain. The dataset consists of 300 snapshots of the parameter fields, which in this case are the magnitude of velocity and the pressure, and the corresponding parameter values $u$ and $p$. Each snapshot corresponds to a different value of the tangential velocity $\mu$ of the lid, which has been sampled uniformly between 0.01 m/s and 1 m/s. -# -# Let's start by importing the dataset: - -# In[2]: - - -import smithers -from smithers.dataset import LidCavity - -dataset = LidCavity() - - -# Let's plot two the data points and the corresponding solution for both parameters at different snapshots, in order to better visualise the data we're using: - -# In[3]: - - -fig, axs = plt.subplots(1, 3, figsize=(14, 3)) -for ax, par, u in zip(axs, dataset.params[:3], dataset.snapshots["mag(v)"][:3]): - ax.tricontourf(dataset.triang, u, levels=16) - ax.set_title(f"$u$ field for $\mu$ = {par[0]:.4f}") -fig, axs = plt.subplots(1, 3, figsize=(14, 3)) -for ax, par, u in zip(axs, dataset.params[:3], dataset.snapshots["p"][:3]): - ax.tricontourf(dataset.triang, u, levels=16) - ax.set_title(f"$p$ field for $\mu$ = {par[0]:.4f}") - - -# To train the model we only need the snapshots for the two parameters. In order to be able to work with the snapshots in **PINA** we first need to assure they're in a compatible format, hence why we start by casting them into `LabelTensor` objects: - -# In[4]: - - -"""velocity magnitude data, 5041 for each snapshot""" - -u = torch.tensor(dataset.snapshots["mag(v)"]).float() -u = LabelTensor(u, labels=[f"s{i}" for i in range(u.shape[1])]) -"""pressure data, 5041 for each snapshot""" -p = torch.tensor(dataset.snapshots["p"]).float() -p = LabelTensor(p, labels=[f"s{i}" for i in range(p.shape[1])]) -"""mu corresponding to each snapshot""" -mu = torch.tensor(dataset.params).float() -mu = LabelTensor(mu, labels=["mu"]) - - -# The goal of our training is to be able to predict the solution for new test parameters. The first thing we need to do is validate the accuracy of the model, and in order to do so we split the 300 snapshots in training and testing dataset. In the example we set the training `ratio` to 0.9, which means that 90% of the total snapshots is used for training and the remaining 10% for testing. - -# In[5]: - - -"""number of snapshots""" - -n = u.shape[0] -"""training over total snapshots ratio and number of training snapshots""" -ratio = 0.9 -n_train = int(n * ratio) -"""split u and p data""" -u_train, u_test = u[:n_train], u[n_train:] # for mag(v) -p_train, p_test = p[:n_train], p[n_train:] # for p -"""split snapshots""" -mu_train, mu_test = mu[:n_train], mu[n_train:] - - -# We now proceed by defining the model we intend to use. We inherit from the `torch.nn.Module` class, but in addition we require a `pod_rank` for the POD part and a function `rbf_kernel` in order to perform the RBF part: - -# In[6]: - - -class PODRBF(torch.nn.Module): - """ - Proper orthogonal decomposition with Radial Basis Function interpolation model. - """ - - def __init__(self, pod_rank, rbf_kernel): - - super().__init__() - self.pod = PODBlock(pod_rank) - self.rbf = RBFBlock(kernel=rbf_kernel) - - -# We complete our model by adding two crucial methods. The first is `forward`, and it expands the input POD coefficients. After being expanded the POD layer needs to be fit, hence why we add a `fit` method that gives us the POD basis (current **PINA** default is by performing truncated Singular Value Decomposition). The same method then uses the basis to fit the RBF interpolation. Overall, the completed class looks like this: - -# In[7]: - - -class PODRBF(torch.nn.Module): - """ - Proper orthogonal decomposition with Radial Basis Function interpolation model. - """ - - def __init__(self, pod_rank, rbf_kernel): - - super().__init__() - self.pod = PODBlock(pod_rank) - self.rbf = RBFBlock(kernel=rbf_kernel) - - def forward(self, x): - """ - Defines the computation performed at every call. - :param x: The tensor to apply the forward pass. - :type x: torch.Tensor - :return: the output computed by the model. - :rtype: torch.Tensor - """ - coefficients = self.rbf(x) - return self.pod.expand(coefficients) - - def fit(self, p, x): - """ - Call the :meth:`pina.model.layers.PODBlock.fit` method of the - :attr:`pina.model.layers.PODBlock` attribute to perform the POD, - and the :meth:`pina.model.layers.RBFBlock.fit` method of the - :attr:`pina.model.layers.RBFBlock` attribute to fit the interpolation. - """ - self.pod.fit(x) - self.rbf.fit(p, self.pod.reduce(x)) - - -# Now that we've built our class, we can fit the model and ask it to predict the parameters for the remaining snapshots. We remember that we don't need to train the model, as it doesn't involve any learnable parameter. The only things we have to set are the rank of the decomposition and the radial basis function (here we use thin plate). Here we focus on predicting the magnitude of velocity: - -# In[8]: - - -"""create the model""" - -pod_rbfu = PODRBF(pod_rank=20, rbf_kernel="thin_plate_spline") - -"""fit the model to velocity training data""" -pod_rbfu.fit(mu_train, u_train) - -"""predict the parameter using the fitted model""" -u_train_rbf = pod_rbfu(mu_train) -u_test_rbf = pod_rbfu(mu_test) - - -# Finally we can calculate the relative error for our model: - -# In[9]: - - -relative_u_error_train = torch.norm(u_train_rbf - u_train) / torch.norm(u_train) -relative_u_error_test = torch.norm(u_test_rbf - u_test) / torch.norm(u_test) - -print("Error summary for POD-RBF model:") -print(f" Train: {relative_u_error_train.item():e}") -print(f" Test: {relative_u_error_test.item():e}") - - -# The results are promising! Now let's visualise them, comparing four random predicted snapshots to the true ones: - -# In[10]: - - -import numpy as np -import matplotlib -import matplotlib.pyplot as plt - -idx = torch.randint(0, len(u_test), (4,)) -u_idx_rbf = pod_rbfu(mu_test[idx]) -fig, axs = plt.subplots(3, 4, figsize=(14, 10)) - -relative_u_error_rbf = np.abs(u_test[idx] - u_idx_rbf.detach()) -relative_u_error_rbf = np.where( - u_test[idx] < 1e-7, 1e-7, relative_u_error_rbf / u_test[idx] -) - -for i, (idx_, rbf_, rbf_err_) in enumerate( - zip(idx, u_idx_rbf, relative_u_error_rbf) -): - axs[0, i].set_title("Prediction for " f"$\mu$ = {mu_test[idx_].item():.4f}") - axs[1, i].set_title( - "True snapshot for " f"$\mu$ = {mu_test[idx_].item():.4f}" - ) - axs[2, i].set_title("Error for " f"$\mu$ = {mu_test[idx_].item():.4f}") - - cm = axs[0, i].tricontourf( - dataset.triang, rbf_.detach() - ) # POD-RBF prediction - plt.colorbar(cm, ax=axs[0, i]) - - cm = axs[1, i].tricontourf(dataset.triang, u_test[idx_].flatten()) # Truth - plt.colorbar(cm, ax=axs[1, i]) - - cm = axs[2, i].tripcolor( - dataset.triang, rbf_err_, norm=matplotlib.colors.LogNorm() - ) # Error for POD-RBF - plt.colorbar(cm, ax=axs[2, i]) - -plt.show() - - -# Overall we have reached a good level of approximation while avoiding time-consuming training procedures. Let's try doing the same to predict the pressure snapshots: - -# In[11]: - - -"""create the model""" - -pod_rbfp = PODRBF(pod_rank=20, rbf_kernel="thin_plate_spline") - -"""fit the model to pressure training data""" -pod_rbfp.fit(mu_train, p_train) - -"""predict the parameter using the fitted model""" -p_train_rbf = pod_rbfp(mu_train) -p_test_rbf = pod_rbfp(mu_test) - -relative_p_error_train = torch.norm(p_train_rbf - p_train) / torch.norm(p_train) -relative_p_error_test = torch.norm(p_test_rbf - p_test) / torch.norm(p_test) - -print("Error summary for POD-RBF model:") -print(f" Train: {relative_p_error_train.item():e}") -print(f" Test: {relative_p_error_test.item():e}") - - -# Unfortunately here we obtain a very high relative test error, although this is likely due to the nature of the available data. Looking at the plots we can see that the pressure field is subject to high variations between subsequent snapshots, especially here: - -# In[12]: - - -fig, axs = plt.subplots(2, 3, figsize=(14, 6)) -for ax, par, u in zip( - axs.ravel(), dataset.params[66:72], dataset.snapshots["p"][66:72] -): - cm = ax.tricontourf(dataset.triang, u, levels=16) - plt.colorbar(cm, ax=ax) - ax.set_title(f"$p$ field for $\mu$ = {par[0]:.4f}") -plt.tight_layout() -plt.show() - - -# Or here: - -# In[13]: - - -fig, axs = plt.subplots(2, 3, figsize=(14, 6)) -for ax, par, u in zip( - axs.ravel(), dataset.params[98:104], dataset.snapshots["p"][98:104] -): - cm = ax.tricontourf(dataset.triang, u, levels=16) - plt.colorbar(cm, ax=ax) - ax.set_title(f"$p$ field for $\mu$ = {par[0]:.4f}") -plt.tight_layout() -plt.show() - - -# Scrolling through the velocity snapshots we can observe a more regular behaviour, with no such variations in subsequent snapshots. Moreover, if we decide not to consider the abovementioned "problematic" snapshots, we can already observe a huge improvement: - -# In[14]: - - -"""excluding problematic snapshots""" - -data = list(range(300)) -data_to_consider = data[:67] + data[71:100] + data[102:] -"""proceed as before""" -newp = torch.tensor(dataset.snapshots["p"][data_to_consider]).float() -newp = LabelTensor(newp, labels=[f"s{i}" for i in range(newp.shape[1])]) - -newmu = torch.tensor(dataset.params[data_to_consider]).float() -newmu = LabelTensor(newmu, labels=["mu"]) - -newn = newp.shape[0] -ratio = 0.9 -new_train = int(newn * ratio) - -new_p_train, new_p_test = newp[:new_train], newp[new_train:] - -new_mu_train, new_mu_test = newmu[:new_train], newmu[new_train:] - -new_pod_rbfp = PODRBF(pod_rank=20, rbf_kernel="thin_plate_spline") - -new_pod_rbfp.fit(new_mu_train, new_p_train) - -new_p_train_rbf = new_pod_rbfp(new_mu_train) -new_p_test_rbf = new_pod_rbfp(new_mu_test) - -new_relative_p_error_train = torch.norm( - new_p_train_rbf - new_p_train -) / torch.norm(new_p_train) -new_relative_p_error_test = torch.norm( - new_p_test_rbf - new_p_test -) / torch.norm(new_p_test) - -print("Error summary for POD-RBF model:") -print(f" Train: {new_relative_p_error_train.item():e}") -print(f" Test: {new_relative_p_error_test.item():e}") - - -# ## What's next? -# -# Congratulations on completing the **PINA** tutorial on building and using a custom POD class! Now you can try: -# -# 1. Varying the inputs of the model (for a list of the supported RB functions look at the `rbf_layer.py` file in `pina.layers`) -# -# 2. Changing the POD model, for example using Artificial Neural Networks. For a more in depth overview of POD-NN and a comparison with the POD-RBF model already shown, look at [Tutorial: Reduced order model (POD-RBF or POD-NN) for parametric problems](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial9/tutorial.ipynb) -# -# 3. Building your own classes or adapt the one shown to other datasets/problems diff --git a/tutorials/tutorial15/tutorial.ipynb b/tutorials/tutorial15/tutorial.ipynb new file mode 100644 index 0000000..7c94510 --- /dev/null +++ b/tutorials/tutorial15/tutorial.ipynb @@ -0,0 +1,602 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Tutorial: Chemical Properties Prediction with Graph Neural Networks\n", + "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial15/tutorial.ipynb)\n", + "\n", + "In this tutorial we will use **Graph Neural Networks** (GNNs) for chemical properties prediction. Chemical properties prediction involves estimating or determining the physical, chemical, or biological characteristics of molecules based on their structure. \n", + "\n", + "Molecules can naturally be represented as graphs, where atoms serve as the nodes and chemical bonds as the edges connecting them. This graph-based structure makes GNNs a great fit for predicting chemical properties.\n", + "\n", + "In the tutorial we will use the [QM9 dataset](https://pytorch-geometric.readthedocs.io/en/latest/generated/torch_geometric.datasets.QM9.html#torch_geometric.datasets.QM9) from Pytorch Geometric. The dataset contains small molecules, each consisting of up to 29 atoms, with every atom having a corresponding 3D position. Each atom is also represented by a five-dimensional one-hot encoded vector that indicates the atom type (H, C, N, O, F).\n", + "\n", + "First of all, let's start by importing useful modules!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## routine needed to run the notebook on Google Colab\n", + "try:\n", + " import google.colab\n", + "\n", + " IN_COLAB = True\n", + "except:\n", + " IN_COLAB = False\n", + "if IN_COLAB:\n", + " !pip install \"pina-mathlab[tutorial]\"\n", + "\n", + "import torch\n", + "import warnings\n", + "\n", + "from pina import Trainer\n", + "from pina.solver import SupervisedSolver\n", + "from pina.problem.zoo import SupervisedProblem\n", + "\n", + "from torch_geometric.datasets import QM9\n", + "from torch_geometric.nn import GCNConv, global_mean_pool\n", + "\n", + "warnings.filterwarnings(\"ignore\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Download Data and create the Problem" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We download the dataset and save the molecules as a list of `Data` objects (`input_`), where each element contains one molecule encoded in a graph structure. The corresponding target properties (`target_`) are listed below:\n", + "\n", + "| Target | Property | Description | Unit |\n", + "|--------|----------------------------------|-----------------------------------------------------------------------------------|---------------------------------------------|\n", + "| 0 | $\\mu$ | Dipole moment | $D$ |\n", + "| 1 | $\\alpha$ | Isotropic polarizability | $a₀³$ |\n", + "| 2 | $\\epsilon_{\\textrm{HOMO}}$ | Highest occupied molecular orbital energy | $eV$ |\n", + "| 3 | $\\epsilon_{\\textrm{LUMO}}$ | Lowest unoccupied molecular orbital energy | $eV$ |\n", + "| 4 | $\\Delta \\epsilon$ | Gap between $\\epsilon_{\\textrm{HOMO}}$ and $\\epsilon_{\\textrm{LUMO}}$ | $eV$ |\n", + "| 5 | $\\langle R^2 \\rangle$ | Electronic spatial extent | $a₀²$ |\n", + "| 6 | $\\textrm{ZPVE}$ | Zero point vibrational energy | $eV$ |\n", + "| 7 | $U_0$ | Internal energy at 0K | $eV$ |\n", + "| 8 | $U$ | Internal energy at 298.15K | $eV$ |\n", + "| 9 | $H$ | Enthalpy at 298.15K | $eV$ |\n", + "| 10 | $G$ | Free energy at 298.15K | $eV$ |\n", + "| 11 | $c_{\\textrm{v}}$ | Heat capacity at 298.15K | $cal/(mol·K)$ |\n", + "| 12 | $U_0^{\\textrm{ATOM}}$ | Atomization energy at 0K | $eV$ |\n", + "| 13 | $U^{\\textrm{ATOM}}$ | Atomization energy at 298.15K | $eV$ |\n", + "| 14 | $H^{\\textrm{ATOM}}$ | Atomization enthalpy at 298.15K | $eV$ |\n", + "| 15 | $G^{\\textrm{ATOM}}$ | Atomization free energy at 298.15K | $eV$ |\n", + "| 16 | $A$ | Rotational constant | $GHz$ |\n", + "| 17 | $B$ | Rotational constant | $GHz$ |\n", + "| 18 | $C$ | Rotational constant | $GHz$ |\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# download the data + shuffling\n", + "dataset = QM9(root=\"./tutorial_logs\").shuffle()\n", + "\n", + "# save the dataset\n", + "input_ = [data for data in dataset]\n", + "target_ = torch.stack([data.y for data in dataset])\n", + "\n", + "# normalize the target\n", + "mean = target_.mean(dim=0, keepdim=True)\n", + "std = target_.std(dim=0, keepdim=True)\n", + "target_ = (target_ - mean) / std" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Great! Once the data are downloaded, building the problem is straightforward by using the [`SupervisedProblem`](https://mathlab.github.io/PINA/_rst/problem/zoo/supervised_problem.html) class." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# build the problem\n", + "problem = SupervisedProblem(input_=input_, output_=target_)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Build the Model\n", + "\n", + "To predict molecular properties, we will construct a simple Convolutional Graph Neural Network using the [`GCNConv`]() module from PyG. While this tutorial focuses on a straightforward model, more advanced architectures—such as Equivariant Networks—could potentially yield better performance. Please note that this tutorial serves only for demonstration purposes.\n", + "\n", + "**Importantly** notice that in the `forward` pass we pass a data object as input, and unpack inside the graph attributes. This is the only requirement in **PINA** to use graphs and solvers together." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "class GNN(torch.nn.Module):\n", + " def __init__(self, in_features, out_features, hidden_dim=256):\n", + " super(GNN, self).__init__()\n", + " self.conv1 = GCNConv(in_features, hidden_dim)\n", + " self.conv2 = GCNConv(hidden_dim, hidden_dim)\n", + " self.fc = torch.nn.Linear(hidden_dim, out_features)\n", + "\n", + " def forward(self, data):\n", + " # extract attributes, N.B. in PINA Data object are passed as input\n", + " x, edge_index, batch = data.x, data.edge_index, data.batch\n", + " # perform normal graph operations\n", + " x = torch.relu(self.conv1(x, edge_index))\n", + " x = torch.relu(self.conv2(x, edge_index))\n", + " x = global_mean_pool(x, batch)\n", + " return self.fc(x)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Train the Model\n", + "\n", + "Now that the problem is created and the model is built, we can train the model using the [`SupervisedSolver`](https://mathlab.github.io/PINA/_rst/solver/supervised.html), which is the solver for standard supervised learning task. We will optimize the Maximum Absolute Error and test on the same metric. In the [`Trainer`](https://mathlab.github.io/PINA/_rst/trainer.html) class we specify the optimization hyperparameters." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "GPU available: True (mps), used: False\n", + "TPU available: False, using: 0 TPU cores\n", + "HPU available: False, using: 0 HPUs\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "4c17f0dee08d41ef8cf24f8d7f34a245", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Sanity Checking: | | 0/? [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "# Set up the plot grid\n", + "num_properties = 19\n", + "fig, axes = plt.subplots(4, 5, figsize=(10, 8))\n", + "axes = axes.flatten()\n", + "\n", + "# Outlier removal using IQR (with torch)\n", + "for idx in range(num_properties):\n", + " target_vals = target_test[:, idx]\n", + " pred_vals = prediction_test[:, idx]\n", + "\n", + " # Calculate Q1 (25th percentile) and Q3 (75th percentile) using torch\n", + " Q1 = torch.quantile(target_vals, 0.25)\n", + " Q3 = torch.quantile(target_vals, 0.75)\n", + " IQR = Q3 - Q1\n", + "\n", + " # Define the outlier range\n", + " lower_bound = Q1 - 1.5 * IQR\n", + " upper_bound = Q3 + 1.5 * IQR\n", + "\n", + " # Filter out the outliers\n", + " mask = (target_vals >= lower_bound) & (target_vals <= upper_bound)\n", + " filtered_target = target_vals[mask]\n", + " filtered_pred = pred_vals[mask]\n", + "\n", + " # Plotting\n", + " ax = axes[idx]\n", + " ax.scatter(\n", + " filtered_target.detach(),\n", + " filtered_pred.detach(),\n", + " alpha=0.5,\n", + " label=\"Data points (no outliers)\",\n", + " )\n", + " ax.plot(\n", + " [filtered_target.min().item(), filtered_target.max().item()],\n", + " [filtered_target.min().item(), filtered_target.max().item()],\n", + " \"r--\",\n", + " label=\"y=x\",\n", + " )\n", + "\n", + " ax.set_title(properties[idx])\n", + " ax.set_xlabel(\"Target\")\n", + " ax.set_ylabel(\"Prediction\")\n", + "\n", + "# Remove the extra subplot (since there are 19 properties, not 20)\n", + "if num_properties < len(axes):\n", + " fig.delaxes(axes[-1])\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "By looking more into details, we can see that $A$ is not predicted that well, but the small values of the quantity lead to a lower MAE than the other properties. From the plot we can see that the atomatization energies, free energy and enthalpy are the predicted properties with higher correlation with the true chemical properties." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## What's Next?\n", + "\n", + "Congratulations on completing the tutorial on chemical properties prediction with **PINA**! Now that you've got the basics, there are several exciting directions to explore:\n", + "\n", + "1. **Train the network for longer or with different layer sizes**: Experiment with various configurations to see how the network's accuracy improves.\n", + "\n", + "2. **Use a different network**: For example, Equivariant Graph Neural Networks (EGNNs) have shown great results on molecular tasks by leveraging group symmetries. If you're interested, check out [*E(n) Equivariant Graph Neural Networks*](https://arxiv.org/abs/2102.09844) for more details.\n", + "\n", + "3. **What if the input is time-dependent?**: For example, predicting force fields in Molecular Dynamics simulations. In PINA, you can predict force fields with ease, as it's still a supervised learning task. If this interests you, have a look at [*Machine Learning Force Fields*](https://pubs.acs.org/doi/10.1021/acs.chemrev.0c01111).\n", + "\n", + "4. **...and many more!**: The possibilities are vast, including exploring new architectures, working with larger datasets, and applying this framework to more complex systems.\n", + "\n", + "For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/)." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pina", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.21" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/tutorials/tutorial16/tutorial.ipynb b/tutorials/tutorial16/tutorial.ipynb new file mode 100644 index 0000000..8cf47dd --- /dev/null +++ b/tutorials/tutorial16/tutorial.ipynb @@ -0,0 +1,574 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "id": "6f71ca5c", + "metadata": {}, + "source": [ + "# Tutorial: How to build a Problem in PINA\n", + "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial16/tutorial.ipynb)\n" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "ef4949c9", + "metadata": {}, + "source": [ + "In this tutorial, we will demonstrate how to build a **Problem** in **PINA** using a toy example. The tutorial will cover the following topics:\n", + "\n", + "- **Building a Problem**: Learn how to construct a problem using the built-in PINA classes.\n", + "- **Generating Data for Physics-Informed Training**: Understand how to generate the necessary data for training.\n", + "- **Exploring the `problem.zoo` Module**: Get familiar with the `problem.zoo` module, which collects pre-built problems for easy use.\n", + "\n", + "By the end of this tutorial, you'll be able to write **data-driven** or **differential problems** in **PINA** and prepare them for model training!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "014bbd86", + "metadata": {}, + "outputs": [], + "source": [ + "## routine needed to run the notebook on Google Colab\n", + "try:\n", + " import google.colab\n", + "\n", + " IN_COLAB = True\n", + "except:\n", + " IN_COLAB = False\n", + "if IN_COLAB:\n", + " !pip install \"pina-mathlab[tutorial]\"\n", + "\n", + "import warnings\n", + "import torch\n", + "import matplotlib.pyplot as plt\n", + "\n", + "warnings.filterwarnings(\"ignore\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "cf9c96e3", + "metadata": {}, + "source": [ + "## Build a PINA problem" + ] + }, + { + "cell_type": "markdown", + "id": "46ba1d43", + "metadata": {}, + "source": [ + "In **PINA**, defining a problem is done by creating a Python `class` that inherits from one or more problem classes, such as `SpatialProblem`, `TimeDependentProblem`, or `ParametricProblem`, depending on the nature of the problem. We refer to the `model` as the object that solves the problem, e.g., a **Neural Network**.\n", + "\n", + "We can have two types of problems:\n", + "1. ***Data-Driven Problems***: The model is trained using data, such as in classification networks or autoencoders.\n", + "2. **&Physics-Driven Problems***: The model is trained using physical laws representing the problem, such as in **PINNs**.\n", + "Let's start by building the first type, the data driven type. \n", + "\n", + "### Data driven modelling\n", + "In data-driven modelling, we always have an **input** and a **target**. The model's objective is to reconstruct the target from the input. Examples include:\n", + "- Image reconstruction (perturbed image as input, clear image as target)\n", + "- Classification (e.g., input: molecule, target: chemical properties)\n", + "\n", + "To build a data-driven problem in **PINA**, you can inherit from the `AbstractProblem` class. Below is an example of a regression problem where the input is a scalar value `x` and the target is a scalar value `y`.\n", + "\n", + "```python\n", + "from pina.problem import AbstractProblem\n", + "\n", + "class SupervisedProblem(AbstractProblem):\n", + " \n", + " input_variables = ['x']\n", + " output_variables = ['y']\n", + "\n", + " # other stuff ...\n", + "```\n", + "Observe that we define `input_variables` and `output_variables` as lists of symbols. This is because, in PINA, `torch.Tensors` can be labeled (see [`LabelTensor`](https://mathlab.github.io/PINA/_rst/label_tensor.html)), providing maximum flexibility for tensor manipulation. If you prefer to use regular tensors, you can simply set these to ``None``.\n", + "\n", + "To specify the input and target data, you need to use the [`Condition`](https://mathlab.github.io/PINA/_rst/condition/condition.html) interface. A condition defines the constraints (such as physical equations, boundary conditions, etc.) that must be satisfied within the problem. Once the condition is applied, the full problem is outlined below:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "464d4ab2", + "metadata": {}, + "outputs": [], + "source": [ + "from pina import Condition, LabelTensor\n", + "from pina.problem import AbstractProblem\n", + "\n", + "# creating some fictitious data\n", + "input_1 = LabelTensor(torch.randn(10, 1), \"x\") # <== input_variables\n", + "input_2 = LabelTensor(torch.randn(10, 1), \"x\") # <== input_variables\n", + "target_1 = LabelTensor(torch.randn(10, 1), \"y\") # <== output_variables\n", + "target_2 = LabelTensor(torch.randn(10, 1), \"y\") # <== output_variables\n", + "\n", + "class SupervisedProblem(AbstractProblem):\n", + " \n", + " input_variables = ['x']\n", + " output_variables = ['y']\n", + "\n", + " conditions = {\n", + " \"condition_1\": Condition(input=input_1, target=target_1),\n", + " \"condition_2\": Condition(input=input_2, target=target_2),\n", + " }\n", + "\n", + "problem = SupervisedProblem()" + ] + }, + { + "cell_type": "markdown", + "id": "d27c1341", + "metadata": {}, + "source": [ + "You can define as many conditions as needed, and the model will attempt to minimize all of them simultaneously! You can access the data in various ways:\n", + "\n", + "- `problem.conditions[''].input`, `problem.conditions[''].output` – Access the input and output data for the specified condition ``.\n", + "- `problem.input_pts` – Access the input points for all conditions.\n", + "\n", + "To ensure that the problem is ready, you can check if all domains have been discretized, meaning all conditions have input points available to pass to the model:" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "5bd8397e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# check if all domains are discretised\n", + "problem.are_all_domains_discretised" + ] + }, + { + "cell_type": "markdown", + "id": "59d80694", + "metadata": {}, + "source": [ + ">👉 **You can use multiple data structures in PINA conditions, including `Graph` or `Data` from `PyG`. To explore the different data structures available in PINA, check out [this tutorial](), and for more information on input-target conditions, visit the conditions factory classes [here](https://mathlab.github.io/PINA/_rst/condition/input_target_condition.html)**." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "8a819659", + "metadata": {}, + "source": [ + "### Simple Ordinary Differential Equation\n", + "What if we don't have data but we know the physical laws that define the data? Then physics-informed training is the solution! As an example, consider the following Ordinary Differential Equation (ODE):\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\begin{cases}\n", + "\\frac{d}{dx}u(x) &= u(x) \\quad x\\in(0,1)\\\\\n", + "u(x=0) &= 1 \\\\\n", + "\\end{cases}\n", + "\\end{equation}\n", + "$$\n", + "\n", + "with the analytical solution $u(x) = e^x$. This problem is a spatial problem because the ODE depends only on the spatial variable $x\\in(0,1)$. In PINA, differential problems are categorized by their nature, e.g.:\n", + "* `SpatialProblem` $\\rightarrow$ a differential equation with spatial variable(s)\n", + "* `TimeDependentProblem` $\\rightarrow$ a time-dependent differential equation with temporal variable(s)\n", + "* `ParametricProblem` $\\rightarrow$ a parametrized differential equation with parametric variable(s)\n", + "* `InverseProblem` $\\rightarrow$ this is a more advanced topic, see [this tutorial](https://mathlab.github.io/PINA/tutorial7/tutorial.html) for more details.\n", + "\n", + "In our case, the physical ODE inherits from the `SpatialProblem` class, since only spatial variables define the ODE.\n", + "\n", + "```python\n", + "class SimpleODE(SpatialProblem):\n", + " \n", + " output_variables = ['u']\n", + " spatial_domain = CartesianDomain{'x': [0, 1]})\n", + "\n", + " # other stuff ...\n", + "```\n", + "\n", + "What if our equation is was also time-dependent, e.g. Partial Differential Equations (PDE)? In this case, our `class` will inherit from both `SpatialProblem` and `TimeDependentProblem`:\n", + "\n", + "\n", + "```python\n", + "class TimeSpaceODE(SpatialProblem, TimeDependentProblem):\n", + "\n", + " output_variables = [\"u\"]\n", + " spatial_domain = CartesianDomain({\"x\": [0, 1]})\n", + " temporal_domain = CartesianDomain({\"t\": [0, 1]})\n", + "\n", + " # other stuff ...\n", + "```\n", + "\n", + "Differently from data-driven problems, differential-problems need to specify the domain type. If you look at our ODE definition, the spatial varibale $x$ is defined in the interval $(0,1)$, and accordingly the `spatial_domain` is a `CartesianDomain` with the input variable `x` in `[0,1]`. To know more about the Domain class see the [related tutorial](https://mathlab.github.io/PINA/tutorial6/tutorial.html). Different problems require different domain, here below we summarize the relevant ones:\n", + "\n", + "| Problem Type | Required Domain |\n", + "|-------------------------|--------------------------------|\n", + "| `SpatialProblem` | `spatial_domain` |\n", + "| `TimeDependentProblem` | `temporal_domain` |\n", + "| `ParametricProblem` | `parameter_domain` |\n", + "| `InverseProblem` | `unknown_parameter_domain` |" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "592a4c43", + "metadata": {}, + "source": [ + "Nice, the Problem class is initialized! How to represent the differential equation in **PINA**? To do this, we need to load the **PINA** operators from `pina.operator` module. Again, we'll consider Equation (1) and represent it in **PINA**:" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "f2608e2e", + "metadata": {}, + "outputs": [], + "source": [ + "from pina.problem import SpatialProblem\n", + "from pina.operator import grad\n", + "from pina.domain import CartesianDomain\n", + "from pina.equation import Equation, FixedValue\n", + "\n", + "\n", + "# defining the ode equation\n", + "def ode_equation(input_, output_):\n", + "\n", + " # computing the derivative\n", + " u_x = grad(output_, input_, components=[\"u\"], d=[\"x\"])\n", + "\n", + " # extracting the u input variable\n", + " u = output_.extract([\"u\"])\n", + "\n", + " # calculate the residual and return it\n", + " return u_x - u\n", + "\n", + "\n", + "class SimpleODE(SpatialProblem):\n", + "\n", + " output_variables = [\"u\"]\n", + " spatial_domain = CartesianDomain({\"x\": [0, 1]})\n", + "\n", + " domains = {\n", + " \"x0\": CartesianDomain({\"x\": 0.0}),\n", + " \"D\": CartesianDomain({\"x\": [0, 1]}),\n", + " }\n", + "\n", + " # conditions to hold\n", + " conditions = {\n", + " \"bound_cond\": Condition(domain=\"x0\", equation=FixedValue(1.0)),\n", + " \"phys_cond\": Condition(domain=\"D\", equation=Equation(ode_equation)),\n", + " }\n", + "\n", + " # defining the true solution\n", + " def solution(self, pts):\n", + " return torch.exp(pts.extract([\"x\"]))" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "7cf64d01", + "metadata": {}, + "source": [ + "As you can see, we implemented the `ode_equation` function which given the model ouput and input returns the equation residual. These residuals are the ones minimized during PINN optimization (for more on PINN see [the related tutorials](https://mathlab.github.io/PINA/_tutorial.html#physics-informed-neural-networks)). \n", + "\n", + "How are the residuals computed?\n", + "Givem the output we perform differential operation using the [operator modulus](https://mathlab.github.io/PINA/_rst/operator.html). It is pretty intuitive, each differential operator takes the following inputs: \n", + "- A tensor on which the operator is applied. \n", + "- A tensor with respect to which the operator is computed. \n", + "- The names of the output variables for which the operator is evaluated. \n", + "- The names of the variables with respect to which the operator is computed.\n", + "We also have a `fast` version of differential operators, where no checks are performed. This can be used to boost performances, once you know the standard ones are doing their job. \n", + "\n", + "Notice that we do not pass directly a `python` function, but an `Equation` object, which is initialized with the `python` function. This is done so that all the computations and internal checks are done inside **PINA**, see [the related tutorials](https://mathlab.github.io/PINA/tutorial12/tutorial.html) for more.\n", + "\n", + "Once we have defined the function, we need to tell the neural network where these methods are to be applied. To do so, we use again the `Condition` class. In the `Condition` class, we pass the location points and the equation we want minimized on those points.\n", + "\n", + "Finally, it's possible to define a `solution` function, which can be useful if we want to plot the results and see how the real solution compares to the expected (true) solution. Notice that the `solution` function is a method of the `Problem` class, but it is not mandatory for problem definition.\n" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "78b30f95", + "metadata": {}, + "source": [ + "## Generate data for Physical Problems\n", + "\n", + "When training physics based models, data can come in form of direct numerical simulation results (tensors, graph), or points in the domains which need to be sampled. In case we perform unsupervised learning, we just need the collocation points for training, i.e. points where we want to evaluate the neural network. Sampling point in **PINA** is very easy. But first, let's check if the domains are dicsretized by using the `are_all_domains_discretised` method." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "a561b984", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "problem = SimpleODE()\n", + "problem.are_all_domains_discretised" + ] + }, + { + "cell_type": "markdown", + "id": "ff0852f9", + "metadata": {}, + "source": [ + "This is false becase the input points are not available (we need to discretize!). If you call `problem.input_points` at this stage you will get an error due to point missing in the condition.\n", + "\n", + "```bash\n", + ">>> problem.input_pts\n", + "```\n", + "```python\n", + "---------------------------------------------------------------------------\n", + "KeyError Traceback (most recent call last)\n", + "Cell In[32], line 1\n", + "----> 1 problem.input_pts\n", + "\n", + "File ~/GitHub/PINA/pina/problem/abstract_problem.py:78, in AbstractProblem.input_pts(self)\n", + " 76 to_return[cond_name] = cond.input\n", + " 77 elif hasattr(cond, \"domain\"):\n", + "---> 78 to_return[cond_name] = self._discretised_domains[cond.domain]\n", + " 79 return to_return\n", + "\n", + "KeyError: 'x0'\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "db601e90", + "metadata": {}, + "source": [ + "To discretise the problem you can use the `discretise_domain` method:" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "09ce5c3a", + "metadata": {}, + "outputs": [], + "source": [ + "# sampling 20 points in [0, 1] through discretization in all locations\n", + "problem.discretise_domain(n=20, mode=\"grid\", domains=\"all\")\n", + "\n", + "# sampling 20 points in (0, 1) through latin hypercube sampling in D, and 1 point in x0\n", + "problem.discretise_domain(n=20, mode=\"latin\", domains=[\"D\"])\n", + "problem.discretise_domain(n=1, mode=\"random\", domains=[\"x0\"])\n", + "\n", + "# sampling 20 points in (0, 1) randomly\n", + "problem.discretise_domain(n=20, mode=\"random\")" + ] + }, + { + "cell_type": "markdown", + "id": "8fbb679f", + "metadata": {}, + "source": [ + "We are going to use latin hypercube points for sampling. We need to sample in all the conditions domains. In our case we sample in `D` and `x0`." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "329962b6", + "metadata": {}, + "outputs": [], + "source": [ + "# sampling for training\n", + "problem.discretise_domain(1, \"random\", domains=[\"x0\"])\n", + "problem.discretise_domain(5, \"lh\", domains=[\"D\"])" + ] + }, + { + "cell_type": "markdown", + "id": "ca2ac5c2", + "metadata": {}, + "source": [ + "The points are saved in a python `dict`, and can be accessed by calling the attributes `input_pts` or `discretised_domains` of the problem." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "d6ed9aaf", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Input points: {'bound_cond': LabelTensor([[0.]]), 'phys_cond': LabelTensor([[0.5744],\n", + " [0.0416],\n", + " [0.6890],\n", + " [0.9406],\n", + " [0.3500]])}\n", + "Input points labels: {'x0': LabelTensor([[0.]]), 'D': LabelTensor([[0.5744],\n", + " [0.0416],\n", + " [0.6890],\n", + " [0.9406],\n", + " [0.3500]])}\n" + ] + } + ], + "source": [ + "print(\"Input points:\", problem.input_pts)\n", + "print(\"Input points labels:\", problem.discretised_domains)" + ] + }, + { + "cell_type": "markdown", + "id": "669e8534", + "metadata": {}, + "source": [ + "To visualize the sampled points we can use `matplotlib.pyplot`:" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "3802e22a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for location in problem.input_pts:\n", + " coords = (\n", + " problem.input_pts[location].extract(problem.spatial_variables).flatten()\n", + " )\n", + " plt.scatter(coords, torch.zeros_like(coords), s=10, label=location)\n", + "plt.legend()" + ] + }, + { + "cell_type": "markdown", + "id": "7bb09c53", + "metadata": {}, + "source": [ + "## The Problem Zoo module\n", + "\n", + "In PINA many problems are already implemented for you in the [Problem Zoo module](https://mathlab.github.io/PINA/_rst/_code.html#problems-zoo). For example, the supervised problem at the beginning of the tutorial is implemented in [`SupervisedProblem`](https://mathlab.github.io/PINA/_rst/problem/zoo/supervised_problem.html)!\n", + "\n", + "Let's see now a physics based example, the advection equation" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "c70dfd4b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The AdvectionProblem has 2 conditions with names ['t0', 'D'] \n", + "The problem inherits from ['SpatialProblem', 'TimeDependentProblem'] \n", + "and the domains are of type CartesianDomain\n" + ] + } + ], + "source": [ + "from pina.problem.zoo import AdvectionProblem\n", + "\n", + "# defining the problem\n", + "problem = AdvectionProblem()\n", + "\n", + "# some infos\n", + "print(\n", + " f\"The {problem.__class__.__name__} has {len(problem.conditions)} \"\n", + " f\"conditions with names {list(problem.conditions.keys())} \\n\"\n", + " \"The problem inherits from \"\n", + " f\"{[cls.__name__ for cls in problem.__class__.__bases__]} \\n\"\n", + " f\"and the domains are of type {type(problem.domains['t0']).__name__}\"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "33e672da", + "metadata": {}, + "source": [ + "## What's Next?\n", + "\n", + "Congratulations on completing the introductory tutorial of **PINA** problems! There are several directions you can explore next:\n", + "\n", + "1. **Create Custom Problems**: Try building your own problems using the PINA framework, experiment with different PDEs, initial/boundary conditions, and data structures.\n", + "\n", + "2. **Explore the Problem Zoo**: Dive into the [`problem.zoo` module](https://mathlab.github.io/PINA/_rst/_code.html#problems-zoo) to find a variety of predefined problem setups and use them as a starting point or inspiration for your own.\n", + "\n", + "3. **...and many more!**: The possibilities are vast! Consider experimenting with different solver strategies, model architectures, or even implementing your own physical constraints.\n", + "\n", + "For more examples and in-depth guides, be sure to check out the [PINA Documentation](https://mathlab.github.io/PINA/)." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pina", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.21" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/tutorials/tutorial17/tutorial.ipynb b/tutorials/tutorial17/tutorial.ipynb new file mode 100644 index 0000000..3a56c6f --- /dev/null +++ b/tutorials/tutorial17/tutorial.ipynb @@ -0,0 +1,841 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "id": "6f71ca5c", + "metadata": {}, + "source": [ + "# Tutorial: Introductory Tutorial: A Beginner’s Guide to PINA\n", + "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial17/tutorial.ipynb)\n", + "\n", + "

\n", + " \"PINA\n", + "

\n", + "\n", + "Welcome to **PINA**!\n", + "\n", + "PINA [1] is an open-source Python library designed for **Scientific Machine Learning (SciML)** tasks, particularly involving:\n", + "\n", + "- **Physics-Informed Neural Networks (PINNs)**\n", + "- **Neural Operators (NOs)**\n", + "- **Reduced Order Models (ROMs)**\n", + "- **Graph Neural Networks (GNNs)**\n", + "- ...\n", + "\n", + "Built on **PyTorch**, **PyTorch Lightning**, and **PyTorch Geometric**, it provides a **user-friendly, intuitive interface** for formulating and solving differential problems using neural networks.\n", + "\n", + "This tutorial offers a **step-by-step guide** to using PINA—starting from basic to advanced techniques—enabling users to tackle a broad spectrum of differential problems with minimal code.\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "3014129d", + "metadata": {}, + "source": [ + "## The PINA Workflow \n", + "\n", + "

\n", + " \"PINA\n", + "

\n", + "\n", + "Solving a differential problem in **PINA** involves four main steps:\n", + "\n", + "1. ***Problem & Data***\n", + " Define the mathematical problem and its physical constraints using PINA’s base classes: \n", + " - `AbstractProblem`\n", + " - `SpatialProblem`\n", + " - `InverseProblem` \n", + " - ...\n", + "\n", + " Then prepare inputs by discretizing the domain or importing numerical data. PINA provides essential tools like the `Conditions` class and the `pina.domain` module to facilitate domain sampling and ensure that the input data aligns with the problem's requirements.\n", + "\n", + "> **👉 We have a dedicated [tutorial](https://mathlab.github.io/PINA/tutorial16/tutorial.html) to teach how to build a Problem from scratch — have a look if you're interested!**\n", + "\n", + "2. ***Model Design*** \n", + " Build neural network models as **PyTorch modules**. For graph-structured data, use **PyTorch Geometric** to build Graph Neural Networks. You can also import models from `pina.model` module!\n", + "\n", + "3. ***Solver Selection*** \n", + " Choose and configure a solver to optimize your model. Options include:\n", + " - **Supervised solvers**: `SupervisedSolver`, `ReducedOrderModelSolver`\n", + " - **Physics-informed solvers**: `PINN` and (many) variants\n", + " - **Generative solvers**: `GAROM` \n", + " Solvers can be used out-of-the-box, extended, or fully customized.\n", + "\n", + "4. ***Training*** \n", + " Train your model using the `Trainer` class (built on **PyTorch Lightning**), which enables scalable and efficient training with advanced features.\n", + "\n", + "\n", + "By following these steps, PINA simplifies applying deep learning to scientific computing and differential problems.\n", + "\n", + "\n", + "## A Simple Regression Problem in PINA\n", + "We'll start with a simple regression problem [2] of approximating the following function with a Neural Net model $\\mathcal{M}_{\\theta}$:\n", + "$$y = x^3 + \\epsilon, \\quad \\epsilon \\sim \\mathcal{N}(0, 9)$$ \n", + "using only 20 samples: \n", + "\n", + "$$x_i \\sim \\mathcal{U}[-3, 3], \\; \\forall i \\in \\{1, \\dots, 20\\}$$\n", + "\n", + "Using PINA, we will:\n", + "\n", + "- Generate a synthetic dataset.\n", + "- Implement a **Bayesian regressor**.\n", + "- Use **Monte Carlo (MC) Dropout** for **Bayesian inference** and **uncertainty estimation**.\n", + "\n", + "This example highlights how PINA can be used for classic regression tasks with probabilistic modeling capabilities. Let's first import useful modules!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0981f1e9", + "metadata": {}, + "outputs": [], + "source": [ + "## routine needed to run the notebook on Google Colab\n", + "try:\n", + " import google.colab\n", + " IN_COLAB = True\n", + "except:\n", + " IN_COLAB = False\n", + "if IN_COLAB:\n", + " !pip install \"pina-mathlab[tutorial]\"\n", + "\n", + "import warnings\n", + "import torch\n", + "import matplotlib.pyplot as plt\n", + "\n", + "warnings.filterwarnings(\"ignore\")\n", + "\n", + "from pina import Condition, LabelTensor\n", + "from pina.problem import AbstractProblem\n", + "from pina.geometry import CartesianDomain" + ] + }, + { + "cell_type": "markdown", + "id": "7b91de38", + "metadata": {}, + "source": [ + "#### ***Problem & Data***\n", + "\n", + "We'll start by defining a `BayesianProblem` inheriting from `AbstractProblem` to handle input/output data. This is suitable when data is available. For other cases like PDEs without data, use:\n", + "\n", + "- `SpatialProblem` – for spatial variables\n", + "- `TimeDependentProblem` – for temporal variables\n", + "- `ParametricProblem` – for parametric inputs\n", + "- `InverseProblem` – for parameter estimation from observations\n", + " \n", + "but we will see this more in depth in a while!" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "014bbd86", + "metadata": {}, + "outputs": [], + "source": [ + "# (a) Data generation and plot\n", + "domain = CartesianDomain({'x' : [-3, 3]})\n", + "x = domain.sample(n=20, mode=\"random\")\n", + "y = LabelTensor(x.pow(3) + 3*torch.randn_like(x), 'y')\n", + "\n", + "# (b) PINA Problem formulation\n", + "class BayesianProblem(AbstractProblem):\n", + "\n", + " output_variables = ['y']\n", + " input_variables = ['x']\n", + " conditions = {'data': Condition(input_points=x, output_points=y)}\n", + "\n", + "problem = BayesianProblem()\n", + "\n", + "# # (b) EXTRA!\n", + "# # alternatively you can do the following which is easier\n", + "# # uncomment to try it!\n", + "# from pina.problem.zoo import SupervisedProblem\n", + "# problem = SupervisedProblem(input_=x, output_=y)" + ] + }, + { + "cell_type": "markdown", + "id": "b1b1e4c4", + "metadata": {}, + "source": [ + "We highlight two very important features of PINA\n", + "\n", + "1. **`LabelTensor` Structure** \n", + " - Alongside the standard `torch.Tensor`, PINA introduces the `LabelTensor` structure, which allows **string-based indexing**. \n", + " - Ideal for managing and stacking tensors with different labels (e.g., `\"x\"`, `\"t\"`, `\"u\"`) for improved clarity and organization. \n", + " - You can still use standard PyTorch tensors if needed.\n", + "\n", + "2. **`Condition` Object** \n", + " - The `Condition` object enforces the **constraints** that the model $\\mathcal{M}_{\\theta}$ must satisfy, such as boundary or initial conditions. \n", + " - It ensures that the model adheres to the specific requirements of the problem, making constraint handling more intuitive and streamlined." + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "id": "6f25d3a6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The Label Tensor object, a very short introduction... \n", + "\n", + "1: {'dof': ['a', 'b', 'c', 'd'], 'name': 1}\n", + "\n", + "tensor([[0.7630, 0.1998, 0.3470, 0.4409],\n", + " [0.7179, 0.5710, 0.2510, 0.3984],\n", + " [0.0724, 0.5714, 0.9199, 0.7571]]) \n", + "\n", + "Torch methods can be used, label_tensor.shape=torch.Size([3, 4])\n", + "also label_tensor.requires_grad=False \n", + "\n", + "But we have labels as well, e.g. label_tensor.labels=['a', 'b', 'c', 'd']\n", + "And we can slice with labels: \n", + " label_tensor[\"a\"]=LabelTensor([[0.7630],\n", + " [0.7179],\n", + " [0.0724]])\n", + "Similarly to: \n", + " label_tensor[:, 0]=LabelTensor([[0.7630],\n", + " [0.7179],\n", + " [0.0724]])\n" + ] + } + ], + "source": [ + "# EXTRA - on the use of LabelTensor\n", + "\n", + "# We define a 2D tensor, and we index with ['a', 'b', 'c', 'd'] its columns\n", + "label_tensor = LabelTensor(torch.rand(3, 4), [\"a\", \"b\", \"c\", \"d\"])\n", + "\n", + "print(f\"The Label Tensor object, a very short introduction... \\n\")\n", + "print(label_tensor, \"\\n\")\n", + "print(f\"Torch methods can be used, {label_tensor.shape=}\")\n", + "print(f\"also {label_tensor.requires_grad=} \\n\")\n", + "print(f\"But we have labels as well, e.g. {label_tensor.labels=}\")\n", + "print(f'And we can slice with labels: \\n {label_tensor[\"a\"]=}')\n", + "print(f\"Similarly to: \\n {label_tensor[:, 0]=}\")" + ] + }, + { + "cell_type": "markdown", + "id": "98cba096", + "metadata": {}, + "source": [ + "#### ***Model Design***\n", + "\n", + "We will now solve the problem using a **simple PyTorch Neural Network** with **Dropout**, which we will implement from scratch following [2]. \n", + "It's important to note that PINA provides a wide range of **state-of-the-art (SOTA)** architectures in the `pina.model` module, which you can explore further [here](https://mathlab.github.io/PINA/_rst/_code.html#models).\n", + "\n", + "#### ***Solver Selection***\n", + "\n", + "For this task, we will use a straightforward **supervised learning** approach by importing the `SupervisedSolver` from `pina.solvers`. The solver is responsible for defining the training strategy. \n", + "\n", + "The `SupervisedSolver` is designed to handle typical regression tasks effectively by minimizing the following loss function:\n", + "$$\n", + "\\mathcal{L}_{\\rm{problem}} = \\frac{1}{N}\\sum_{i=1}^N\n", + "\\mathcal{L}(y_i - \\mathcal{M}_{\\theta}(x_i))\n", + "$$\n", + "where $\\mathcal{L}$ is the loss function, with the default being **Mean Squared Error (MSE)**:\n", + "$$\n", + "\\mathcal{L}(v) = \\| v \\|^2_2.\n", + "$$\n", + "\n", + "#### **Training**\n", + "\n", + "Next, we will use the `Trainer` class to train the model. The `Trainer` class, based on **PyTorch Lightning**, offers many features that help:\n", + "- **Improve model accuracy**\n", + "- **Reduce training time and memory usage**\n", + "- **Facilitate logging and visualization** \n", + "\n", + "The great work done by the PyTorch Lightning team ensures a streamlined training process." + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "id": "5388aaaa", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "GPU available: True (mps), used: False\n", + "TPU available: False, using: 0 TPU cores\n", + "HPU available: False, using: 0 HPUs\n", + "\n", + " | Name | Type | Params | Mode \n", + "----------------------------------------------------\n", + "0 | _pina_models | ModuleList | 301 | train\n", + "1 | _loss_fn | MSELoss | 0 | train\n", + "----------------------------------------------------\n", + "301 Trainable params\n", + "0 Non-trainable params\n", + "301 Total params\n", + "0.001 Total estimated model params size (MB)\n", + "8 Modules in train mode\n", + "0 Modules in eval mode\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "73747bd57cac432eb8dddd5254be755c", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "x_test = LabelTensor(torch.linspace(-4, 4, 100).reshape(-1, 1), 'x')\n", + "y_test = torch.stack([solver(x_test) for _ in range(1000)], dim=0)\n", + "y_mean, y_std = y_test.mean(0).detach(), y_test.std(0).detach()\n", + "# plot\n", + "x_test = x_test.flatten()\n", + "y_mean = y_mean.flatten()\n", + "y_std = y_std.flatten()\n", + "plt.plot(x_test, y_mean, label=r'$\\mu_{\\theta}$')\n", + "plt.fill_between(x_test, y_mean-3*y_std, y_mean+3*y_std, alpha=0.3, label=r'3$\\sigma_{\\theta}$')\n", + "plt.plot(x_test, x_test.pow(3), label='true')\n", + "plt.scatter(x, y, label='train data')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "ea79c71d", + "metadata": {}, + "source": [ + "## PINA for Physics-Informed Machine Learning\n", + "\n", + "In the previous section, we used PINA for **supervised learning**. However, one of its main strengths lies in **Physics-Informed Machine Learning (PIML)**, specifically through **Physics-Informed Neural Networks (PINNs)**.\n", + "\n", + "### What Are PINNs?\n", + "\n", + "PINNs are deep learning models that integrate the laws of physics directly into the training process. By incorporating **differential equations** and **boundary conditions** into the loss function, PINNs allow the modeling of complex physical systems while ensuring the predictions remain consistent with scientific laws.\n", + "\n", + "### Solving a 2D Poisson Problem\n", + "\n", + "In this section, we will solve a **2D Poisson problem** with **Dirichlet boundary conditions** on an **hourglass-shaped domain** using a simple PINN [4]. You can explore other PINN variants, e.g. [5] or [6] in PINA by visiting the [PINA solvers documentation](https://mathlab.github.io/PINA/_rst/_code.html#solvers). We aim to solve the following 2D Poisson problem:\n", + "\n", + "$$\n", + "\\begin{cases}\n", + "\\Delta u(x, y) = \\sin{(\\pi x)} \\sin{(\\pi y)} & \\text{in } D, \\\\\n", + "u(x, y) = 0 & \\text{on } \\partial D \n", + "\\end{cases}\n", + "$$\n", + "\n", + "where $D$ is an **hourglass-shaped domain** defined as the difference between a **Cartesian domain** and two intersecting **ellipsoids**, and $\\partial D$ is the boundary of the domain.\n", + "\n", + "### Building Complex Domains\n", + "\n", + "PINA allows you to build complex geometries easily. It provides many built-in domain shapes and Boolean operators for combining them. For this problem, we will define the hourglass-shaped domain using the existing `CartesianDomain` and `EllipsoidDomain` classes, with Boolean operators like `Difference` and `Union`.\n", + "\n", + "> **👉 If you are interested in exploring the `domain` module in more detail, check out [this tutorial](https://mathlab.github.io/PINA/_rst/tutorials/tutorial6/tutorial.html).**\n" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "id": "02518706", + "metadata": {}, + "outputs": [], + "source": [ + "from pina.domain import EllipsoidDomain, Difference, CartesianDomain, Union\n", + "\n", + "# (a) Building the interior of the hourglass-shaped domain\n", + "cartesian = CartesianDomain({\"x\": [-3, 3], \"y\": [-3, 3]})\n", + "ellipsoid_1 = EllipsoidDomain({\"x\": [-5, -1], \"y\": [-3, 3]})\n", + "ellipsoid_2 = EllipsoidDomain({\"x\": [1, 5], \"y\": [-3, 3]})\n", + "interior = Difference([cartesian, ellipsoid_1, ellipsoid_2])\n", + "\n", + "# (a) Building the boundary of the hourglass-shaped domain\n", + "border_ellipsoid_1 = EllipsoidDomain(\n", + " {\"x\": [-5, -1], \"y\": [-3, 3]}, sample_surface=True\n", + ")\n", + "border_ellipsoid_2 = EllipsoidDomain(\n", + " {\"x\": [1, 5], \"y\": [-3, 3]}, sample_surface=True\n", + ")\n", + "border_1 = CartesianDomain({\"x\": [-3, 3], \"y\": 3})\n", + "border_2 = CartesianDomain({\"x\": [-3, 3], \"y\": -3})\n", + "ex_1 = CartesianDomain({\"x\": [-5, -3], \"y\": [-3, 3]})\n", + "ex_2 = CartesianDomain({\"x\": [3, 5], \"y\": [-3, 3]})\n", + "border_ells = Union([border_ellipsoid_1, border_ellipsoid_2])\n", + "border = Union(\n", + " [\n", + " border_1,\n", + " border_2,\n", + " Difference(\n", + " [Union([border_ellipsoid_1, border_ellipsoid_2]), ex_1, ex_2]\n", + " ),\n", + " ]\n", + ")\n", + "\n", + "# (c) Sample the domains\n", + "interior_samples = interior.sample(n=1000, mode=\"random\")\n", + "border_samples = border.sample(n=1000, mode=\"random\")" + ] + }, + { + "cell_type": "markdown", + "id": "b0da3d52", + "metadata": {}, + "source": [ + "#### Plotting the domain\n", + "\n", + "Nice! Now that we have built the domain, let's try to plot it" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "id": "47459922", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(8, 4))\n", + "plt.subplot(1, 2, 1)\n", + "plt.scatter(\n", + " interior_samples.extract(\"x\"),\n", + " interior_samples.extract(\"y\"),\n", + " c=\"blue\",\n", + " alpha=0.5,\n", + ")\n", + "plt.title(\"Hourglass Interior\")\n", + "plt.subplot(1, 2, 2)\n", + "plt.scatter(\n", + " border_samples.extract(\"x\"),\n", + " border_samples.extract(\"y\"),\n", + " c=\"blue\",\n", + " alpha=0.5,\n", + ")\n", + "plt.title(\"Hourglass Border\")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "4d2e59a9", + "metadata": {}, + "source": [ + "#### Writing the Poisson Problem Class\n", + "\n", + "Very good! Now we will implement the problem class for the 2D Poisson problem. Unlike the previous examples, where we inherited from `AbstractProblem`, for this problem, we will inherit from the `SpatialProblem` class. \n", + "\n", + "The reason for this is that the Poisson problem involves **spatial variables** as input, so we use `SpatialProblem` to handle such cases.\n", + "\n", + "This will allow us to define the problem with spatial dependencies and set up the neural network model accordingly." + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "id": "e1eb5a09", + "metadata": {}, + "outputs": [], + "source": [ + "from pina.problem import SpatialProblem\n", + "from pina.operator import laplacian\n", + "from pina.equation import FixedValue, Equation\n", + "\n", + "\n", + "def poisson_equation(input_, output_):\n", + " force_term = torch.sin(input_.extract([\"x\"]) * torch.pi) * torch.sin(\n", + " input_.extract([\"y\"]) * torch.pi\n", + " )\n", + " laplacian_u = laplacian(output_, input_, components=[\"u\"], d=[\"x\", \"y\"])\n", + " return laplacian_u - force_term\n", + "\n", + "\n", + "class Poisson(SpatialProblem):\n", + " # define output_variables and spatial_domain\n", + " output_variables = [\"u\"]\n", + " spatial_domain = Union([interior, border])\n", + " # define the domains\n", + " domains = {\"border\": border, \"interior\": interior}\n", + " # define the conditions\n", + " conditions = {\n", + " \"border\": Condition(domain=\"border\", equation=FixedValue(0.0)),\n", + " \"interior\": Condition(\n", + " domain=\"interior\", equation=Equation(poisson_equation)\n", + " ),\n", + " }\n", + "\n", + "\n", + "poisson_problem = Poisson()" + ] + }, + { + "cell_type": "markdown", + "id": "f49a8307", + "metadata": {}, + "source": [ + "As you can see, writing the problem class for a differential equation in PINA is straightforward! The main differences are:\n", + "\n", + "- We inherit from **`SpatialProblem`** instead of `AbstractProblem` to account for spatial variables.\n", + "- We use **`domain`** and **`equation`** inside the `Condition` to define the problem.\n", + "\n", + "The `Equation` class can be very useful for creating modular problem classes. If you're interested, check out [this tutorial](https://mathlab.github.io/PINA/_rst/tutorial12/tutorial.html) for more details. There's also a dedicated [tutorial](https://mathlab.github.io/PINA/_rst/tutorial16/tutorial.html) for building custom problems!\n", + "\n", + "Once the problem class is set, we need to **sample the domain** to obtain the data. PINA will automatically handle this, and if you forget to sample, an error will be raised before training begins 😉." + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "id": "a95bb250", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Points are not automatically sampled, you can see this by:\n", + " poisson_problem.are_all_domains_discretised=False\n", + "\n", + "But you can easily sample by running .discretise_domain:\n", + " poisson_problem.are_all_domains_discretised=True\n" + ] + } + ], + "source": [ + "print('Points are not automatically sampled, you can see this by:')\n", + "print(f\" {poisson_problem.are_all_domains_discretised=}\\n\")\n", + "print('But you can easily sample by running .discretise_domain:')\n", + "poisson_problem.discretise_domain(n=1000, domains=['interior'])\n", + "poisson_problem.discretise_domain(n=100, domains=[\"border\"])\n", + "print(f\" {poisson_problem.are_all_domains_discretised=}\")" + ] + }, + { + "cell_type": "markdown", + "id": "a2c7b406", + "metadata": {}, + "source": [ + "### Building the Model\n", + "\n", + "After setting the problem and sampling the domain, the next step is to **build the model** $\\mathcal{M}_{\\theta}$.\n", + "\n", + "For this, we will use the custom PINA models available [here](https://mathlab.github.io/PINA/_rst/_code.html#models). Specifically, we will use a **feed-forward neural network** by importing the `FeedForward` class.\n", + "\n", + "This neural network takes the **coordinates** (in this case `['x', 'y']`) as input and outputs the unknown field of the Poisson problem. \n", + "\n", + "In this tutorial, the neural network is composed of 2 hidden layers, each with 120 neurons and tanh activation." + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "id": "b893232b", + "metadata": {}, + "outputs": [], + "source": [ + "from pina.model import FeedForward\n", + "\n", + "model = FeedForward(\n", + " func = torch.nn.Tanh,\n", + " layers=[120]*2,\n", + " output_dimensions=len(poisson_problem.output_variables),\n", + " input_dimensions=len(poisson_problem.input_variables)\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "37b09ea9", + "metadata": {}, + "source": [ + "### Solver Selection\n", + "\n", + "The thir part of the PINA pipeline involves using a **Solver**.\n", + "\n", + "In this tutorial, we will use the **classical PINN** solver. However, many other variants are also available and we invite to try them!\n", + "\n", + "#### Loss Function in PINA\n", + "\n", + "The loss function in the **classical PINN** is defined as follows:\n", + "\n", + "$$\\theta_{\\rm{best}}=\\min_{\\theta}\\mathcal{L}_{\\rm{problem}}(\\theta), \\quad \\mathcal{L}_{\\rm{problem}}(\\theta)= \\frac{1}{N_{D}}\\sum_{i=1}^N\n", + "\\mathcal{L}(\\Delta\\mathcal{M}_{\\theta}(\\mathbf{x}_i, \\mathbf{y}_i) - \\sin(\\pi x_i)\\sin(\\pi y_i)) +\n", + "\\frac{1}{N}\\sum_{i=1}^N\n", + "\\mathcal{L}(\\mathcal{M}_{\\theta}(\\mathbf{x}_i, \\mathbf{y}_i))$$\n", + "\n", + "This loss consists of:\n", + "1. The **differential equation residual**: Ensures the model satisfies the Poisson equation.\n", + "2. The **boundary condition**: Ensures the model satisfies the Dirichlet boundary condition.\n", + "\n", + "### Training\n", + "\n", + "For the last part of the pipeline we need a `Trainer`. We will train the model for **1000 epochs** using the default optimizer parameters. These parameters can be adjusted as needed. For more details, check the solvers documentation [here](https://mathlab.github.io/PINA/_rst/_code.html#solvers).\n", + "\n", + "To track metrics during training, we use the **`MetricTracker`** class.\n", + "\n", + "> **👉 Want to know more about `Trainer` and how to boost PINA performance, check out [this tutorial](https://mathlab.github.io/PINA/_rst/tutorials/tutorial11/tutorial.html).**" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "id": "0f135cc4", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "GPU available: True (mps), used: False\n", + "TPU available: False, using: 0 TPU cores\n", + "HPU available: False, using: 0 HPUs\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "2e865b123dbb4f39bef00e0501eb6a61", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# sample points in the domain. remember to set requires_grad!\n", + "pts = poisson_problem.spatial_domain.sample(1000).requires_grad_(True)\n", + "# compute the solution\n", + "solution = solver(pts)\n", + "# compute the residual in the interior\n", + "equation = poisson_problem.conditions[\"interior\"].equation\n", + "residual = solver.compute_residual(pts, equation)\n", + "# simple plot\n", + "with torch.no_grad():\n", + " plt.subplot(1, 2, 1)\n", + " plt.scatter(\n", + " pts.extract(\"x\").flatten(),\n", + " pts.extract(\"y\").flatten(),\n", + " c=solution.extract(\"u\").flatten(),\n", + " )\n", + " plt.colorbar()\n", + " plt.title(\"Solution\")\n", + " plt.subplot(1, 2, 2)\n", + " plt.scatter(\n", + " pts.extract(\"x\").flatten(),\n", + " pts.extract(\"y\").flatten(),\n", + " c=residual.flatten(),\n", + " )\n", + " plt.colorbar()\n", + " plt.tight_layout()\n", + " plt.title(\"Residual\")" + ] + }, + { + "cell_type": "markdown", + "id": "487c1d47", + "metadata": {}, + "source": [ + "## What's Next?\n", + "\n", + "Congratulations on completing the introductory tutorial of **PINA**! Now that you have a solid foundation, here are a few directions you can explore:\n", + "\n", + "1. **Explore Advanced Solvers**: Dive into more advanced solvers like **SAPINN** or **RBAPINN** and experiment with different variations of Physics-Informed Neural Networks.\n", + "2. **Apply PINA to New Problems**: Try solving other types of differential equations or explore inverse problems and parametric problems using the PINA framework.\n", + "3. **Optimize Model Performance**: Use the `Trainer` class to enhance model performance by exploring features like dynamic learning rates, early stopping, and model checkpoints.\n", + "\n", + "4. **...and many more!** — There are countless directions to further explore, from testing on different problems to refining the model architecture!\n", + "\n", + "For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/).\n", + "\n", + "\n", + "### References\n", + "\n", + "[1] *Coscia, Dario, et al. \"Physics-informed neural networks for advanced modeling.\" Journal of Open Source Software, 2023.*\n", + "\n", + "[2] *Hernández-Lobato, José Miguel, and Ryan Adams. \"Probabilistic backpropagation for scalable learning of bayesian neural networks.\" International conference on machine learning, 2015.*\n", + "\n", + "[3] *Gal, Yarin, and Zoubin Ghahramani. \"Dropout as a bayesian approximation: Representing model uncertainty in deep learning.\" International conference on machine learning, 2016.*\n", + "\n", + "[4] *Raissi, Maziar, Paris Perdikaris, and George E. Karniadakis. \"Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations.\" Journal of Computational Physics, 2019.*\n", + "\n", + "[5] *McClenny, Levi D., and Ulisses M. Braga-Neto. \"Self-adaptive physics-informed neural networks.\" Journal of Computational Physics, 2023.*\n", + "\n", + "[6] *Anagnostopoulos, Sokratis J., et al. \"Residual-based attention in physics-informed neural networks.\" Computer Methods in Applied Mechanics and Engineering, 2024.*" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pina", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.21" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/tutorials/tutorial18/tutorial.ipynb b/tutorials/tutorial18/tutorial.ipynb new file mode 100644 index 0000000..dc6a3a7 --- /dev/null +++ b/tutorials/tutorial18/tutorial.ipynb @@ -0,0 +1,443 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "id": "6f71ca5c", + "metadata": {}, + "source": [ + "# Tutorial: Introduction to Solver classes\n", + "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial18/tutorial.ipynb)\n", + "\n", + "In this tutorial, we will explore the Solver classes in PINA, that are the core components for optimizing models. Solvers are designed to manage and execute the optimization process, providing the flexibility to work with various types of neural networks and loss functions. We will show how to use this class to select and implement different solvers, such as Supervised Learning, Physics-Informed Neural Networks (PINNs), and Generative Learning solvers. By the end of this tutorial, you'll be equipped to easily choose and customize solvers for your own tasks, streamlining the model training process.\n", + "\n", + "## Introduction to Solvers\n", + "\n", + "[`Solvers`](https://mathlab.github.io/PINA/_rst/_code.html#solvers) are versatile objects in PINA designed to manage the training and optimization of machine learning models. They handle key components of the learning process, including:\n", + "\n", + "- Loss function minimization \n", + "- Model optimization (optimizer, schedulers)\n", + "- Validation and testing workflows\n", + "\n", + "PINA solvers are built on top of the [PyTorch Lightning `LightningModule`](https://lightning.ai/docs/pytorch/stable/common/lightning_module.html), which provides a structured and scalable training framework. This allows solvers to leverage advanced features such as distributed training, early stopping, and logging — all with minimal setup.\n", + "\n", + "## Solvers Hierarchy: Single and MultiSolver\n", + "\n", + "PINA provides two main abstract interfaces for solvers, depending on whether the training involves a single model or multiple models. These interfaces define the base functionality that all specific solver implementations inherit from.\n", + "\n", + "### 1. [`SingleSolverInterface`](https://mathlab.github.io/PINA/_rst/solver/solver_interface.html)\n", + "\n", + "This is the abstract base class for solvers that train **a single model**, such as in standard supervised learning or physics-informed training. All specific solvers (e.g., `SupervisedSolver`, `PINN`) inherit from this interface.\n", + "\n", + "**Arguments:**\n", + "- `problem` – The problem to be solved.\n", + "- `model` – The neural network model.\n", + "- `optimizer` – Defaults to `torch.optim.Adam` if not provided.\n", + "- `scheduler` – Defaults to `torch.optim.lr_scheduler.ConstantLR`.\n", + "- `weighting` – Optional loss weighting schema., see [here](https://mathlab.github.io/PINA/_rst/_code.html#losses-and-weightings). We weight already for you!\n", + "- `use_lt` – Whether to use LabelTensors as input.\n", + "\n", + "---\n", + "\n", + "### 2. [`MultiSolverInterface`](https://mathlab.github.io/PINA/_rst/solver/multi_solver_interface.html)\n", + "\n", + "This is the abstract base class for solvers involving **multiple models**, such as in GAN architectures or ensemble training strategies. All multi-model solvers (e.g., `DeepEnsemblePINN`, `GAROM`) inherit from this interface.\n", + "\n", + "**Arguments:**\n", + "- `problem` – The problem to be solved.\n", + "- `models` – The model or models used for training.\n", + "- `optimizers` – Defaults to `torch.optim.Adam`.\n", + "- `schedulers` – Defaults to `torch.optim.lr_scheduler.ConstantLR`.\n", + "- `weightings` – Optional loss weighting schema, see [here](https://mathlab.github.io/PINA/_rst/_code.html#losses-and-weightings). We weight already for you!\n", + "- `use_lt` – Whether to use LabelTensors as input.\n", + "\n", + "---\n", + "\n", + "These base classes define the structure and behavior of solvers in PINA, allowing you to create customized training strategies while leveraging PyTorch Lightning's features under the hood. \n", + "\n", + "These classes are used to define the backbone, i.e. setting the problem, the model(s), the optimizer(s) and scheduler(s), but miss a key component the `optimization_cycle` method.\n", + "\n", + "\n", + "## Optimization Cycle\n", + "The `optimization_cycle` method is the core function responsible for computing losses for **all conditions** in a given training batch. Each condition (e.g. initial condition, boundary condition, PDE residual) contributes its own loss, which is tracked and returned in a dictionary. This method should return a dictionary mapping **condition names** to their respective **scalar loss values**.\n", + "\n", + "For supervised learning tasks, where each condition consists of an input-target pair, for example, the `optimization_cycle` may look like this:\n", + "\n", + "```python\n", + "def optimization_cycle(self, batch):\n", + " \"\"\"\n", + " The optimization cycle for Supervised solvers.\n", + " Computes loss for each condition in the batch.\n", + " \"\"\"\n", + " condition_loss = {}\n", + " for condition_name, data in batch:\n", + " condition_loss[condition_name] = self.loss_data(\n", + " input=data[\"input\"], target=data[\"target\"]\n", + " )\n", + " return condition_loss\n", + "```\n", + "In PINA, a **batch** is structured as a list of tuples, where each tuple corresponds to a specific training condition. Each tuple contains:\n", + "\n", + "- The **name of the condition**\n", + "- A **dictionary of data** associated with that condition\n", + "\n", + "for example:\n", + "\n", + "```python\n", + "batch = [\n", + " (\"condition1\", {\"input\": ..., \"target\": ...}),\n", + " (\"condition2\", {\"input\": ..., \"equation\": ...}),\n", + " (\"condition3\", {\"input\": ..., \"target\": ...}),\n", + "]\n", + "```\n", + "\n", + "Fortunately, you don't need to implement the `optimization_cycle` yourself in most cases — PINA already provides default implementations tailored to common solver types. These implementations are available through the solver interfaces and cover various training strategies.\n", + "\n", + "1. [`PINNInterface`](https://mathlab.github.io/PINA/_rst/solver/physics_informed_solver/pinn_interface.html) \n", + " Implements the optimization cycle for **physics-based solvers** (e.g., PDE residual minimization) as well as other useful methods to compute PDE residuals. \n", + " ➤ [View method](https://mathlab.github.io/PINA/_rst/solver/physics_informed_solver/pinn_interface.html#pina.solver.physics_informed_solver.pinn_interface.PINNInterface.optimization_cycle)\n", + "\n", + "2. [`SupervisedSolverInterface`](https://mathlab.github.io/PINA/_rst/solver/supervised_solver/supervised_solver_interface.html) \n", + " Defines the optimization cycle for **supervised learning tasks**, including traditional regression and classification. \n", + " ➤ [View method](https://mathlab.github.io/PINA/_rst/solver/supervised_solver/supervised_solver_interface.html#pina.solver.supervised_solver.supervised_solver_interface.SupervisedSolverInterface.optimization_cycle)\n", + "\n", + "3. [`DeepEnsembleSolverInterface`](https://mathlab.github.io/PINA/_rst/solver/ensemble_solver/ensemble_solver_interface.html) \n", + " Provides the optimization logic for **deep ensemble methods**, commonly used for uncertainty quantification or robustness. \n", + " ➤ [View method](https://mathlab.github.io/PINA/_rst/solver/ensemble_solver/ensemble_solver_interface.html#pina.solver.ensemble_solver.ensemble_solver_interface.DeepEnsembleSolverInterface.optimization_cycle)\n", + "\n", + "These ready-to-use implementations ensure that your solvers are properly structured and compatible with PINA’s training workflow. You can also inherit and override them to fit more specialized needs. They only require, the following arguments:\n", + "**Arguments:**\n", + "- `problem` – The problem to be solved.\n", + "- `loss` - The loss to be minimized\n", + "- `weightings` – Optional loss weighting schema.\n", + "- `use_lt` – Whether to use LabelTensors as input.\n", + "\n", + "## Structure a Solver with Multiple Inheritance:\n", + "\n", + "Thanks to PINA’s modular design, creating a custom solver is straightforward using **multiple inheritance**. You can combine different interfaces to define both the **optimization logic** and the **model structure**.\n", + "\n", + "- **`PINN` Solver**\n", + " - Inherits from: \n", + " - [`PINNInterface`](https://mathlab.github.io/PINA/_rst/solver/physics_informed_solver/pinn_interface.html) → physics-based optimization loop \n", + " - [`SingleSolverInterface`](https://mathlab.github.io/PINA/_rst/solver/solver_interface.html) → training a single model\n", + "\n", + "- **`SupervisedSolver`**\n", + " - Inherits from: \n", + " - [`SupervisedSolverInterface`](https://mathlab.github.io/PINA/_rst/solver/supervised_solver/supervised_solver_interface.html) → data-driven optimization loop \n", + " - [`SingleSolverInterface`](https://mathlab.github.io/PINA/_rst/solver/solver_interface.html) → training a single model\n", + "\n", + "- **`GAROM`** (a variant of GAN)\n", + " - Inherits from: \n", + " - [`SupervisedSolverInterface`](https://mathlab.github.io/PINA/_rst/solver/supervised_solver/supervised_solver_interface.html) → data-driven optimization loop \n", + " - [`MultiSolverInterface`](https://mathlab.github.io/PINA/_rst/solver/multi_solver_interface.html) → training multiple models (e.g., generator and discriminator)\n", + "\n", + "This structure promotes **code reuse** and **extensibility**, allowing you to quickly prototype new solver strategies by reusing core training and optimization logic.\n", + "\n", + "## Let's try to build some solvers!\n", + "\n", + "We will now start building a simple supervised solver in PINA. Let's first import useful modules! " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0981f1e9", + "metadata": {}, + "outputs": [], + "source": [ + "## routine needed to run the notebook on Google Colab\n", + "try:\n", + " import google.colab\n", + " IN_COLAB = True\n", + "except:\n", + " IN_COLAB = False\n", + "if IN_COLAB:\n", + " !pip install \"pina-mathlab[tutorial]\"\n", + "\n", + "import warnings\n", + "import torch\n", + "import matplotlib.pyplot as plt\n", + "\n", + "warnings.filterwarnings(\"ignore\")\n", + "\n", + "from pina import Trainer\n", + "from pina.solver import SingleSolverInterface, SupervisedSolverInterface\n", + "from pina.model import FeedForward\n", + "from pina.problem.zoo import SupervisedProblem" + ] + }, + { + "cell_type": "markdown", + "id": "7b91de38", + "metadata": {}, + "source": [ + "Since we are using only one model for this task, we will inherit from two base classes:\n", + "\n", + "- `SingleSolverInterface`: This ensures we are working with a single model.\n", + "- `SupervisedSolverInterface`: This allows us to use supervised learning strategies for training the model." + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "id": "014bbd86", + "metadata": {}, + "outputs": [], + "source": [ + "class MyFirstSolver(SupervisedSolverInterface, SingleSolverInterface):\n", + " def __init__(\n", + " self,\n", + " problem,\n", + " model,\n", + " loss=None,\n", + " optimizer=None,\n", + " scheduler=None,\n", + " weighting=None,\n", + " use_lt=True,\n", + " ):\n", + " super().__init__(\n", + " model=model,\n", + " problem=problem,\n", + " loss=loss,\n", + " optimizer=optimizer,\n", + " scheduler=scheduler,\n", + " weighting=weighting,\n", + " use_lt=use_lt,\n", + " )" + ] + }, + { + "cell_type": "markdown", + "id": "b1b1e4c4", + "metadata": {}, + "source": [ + "By default, Python follows a specific method resolution order (MRO) when a class inherits from multiple parent classes. This means that the initialization (`__init__`) method is called based on the order of inheritance.\n", + "\n", + "Since we inherit from `SupervisedSolverInterface` first, Python will call the `__init__` method from `SupervisedSolverInterface` (initialize `problem`, `loss`, `weighting` and `use_lt`) before calling the `__init__` method from `SingleSolverInterface` (initialize `model`, `optimizer`, `scheduler`). This allows us to customize the initialization process for our custom solver. \n", + "\n", + "We will learn a very simple problem, try to learn $y=\\sin(x)$." + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "id": "6f25d3a6", + "metadata": {}, + "outputs": [], + "source": [ + "# get the data\n", + "x = torch.linspace(0, torch.pi, 100).view(-1, 1)\n", + "y = torch.sin(x)\n", + "# build the problem\n", + "problem = SupervisedProblem(x, y)\n", + "# build the model\n", + "model = FeedForward(1, 1)" + ] + }, + { + "cell_type": "markdown", + "id": "9f7551bf", + "metadata": {}, + "source": [ + "If we now try to initialize the solver `MyFirstSolver` we will get the following error:\n", + "\n", + "```python\n", + "---------------------------------------------------------------------------\n", + "TypeError Traceback (most recent call last)\n", + "Cell In[41], line 1\n", + "----> 1 MyFirstSolver(problem, model)\n", + "\n", + "TypeError: Can't instantiate abstract class MyFirstSolver with abstract method loss_data\n", + "```\n", + "\n", + "### Data and Physics Loss\n", + "The error above is because in PINA, all solvers must specify how to compute the loss during training. There are two main types of losses that can be computed, depending on the nature of the problem:\n", + "\n", + "1. **`loss_data`**: Computes the **data loss** between the model's output and the true solution. This is typically used in **supervised learning** setups, where we have ground truth data to compare the model's predictions. It expects some `input` (tensor, graph, ...) and a `target` (tensor, graph, ...)\n", + " \n", + "2. **`loss_phys`**: Computes the **physics loss** for **physics-informed solvers** (PINNs). This loss is based on the residuals of the governing equations that model physical systems, enforcing the equations during training. It expects some `samples` (`LabelTensor`) and an `equation` (`Equation`)\n", + "\n", + "Therefore our implementation becomes:" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "336e8060", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "GPU available: True (mps), used: False\n", + "TPU available: False, using: 0 TPU cores\n", + "HPU available: False, using: 0 HPUs\n", + "\n", + " | Name | Type | Params | Mode \n", + "----------------------------------------------------\n", + "0 | _pina_models | ModuleList | 481 | train\n", + "1 | _loss_fn | MSELoss | 0 | train\n", + "----------------------------------------------------\n", + "481 Trainable params\n", + "0 Non-trainable params\n", + "481 Total params\n", + "0.002 Total estimated model params size (MB)\n", + "9 Modules in train mode\n", + "0 Modules in eval mode\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "d6d009cd7efb4c76ba2115f828e46dc8", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00)\n" + ] + } + ], + "source": [ + "# Accessing node features\n", + "print(data.x) # Node features\n", + "\n", + "# Accessing edge list\n", + "print(data.edge_index) # Edge indices\n", + "\n", + "# Applying Graph Convolution (Graph Neural Networks - GCN)\n", + "from torch_geometric.nn import GCNConv\n", + "\n", + "# Define a simple GCN layer\n", + "conv = GCNConv(3, 2) # 3 input features, 2 output features\n", + "out = conv(data.x, data.edge_index)\n", + "print(out) # Output node features after applying GCN" + ] + }, + { + "cell_type": "markdown", + "id": "287a0d4f", + "metadata": {}, + "source": [ + "## PINA Graph\n", + "\n", + "If you've understood Label Tensors and Data in PINA, then you're well on your way to grasping how **PINA Graph** works. Simply put, a **Graph** in PINA is a `Data` object with extra methods for handling label tensors. We highly suggest to use `Graph` instead of `Data` in PINA, expecially when using label tensors." + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "27f5c9ac", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Graph(x=[2, 3], edge_index=[2, 2])\n", + "tensor([[1., 2., 3.],\n", + " [4., 5., 6.]])\n", + "tensor([[0, 1],\n", + " [1, 0]])\n", + "tensor([[-0.0606, 5.7191],\n", + " [-0.0606, 5.7191]], grad_fn=)\n" + ] + } + ], + "source": [ + "# Node features: [2 nodes, 3 features]\n", + "x = torch.tensor([[1, 2, 3], [4, 5, 6]], dtype=torch.float)\n", + "\n", + "# Edge indices: representing a graph with two edges (node 0 to node 1, node 1 to node 0)\n", + "edge_index = torch.tensor([[0, 1], [1, 0]], dtype=torch.long)\n", + "\n", + "# Create a PINA graph object (similar to PyG)\n", + "data = Graph(x=x, edge_index=edge_index)\n", + "\n", + "print(data)\n", + "\n", + "# Accessing node features\n", + "print(data.x) # Node features\n", + "\n", + "# Accessing edge list\n", + "print(data.edge_index) # Edge indices\n", + "\n", + "# Applying Graph Convolution (Graph Neural Networks - GCN)\n", + "from torch_geometric.nn import GCNConv\n", + "\n", + "# Define a simple GCN layer\n", + "conv = GCNConv(3, 2) # 3 input features, 2 output features\n", + "out = conv(data.x, data.edge_index)\n", + "print(out) # Output node features after applying GCN" + ] + }, + { + "cell_type": "markdown", + "id": "6ee7cc14", + "metadata": {}, + "source": [ + "But we can also use labeltensors...." + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "3866a8ae", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Graph(x=[2, 3], edge_index=[2, 2])\n", + "Graph(x=[2, 1], edge_index=[2, 2])\n" + ] + } + ], + "source": [ + "# Node features: [2 nodes, 3 features]\n", + "x = LabelTensor(torch.tensor([[1, 2, 3], [4, 5, 6]], dtype=torch.float),\n", + " [\"a\", \"b\", \"c\"])\n", + "\n", + "# Edge indices: representing a graph with two edges (node 0 to node 1, node 1 to node 0)\n", + "edge_index = torch.tensor([[0, 1], [1, 0]], dtype=torch.long)\n", + "\n", + "# Create a PINA graph object (similar to PyG)\n", + "data = Graph(x=x, edge_index=edge_index)\n", + "\n", + "print(data)\n", + "print(data.extract(attr=\"x\", labels=[\"a\"])) # here we extract 1 feature" + ] + }, + { + "cell_type": "markdown", + "id": "7a2ef072", + "metadata": {}, + "source": [ + "In PINA Conditions, you always need to pass a list of `Graph` or `Data`, see [here]() for details. In case you are loading a PyG dataset remember to put it in this format!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c8edb68f", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Downloading https://deepchemdata.s3-us-west-1.amazonaws.com/datasets/qm7b.mat\n", + "Processing...\n", + "Done!\n" + ] + }, + { + "data": { + "text/plain": [ + "Data(edge_index=[2, 324], edge_attr=[324], y=[1, 14], num_nodes=18)" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from torch_geometric.datasets import QM7b\n", + "\n", + "dataset = QM7b(root=\"./tutorial_logs\").shuffle()\n", + "\n", + "# save the dataset\n", + "input_ = [data for data in dataset]\n", + "input_[0]" + ] + }, + { + "cell_type": "markdown", + "id": "487c1d47", + "metadata": {}, + "source": [ + "## What's Next?\n", + "\n", + "Congratulations on completing the tutorials on the **PINA Data Structures**! You now have a solid foundation in using the different data structures within PINA, such as **Tensors**, **Label Tensors**, and **Graphs**. Here are some exciting next steps you can take to continue your learning journey:\n", + "\n", + "1. **Deep Dive into Label Tensors**: Check the documentation of [`LabelTensor`](https://mathlab.github.io/PINA/_rst/label_tensor.html) to learn more about the available methods.\n", + "\n", + "2. **Working with Graphs in PINA**: In PINA we implement many graph structures, e.g. `KNNGraph`, `RadiusGraph`, .... see [here](https://mathlab.github.io/PINA/_rst/_code.html#graphs-structures) for further details.\n", + "\n", + "3. **...and many more!**: Consider exploring `LabelTensor` for PINNs!\n", + "\n", + "For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/)." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pina", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.21" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/tutorials/tutorial2/tutorial.ipynb b/tutorials/tutorial2/tutorial.ipynb index d0d891c..e93850a 100644 --- a/tutorials/tutorial2/tutorial.ipynb +++ b/tutorials/tutorial2/tutorial.ipynb @@ -5,7 +5,7 @@ "id": "de19422d", "metadata": {}, "source": [ - "# Tutorial: Two dimensional Poisson problem using Extra Features Learning\n", + "# Tutorial: Enhancing PINNs with Extra Features to solve the Poisson Problem\n", "\n", "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial2/tutorial.ipynb)\n", "\n", @@ -29,7 +29,7 @@ "except:\n", " IN_COLAB = False\n", "if IN_COLAB:\n", - " !pip install \"pina-mathlab\"\n", + " !pip install \"pina-mathlab[tutorial]\"\n", "\n", "import torch\n", "import matplotlib.pyplot as plt\n", @@ -66,14 +66,14 @@ "where $D$ is a square domain $[0,1]^2$, and $\\Gamma_i$, with $i=1,...,4$, are the boundaries of the square.\n", "\n", "The Poisson problem is written in **PINA** code as a class. The equations are written as *conditions* that should be satisfied in the corresponding domains. The *solution*\n", - "is the exact solution which will be compared with the predicted one. If interested in how to write problems see [this tutorial](https://mathlab.github.io/PINA/_rst/tutorials/tutorial1/tutorial.html).\n", + "is the exact solution which will be compared with the predicted one. If interested in how to write problems see [this tutorial](https://mathlab.github.io/PINA/_rst/tutorials/tutorial16/tutorial.html).\n", "\n", "We will directly import the problem from `pina.problem.zoo`, which contains a vast list of PINN problems and more." ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "id": "82c24040", "metadata": {}, "outputs": [ @@ -127,7 +127,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "id": "e7d20d6d", "metadata": { "scrolled": true @@ -143,11 +143,18 @@ ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 143.27it/s, v_num=41, g1_loss=0.0148, g2_loss=0.0118, g3_loss=0.0346, g4_loss=0.00393, D_loss=0.206, train_loss=0.271] " - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "38a34ce3c1214e90be1f5e0194d80674", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" ] @@ -304,7 +304,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "id": "ef3ad372", "metadata": {}, "outputs": [ @@ -318,11 +318,18 @@ ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 121.03it/s, v_num=42, g1_loss=7.75e-5, g2_loss=6.85e-5, g3_loss=0.000217, g4_loss=0.000195, D_loss=0.000491, train_loss=0.00105] " - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "62180078584f4dfea97d9dc6f8d20856", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" ] @@ -449,7 +449,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 10, "id": "ae8716e7", "metadata": {}, "outputs": [ @@ -463,11 +463,18 @@ ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 102.62it/s, v_num=43, g1_loss=7.54e-6, g2_loss=2.9e-5, g3_loss=3.65e-5, g4_loss=1.22e-5, D_loss=0.00208, train_loss=0.00217] " - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "3eed1678b6c14cf2a190c248766815c7", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00 ##### ⚠️ ***Before starting:***\n", + "> We assume you are already familiar with the concepts covered in the [Getting started with PINA](https://mathlab.github.io/PINA/_tutorial.html#getting-started-with-pina) tutorials. If not, we strongly recommend reviewing them before exploring this advanced topic.\n", + "\n", + "In this tutorial, we will demonstrate a typical use case of **PINA** for Supervised Learning training. We will cover the basics of training a Supervised Solver with PINA, if you want to go further into PINNs look at our dedicated [tutorials](https://mathlab.github.io/PINA/_tutorial.html#supervised-learning) on the topic.\n", + "\n", + "Let's start by importing the useful modules:" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "0981f1e9", + "metadata": {}, + "outputs": [], + "source": [ + "## routine needed to run the notebook on Google Colab\n", + "try:\n", + " import google.colab\n", + " IN_COLAB = True\n", + "except:\n", + " IN_COLAB = False\n", + "if IN_COLAB:\n", + " !pip install \"pina-mathlab[tutorial]\"\n", + "\n", + "import torch\n", + "import warnings\n", + "\n", + "import matplotlib.pyplot as plt\n", + "\n", + "warnings.filterwarnings(\"ignore\")\n", + "\n", + "from pina import Trainer\n", + "from pina.model import FeedForward\n", + "from pina.domain import CartesianDomain\n", + "from pina.solver import SupervisedSolver\n", + "from pina.adaptive_function import AdaptiveSIREN\n", + "from pina.problem.zoo import SupervisedProblem" + ] + }, + { + "cell_type": "markdown", + "id": "f0c937e6", + "metadata": {}, + "source": [ + "## Building a Neural Implicit Field for a Sphere\n", + "\n", + "In this tutorial, we will construct a **Neural Implicit Field** to learn the **Signed Distance Function (SDF)** of a sphere. The problem is relatively simple: we aim to learn a function $d_\\theta$, parameterized by a neural network, that captures the signed distance to the surface of a sphere.\n", + "\n", + "The function $d_\\theta(\\mathbf{x})$$ should satisfy the following properties:\n", + "\n", + "- $d_\\theta(\\mathbf{x}) = 0$ on the surface of the sphere \n", + "- $d_\\theta(\\mathbf{x}) > 0$ outside the sphere \n", + "- $d_\\theta(\\mathbf{x}) < 0$ inside the sphere \n", + "\n", + "This setup allows us to implicitly represent the geometry of the sphere through the learned function.\n", + "\n", + "### Mathematical Description\n", + "\n", + "We define the signed distance function (SDF) for a sphere centered at the origin with radius $r$ as:\n", + "$d(\\mathbf{x}) = \\|\\mathbf{x}\\| - r$, where $\\mathbf{x} \\in \\mathbb{R}^3$ is a point in 3D space.\n", + "\n", + "Our goal is to approximate this function using a neural network: $d_\\theta(\\mathbf{x}) \\approx d(\\mathbf{x})$ with a Neural Network. Let's start by generating the data for the problem by:\n", + "1. Sample random 3D points within a bounding cube (e.g., $[-1.5, 1.5]^3$).\n", + "2. Compute their ground truth signed distances from a sphere of radius $r$ centered at the origin.\n", + "3. Package this into tensors for training." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "d331c971", + "metadata": {}, + "outputs": [], + "source": [ + "def generate_sdf_data(num_points=1000000, radius=1.0, cube_bound=1.5):\n", + " # Create the 3D cube\n", + " domain = CartesianDomain(\n", + " {\n", + " \"x\": [-cube_bound, cube_bound],\n", + " \"y\": [-cube_bound, cube_bound],\n", + " \"z\": [-cube_bound, cube_bound],\n", + " }\n", + " )\n", + " # Sample random 3D points in cube\n", + " coords = domain.sample(num_points, mode=\"random\").tensor\n", + " # Compute signed distance to the sphere\n", + " sdf = coords.norm(dim=-1, keepdim=True) - radius # ||x|| - r\n", + "\n", + " return coords, sdf" + ] + }, + { + "cell_type": "markdown", + "id": "37f5a35b", + "metadata": {}, + "source": [ + "### Visualizing the Data\n", + "\n", + "To better understand the problem and the nature of the solutions, we can visualize the generated data:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "ee9b1b1a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# --- Generate Data ---\n", + "coords, sdf = generate_sdf_data()\n", + "\n", + "# --- 2D Slice at z ≈ 0 ---\n", + "z_slice_thresh = 0.01 # How close to z=0\n", + "mask_2d = coords[:, 2].abs() < z_slice_thresh\n", + "coords_2d = coords[mask_2d]\n", + "sdf_2d = sdf[mask_2d]\n", + "\n", + "plt.figure(figsize=(6, 6))\n", + "plt.scatter(\n", + " coords_2d[:, 0], coords_2d[:, 1], c=sdf_2d.squeeze(), cmap=\"coolwarm\", s=1\n", + ")\n", + "plt.colorbar(label=\"Signed Distance\")\n", + "plt.title(\"2D Slice of SDF Data (z ≈ 0)\")\n", + "plt.xlabel(\"x\")\n", + "plt.ylabel(\"y\")\n", + "plt.axis(\"equal\")\n", + "plt.grid(True)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "8e1b1ae3", + "metadata": {}, + "source": [ + "## Creating the Problem\n", + "\n", + "The problem we will define is a basic `SupervisedProblem`, where the inputs are the coordinates and the outputs are the corresponding Signed Distance Function (SDF) values.\n", + "\n", + "> **👉 We have a dedicated [tutorial](https://mathlab.github.io/PINA/tutorial16/tutorial.html) to teach how to build a Problem from scratch — have a look if you're interested!**" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "a883f43d", + "metadata": {}, + "outputs": [], + "source": [ + "problem = SupervisedProblem(coords, sdf)" + ] + }, + { + "cell_type": "markdown", + "id": "085b412b", + "metadata": {}, + "source": [ + "## Solving the Problem with Supervised Solver\n", + "\n", + "We will use the `SupervisedSolver` to solve the task. A Supervised Solver in PINA aims to find a mapping between an input \\( x \\) and an output \\( y \\).\n", + "Given a PINA `model` $\\mathcal{M}$, the following loss function is minimized during training:\n", + "\n", + "$$\n", + "\\mathcal{L}_{\\rm{supervised}} = \\frac{1}{N}\\sum_{i=1}^N \\mathcal{l}(y_i, \\mathcal{M}(x_i)),\n", + "$$\n", + "\n", + "where $l$ is a specific loss function, typically the MSE (Mean Squared Error).\n", + "\n", + "### Specify the Loss Function\n", + "By default, the loss function applies a forward pass of the `model` on the input and compares it to the target using the `loss` attribute of `SupervisedSolver`. The [`loss_data`](https://mathlab.github.io/PINA/_rst/solver/supervised.html#pina.solver.supervised.SupervisedSolver.loss_data) function computes the loss for supervised solvers, and it can be overridden by the user to match specific needs (e.g., performing pre-process operations on the input, post-process operations on the output, etc.)." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "65ed2697", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "GPU available: True (mps), used: False\n", + "TPU available: False, using: 0 TPU cores\n", + "HPU available: False, using: 0 HPUs\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "49b972675e8f41b3aa477c28f3cb2349", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import torch\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# --- Generate new Data ---\n", + "coords, sdf = generate_sdf_data()\n", + "\n", + "# --- 2D Slice at z ≈ 0 ---\n", + "z_slice_thresh = 0.01 # How close to z=0\n", + "mask_2d = coords[:, 2].abs() < z_slice_thresh\n", + "coords_2d = coords[mask_2d]\n", + "true_sdf = sdf[mask_2d]\n", + "model_sdf = solver(coords).detach()[mask_2d]\n", + "\n", + "# --- Plot ---\n", + "fig, axes = plt.subplots(1, 2, figsize=(14, 6), sharey=True)\n", + "\n", + "# Create a common color normalization for both subplots\n", + "vmin = min(true_sdf.min(), model_sdf.min())\n", + "vmax = max(true_sdf.max(), model_sdf.max())\n", + "norm = plt.Normalize(vmin=vmin, vmax=vmax)\n", + "\n", + "# Plot the data on both subplots\n", + "for idx, sdf_2d in enumerate([true_sdf, model_sdf]):\n", + " ax = axes[idx]\n", + "\n", + " # Plot the scatter for the SDF values with shared color normalization\n", + " sc = ax.scatter(\n", + " coords_2d[:, 0],\n", + " coords_2d[:, 1],\n", + " c=sdf_2d.squeeze(),\n", + " cmap=\"coolwarm\",\n", + " s=2,\n", + " edgecolors=\"none\",\n", + " norm=norm,\n", + " )\n", + "\n", + " ax.set_title(f\"SDF Slice: {'True' if idx == 0 else 'Model'}\", fontsize=14)\n", + " ax.set_xlabel(\"x\", fontsize=12)\n", + " ax.set_ylabel(\"y\", fontsize=12)\n", + " ax.set_xlim([-1.5, 1.5]) # Set consistent axis limits\n", + " ax.set_ylim([-1.5, 1.5]) # for both plots to have the same scale\n", + " ax.grid(True, linestyle=\"--\", alpha=0.5)\n", + " ax.set_aspect(\"equal\", \"box\") # Make sure the plot is square\n", + "\n", + "# Add a colorbar for the entire figure (shared between both plots)\n", + "fig.colorbar(sc, ax=axes, label=\"Signed Distance\", fraction=0.046, pad=0.04)\n", + "\n", + "# Title and layout adjustments\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "c152bfd1", + "metadata": {}, + "source": [ + "Nice! We can see that the network is correctly learning the signed distance function! Let's now visualize the rendering of the sphere surface learned by the network.\n", + "\n", + "### Visualizing the Sphere Surface\n", + "\n", + "To visualize the surface, we will extract the level set where the SDF equals zero and plot the resulting sphere. This will show how well the network has learned the geometry of the object." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "0f200270", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# --- Generate new Data ---\n", + "coords, sdf = generate_sdf_data()\n", + "\n", + "# Find points where SDF is approximately 0\n", + "zero_sdf_mask = torch.abs(sdf) < 0.01 # Adjust the threshold as needed\n", + "zero_sdf_coords = coords[zero_sdf_mask.flatten()]\n", + "\n", + "# --- 3D Plot ---\n", + "fig = plt.figure(figsize=(10, 8))\n", + "ax = fig.add_subplot(111, projection=\"3d\")\n", + "\n", + "# Plot the black points where SDF is 0 (the surface)\n", + "ax.scatter(\n", + " zero_sdf_coords[:, 0],\n", + " zero_sdf_coords[:, 1],\n", + " zero_sdf_coords[:, 2],\n", + " c=\"deepskyblue\",\n", + " s=2,\n", + " label=\"SDF = 0\",\n", + " alpha=0.7,\n", + ")\n", + "\n", + "# Labels and title\n", + "ax.set_xlabel(\"x\", fontsize=12)\n", + "ax.set_ylabel(\"y\", fontsize=12)\n", + "ax.set_zlabel(\"z\", fontsize=12)\n", + "ax.set_title(\"3D Visualization of the Surface where SDF = 0\", fontsize=14)\n", + "ax.grid(True)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "dd049b6a", + "metadata": {}, + "source": [ + "## What's Next?\n", + "\n", + "Congratulations on completing the introductiory tutorial on supervised solver! Now that you have a solid foundation, here are a few directions you can explore:\n", + "\n", + "\n", + "1. **Experiment with Training Duration & Network Architecture**: Try different training durations and tweak the network architecture to optimize performance.\n", + "\n", + "2. **Explore Other Models in `pina.model`**: Check out other models available in `pina.model` or design your own custom PyTorch module to suit your needs.\n", + "\n", + "3. **... and many more!**: The possibilities are vast! Continue experimenting with advanced configurations, solvers, and other features in PINA.\n", + "\n", + "For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/)." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pina", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.21" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/tutorials/tutorial21/tutorial.ipynb b/tutorials/tutorial21/tutorial.ipynb new file mode 100644 index 0000000..ab23bfb --- /dev/null +++ b/tutorials/tutorial21/tutorial.ipynb @@ -0,0 +1,459 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "id": "6f71ca5c", + "metadata": {}, + "source": [ + "# Tutorial: Introductory Tutorial: Supervised Learning with PINA\n", + "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial20/tutorial.ipynb)\n", + "\n", + "\n", + "> ##### ⚠️ ***Before starting:***\n", + "> We assume you are already familiar with the concepts covered in the [Getting started with PINA](https://mathlab.github.io/PINA/_tutorial.html#getting-started-with-pina) tutorials. If not, we strongly recommend reviewing them before exploring this advanced topic.\n", + "\n", + "In this tutorial, we will demonstrate a typical use case of **PINA** for Neural Operator learning. We will cover the basics of training a Neural Operator with PINA, if you want to go further into the topic look at our dedicated [tutorials](https://mathlab.github.io/PINA/_tutorial.html#neural-operator-learning) on the topic.\n", + "\n", + "Let's start by importing the useful modules:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0981f1e9", + "metadata": {}, + "outputs": [], + "source": [ + "## routine needed to run the notebook on Google Colab\n", + "try:\n", + " import google.colab\n", + " IN_COLAB = True\n", + "except:\n", + " IN_COLAB = False\n", + "if IN_COLAB:\n", + " !pip install \"pina-mathlab[tutorial]\"\n", + "\n", + "import torch\n", + "import matplotlib.pyplot as plt\n", + "import warnings\n", + "\n", + "warnings.filterwarnings(\"ignore\")\n", + "\n", + "from pina import Trainer\n", + "from pina.solver import SupervisedSolver\n", + "from pina.model import KernelNeuralOperator\n", + "from pina.model.block import FourierBlock1D\n", + "from pina.problem.zoo import SupervisedProblem" + ] + }, + { + "cell_type": "markdown", + "id": "f0c937e6", + "metadata": {}, + "source": [ + "## Learning Differential Operators via Neural Operator\n", + "\n", + "In this tutorial, we explore how **Neural Operators** can be used to learn and approximate **differential operators**, which are fundamental in modeling physical and engineering systems governed by differential equations.\n", + "\n", + "### What Are Neural Operators?\n", + "\n", + "**Neural Operators (NOs)** are a class of machine learning models designed to learn mappings *between function spaces*, unlike traditional neural networks which learn mappings between finite-dimensional vectors. In the context of differential equations, this means a Neural Operator can learn the **solution operator**:\n", + "$$\n", + "\\mathcal{G}(a) = u,\n", + "$$\n", + "where $a$ is an input function (e.g., a PDE coefficient) and $u$ is the solution function.\n", + "\n", + "### Why Are Neural Operators Useful?\n", + "\n", + "- **Mesh-free learning**: Neural Operators work directly with functions, allowing them to generalize across different spatial resolutions or grids.\n", + "- **Fast inference**: Once trained, they can predict the solution of a PDE for new input data almost instantaneously.\n", + "- **Physics-aware extensions**: Some variants can incorporate physical laws and constraints into the training process, improving accuracy and generalization.\n", + "\n", + "## Learning the 1D Advection Equation with a Neural Operator\n", + "\n", + "To make things concrete, we'll a Neural Operator to learn the 1D advection equation. We generate synthetic data based on the analytical solution:\n", + "\n", + "$$\n", + "\\frac{\\partial u}{\\partial t} + c \\frac{\\partial u}{\\partial x} = 0\n", + "$$\n", + "\n", + "For a given initial condition $u(x, 0)$, the exact solution at time $t$ is:\n", + "\n", + "$$\n", + "u(x, t) = u(x - ct)\n", + "$$\n", + "\n", + "We use this property to generate training data without solving the PDE numerically.\n", + "\n", + "### Problem Setup\n", + "\n", + "1. **Define the spatial domain**: We work on a 1D grid $x \\in [0, 1]$ with periodic boundary conditions.\n", + "\n", + "2. **Generate initial conditions**: Each initial condition $u(x, 0)$ is created as a sum of sine waves with random amplitudes and phases:\n", + " $$\n", + " u(x, 0) = \\sum_{k=1}^K A_k \\sin(2\\pi k x + \\phi_k)\n", + " $$\n", + " where $A_k \\in [0, 0.5]$ and $\\phi_k \\in [0, 2\\pi]$ are sampled randomly for each sample.\n", + "\n", + "3. **Compute the solution at time $t$**: \n", + " Using the analytical solution, we shift each initial condition by $t=0.5$ ($c=1$), applying periodic wrap-around:\n", + " $$\n", + " u(x, t=0.5) = u(x - 0.5)\n", + " $$\n", + "\n", + "4. **Create input-output pairs**: The input to the model is the function $u(x, 0)$, and the target output is $u(x, 0.5)$. These pairs can be used to train a Neural Operator to learn the underlying differential operator." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "d331c971", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def generate_data(n_samples, x, c=1, t=0.5):\n", + " x = x.T.repeat(n_samples, 1)\n", + " u0 = torch.zeros_like(x)\n", + " ut = torch.zeros_like(x)\n", + " for k in range(1, 4):\n", + " amplitude = torch.rand(n_samples, 1) * 0.5\n", + " phase = torch.rand(n_samples, 1) * 2 * torch.pi\n", + " u0 += amplitude * torch.sin(2 * torch.pi * k * x + phase)\n", + " shifted_x = (x - c * t) % 1.0 # periodic shift\n", + " ut += amplitude * torch.sin(2 * torch.pi * k * shifted_x + phase)\n", + " return u0, ut\n", + "\n", + "\n", + "# define discretization train\n", + "x_train = torch.linspace(0, 1, 100).reshape(-1, 1)\n", + "\n", + "# define input and target\n", + "input, target = generate_data(10000, x_train)\n", + "\n", + "# visualize the data\n", + "plt.plot(x_train, input[0], label=f\"Input u(x, t=0)\")\n", + "plt.plot(x_train, target[0], label=f\"Target u(x, t=0.5)\")\n", + "plt.title(\"Generated 1D Advection Data\")\n", + "plt.xlabel(\"x\")\n", + "plt.legend()\n", + "plt.grid(True)" + ] + }, + { + "cell_type": "markdown", + "id": "1dda7888", + "metadata": {}, + "source": [ + "## Solving the Neural Operator Problem\n", + "\n", + "At their core, **Neural Operators** transform an input function $a$ into an output function $u$. The general structure of a Neural Operator consists of three key components:\n", + "\n", + "

\n", + " \"Neural\n", + "

\n", + "\n", + "\n", + "1. **Encoder**: The encoder maps the input into a specific embedding space.\n", + "\n", + "2. **Processor**: The processor consists of multiple layers performing **function convolutions**, which is the core computational unit in a Neural Operator. \n", + "3. **Decoder**: The decoder maps the processor's output back into the desired output space.\n", + "\n", + "By varying the design and implementation of these three components — encoder, processor, and decoder — different Neural Operators are created, each tailored for specific applications or types of data.\n", + "\n", + "### Types of Neural Operators\n", + "\n", + "Different variants of Neural Operators are designed to solve specific tasks. Some prominent examples include:\n", + "\n", + "- **Fourier Neural Operator (FNO)**: \n", + " The **Fourier Neural Operator** utilizes the **Fourier transform** in the processor to perform global convolutions. This enables the operator to capture long-range dependencies efficiently. FNOs are particularly useful for problems with periodic data or problems where global patterns and interactions are important. \n", + " ➤ [Learn more about FNO](https://mathlab.github.io/PINA/_rst/model/fourier_neural_operator.html).\n", + "\n", + "- **Graph Neural Operator (GNO)**: \n", + " The **Graph Neural Operator** leverages **Graph Neural Networks (GNNs)** to exchange information between nodes, enabling the operator to perform convolutions on unstructured domains, such as graphs or meshes. GNOs are especially useful for problems that naturally involve irregular data, such as graph-based datasets or data on non-Euclidean spaces. \n", + " ➤ [Learn more about GNO](https://mathlab.github.io/PINA/_rst/model/graph_neural_operator.html).\n", + "\n", + "- **Deep Operator Network (DeepONet)**: \n", + " **DeepONet** is a variant of Neural Operators designed to solve operator equations by learning mappings between input and output functions. Unlike other Neural Operators, **DeepONet** does not use the typical encoder-processor-decoder structure. Instead, it uses two distinct neural networks:\n", + " \n", + " 1. **Branch Network**: Takes the **function inputs** (e.g., $u(x)$) and learns a feature map of the input function.\n", + " 2. **Trunk Network**: Takes the **spatial locations** (e.g., $x$) and maps them to the output space.\n", + " \n", + " The output of **DeepONet** is the combination of these two networks' outputs, which together provide the mapping from the input function to the output function. \n", + " ➤ [Learn more about DeepONet](https://mathlab.github.io/PINA/_rst/model/deeponet.html).\n", + "\n", + "In this tutorial we will focus on Neural Operator which follow the Encoder - Processor - Decoder structure, which we call *Kernel* Neural Operator. Implementing kernel neural Operators in PINA is very simple, you just need to use the `KernelNeuralOperator` API.\n", + "\n", + "### KernelNeuralOperator API\n", + "The `KernelNeuralOperator` API requires three parameters: \n", + "\n", + "1. `lifting_operator`: a `torch.nn.Module` apping the input to its hidden dimension (Encoder).\n", + "\n", + "2. `integral_kernels`: a `torch.nn.Module` representing the integral kernels mapping each hidden representation to the next one.\n", + "\n", + "3. `projection_operator`: a `torch.nn.Module` representing the hidden representation to the output function.\n", + "\n", + "To construct the kernel, you can use the Neural Operator Blocks available in PINA (see [here](https://mathlab.github.io/PINA/_rst/_code.html#blocks)) or implement you own one! Let's build a simple FNO using the `FourierBlock1D`. In particular we will:\n", + "\n", + "1. Define the encoder, a simple linear layer mapping the input dimension to the hidden dimension\n", + "2. Define the decoder, two linear layers mapping the hidden dimension to 128 and back to the input dimension\n", + "3. Define the processor, a two layer Fourier block with a specific hidden dimension.\n", + "4. Combine the encoder-processor-decoder using the `KernelNeuralOperator` API to create the `model`.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "ee9b1b1a", + "metadata": {}, + "outputs": [], + "source": [ + "# 1. Define the encoder (simple linear layer 1->64)\n", + "class Encoder(torch.nn.Module):\n", + " def __init__(self, hidden_dim=64):\n", + " super().__init__()\n", + " self.enc = torch.nn.Linear(1, hidden_dim)\n", + "\n", + " def forward(self, x):\n", + " # [B, Nx] -> [B, Nx, 1]\n", + " x = x.unsqueeze(-1)\n", + " # [B, Nx, 1] -> [B, Nx, 64]\n", + " x = self.enc(x)\n", + " # [B, Nx, 1] -> [B, 64, Nx]\n", + " return x.permute(0, 2, 1)\n", + "\n", + "\n", + "# 2. Define the decoder (two linear layer 64->128->1)\n", + "class Decoder(torch.nn.Module):\n", + " def __init__(self, hidden_dim=64):\n", + " super().__init__()\n", + " self.dec = torch.nn.Sequential(\n", + " torch.nn.Linear(hidden_dim, 128),\n", + " torch.nn.ReLU(),\n", + " torch.nn.Linear(128, 1),\n", + " )\n", + "\n", + " def forward(self, x):\n", + " # [B, 64, Nx] -> [B, Nx, 64]\n", + " x = x.permute(0, 2, 1)\n", + " # [B, Nx, 64] -> [B, Nx, 1]\n", + " x = self.dec(x)\n", + " # [B, Nx, 1] -> [B, Nx]\n", + " return x.squeeze(-1)\n", + "\n", + "\n", + "# 3. Define the processor (two FNO blocks of size 64)\n", + "class Processor(torch.nn.Module):\n", + " def __init__(self, hidden_dim=64):\n", + " super().__init__()\n", + " self.proc = torch.nn.Sequential(\n", + " FourierBlock1D(64, 64, 8, torch.nn.ReLU),\n", + " FourierBlock1D(64, 64, 8, torch.nn.ReLU),\n", + " )\n", + "\n", + " def forward(self, x):\n", + " return self.proc(x)\n", + "\n", + "\n", + "# 4. Define the model with KernelNeuralOperator\n", + "model = KernelNeuralOperator(\n", + " lifting_operator=Encoder(),\n", + " integral_kernels=Processor(),\n", + " projection_operator=Decoder(),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "4aa44dd1", + "metadata": {}, + "source": [ + "Done! Let's now solve the Neural Operator problem. The problem we will define is a basic `SupervisedProblem`, and we will use the `SupervisedSolver` to train the Neural Operator.\n", + "\n", + "> **👉 We have a dedicated [tutorial](https://mathlab.github.io/PINA/tutorial16/tutorial.html) to teach how to build a Problem from scratch — have a look if you're interested!**\n", + "\n", + "> **👉 We have a dedicated [tutorial](http://mathlab.github.io/PINA/_rst/tutorials/tutorial18/tutorial.html) for an overview of Solvers in PINA — have a look if you're interested!**" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "304094a0", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "GPU available: True (mps), used: False\n", + "TPU available: False, using: 0 TPU cores\n", + "HPU available: False, using: 0 HPUs\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "2fceec83f20c49d48c5b22540d5a5f1b", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# generate new data\n", + "input, target = generate_data(100, x_train)\n", + "\n", + "# compute the predicted solution\n", + "prediction = solver(input).detach()\n", + "\n", + "# plot\n", + "plt.plot(x_train, input[0], label=f\"Input u(x, t=0)\")\n", + "plt.plot(x_train, target[0], label=f\"Target u(x, t=0.5)\")\n", + "plt.plot(x_train, prediction[0], \"--r\", label=f\"NO prediction u(x, t=0.5)\")\n", + "plt.title(\"Generated 1D Advection Data\")\n", + "plt.xlabel(\"x\")\n", + "plt.legend()\n", + "plt.grid(True)" + ] + }, + { + "cell_type": "markdown", + "id": "c152bfd1", + "metadata": {}, + "source": [ + "Nice! We can see that the network is correctly learning the solution operator and it was very simple!\n", + "\n", + "## What's Next?\n", + "\n", + "Congratulations on completing the introductory tutorial on Neural Operators! Now that you have a solid foundation, here are a few directions you can explore:\n", + "\n", + "1. **Experiment with Training Duration & Network Architecture** — Try different training durations and tweak the network architecture to optimize performance. Choose different integral kernels and see how the results vary.\n", + "\n", + "2. **Explore Other Models in `pina.model`** — Check out other models available in `pina.model` or design your own custom PyTorch module to suit your needs. What about trying a `DeepONet`?\n", + "\n", + "3. **...and many more!** — The possibilities are vast! Continue experimenting with advanced configurations, solvers, and features in PINA. For example, consider incorporating physics-informed terms during training to enhance model generalization.\n", + "\n", + "For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/)." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pina", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.21" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/tutorials/tutorial3/tutorial.ipynb b/tutorials/tutorial3/tutorial.ipynb index 3ef328e..f02f5a0 100644 --- a/tutorials/tutorial3/tutorial.ipynb +++ b/tutorials/tutorial3/tutorial.ipynb @@ -5,11 +5,11 @@ "id": "6a739a84", "metadata": {}, "source": [ - "# Tutorial: Two dimensional Wave problem with hard constraint\n", + "# Tutorial: Applying Hard Constraints in PINNs to solve the Wave Problem\n", "\n", "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial3/tutorial.ipynb)\n", "\n", - "In this tutorial we present how to solve the wave equation using hard constraint PINNs. For doing so we will build a costum `torch` model and pass it to the `PINN` solver.\n", + "In this tutorial, we will present how to solve the wave equation using **hard constraint Physics-Informed Neural Networks (PINNs)**. To achieve this, we will build a custom `torch` model and pass it to the **PINN solver**.\n", "\n", "First of all, some useful imports." ] @@ -29,7 +29,7 @@ "except:\n", " IN_COLAB = False\n", "if IN_COLAB:\n", - " !pip install \"pina-mathlab\"\n", + " !pip install \"pina-mathlab[tutorial]\"\n", "\n", "import torch\n", "import matplotlib.pyplot as plt\n", @@ -51,15 +51,9 @@ "id": "2316f24e", "metadata": {}, "source": [ - "## The problem definition " - ] - }, - { - "cell_type": "markdown", - "id": "bc2bbf62", - "metadata": {}, - "source": [ - "The problem is written in the following form:\n", + "## The problem definition \n", + "\n", + "The problem is described by the following system of partial differential equations (PDEs):\n", "\n", "\\begin{equation}\n", "\\begin{cases}\n", @@ -69,15 +63,11 @@ "\\end{cases}\n", "\\end{equation}\n", "\n", - "where $D$ is a squared domain $[0,1]^2$, and $\\Gamma_i$, with $i=1,...,4$, are the boundaries of the square, and the velocity in the standard wave equation is fixed to one." - ] - }, - { - "cell_type": "markdown", - "id": "cbc50741", - "metadata": {}, - "source": [ - "Now, the wave problem is written in PINA code as a class, inheriting from `SpatialProblem` and `TimeDependentProblem` since we deal with spatial, and time dependent variables. The equations are written as `conditions` that should be satisfied in the corresponding domains. `solution` is the exact solution which will be compared with the predicted one." + "Where:\n", + "\n", + "- $D$ is a square domain $[0, 1]^2$.\n", + "- $\\Gamma_i$, where $i = 1, \\dots, 4$, are the boundaries of the square where Dirichlet conditions are applied.\n", + "- The velocity in the standard wave equation is fixed to $1$." ] }, { @@ -144,19 +134,15 @@ "id": "03557e0c-1f82-4dad-b611-5d33fddfd0ef", "metadata": {}, "source": [ - "## Hard Constraint Model" - ] - }, - { - "cell_type": "markdown", - "id": "356fe363", - "metadata": {}, - "source": [ - "After the problem, a **torch** model is needed to solve the PINN. Usually, many models are already implemented in **PINA**, but the user has the possibility to build his/her own model in `torch`. The hard constraint we impose is on the boundary of the spatial domain. Specifically, our solution is written as:\n", + "## Hard Constraint Model\n", + "\n", + "Once the problem is defined, a **torch** model is needed to solve the PINN. While **PINA** provides several pre-implemented models, users have the option to build their own custom model using **torch**. The hard constraint we impose is on the boundary of the spatial domain. Specifically, the solution is written as:\n", "\n", "$$ u_{\\rm{pinn}} = xy(1-x)(1-y)\\cdot NN(x, y, t), $$\n", "\n", - "where $NN$ is the neural net output. This neural network takes as input the coordinates (in this case $x$, $y$ and $t$) and provides the unknown field $u$. By construction, it is zero on the boundaries. The residuals of the equations are evaluated at several sampling points (which the user can manipulate using the method `discretise_domain`) and the loss minimized by the neural network is the sum of the residuals." + "where $NN$ represents the neural network output. This neural network takes the spatial coordinates $x$, $y$, and time $t$ as input and provides the unknown field $u$. By construction, the solution is zero at the boundaries.\n", + "\n", + "The residuals of the equations are evaluated at several sampling points (which the user can manipulate using the `discretise_domain` method). The loss function minimized by the neural network is the sum of the residuals." ] }, { @@ -195,15 +181,8 @@ "id": "f79fc901-4720-4fac-8b72-84ac5f7d2ec3", "metadata": {}, "source": [ - "## Train and Inference" - ] - }, - { - "cell_type": "markdown", - "id": "b465bebd", - "metadata": {}, - "source": [ - "In this tutorial, the neural network is trained for 1000 epochs with a learning rate of 0.001 (default in `PINN`). As always, we will log using `Tensorboard`." + "## Train and Inference\n", + "In this tutorial, the neural network is trained for 1000 epochs with a learning rate of 0.001 (default in `PINN`)." ] }, { @@ -222,11 +201,18 @@ ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 37.78it/s, v_num=2, g1_loss=0.000, g2_loss=0.000, g3_loss=0.000, g4_loss=0.000, initial_loss=0.0711, D_loss=0.0291, train_loss=0.100]" - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "bd87021d986a45c8bf0dc24c20c2e094", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" + "" ] }, "execution_count": 5, @@ -293,7 +272,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -318,7 +297,7 @@ "id": "c2a5c405", "metadata": {}, "source": [ - "Notice that the loss on the boundaries of the spatial domain is exactly zero, as expected! After the training is completed one can now plot some results using the `matplotlib`. We plot the predicted output on the left side, the true solution at the center and the difference on the right side using the `plot_solution` function." + "Notice that the loss on the boundaries of the spatial domain is exactly zero, as expected! Once the training is completed, we can plot the results using `matplotlib`. We will display the predicted output on the left side, the true solution in the center, and the difference between them on the right side using the `plot_solution` function." ] }, { @@ -375,7 +354,7 @@ "outputs": [ { "data": { - "image/png": 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nWtmm69GQUo/POspFwzoNL/W3pB73tE+l7i/tj6zr0CH5QA5uTxeIwnGm/cxrOu3wKVhfe+21At3XmcZap8guyPSn//vf/8w0o9kfI5q//OUvWZdccklWlSpVskqWLJnVuHHjrGHDhmXt378/Yrk1a9aYKUjLli2bVaZMmazLL788a/ny5VGfV/apZZ988sms2rVrm/VfdNFFZspcneo7+3Tf//rXv7KaN2+elZaWFjEVbbSpXw8ePGimU61Vq1ZW8eLFzRSpOmVu+BSpuU0FG22qcgDwgmjTcutnafbjg0OnCL///vuzqlataj679XP822+/jfoZqJ+rI0aMyDrjjDPMFON6H53eeuLEiVmZmZm5bpMeH2655ZasevXqmc/56tWrZ1199dXmsz6ez+1o27Z69WozVbZulz7OpEmTQsdNnbbbkZGRYY6LOrW23uYcZ3I7Ps2bNy/r3HPPNdtduXLlrF69ekVM0a50W3T68NymMgeAeFxzzTVZpUqVyjp8+HCuy9x2223m83LPnj3ms04/c/RzU79b161b13x2XXzxxVlffPFF6D66rB4rmjZtaj67KlSoYD4///73v+dY/zPPPGOW08eoUaNG1p133pm1d+/eiGWifQ/fvXt3Vo8ePcxxpVKlSlm///3vs7766quI7+/qxIkTWX/4wx+yqlWrllWkSJEcn5nPP/98Vps2bbJKly5tPrdbtmyZdd9992Xt2LEjz33nfP46F92PderUMceeWbNmZR09ejTHfaI9j9x+S+X2+6Egx8nw1ymaTZs2ZfXp0yerZs2aZr/rbyTd7tdffz3f34W5Hcveeustsx26H8uXL5/Vrl27rL/97W8Ry3z++edZN9xwQ+g3nz733/zmN1lLlizJZS8j6Iro/+SMrAAAAAAAAIDko+cUAAAAAAAAXEM4BQAAAAAAANcQTgEAAAAAAMA74ZRO4akz4NSqVcvMlqBTi+Zn2bJlct5550nJkiXNbA8vvfRSvNsLAJ6hM6ToLFylSpUyM0Hq1Mt50VlemjZtapbXWVXefffdiNu1ReCoUaPk9NNPl9KlS5tpmXWWmXA//vij9OrVy8yEorNR6mxj2afx/e9//ysXX3yxeZy6devmOwNmsnA8AQB3jid6XBg8eLDUqVPHHE90hjWdvdjLOKYAQHKOKfv27ZNBgwaZ3yD6eXnWWWflOK44HnvsMfMZrDMjJz2c0ukrdapMfUIFsXnzZunevbuZzlmn7dSN1KknddpNAPCrefPmydChQ2X06NGyZs0a87mpUxpHm/ZYLV++3Ewtr2HS559/Ltdff725fPXVV6FlNER6+umnzQ+IlStXymmnnWbWefTo0dAyGkytW7dOFi9ebKZZ1i/rAwcODN1+4MABM31y/fr1ZfXq1fLEE0/ImDFj5Pnnn5dU43gCAO4cT3R9CxYskFdffVXWr19vPk81rNJp672KYwoAJP6YkpmZKVdeeaVs2bJFXn/9ddm4caPMmDFDateunWPZTz/9VP7yl7/IOeecI3EpzFR/evc33ngjz2V0as7s003ffPPNZmppAPArnVI3fErgkydPmunsx48fH3V5nVo3+9TCOg2zTpWsTp06ZaYADp8meN++fWZqXmfq3q+//jrHNMD//ve/zVTK27dvN38/++yzZgrmY8eOhZa5//77s5o0aZLlJo4nAJCa44nSz9KxY8dGLHPeeedlPfjgg1l+wDEFABJzTHnuueeyGjVqlJWZmZmVl4MHD2adeeaZWYsXL8669NJLs+6+++6sWKVJkq1YscIMPQmnyVxeZV7Hjh0zF8epU6fMUJUqVaqYEjEA/qLfIw8ePGhK8YsWja8VnlYPabKfzG3M/vmjZa16yU63Q6uSRowYEbpOn5d+FupnYjR6vZ7FyP5Z6QxL0DO8GRkZEZ+nFSpUMKW4et+ePXuaf3UoX9u2bUPL6PL62Fpp9etf/9osc8kll0iJEiUiHmfChAmyd+9eqVSpktiK4wmAVBxTkn08ieWYkozjibrwwgtNldTvfvc7s590eNs333wjkydPlqDgmALAD79Rkn1M0WNFhw4dzLC+f/3rX1KtWjW59dZb5f7775dixYqFltPbtRpV1/XnP/9Z4pH0cEp/TNWoUSPiOv1bh5b89NNPZpx7duPHj5eHH3442ZsGwDJbt241/S/i+dCvW+802bP7lCRL2bJlc/Ru0nJYHRKX3Z49e+TkyZNRP/s2bNgQ02elXu/c7lyX1zLVq1ePuD0tLU0qV64csUzDhg1zrMO5zeZwiuMJgGQfU/R4Uq/+abJ7V/KOJ7EcU5JxPFFTp041Q751/+hxQn+c6DANPXkRFBxTAKTiN0q9eqfJ7iT+Rkn2MeW7776TpUuXmtYh2mfq22+/lbvuukuOHz9uHkPNnTvXDBHUYX2FkfRwKh6a5IWf8dm/f7/Uq1fPvCm0yW92X25tluItBBCPlnXXR71evwhqY+5y5crFtV49C6DB1MJPasppZRM/CenhQ6ek6wUZOT6DolVNwRvHkw9XVZOyebxXFh1umqItBBCrLqdF/wLtOHTolFzSbndcxxQ9nmgw9eGq6lK2bHIqYQ4dypJL2u1y9Zii4dQnn3xizohrD0LtT6hnvbU6IHs1EfI/plxWtY+kFf2lIhmAP5w4lSnL9rxSqN8oGkwtW5ncY8pl7ZN3TNEKUT35rf1ptVKqTZs2sn37dtO3VsMpfdy7777b9LvVButWh1M1a9aUnTt3Rlynf+uOi3ZGIq+hMnqfaOFU2XKJ/zEKIPGi/f83XGFL4jWYSubnQW6fQdlVrVrVfHhH++zTz8RYPiud5Z1/9TqdKSN8mdatW4eWyd7M8MSJE2bIQfh6oj1O+GPYKpHHk7L5vFdKFbHy3A0AnZVNWshVZb/Od7nCHFP0R0TyjienCnxMScbxRKuCHnjgAXnjjTfMEAylzWu1KfjEiRMDE04l8piiwRThFOBfhf2N4uVjyumnny7FixePGMLXrFkzU33qDBPU3x8686lDq7P0pMczzzxjhkKH3zcvSU91dHzikiVLIq7TVE2vT4Qv0usmZD0Aki8o/3/Vfk56ViH8s0/POujfuX325fdZqUPx9KARvoxWnGkvKWcZ/VenetWDhEPLcPWxtTeVs4weLLQUN/xxmjRpYvWQvlQcTxzvHmqe0PUBgE3HE/3810v2/in640HXHRSpOqYAgJePKRdddJEZyhd+fNAehRpa6fo6deokX375pTnB4Vy0/60OA9T/LmgwFVc4pWMZnQd1mvTqf6enp4fKXfv06RNa/o477jDjFO+77z4zjvHZZ5+Vv//97zJkyJBYHxoAPEPL/rV/x8svv2ym6b7zzjvNNNf9+vUzt+vnZHgzQi2H1Wm9n3zySfNZqWPEP/vsMzO1t3PGRpu0aoNBHYahBwFdhw7B0CnCnbMY3bp1kwEDBsiqVavk448/NvfXZum6nNIGhnog0SnG161bZ6aTfeqpp3I0z00FjicA4hWkEDnRxxM9s37ppZfKsGHDTCN0/ex96aWX5JVXXjETZ3gVxxQASPwxRW/XURh6bNFQ6p133pFHH33UDAVXOuSxRYsWEZfTTjvNTBSh/x2LmMct6MHt8ssvj3hyqm/fvubA9sMPP4QOAs7Zfn0C+kGvP4C0kdjMmTPNbBiFFZQqDMBP9P+3reptFb+7+eabZffu3TJq1ChT9qpD7/THgtOAUD8nw89a68xJc+bMkZEjR5rhFmeeeaaZWSn8Q12/QOvBQ5vYaoVUx44dzTrDx3fPnj3b/ADRsxi6/h49esjTTz8dMcPfokWLzAFFz5xoea9uo64z1Ww6ngTxBy+A4B5PtHmt/vjQM9v6o0P7Tj3yyCMmsPEqG48pAOD1Y0rdunVl4cKF5rNSh4DXrl3bBFU6W1+iFcnSeQctp0NX9AeVNh10xlESTAHelT2civb/8Vg49//oq1pJGc996OAp6dhiR9zbB3s475U1X9eI+l4hnAK8JVrvKf3MPq/5zrg+s/P7jEiEwmwf7OK8XzpXv52eU4BPG6K/t2tmoX+jfLYuuceUtmf745hCJ3EAKUe4DBsRTAEAAADu8GQ4xQ9bAAAAECoDAOAPngynAHgfITNswg9cAAAAwD2eC6f4QQsAAAAH4TIAAN7nuXAKgH8QNsMG/LAFAAAA3OWpcOrLrc3c3gQAgI8QTAH+wP+XAQDwNk+FUwD8h+opAAAAAAg2wikAQCBRaQH4C/+fBgDAuwinALiOIbsAAAAAEFyEUwCAwFl0uKnbmwAgCaieAgDAmwinAAAAAAAA4BrCKQAAAPgGlZEAAHgP4RQAAAAAAABcQzgFAAAAAAAA16S599AAAAAAACRWZtM64jUlNmxzexMAVxFOAQAA1y3d470+QVdU3eD2JgBAYHgxcErG8yPEgl8RTgEAgKTxYuiU6OdGiAUABef3ECrZ+4fwCl5FOIXA+eveC2Navnel5UnbFgDwCz+HUMneN4RXAIKMMCo1+5PQCrYjnILvwyU3H49gC4AfEUQlf38SWAHwG0Ioe/Y/QRVsRDiFQAdPtjwfQiwAtiKIsmO/E1YB8CICKTsRVMFGhFNwjd+CqETvCwIrAG4hkLL7NSGoAmAjgihvYhggbEE4haQhfErs/iOsApBohFD+et0IrQCkGoGUf1FdhVQjnELCEEalbv8SVAEoDEIpf6K6CkAqEEgF9zUnpEIyEU4hLgRR7iKoAhArAqlgvt6EVAAShVAKVFMhmQinUGAEUna/LoRUAKIhlAo2qqkAFBahFKKhmgqJRjiFXBFGeQvVVADCEUohO6qpAMSCUAoFQUiFRCGcQgQCKX+gmgoILkIp5IeQCkBeCKUQD0IqFBbhFAikfIyQCggOQinE854hoALgIJRCot5HBFSIB+FUQBFIBe/1JqAC/IlQCoVBFRUARTCFRKKKCvEgnAoQAqlgo4oK8B+CKSQKVVRAMBFKIZmookIsCKd8jkAK2RFSAd5HKIVkoIoKCBaCKaQCVVQoqKIFXhKeCyAIppAX3h+ANxFMIdl4jwH+DwsIppBqvOeQHyqnfISwAQD8i8AAqUQVFeBPBARwE8P8kBcqp3yAKinEi/cN4A0EU3AL7z3APwimYAMq95AbwikPI5RCIvAeAuxGOAC38R4EvI8wALbhPYnsGNbnUQQKSPT7iQbpgH0IBWALhvkB3kUIkNP+xiVdedwKm4658ri2YpgfwhFOeQyhFAAEA8FUTuszaqT8MZvV3Jnyx7T9fUlABXhHUIMpt8KnwmxXUIMrZvODg3DKIwilkGxUTwH2CGow5Ub4VJhtCmpwRUAFeEOQgilbw6jCPoegBlYIJsIpixFIIdUIqAD3BSWYsjGISsRzCEpgRUAF2M3PwZQfgqiCClJgxRA/EE5ZhkAKAILLr8GUH4Kowj5XP4ZWBFSAnfwWTAUpjIpnf/gprCKgCjbCKUsQSsEWVE8B7vBbMBWkQCrW/eHHoAqAHfwQTBFGxb+//BBUEVAFF+GUBQimYBsCKiC1/BBMEUYFM6iiegqwh5eDKQKpxPBbUIVgIZxyEaGUPRalN4n4u0u9jRJ0BFQA8kMglbh96OWQioAKQLwIpZK/b70YUlE9FUyEUy4glEpdyJSq9RBmAQhS1RShVOJ5vZqKgCq5pk2bJk888YRkZGRIq1atZOrUqdKuXbtcl3/ttdfkoYceki1btsiZZ54pEyZMkKuuuip0e1ZWlowePVpmzJgh+/btk4suukiee+45syy8yWtVU4RSqePVaioCquAhnEoxgim7Qqhkb4/XQyuqp4Dk8lIwRSCVOl4PqpBY8+bNk6FDh8r06dOlffv2MmXKFOnatats3LhRqlevnmP55cuXyy233CLjx4+Xq6++WubMmSPXX3+9rFmzRlq0aGGWefzxx+Xpp5+Wl19+WRo2bGiCLF3n119/LaVKlXLhWSIIwRSBlPu8XE0F/yvq9gYECcFU/MFP9otXeHW7w/G+BYIdTGlQQjDlHi/tf6+8p71m0qRJMmDAAOnXr580b97chFRlypSRWbNmRV3+qaeekm7dusmwYcOkWbNmMm7cODnvvPPkmWeeCVVNacA1cuRIue666+Scc86RV155RXbs2CFvvvlmip8dghBMaSBCMGUXr7wmXnh/I3GonEoRfuAXnFdDnFifm9erqgD4+0e8VwKRoPBDbyrELjMzU1avXi0jRowIXVe0aFHp3LmzrFixIup99HqttAqnVVFO8LR582YzPFDX4ahQoYKpytL79uzZM2nPB8HihfAj6Kikgk0Ip1KAYCrYgVRuCKoA2IhQym62h1T0niq4AwcORPxdsmRJcwm3Z88eOXnypNSoEfn/S/17w4bo+1mDp2jL6/XO7c51uS0Db7C5qoRgyltsDqnoPRUchFNJRjCVuyAGUvntC1tDKnpPAcGomiKY8g7bQyqvW3S4qZQqkpyvyUcPnxCRnVK3bt2I67VB+ZgxY5LymPAfW4MpQilv09fPxoAKwUA4lUQEUzkRSOWNairA32wNpgilvEtfO9sCKqqnCmbr1q1Svnz50N/Zq6ZU1apVpVixYrJzZ+RrrH/XrFkz6nr1+ryWd/7V604//fSIZVq3bl3IZ4UgI5jyBxsDKqqngoGG6ElCMBXJyw3B3WLb/uI9DfgTwZT38Rp6kwZT4Zdo4VSJEiWkTZs2smTJktB1p06dMn936NAh6nr1+vDl1eLFi0PL6+x8GlCFL6NDDFeuXJnrOmEXG6umCKb8xSsN0xGfadOmSYMGDczsrNpvcNWqVbku+9JLL0mRIkUiLtFmdV2/fr1ce+21pofhaaedJueff76kp6fHtF2EU0nAj/hfEEoVDvsP8A8bq6YINfzDttfSxve7V2lz8xkzZsjLL79svvzfeeedcvjwYTN7n+rTp09Ew/S7775bFixYIE8++aTpS6VDBT/77DMZPHiwuV1/WNxzzz3y5z//Wd566y358ssvzTpq1aol119/vWvPE95EiOFvNr22NoayXjRv3jxzXNGh5GvWrJFWrVqZSTN27dqV6330BMoPP/wQunz//fcRt2/atEk6duwoTZs2lWXLlsl///tfeeihh6KGWHlhWF+CEUzZV/Hjl31qwzA/ek8B/mBbkIHEoA+VP918882ye/duGTVqlGlYrkPvNHxyGprrmWmdwc9x4YUXypw5c2TkyJHywAMPyJlnnmlm6mvRokVomfvuu88EXAMHDpR9+/aZHxW6zlh/SCDYP9BtCi4QrGF+iN+kSZNkwIABoRMc06dPl3feeUdmzZolw4cPj3ofPamR21By9eCDD8pVV10ljz/+eOi6xo0bx7xtVE4hYajySS72L+BdNlWREEz5ny2vsU3ve6/Tqic9U33s2DEz/E6HYTj0LLUOuwh30003ycaNG83yX331lfnRkP2HxtixY03YdfToUXnvvffkrLPOStnzgfcRTAWLLRVyNoWzXpSZmSmrV6+Wzp07h67Tkxv694oVK3K936FDh6R+/fpmIo/rrrtO1q1bFzHUXMMtPYZoBVb16tXNMUpPisSKcCqBglo1RWiSWuxvAPEGFraEFkg+Xm/Af2z4YW5LSAF38Nrb68CBAxEXPTmR3Z49e+TkyZOhyluH/q0nK6Jp0qSJqar617/+Ja+++qoJo7RCd9u2nxvU63BADa8ee+wx6datmyxatEh+/etfyw033CAffPBBTM+BYX0JErRginAkuEP9GNoHeA8hRXC5PZsfM/cB/kEwARuG+Xlx5r43D7aSUlnFk7Luo4eO6y9DU9UUTntKac/BwtKJMsIny9BgqlmzZvKXv/xFxo0bZ8IqpRVVQ4YMMf+tw8+XL19uhgxeeumlBX4swinEjGDKvtfChn5UAOwc2kQwBbcDKgDeRzAFmwIq5LR161bTuNwRbQbYqlWrSrFixWTnzsjvBPp3Xj2lwhUvXlzOPfdc+fbbb0PrTEtLk+bNm0cspwHWRx99JLEgnEqAoFRNEUrZy5aG6QDsQjAFGwIqqqcAbw/p83MwdbB+kaQ/Rrnvs8SP3AyovFg9lWzly5ePCKeiKVGihLRp00aWLFkSmp1VK5/0b2dG1/zosECd5dXpZajrPP/8802fw3DffPON6VMVC8KpQiKYgi0IqAD7uFk15ddg6sSOMil5nLRaR8RvqKACEORgKhVBVCyP64fQigoq7xk6dKj07dtX2rZtK+3atZMpU6aY2Vud2fv69OkjtWvXlvHjx5u/dfKMCy64QM444wwzu+sTTzxhJui4/fbbQ+scNmyYmVn2kksukcsvv9zM/vr222+bCTtiQUP0QghCMEXzbQT1vZ8qP/74o/Tq1cuc6ahYsaL079/fNBXMi86sNGjQIKlSpYqULVtWevTokaM8V6cW7969u5QpU8bMmqEHjRMnTkQsoweM8847z5T96gEn+2xPelDSMyHlypUz69AzLNnPisBOfgmmNIjKfgnCY/vxveH28FbAy9yqmvJyMKWBUPaLbbywjTa/T2yYIMCLbr75Zpk4caKMGjXK9IZau3atCZOcJun6G+KHH34ILb93714ZMGCAGaan1VLabF37SYUP49MG6Npf6vHHH5eWLVvKzJkz5R//+Id07Ngxpm2jcgq5IpTyHqqnvEeDKT0ALF68WI4fP27OWgwcOFDmzJmT63202aBO2fraa69JhQoVTBmuzojx8ccfh8ptNZjSseN68ND161kQHSP+6KOPmmU2b95slrnjjjtk9uzZppxXz4CcfvrpZhpYpTNsaAimAZUGWw888IB06dJFvv76aznttNNStIcQlGDKC+FPtG30YoUVFVQA/BhMeTXcye05eKmyigoqbxk8eHCuw/iyVztNnjzZXPLzu9/9zlwKg3AqTn6uHCGU8jYCKu9Yv369OVPx6aefmtJaNXXqVHNWQs9o1KpVK8d99u/fLy+88IIJr6644gpz3YsvvmjOZnzyySem7FancNUA6b333jNnQfSsiM6mcf/995tZO3RsuJ7daNiwoTz55JMRTQv14OOEU7pt4bSySiuoVq9ebcp2YV+liNeCKS8EUrE8By8FVW4EVPSeArzBK8GUH8IoPwVVbgRU9J7yF4b1IQLBlD/wOiaHlrGGX44dK9wBeMWKFWYonxNMqc6dO0vRokVl5cqVUe+jwZBWWOlyjqZNm0q9evXM+pz1akmtU56rNHDSbV63bl1omfB1OMs464hGgzFVuXLluJ8zkscrwZTfhsl5+bl55T0DIHW8EEx5eQic35+zF94/sBeVU3Hwa9UUgYa/JLuCSv9/0LvScrHJ3H3tpeSJ4glf77FDx0XkDalbt27E9aNHjzaVSPHKyMgwlUjhdCpWDX/0ttzuo5VPGmqF0yDKuY/+Gx5MObc7t+W1jAZYP/30k5QuXTriNp3J45577pGLLrpIWrRoEfdzRnBDBq8ENol+vrZXUzHED7BbKvvq2B4seCGcSTYvVFMxxA/xIpyCQTAF5G/r1q0RU7RqI/Fohg8fLhMmTMh3SJ+XaO+pr776ygz9g11D+mwOpoIWSHl12F8qAyqG9gGIBYFU/vvGxpCKgArxIJwKeNUUoZS/0X8qsTSYCg+ncnPvvffKbbfdlucyjRo1Mg3Ld+3aFXG9Nh7XGfz0tmj0+szMTDOVa3j1lM7W59xH/121alXE/ZzZ/MKXyT7Dn/6tzy971ZQ2TJw/f758+OGHUqcOM6Mgf4RS3q6mAhA8tlVNEUr5I6RKBfpO+Qc9pwKMYCoYeJ1Tr1q1aqYPVF4XHZrXoUMHEzJpHynH0qVLzRC69u3bR113mzZtzKx7OrueY+PGjWbaV12f0n+//PLLiOBLZwPU4MmZ9lWXCV+Hs4yzDpWVlWWCqTfeeMNslzZQh11sq5ryUr8lN9m4n2x7LwFI3ZA+m4Ipr/RWspFt+86m9xW8gXAqoGEFgQXgPp0hr1u3bjJgwABT6fTxxx+bMKhnz56hmfq2b99uwiynEqpChQrSv39/GTp0qLz//vsm2OrXr58JlXSmPtWlSxcTQvXu3Vu++OILWbhwoYwcOdIMzXOGIt5xxx3y3XffyX333ScbNmyQZ599Vv7+97/LkCFDQtuny7/66qtmZsBy5cqZPlV60Z5UcJ9NYYKNYYsX2LbfUvWecmMmSwB2sy1Y8TKb9iMBFWJBOBWwIX2EUsGUrNfdD/+fcNvs2bNN+NSpUye56qqrpGPHjvL888+HbteZ+bQy6siRX4YBTZ48Wa6++mrp0aOHXHLJJWaI3j//+c/Q7cWKFTPD8PRfDa1++9vfSp8+fWTs2LGhZbQK6p133jHVUq1atZInn3xSZs6caWbsczz33HNmhr7LLrtMTj/99NBl3rx5Kdk3XhWkH962hStexT4EEOTwwKYwxS+CFvalcuIAJA89pwKEYAqwj87Mp5VJuWnQoIEZXheuVKlSMm3aNHPJTf369eXdd9/N87E1dPr8889zvT3748IeNlRNEaj4sx8Vs/cBweF2MBWk8CTI/ahojo6CIpwKSIVI0IOpQ5srJGQ9ZRvuF6+iOTqARCCUSv7+JaAC4PdKEIKp1O9vAirYjnAqAIIUTCUqhIpl/V4OrAB4b0ifm1VTBFPBqqJK9v9Xrqi6we3NAALLzaopgqngVlEBeaHnlM/5PZjSsCj8EtRtcPP94PWqQsBLCKaCxc2eXjYMHQXgL0Hrg2Qrt16DZAeifq82DAIqp3z849uvwZTtAVD49lFVBcDrCKXcZ8NQPwCpk+wf2W5UTRFK2YUqKtiIyimf8lsw5ZXKpOxs3Ga/vTeAoHCjkoVgyh5uvBbJfs8FaWZLwBYEU3DztXG7CT/sRjjlQ34JH7waSPn9uQBI/Q9tgin4NaAC4G8EU/bzU0DF0D5vY1ifz4b0+SGY8nuA4zw/hvwBsBXBlL2C0CwdgD+qVgimvMPt2fwAReWUj3g5mApiZZGbz9XL7xUgaFJduUIw5Q2pfJ2ongJSJ1mVH6kMpmh87k2pfM0Y3odoCKd8wsthQ5ACqez8Esh5rcIQSDQ/9M5xc2Y4BDeg8sP/dwD8glDK23j94CbCKR/84PZqMOWXYCYR3NgPXn3fAEGSqooVQinv4rUDkB+qVGBjQJWs9yV9p7yLnlMe58WAgUAqOnpRAQDiDajoQQV4n9d/VPup6uZYvcyY71MyvYT4BT2o4AbCKaQMoVTB9xMBFQCqpmJTZlt8xeBH6pwSP0hFQKXvyWY1dyb1MQB4s2rKi8FUPAFUvOvzYnCVioBK358VNh1L6mPAOwinPDykz0tVUwRTdgZU+h7qUm9j0h8H8DMv98zxWjAVbwAV7zr9Elx54f9DV1Td4PZmAPB5MJXoMKowj+2VsIoKKqQS4ZRHeSWYIpSKHxVUQHClomrKK8FUMgKpeB7bC0EV1VMAUs32YMrNQKqg2+WVoMprQ2RLbNjm9mYgRoRTSBqCqcIjoAIQtGDKzTAqlu2yNayi/xSAoDdCtzWQ8mpQlezqKYb2wWHnN0B4umqKWfi8xfb3ExA0qeo1ZWP4Y2sw5bXttTl8BOCfZui2VU1pyOO1YMorz8G21xr+ZOe3KpfZ3G/K9iCBUCq4+9Tm/98AsDO4cAIeW0OegrB1+5P5Ogc1QAW8JNlVUzaFFbYGOn57Tsl8zYNa5YdIcX2bmjZtmjRo0EBKlSol7du3l1WrVuW5/JQpU6RJkyZSunRpqVu3rgwZMkSOHj0az0PDYl4JUbyIfQs/45iSuh/9tgRTtgY6heHH55RKXp5YAPbgeJIatgRTNgY4yXqOfn+egIr5W9S8efNk6NChMnr0aFmzZo20atVKunbtKrt27Yq6/Jw5c2T48OFm+fXr18sLL7xg1vHAAw/wCvioaorwxNtsfm/B37x+TPHSD2obgqkgBDg2VYNRPYUg8frxxCtVKDYEU0ENa2x43ja8/vCvmL85TZo0SQYMGCD9+vWT5s2by/Tp06VMmTIya9asqMsvX75cLrroIrn11lvNmYwuXbrILbfcku+ZDHgjPKC/VOqwn+FHHFOCFUwFjQ0hlQ2vPZAKHE/8z4ZwxgZ+DagSHap6sY9b0MX0jSkzM1NWr14tnTt3/mUFRYuav1esWBH1PhdeeKG5j/NB/91338m7774rV111VWG3HS4jLEk99jn8hGNKMCpRbAho3Bb05w8kG8cT/1fNuB3I2IagDn6UFsvCe/bskZMnT0qNGpFfoPXvDRs2RL2Pno3Q+3Xs2FGysrLkxIkTcscdd+RZMnvs2DFzcRw4cECC3NTZxqopQhJ3933ZhvuT8j7rUm9jwtcLuHlMcfN4Ygu3KmcIZKLvjyN1TrnyHkirdSQpgWqzmjsTvl4gVkH4jRLUYIoAJv/9UzK9hCvvh3LfZyWleqrCpl/+P4ZgSfo3x2XLlsmjjz4qzz77rBn//c9//lPeeecdGTduXK73GT9+vFSoUCF00QaFQUUwhWh4DRBUsR5Tgn48IZiyj1v7huF9gL2/URI5/MhPs54RTNldRUX/KSRaTN+QqlatKsWKFZOdOyPPkunfNWvWjHqfhx56SHr37i233367tGzZUn7961+bA4F+uJ86Ff3s4YgRI2T//v2hy9atW2PZTCQRoQiAREnFMcUrxxM/DekjmArWUEc/vXfhXfxG8VcIwZC1+LDP4HUxfTMqUaKEtGnTRpYsWRK6Tj+89e8OHTpEvc+RI0fMmO9wevBQWkIbTcmSJaV8+fIRlyCyrWqKYMouNr4eNg6Lhb1ScUxJ5vHE9pn6Ul0p46fAJVVSvb9sr56y/f9TsBe/UfwVTME7+y8Z7w8/Vf8hiT2nlE7R2rdvX2nbtq20a9dOpkyZIocPHzYzY6g+ffpI7dq1zVkHdc0115jZM84991xp3769fPvtt+ZMhV7vHACQE8EU3EDfKaQaxxR/IJQq3L5LZR+qZPWfAtzG8cT7P+oJprzZhypZ/acSNWS2xIZtbm8GkhVO3XzzzbJ7924ZNWqUZGRkSOvWrWXBggWhBoTp6ekRZyFGjhwpRYoUMf9u375dqlWrZj70H3nkEbENVR/REUwFrzk6kCp+Pqa4OSwqlRUyBFPeC6gSjcbosAHHE29XTRFM+aNReqLQGD2YYg6n1ODBg80lt+aCEQ+QliajR482F3ivaopgCkCycUzxLoIpbwZUVE/BrzieeBPBlPcDKpurp+AdfKsEAMBHUlU1RTCVeOxTFNaPP/4ovXr1Mr2QKlasKP3795dDhw7leZ+jR4/KoEGDpEqVKlK2bFnp0aNHjsbin376qXTq1Mmss1KlStK1a1f54osvkvxs4OaQvlRVTRFMJRf7F17CtyDkiqopb+B1Arwr0UP6CKa8L1X7NtHvFWbts4MGU+vWrZPFixfL/Pnz5cMPP5SBAwfmeZ8hQ4bI22+/La+99pp88MEHsmPHDrnhhhtCt2u41a1bN6lXr56sXLlSPvroIylXrpwJqI4fP56CZ+Vv2hMnqAhO/LWfU908H/7Dt0vL2DKkj8AjuGx5DwKwE8FU8rGPEY/169ebHkszZ840Db47duwoU6dOlblz55rAKZr9+/fLCy+8YBqDX3HFFWbGuxdffFGWL18un3zyiVlmw4YNpiJr7Nix0qRJEzn77LPNUDitrvr+++9T/Czhl5CBYCq1vLi/vd7gH7Hj2w8CEUyV21S00Beb+fE1A2xm45T3qaiaIjRJnVTs61Q2zvfy/7eS5cCBAxGXY8cK1/x3xYoVZtidzlbn6Ny5s2kCrhVP0axevdpUP+lyjqZNm5oqKV2f0kBKh/xpiJWZmSk//fST+e9mzZpJgwYNCrXNCOaPeC8GJX6Qiv1O9RRS3hAd/q1Y8UvIkYwwKfs6Dzb27sxKABArgqnU8/osfl72wf+dJcWPJqeR8PHD+gPxA6lbt27E9VqNNGbMmLjXqzPUVa9ePUfT78qVK5vbcrtPiRIlTKgVTme4c+6jQ/i0mfj1118v48aNM9edeeaZsnDhQrN++EuywwWCKXd5fRY/+BvfNP+/v+69UILO68FUqqucvFBRBcBeiezRk+wKGIIp9yR73yfyvUPfqdhs3brVDKtzLiNGjIi63PDhw6VIkSJ5XnToXbJopZQ2Vr/ooovMUL+PP/5YWrRoId27dze3AQVFMBWM14HqKcSL0x2WsKFqyotsCIfCt8HNaioNF8s23O/a4wPwJ4Ip91FB5U86o55e8nPvvffKbbfdlucyjRo1kpo1a8quXbsirj9x4oTpF6W3RaPX61C9ffv2RVRPaT8p5z5z5syRLVu2mGF+OkTQuU5n7fvXv/4lPXv2LNDzhf2SGSoQTNnFKxVUOmS1wqZjhZ50oMSGbQnbJiQP4RQ8WTVlQyiV13Z5fcifhqVd6m10ezMAuFw1RTAVjIBK30NptY4kZd0ovGrVqplLfjp06GBCJu0jpY3N1dKlS+XUqVOmQXo0ulzx4sVlyZIl0qNHD3Pdxo0bJT093axPHTlyxIRSWqHlcP7WdcNdXug3RTBlJ68EVAgOwikLuF015ZVgytZAyqaQyobqKR0i27vScle3AQD8iAoq5EUblHfr1k0GDBgg06dPN43OBw8ebCqbatWqZZbZvn27dOrUSV555RVp166dVKhQwQzZGzp0qOlNpZVcf/jDH0wwdcEFF5j7XHnllTJs2DAZNGiQuU0Dqccee8z0m7r88stdftbephUdtmAoVqQGdXbHfJ8t2/IPkYMSUOn7qdz3WQlfL/yNcArW81Io5ddKKgCJ5YXePF6rmiq7Pb7P2UO1vfU8vfDeblZzp9ubEVizZ882gZQGUFrdpNVQTz/9dOh2Day0MkqroRyTJ08OLaszBnbt2lWeffbZiNn73n77bXn44YdNaKXLnnvuubJgwQI5/fTTU/4c4S1eqJqKJ4gq6Hq8GFgBbiGcCjjbq6a8HExlfx4EVIA/2DTVfbKG9NkeTMUbRBV0XTYHVsmqnmJonz9o9ZP2g8pNgwYNJCsrspqhVKlSMm3aNHPJjVZP6QX+lKyqKZuDqUQFUrE+jo1hle3VU4noOwVvIJwK8JA+m4Mpv4RSblRR2TC0D4B32RpMJTKQiuWxbAyq/D68TwPgK6omb/Y5wC+80G8qiIFUQbbBtpCK/lOwAeEUrOPHYMqLVVQ0RQeC2wg9iIGUV4OqRKJ6CoDfqqZsCKTy2y7bgqpEovcUYuHvb1mWo2oqZ2jj92DKkeznaePrC8D+flO2VE1pIGRDMGXzdtnyWnntPQ4g+UP6bAimNPyxNZiydVtteN0QbPZ+s0nx7GJBYmNwEZRQKujPGYC9bAg7bAp/vLCdyXjNglCRB8DfbAh6vBpS2RpQFXYIq00zY9pg2rRppgeh9hxs3769rFq1qkD3mzt3rhQpUkSuv/76iOsPHTpkJuOoU6eOlC5dWpo3b25mjY2V+99EA8rNqimbBKlaCgASxW8Bgi1hT1C2G4D32dpvys1ww4ZwJxH88BxS0XAf8Zk3b54MHTpURo8eLWvWrJFWrVqZWVp37dqV5/22bNkif/rTn+Tiiy/OcZuuT2dwffXVV2X9+vVyzz33mLDqrbfeimnbSAUCxqaqKUKp5O4Dm15rAHZzs2rKD+GOm8/Bhoo3AN6U6NDA7WDKT9wM2mytnkJiTJo0SQYMGCD9+vULVTiVKVNGZs2alet9Tp48Kb169ZKHH35YGjVqlOP25cuXS9++feWyyy4zFVkDBw40oVdBK7IcfKOBKwimvIEKPyCx6MXj36ojPz0fv1XmATZimFFi+KVaKjd+fm5IrAMHDkRcjh07lmOZzMxMWb16tXTu3Dl0XdGiRc3fK1asyHXdY8eOlerVq0v//v2j3n7hhReaKqnt27dLVlaWvP/++/LNN99Ily5dYnoOzNYXoB/8tlTSEEx5c/a+WPu49a603O3NAHwp0cGBG5U3fglxcntuqZ7VT1/DI3VOWRfENqu50+3NAODjapugBDfO80zlrH76epZML5Gw9QV91r73d54laYeSMxT3xGENoRZJ3bp1I67XYXtjxoyJuG7Pnj2mCqpGjciTpfr3hg0boq7/o48+khdeeEHWrl2b6zZMnTrVVEtpz6m0tDQTeM2YMUMuueSSmJ4L4VRAEEwBALIjmEoO5zmmOqQCgKAISjCV/TmnMqCCt2zdulXKly8f+rtkycKHYQcPHpTevXuboKlq1ap5hlOffPKJqZ6qX7++fPjhhzJo0CCpVatWRJVWfginkDIEU6mvntJQsmzD/QlfLwDEKgihlJtVVImuntIKvbRaR8QtS/c0lSuqRj+LCwRdIpqhJ7LfVKqrpoIYTLkRUNlWPaXv+wqbcg5Vw880mAoPp6LRgKlYsWKyc2dkZbP+XbNmzRzLb9q0yTRCv+aaa0LXnTr183cNrZDauHGjCaAeeOABeeONN6R79+7mtnPOOcdUWk2cODGmcIq0IABD+myomiKYAuAH+oPZL0P6Ulk1FcRgyo3nTnN0AH4X5GDKwT5AvEqUKCFt2rSRJUuWRIRN+neHDh1yLN+0aVP58ssvTdDkXK699lq5/PLLzX/rUMLjx4+biw7lC6chmBNkFRSVU0g6gqng9p4C8IugNkMPcjDlZh8qAEiFVFZNEcqkvoIq0dVTcN/QoUPNzHpt27aVdu3ayZQpU+Tw4cNm9j7Vp08fqV27towfP15KlSolLVq0iLh/xYoVzb/O9Rp4XXrppTJs2DApXbq0Gdb3wQcfyCuvvGJmBowF4ZTPuV01RTAFAPZJVYUNwVTqA6pEDu8r7NA+mqIDdkrkkL5UIZjKiR5Usc+QWWLDNgm6m2++WXbv3i2jRo2SjIwMad26tSxYsCDUJD09PT1HFVR+5s6dKyNGjJBevXrJjz/+aAKqRx55RO64446Y1kM4haQhmLKjeqqwfad0KGqXehsTuk0A3J+lL9kIpnKiggqAn6Sqaopgyt2AKpHVU0Gftc8WgwcPNpdoli1blud9X3rppRzXab+qF198sdDbFfhvSDrlvV/7TblZNUUwFT/2HQCvV00RTLm7b+g9BcAvwQvBVP6CtI8SMRkA7MW3FyQc4QoABBfBVP7YRwDc+nGeqCF9ya6aClLg4oX9leoZGRFMpAg+5VbVFMFUYrAfASRjSF+yK2oIXezZV4l6rb02nBSA9xFM+Xu/ebHnGVKDX8A+HdLnBgIVe7ndGB8IuiDM1EcwFbsg7LMgvPeBoKGKJpgBFa87ko00wYcIIgAAqayaCkLI4sV9R+8pwN5Zw9zghYoVr1T/2Ix9CK/iWwsSgqqpxGOfAlAMq4LbeA8CSEX1DKGK/WyonqIpun/x69dnQ/rcqJoiRAHi9+OPP0qvXr2kfPnyUrFiRenfv78cOnQoz/scPXpUBg0aJFWqVJGyZctKjx49ZOfOnRHLpKenS/fu3aVMmTJSvXp1GTZsmJw4cSLHVLHnnXeelCxZUs4444yoU8M6HnvsMSlSpIjcc889hXzG8BuqpgqP6ikAQUcwFaz96YUqPqQe31hQKARTycX+9T8NptatWyeLFy+W+fPny4cffigDBw7M8z5DhgyRt99+W1577TX54IMPZMeOHXLDDTeEbj958qQJpjIzM2X58uXy8ssvm+Bp1KhRoWU2b95slrn88stl7dq1JnS6/fbbZeHChTke79NPP5W//OUvcs455yT42SNVkhVQEEwlDvsSQH6oGIENAZUN1VPwJ375AgFRmKq6IDT0d8P69etlwYIFMnPmTGnfvr107NhRpk6dKnPnzjWBUzT79++XF154QSZNmiRXXHGFtGnTRl588UUTQn3yySdmmUWLFsnXX38tr776qrRu3Vp+9atfybhx42TatGkmsFLTp0+Xhg0bypNPPinNmjWTwYMHy4033iiTJ0+OeDyt4tIAbcaMGVKpUqUU7BUAfhNvU/Sle5omfFuAoEpEpUqyQgnbq3wApAbhlI+kekgfVT1A4axYscIM5Wvbtm3ous6dO0vRokVl5cqVUe+zevVqOX78uFnO0bRpU6lXr55Zn7Peli1bSo0av/wg7Nq1qxw4cMBUaTnLhK/DWcZZh0OHD2qFVfZl4Z1eP1RNeUey9mki3gP0nQKQDARTycX+hZekub0BfufXihOCqdTu64ON+RFoAw13wmmvJr3EKyMjw/SDCpeWliaVK1c2t+V2nxIlSphQK5wGUc599N/wYMq53bktr2X0Of70009SunRpU8G1Zs0aM6wPqa8asRnBVHL37aHaHGMBAIkLqLZsq5bQdWoVXcn0EoWu5iv3fVbCtgneF+hw6q97LxS/cKMROpDf/796V1qe0sdcuu1MKVYm8f0YTh45Zv6tW7duxPWjR4+WMWPG5Fh++PDhMmHChHyH9Nls69atcvfdd5teWKVKlXJ7c6zAECMAQFAlY0gfVT0oTP+1Cpt+/n4ei8ymdaTEhm1J2SYUXqDDKcSHqilvh5hlG+53ezM8SwMbnVXPkVvV1L333iu33XZbnutq1KiR1KxZU3bt2hVxvc6opzP46W3R6PXaN2rfvn0R1VM6W59zH/131apVEfdzZvMLXyb7DH/6tz4/rZrS4YO6bTqbX3ijdW3Y/swzz8ixY8ekWLFieT5HuC8ZQ/qomvJm9ZS+F47U4bUDgoiZ0WBr9RQQjnAKMSGYcgdD++ygwU14OJWbatWqmUt+OnToYEImDYK0sblaunSpnDp1yjRIj0aXK168uCxZskR69Ohhrtu4caOkp6eb9TnrfeSRR0y45Awb1Aoo3fbmzZuHlnn33Xcj1q3LOOvo1KmTfPnllxG39+vXz/S3uv/++wmmAopgKtjD+7TvVFqtI25vBoAUo2oKQCoQTvmg3xRD+gqu0saCH1z3NuFMAJJLZ8nr1q2bDBgwwMyep43Odda8nj17Sq1atcwy27dvN0HRK6+8Iu3atZMKFSpI//79ZejQoaY3lQZOf/jDH0yodMEFF5j7dOnSxYRQvXv3lscff9z0lxo5cqRpbu5Ue91xxx2mAuq+++6T3/3udyYU+/vf/y7vvPOOub1cuXLSokWLiO097bTTpEqVKjmuR3LQgDp+5Tb/lOftBxuWliCiegrw9jAmv7A9mLqy5oa477s4o2mgqqcKi75TCEc4Bd9XTcUSSOV1P8IqJMPs2bNNIKUBlM7Sp9VQTz/9dOh2Day0MurIkV+qFSZPnhxaVofX6Sx7zz77bOh2rWqaP3++3HnnnSa00lCpb9++Mnbs2NAyDRs2NEHUkCFD5KmnnpI6derIzJkzzbrgD4ke0mdz1VR+YVR+y9saVtlYPQUAflSYQCq39dgYVCU6oGJoHxKJcAq+FG8gVZB1ElIhkbT6ac6cObne3qBBA8nKijyjpA3Kp02bZi65qV+/fo5he9lddtll8vnnnxd4W5ctW1bgZQHbAqmCrsvWoMoPs1Y2qxnZ5w5A8Ib02VQ1lahAyqtBFWAbwimPS9WQPi9UTSUjkLIppKLvFODNH+R+YEvVVCIDKa8EVYmunirs0D76TgHeQjP01IdSeT2mDSGVjcP7AGV/4uBRqeo3hdQGU24/ppuBJu9pINiz9AUhmIr2mG48rq3hIAB4vWrKjWAq++O7vQ1eaJgftD5s+BmVU/B01ZTbAZE+PsP8APi5GbrbwYgN4ZBugw1VVACA+NgWCLldSWVT9RRN0eGwN3WAFUP6CKYKth2p2habXw8A8GPVki3b43ZICCAxMpvWkSBWxLhVNWV7pZLN2wakGpVT8BxbQqnsqKIC4LchfW4FIjaFUrltm5crqQrbdwqANwS535SXQh+3qqhsqp4CFGUYHhXEqqlUVijFy/btAwCbuV2dFAuvbCcA7/N6b51UV015KZjyw3a72XcK/mJX+uATNI4OdujjpW0FYB9b+k2lumrKi2FPqrfZlqF9trxHASQPYUMwAiobmtQDDsIpWF81Rdhj72sDwC5enaXPi8GU17fdjffK+owaMd9n6R73p10HED+qpoL5HIB4ePNbLALDq8GU7dudimGhQNDF80PcFqms0PFquOPWc7ClegoAbOOnUMeLz6Uw1XZB7o+GXxBOeVBQggXbAx4AwUH1RnL4IZjy43MBAK9VTXkxzLHlOTG0D7YgnIKVw8YIpgDAHamqzPFjmJOq50T1FIBk8lq/KT8GU0F4bong9ckCEMn9FALwaTCVzOdhQ4AIwC5e7TflN14K3XjPAP4VlGFSQQhvUvEcqZ6CDfhW4rGZ+pI9pM/t0MMvwZRfMRMlgKAFOPHw+/NTzNhnpx9//FF69eol5cuXl4oVK0r//v3l0KFDed7n+eefl8suu8zcp0iRIrJv376oy73zzjvSvn17KV26tFSqVEmuv/76JD0L+EEqwo4gBFNe47WqO9iFcArW8GMw5cfnBMC/P/hTMVwsCMFNKjC0D9FoMLVu3TpZvHixzJ8/Xz788EMZOHBgnvc5cuSIdOvWTR544IFcl/nHP/4hvXv3ln79+skXX3whH3/8sdx6661JeAZAwQQtmAra80Uwpbm9AbCHm1VThDgA4H9BCqb0uR5sWNrtzUCArF+/XhYsWCCffvqptG3b1lw3depUueqqq2TixIlSq1atqPe75557zL/Lli2LevuJEyfk7rvvlieeeMJUYjmaN2+elOcBd3vqJKLyJdlVU0ENavR5L85I3gQt+rpt2VYtaesH8kPllIf4dZY+gil3+PX9BASRF3oHBSmYStVzTkT1lBfeOyiYFStWmKF8TjClOnfuLEWLFpWVK1fGvd41a9bI9u3bzXrOPfdcOf300+VXv/qVfPXVVwnacgAF5edgLih90pA7vpHAil5Tfpas8I3XDEAiMUwMqbA+o4bbm2CNAwcORFyOHTtWqPVlZGRI9erVI65LS0uTypUrm9vi9d1335l/x4wZIyNHjjTDBbXnlPap0h5XQCr5OZyxQSKq3mzvO5XZtI7bm4BcBHZY31/3Xuj2JoCqKQAIhCBWTTkY3udNG3dWk2JlSiVl3SePHDX/1q1bN+L60aNHmwAou+HDh8uECRPyHdKXLKdO/RxcP/jgg9KjRw/z3y+++KLUqVNHXnvtNfn973+ftMeG9ypQkjmkj2AqNcP7ALcENpxKBmYyi02Qgil9rnublHB7MwCkiNeqQ5JZNRXkYCoVAZW+dodqU0nrRVu3bjUz5DlKlozeW+jee++V2267Lc91NWrUSGrWrCm7du3K0S9Kq5v0tnjpML7sPaZ0W/Ux09PT414v7GN7xQt+QUAFPyKc8ohk9gdyY3hYkIIpAPDCTH0ILu07daTOqbjes2m1jiRlm4JAg6nwcCo31apVM5f8dOjQQfbt2yerV6+WNm3amOuWLl1qKp/at28f93bqujSM2rhxo3Ts2NFcd/z4cdmyZYvUr18/7vUCsaBqKnVojA63cKoNAAAPs7mhNVVTv2BfINmaNWsm3bp1kwEDBsiqVavk448/lsGDB0vPnj1DM/VpY/OmTZua2x3aj2rt2rXy7bffmr+//PJL87fTT0oDtDvuuMMMO1y0aJEJqe68805z20033eTKc4WdkjWkj2AqOvaLOzNaInns/UaLlKBqytvPm6boAGwd0kcYk7p9QjN7OGbPnm3Cp06dOslVV11lKp2ef/750O1a8aTh0pEjv1S8TZ8+3czCp6GWuuSSS8zfb731VmiZJ554woRcvXv3lvPPP1++//57U5WljdEBIFFDRJmxL9gY1hfwIX2pFtRgCgAAINl0Zr45c+bkenuDBg0kKysr4jptwh6tEXu44sWLy8SJE80FSCWqg9zpPcXQPriBsgukDMEUAAQDVVO5Y98AwZWKKezjrTwpbDP0ZM7Sh7wR4MEvCKcCPFMfQ8JSz7aALtlVeX/de2FS1w8ASMzQPpt7lwEIJkIXIFj4JoJAhjIA4IeZ+gobKCSjVxGVQcHaR8wyCQDuI8iDHxBOWc5P/aYAAAAAFEyQZyEjbHFfYYdqFnaoKIKHcCqgUjmkj6qpSOwPAH7lp4qgZGNfFdzSPYlv9gsAfkOgB68jnAI8jt5hAIBkDdMEgFQ3QydkCbZ4m/rD+/hVi6SiSggAghFkUAkUu6Dus/UZNdzeBABhGH7lH4kO9piFEalEOBVAqaq0IZjyJy/OTAkAyB8z9gFwG1VTQHAF8ltIoqe3T9aPdZqh+xfBHeBfqaoKsSlICGoFUCKw7wAkCsOhAHiZPd9s4SuELwAApB59pwCkEsO+7GNT9RlDRhELwqmAoXk2AIAAwy5er546saOM25sAwAdsClXwCwJI/5k2bZo0aNBASpUqJe3bt5dVq1YV6H5z586VIkWKyPXXXx9xfVZWlowaNUpOP/10KV26tHTu3Fn+97//xbxdJBVIOKqmAPhJsqex9/oPe68HKwAA+E3Qgr79jUu6vQmeMW/ePBk6dKiMHj1a1qxZI61atZKuXbvKrl278rzfli1b5E9/+pNcfPHFOW57/PHH5emnn5bp06fLypUr5bTTTjPrPHr0aEzbRjgF+CDEoyIOAAAAqRx2lciKmqCFKYBbJk2aJAMGDJB+/fpJ8+bNTaBUpkwZmTVrVq73OXnypPTq1UsefvhhadSoUY6qqSlTpsjIkSPluuuuk3POOUdeeeUV2bFjh7z55psxbRu/aC2VjGboqQgwqJryHhrvA4gXVVN27svCDNu0qdE+AAAomAMHDkRcjh07lmOZzMxMWb16tRl25yhatKj5e8WKFbmue+zYsVK9enXp379/jts2b94sGRkZEeusUKGCGS6Y1zqjSYtpaQAA4LrCBAj0mwIAwP+0Gm1xRnJbEyRz5sly32eJX6TvqCpFS5dKyrpP/fTz0Lm6detGXK/D9saMGRNx3Z49e0wVVI0akTNL698bNkSvXvzoo4/khRdekLVr10a9XYMpZx3Z1+ncVlCEUwAAAAAAVzCkz346hHPLtmpxDx0tmV4i4duESFu3bpXy5cuH/i5ZsvB9uA4ePCi9e/eWGTNmSNWqVSXZCKcKaVF6E7c3wRoM6QOA4LB1SF/apu0FWu5E49pi4z492LC025sBwAK2N3j2+wxuN5ZfE/N9Xj9wXlK2BYmX2bSOlNiwTfykfPnyEeFUNBowFStWTHbu3Blxvf5ds2bNHMtv2rTJNEK/5pprQtedOvVzBX5aWpps3LgxdD9dh87WF77O1q1bx/QcaCwQEDTMthOBHgAkLpQqaDAVz/IAgGCIJ5hy7hfvfZOFqjSEK1GihLRp00aWLFkSETbp3x06dJDsmjZtKl9++aUZ0udcrr32Wrn88svNf+tQwoYNG5qAKnyd2vNKZ+2Lts68UDllIS82qCZkAQD7+bHfVGEDJuf+NlZSFfa1PlSbE1NAUGiPnlTO1OfH8CRRwZKuhyoq2Gro0KHSt29fadu2rbRr187MtHf48GEze5/q06eP1K5dW8aPHy+lSpWSFi1aRNy/YsWK5t/w6++55x7585//LGeeeaYJqx566CGpVauWXH/99TFtG+EU4KPquION/ffDE4B9bBnSl8jKJ12XDQEVQ/sAIPUSXfHkrI+QCra5+eabZffu3TJq1CjTsFyH3i1YsCDU0Dw9Pd3M4BeL++67zwRcAwcOlH379knHjh3NOjXcigXhFAqNqikA8MZMfX6RrOF4fq2iiuc9dqRObCc7TuwoI2m1jhR4+fUZNaRZzcieFwCQaskehuenKqrCNEWHXQYPHmwu0SxbtizP+7700ks5ritSpIiMHTvWXAqDb7gBQL8pALCT/qBHbFLRJ4peVADgf6nqD+V2Lyqbhk4CeYkrtZg2bZo0aNDAlGm1b99eVq1alefyWto1aNAg071dpzQ866yz5N13343noQEAPuOnY4pWg8AfoREBFeA9fjqeBGGmPjdDE9salwOII5yaN2+eaaI1evRoWbNmjbRq1Uq6du0qu3btirp8ZmamXHnllWYKwtdff91MNzhjxgzTZAvex5A+AIXBMcV7bOk35eeAKlH72I8N8IHccDyB7cFUkAMxG5rvw34x95yaNGmSDBgwINTNffr06fLOO+/IrFmzZPjw4TmW1+t//PFHWb58uRQvXtxcp2c04J+Z+lD4gG9vkxJubwbgCo4pqeP1oIJKJgB54XgCL3CrB5VWqS3OaJryxwWSVjmlZxhWr14tnTt3/mUFRYuav1esWBH1Pm+99ZZ06NDBlMxqB3idcvDRRx+VkydPihv+uvdCCRL6Tf2s9FfbQxcAdvDDMQX+D6YIxQD7cTzxHreG9NlQvWTDNnjBwfpF3N4E2Fw5tWfPHvOB7Uwz6NC/N2yI/gHz3XffydKlS6VXr15mDPe3334rd911lxw/ftyU3UZz7Ngxc3EcOHAgls1EinhhSF+0MMq57qcWlG0DbkrFMYXjifeH9NkQDuk2pHoGP93XBxuWTuljAl7Fb5TYBXGYFaFQ4TFjH5Ip6WU1p06dkurVq8vzzz8vbdq0kZtvvlkefPBBU2qbm/Hjx0uFChVCl7p164qNFqU3cXsTkIf8qqSopAK8J9ZjileOJ7A3mLJxWwAUnp9/o8D+YMq27fGD/Y1Lur0JSGU4VbVqVSlWrJjs3Lkz4nr9u2bNmlHvo7Nf6MwXej9Hs2bNJCMjw5TgRjNixAjZv39/6LJ169ZYNhMBF2voFD7kj7AKSJ1UHFM4ngDxKbONtgDwDn6jeG+mvlSyNQhK9Xa5OTsiUBAxffMoUaKEObOwZMmSiLMO+reO2Y7moosuMmWyupzjm2++MQcEXV80OpVr+fLlIy6wq9+UjUP6CJfiRyN+uCEVxxS/HU+CFBjYWKlk4zb5vRE+UBD8RvEWQhL7gzPADTF/y9UpWnWa1ZdfflnWr18vd955pxw+fDg0M0afPn3MWQWH3q4zYdx9993mA19nzdBmg9p8EJEICOzgRsCVqLAvVQ3wGdKKROGY4p2AIpX9pmwOgVK5bW70+AK8KsjHExpH547wB/BpQ3Sl47F3794to0aNMmWvrVu3lgULFoQaEKanp5vZMRw6FnvhwoUyZMgQOeecc6R27drmIHD//fcn9pkg0KiYAryJYwq8FEy52SAdQN44nsCrwZRu5+sHzktZ1drijKYpeSwg6eGUGjx4sLlEs2zZshzXaTntJ598Es9DwUK2DekjmAK8jWMKACAROJ7Aa8GUGwGVWzP26QyRJdOjD5kFVHCaVwRMqoZ3+TWYIvACgNTzQtWUF7c1VU7sKOP2JgCwHP2mAOQmGAkGfIkACYCXeemHPL2P3MO+B/whs2kd8TovztTnJV6r9gISjXDKEl5phm7LkD6CKQCA26ieAgD7EPIA3kQ4Bc8hmIKf6ExBvXr1MtNRV6xYUfr37y+HDh3K8z5Hjx41swlVqVJFypYtKz169JCdO3dGLKONX7t37y5lypSR6tWry7Bhw+TEiRM5+m+cd955ZmrsM844Q1566aUcj7V9+3b57W9/ax6rdOnS0rJlS/nss88S9OyBXxD02D1bIwAAQDIRTsVpUXoTtzcBgA9oMLVu3TpZvHixzJ8/Xz788EMZOHBgnvfRmYXefvttee211+SDDz6QHTt2yA033BC6/eTJkyaYyszMlOXLl5tptTV40hmMHJs3bzbLXH755bJ27Vq555575PbbbzczFzn27t0rF110kRQvXlz+/e9/y9dffy1PPvmkVKpUKUl7A8lAMAEAyN6YGsGt+qLvF3w1Wx8QhKopfayfWtRO6ZDJvU2YwSJI1q9fb6a5/vTTT6Vt27bmuqlTp8pVV10lEydOlFq1auW4z/79++WFF16QOXPmyBVXXGGue/HFF6VZs2ZmxqELLrhAFi1aZIKk9957z0yhrdNpjxs3zkyPPWbMGClRooRMnz5dGjZsaMImpff/6KOPZPLkydK1a1dz3YQJE8xU27p+h94HQGTF14nGqTtWAAByx5A+wLuonPKhZM3U53a/KYbzwW9WrFhhhvI5wZTq3LmzFC1aVFauXBn1PqtXr5bjx4+b5RxNmzaVevXqmfU569XhdxpMOTRwOnDggKnScpYJX4ezjLMO9dZbb5ltu+mmm8zQwHPPPVdmzJiRwD0A/IwhfQDgf1TsAMgL4RQAFJCGO+GXY8eOFWp9GRkZJvQJl5aWJpUrVza35XYfrXzSUCucBlHOffTf8GDKud25La9l9Hn99NPPs4N999138txzz8mZZ55phvvdeeed8sc//tEMEwTg/xn7ymzjayLghv2NS7q9CXAR1V8IKob1wROomkJBHP6+vBQtVSrh6z119Kj5V4e4hRs9erQZJpfd8OHDzZC4/Ib02e7UqVOmcurRRx81f2vl1FdffWWGBPbt29ftzQsct4ICt4IRL2FoHwC4j1AndRrU2S1btlVL+uMcrF9Eyn2flfTHgR0IpwCggLZu3Wpm1XPoLHfR3HvvvXLbbbflua5GjRpJzZo1ZdeuXRHX64x6OoOf3haNXq+Nzvft2xdRPaWz9Tn30X9XrVoVcT9nNr/wZbLP8Kd/6/PTWfnU6aefLs2bN49YRntT/eMf/8jzuQGxYEgfAAAAqNe2wKHNFcR2bvabcrNqioothNPgJvySWzhVrVo10wcqr4sOzevQoYMJmbSPlGPp0qWmYql9+/ZR192mTRsze96SJUtC123cuFHS09PN+pT+++WXX0YEXzoboG6zEzbpMuHrcJZx1qF0pj5dd7hvvvlG6tevH+OeA4Cc1mdEDi0GAPyMKjAEEeEUALhEq5C6desmAwYMMJVOH3/8sQwePFh69uwZmqlv+/btJsxyKqEqVKgg/fv3l6FDh8r7779vgq1+/fqZUEln6lNdunQxIVTv3r3liy++MP2iRo4cKYMGDQoFanfccYfpKXXffffJhg0b5Nlnn5W///3vMmTIkND26X/rDIA6rO/bb781MwQ+//zzZj0AIlEBBhto5W2vXr3MyQitrtXjxaFDh/Jc/g9/+IM0adLEVM3q5BraW1Bnho3m//7v/6ROnTpSpEgRc3IFwRrGZTPCnNjQnB42IpzymWTN1OcWKpfgd7NnzzbhU6dOneSqq66Sjh07mgDIoTPzafXSkSNHQtdNnjxZrr76aunRo4dccsklZojeP//5z9DtxYoVk/nz55t/NbT67W9/K3369JGxY8eGlmnYsKG88847plqqVatW8uSTT8rMmTPNjH2O888/X9544w3529/+Ji1atJBx48bJlClTzA8fIBEIdIDE0s9nnZVVP9v1OPDhhx/KwIEDc11+x44d5jJx4kTTU/Cll16SBQsWmFArGr3+nHPOSeIzAAAEFT2nYPWQPsDvdGY+rUjKTYMGDSQrK7IRZKlSpWTatGnmkhsdevfuu+/m+diXXXaZfP7553kuoyGYXgB4W9ntp+RQbX+dwELOiTY0WPr000/NZBZq6tSp5sSHhk9ORW44PfEQ3kewcePG8sgjj5iTGtoDUWeQdejsrVotNWrUKPn3v/+domcFv6BSJ75qsNcPnCd+cqxeppRML+H2ZsBSfEuBtaiaAoDCBxLwRyVY0GdNXLqnqdubYL0VK1aYoXxOMKU6d+4sRYsWlZUrVxZ4PTqkT4cFhgdTX3/9tam+feWVV8z6AJswpA/wB44ugM9CMr8N7QS8wo/NnZMZiDCkD0F34MCBiMuxY8cKtb6MjAypXr16xHUaMGmFrt5WEHv27DFDuMOHAup23XLLLfLEE0+YnlSwy8H6RdzeBABICIb1wUpeC4QAAIB/nMwoI1mlSiVl3aeO/nwSqW7duhHXjx49WsaMGZNj+eHDh8uECRPyHdJXWBqQde/e3UyoEb4dI0aMMBN46FA/AKnlx6F9QG4Ip5An+k2lfn/vbcI4bADwKq0IO9G4ttubAQ/YunWrGT7ncGZTze7ee++V2267Lc91NWrUyEyOsWvXrojrtW+Uzsint+Xl4MGDZvbYcuXKmYkwihcvHrpt6dKl8uWXX8rrr79u/nb6IFatWlUefPBBefjhhwvwbIHkYEhf4fqALc5gyDTsQTjlI34ZzkXVFAD4G0P6ADHBVHg4lZtq1aqZS350dlZtWL569Wpp06ZNKFg6deqUtG/fPs+KKZ2pVcOxt956y0y6EU4bpv/00y9DfLXh+u9+9zv5z3/+Yxqow3sNqYFEaFBnt2zZlv9nE1BQgQqn/rr3woSsZ1F6k4SsBwAAAEgEHXqn1U8DBgyQ6dOny/Hjx2Xw4MHSs2fP0Ex927dvl06dOpnG5u3atTPBVJcuXeTIkSPy6quvhvpfKQ3EihUrliOA0r5UzuNpA3YAABIhUOEUAAAA4FezZ882gZQGUDqrXo8ePeTpp58O3a6B1caNG00YpdasWROaye+MM86IWNfmzZulQYMGKX4GAICgIpxy2aHNFdzeBKswpA8AACA+OjPfnDlzcr1dwyanZ5S67LLLIv4uiHjuAyB+NEVHUPijSREAAAASrsw2vioCKHzjbQDID984kCtm6gMAJFoQmqEn6zmW2/xLU2pbndhRxu1NABAQzNQH+AvhFKzBkD4AAAAAAIKHcMonym3ipUwmgjMAQRta5YUqHQAAAPgDiQYAALlYuqdpUtbL0CcAgFc0qLPb7U0AEACEU7AClUkAAAAAkBP9tRAEhFMAAAABUHb7Kbc3AQAAICrCKUTFTH0AAMQvCLMSAgAAJArhFFzHkD4ACAYCGwBAIjDMDfAfwikAAHyIIVwAACAvV9bc4PYmACGEUwAAAAAAAHAN4ZSLDm2u4PYmAAAAAADgefsbl3R7E1AIhFM+UG6Td19G+k0BAAAAABBs3k01AAAAAAAA4HmEU8ih0sZMtzcBAAAAAAAEBOEUAAAAAAAAXEM4BQAAAAAAEADTpk2TBg0aSKlSpaR9+/ayatWqXJf95z//KW3btpWKFSvKaaedJq1bt5a//vWvoduPHz8u999/v7Rs2dLcXqtWLenTp4/s2LEj5u0inIJraIYOAAAAAEBqzJs3T4YOHSqjR4+WNWvWSKtWraRr166ya9euqMtXrlxZHnzwQVmxYoX897//lX79+pnLwoULze1Hjhwx63nooYfMvxpmbdy4Ua699tqYty2t0M8OCICfWtR2exMAAAAAAIjbpEmTZMCAASZgUtOnT5d33nlHZs2aJcOHD8+x/GWXXRbx99133y0vv/yyfPTRRybUqlChgixevDhimWeeeUbatWsn6enpUq9evQJvG5VTAAAAAAAAPpaZmSmrV6+Wzp07h64rWrSo+Vsro/KTlZUlS5YsMZVRl1xySa7L7d+/X4oUKWKGAsaCyikAAAAAAACPOnDgQMTfJUuWNJdwe/bskZMnT0qNGjUirte/N2zYkGfYVLt2bTl27JgUK1ZMnn32WbnyyiujLnv06FHTg+qWW26R8uXLx/QcCKcAAAAAAACSoMTWElKsVImkrPvk0VPm37p160Zcrz2lxowZk5DHKFeunKxdu1YOHTpkKqe0Z1WjRo1yDPnT5ui/+c1vTIXVc889F/PjEE4BAAAAAAB41NatWyMqlbJXTamqVauayqedO3dGXK9/16xZM9d169C/M844w/y3zta3fv16GT9+fEQ45QRT33//vSxdujTmqinzODHfA0gAZuoDAAAAAKDwNAwKv0QLp0qUKCFt2rQx1U+OU6dOmb87dOhQ4MfS++gQv+zB1P/+9z957733pEqVKnE9ByqnYrQovYnYpNymxOaLlTZmJnR9iM3eJskp9wQAAAAABNvQoUOlb9++0rZtWzOj3pQpU+Tw4cOh2fv69Olj+ktpZZTSf3XZxo0bm0Dq3Xfflb/+9a+hYXsaTN14442yZs0amT9/vulplZGRYW6rXLmyCcQKinAKAAAAAADA526++WbZvXu3jBo1yoRIOkxvwYIFoSbp6enpZhifQ4Oru+66S7Zt2yalS5eWpk2byquvvmrWo7Zv3y5vvfWW+W9dV7j3338/R1+qvBBOAQAAAAAABMDgwYPNJZply5ZF/P3nP//ZXHLToEED0wA9Eeg55ZJDmyu4vQkAAAAAAACuI5wCAAAAAACAawinkHJem6nvpxa13d4EAAAAAAB8i3AK8JmDjU+5vQkAAAAAABQY4RQAAAAAAPC0CpuOub0JKATCKQAAAAAAALiGcArIA/2mAHjVodoc4gEAQO4WZzR1exOAEL65AgCAlDjRmMAfAFB4rx84z+1NAJBghFMAAAABCOKopgMAALbiWwoAAAAAAJaiUgxBQDgFWGJvkxJubwKAFEmrdcTtTQAAoEC2bKvm9iYACADCKSAXNEMHcEXVDRJUBxuWdnsTAAAAEBCEUwAAWO5InVNubwIAAACQNIRTCKm0MdPtTQAA+JyNjcK9gmo2APgFfZgAfyGcAgAASCACOAD4xeKMpm5vAgAPIJwCoqDfFAAAsQ8ppdk/ACQWFWIICsIpAAAAAAAAuIZwCgAAAPCBH3/8UXr16iXly5eXihUrSv/+/eXQoUN53uf3v/+9NG7cWEqXLi3VqlWT6667TjZs+GWm0i+++EJuueUWqVu3rlmmWbNm8tRTT6Xg2QAAgoRwCgAAAPABDabWrVsnixcvlvnz58uHH34oAwcOzPM+bdq0kRdffFHWr18vCxculKysLOnSpYucPHnS3L569WqpXr26vPrqq2bdDz74oIwYMUKeeeaZFD0rADbasq2a25sAn0lzewMA29BvCgCS3zA8bdN28SOaocMtGi4tWLBAPv30U2nbtq25burUqXLVVVfJxIkTpVatWlHvFx5eNWjQQP785z9Lq1atZMuWLaai6ne/+13E8o0aNZIVK1bIP//5Txk8eHCSnxUSrWR6CTlWL9NX/ZhuLL/G7c3wJBrVwzZUTgEW2NukRELWc7BxbI1r49Wl3saUPA4AAH514MCBiMuxY8cKtT4NjHQonxNMqc6dO0vRokVl5cqVBVrH4cOHTRVVw4YNzTC+3Ozfv18qV65cqO0FACAclVMApGzD/W5vAuB5zWrulPUZNdzeDMCXrqj6Sw+kVCi9vagUK5mcc7gnj/283uzhz+jRo2XMmDFxrzcjI8MMvwuXlpZmQiS9LS/PPvus3HfffSacatKkiRkWWKJE9BNny5cvl3nz5sk777wT97Yiccp9nyUH6xdxezOQJMzUhyChcgoIw5A+APjFwYalk7ZuPw5/8+NzQvJs3brVVCA5F+3jFM3w4cOlSJEieV7CG5jH26vq888/lw8++EDOOuss+c1vfiNHjx7NsdxXX31lGqZrkKZ9qQAbEOAA/kDlFAAAPnWodlEpuz01w33h3aAQ7tAZ9fSSn3vvvVduu+22PJfRPlA1a9aUXbt2RVx/4sQJM4Of3paXChUqmMuZZ54pF1xwgVSqVEneeOMNM0uf4+uvv5ZOnTqZHlUjR47Md7sBAIgFlVPA/0fVFLwy7beezR40aJBUqVJFypYtKz169JCdO3dGLJOeni7du3eXMmXKmGEew4YNMz9Swi1btkzOO+88KVmypJxxxhny0ksvRdyuMzU99NBDpveITh+ujXHHjRtnZnIC4L2gEt5UrVo1adq0aZ4XHYLXoUMH2bdvn5ldz7F06VI5deqUtG/fvsCPp5/xegnvgaWz9F1++eXSt29feeSRRxL+HOF/NN+OnR8rwrQhP5AbvqkAgMem/R4yZIi8/fbb8tprr5khGDt27JAbbrghIlTSYCozM9P0Bnn55ZdN8DRq1KjQMps3bzbL6I+NtWvXyj333CO33367mUbcMWHCBHnuuefMdOE6C5T+/fjjj5vZn4BE8NMwOD89F3hTs2bNpFu3bjJgwABZtWqVfPzxx2Y2vZ49e4Zm6tu+fbsJs/R29d1338n48eNNoKUnNfSYcdNNN5kTEjrLnzOUT48VOoxv6NChpn+VXnbv3u3q80VqbdlWTWzmxyAHCBqG9QFUTcFD035rX5IXXnhB5syZI1dccYW5TmdW0h8ln3zyiRmOsWjRIjP84r333pMaNWpI69atTcXT/fffb5rt6hn26dOnm4qoJ5980qxD7//RRx/J5MmTpWvXruY6/ZGivUU0xHKmGP/b3/4W+lEDAIWdRACJNXv2bBNI6fA7naVPK2uffvrp0O3Hjx+XjRs3ypEjR8zfpUqVkv/85z8yZcoU2bt3rzlmXHLJJebz32mu/vrrr5sg6tVXXzUXR/369WXLli0uPEsAhUUlG2xE5RTgsr1NKG8Nqnim/daz2/rjQpdz6FnwevXqmfU5623ZsqX5keHQwEmnKtcqLWeZ8HU4yzjrUBdeeKEsWbJEvvnmG/P3F198YQKsX/3qVwnbBwCAxNGZ+fTkxcGDB83JjFmzZpnh3w49yaBD9i677DLzt54Eeffdd83QcK221SbtGnDpjH0OPanhDPULvxBMAclDJRiCiMopBB5VUygoDXfCaa8mvaRy2m+9XiufNNQKp0GUcx/9NzyYcm53bstrGX2OP/30kxnSoTNE6d8afhUrVswMF9ReIzoUEUjkcLi0TdvFyxjSBwB2BDo3ll/j9mYAiBPhFCIqeCptzJQgIZjyl7LfFZViJRNfEHry2M/rrFu3bsT1OpW2nlHOTkMd7c+U35A+2/397383Z9D1LPzZZ58d6k2lZ9q1KS5S60idU1JmW1FXZokrt/mnlD8ufsFMfQCAIPYgK/c9k/AECeFUjLrU2yiL0n8pdUZ8gVDpr7x9ltxGBxszXXyy6XCH8Gm/c6uaSua033q9Dr3QGZnCq6d0SIZzH/03e18oZza/8GWyz/Cnf+vz06oppTP8adCmzXSVDhX8/vvvTfNcwikgGIEogNSrsOmY7G8cf2W2zX2Orqy5we3NsB5D+hBUhFMILKqmECsNbsLDqbym/dZLfsKn/W7Tpk2Bpv3W5YoXL256QWmjW6XNbXWWJV2fs14dfqfBlzNsUGcD1G1v3rx5aBntMxJOl3HWobRhrva/CqfD+3T7gETy8tA+hvQBgD0Y2gd4Fw3RAcBD035XqFBB+vfvb6bzfv/9902w1a9fPxMq6Ux9Sqf71hCqd+/epon5woULZeTIkTJo0KBQtdcdd9xhphC/7777ZMOGDfLss8+aYXxDhgwJbd8111xjQq533nnHNL594403ZNKkSfLrX//alf0FAAAKr2Q6k/EAsA+VUwjk0D5bqqaYqQ+xTvutJk+eHFr22LFjZpY9DZfCq5vmz58vd955pwmtTjvtNDMMb+zYsaFlGjZsaEInDaOeeuopqVOnjsycOdOsyzF16lR56KGH5K677jJVWBqY/f73v5dRo0alZN8gMQ7VLiplt1PtBgCA7VIxpE+HVwI2IpwCAAum/c6NM+13uFKlSsm0adPMJTf169fPMWwvO51K/PPPP8/19nLlysmUKVPMBUg2Lw7t88qQPg0oASAoGNoHeBPfVhA4tlRNAQi2tFq/VMPZjtniAACpmqENQDARTiFQIRHBFADASwgGAX8osWGb25sAyzFLH4KOcAoAAFjBK8PkvLatqeKlakAA7khVvyOCHvvQiB9JCae0z4n2QdG+JzrduTOLVH7mzp0rRYoUkeuvvz6eh4UPpaqSSR/HtqopmqEDP+OYAq+FPl7YRiCIOJ7Aq1IVpiUiHGR4J6wJp+bNm2emMB89erSsWbNGWrVqZWZ30pmc8qLTkP/pT3+Siy++uDDbC8TMtlAqGQ42jn8mrrIN9yd0W4BYcEwBACRCkI8n5b6PnDgF3qqe8sp2AtaFU5MmTZIBAwZIv379pHnz5jJ9+nQpU6aMzJo1K9f7nDx5Unr16iUPP/ywNGrUqLDbDJ9JVnhkY7UUgEgcU2JzpM4p12ZrS2XvI5srk1K5bYnY58zUh6DgeAIvBj+2bx+QSjF9Y8nMzJTVq1dL586df1lB0aLm7xUrVuR6v7Fjx0r16tWlf//+hdta+FaiQyRCKcB+HFPgtYDKxm2yLQgF3MDxxFtS1XfKQQAEeENaLAvv2bPHnGGoUaNGxPX694YNG6Le56OPPpIXXnhB1q5dW+DHOXbsmLk4Dhw4EMtmwqPCA6XSX20v9DpsRr8pIDXHFI4n3qZhUNqm+I4HiRakYArwGn6jxNec+li9zLj6DTWos1u8RgOqG8uvEZukOjRLdSgIxCqptd4HDx6U3r17y4wZM6Rq1aoFvt/48eOlQoUKoUvdunWTuZmwUDxD8rwSTAFI3TGF40lipXJon4NQCECi8RsFbqOaK/EqbPolOEYAKqf0w7tYsWKyc+fOiOv175o1a+ZYftOmTabJ4DXXXBO67tSpn8vE09LSZOPGjdK4ceMc9xsxYoRpaBh+VoIP/9RV9FTaGPtZlGQhcAL8KxXHFI4n8GpA5kYQCHgVv1G8R6t4rqwZvarN79VTXg6mmKkP1lROlShRQtq0aSNLliyJ+CDXvzt06JBj+aZNm8qXX35pymWdy7XXXiuXX365+e/cPsxLliwp5cuXj7gAAPwlFccUjif+4Gb1FJVbgP34jYIgBENBwyyUwRNT5ZTSswV9+/aVtm3bSrt27WTKlCly+PBhMzOG6tOnj9SuXduUvZYqVUpatGgRcf+KFSuaf7NfDwRFovtNHWxM01p4F8eU1NFZ28pu9+7nhRv9p7weTDFTH4KE4wm8UEHlVjjmdr8p7XEGJDycuvnmm2X37t0yatQoycjIkNatW8uCBQtCDQjT09PN7BgA/KlLvY1ubwJ8hGOK9+hws3Kbf/J9QOVmMMWQPiB2HE9Sx6tN0d1G1RaQ4HBKDR482FyiWbZsWZ73femll+J5SACAT/npmNKs5k5ZnxE5W1Re0modkRM7ysT0GEfqnJIy2/iBBQB+Pp4EgRt9p9yqniKYApIUTsEeOqSr3CZ+pMBOvSstd3sTAPiMU9GUrAoqrw/lSwQNQFMR5AKAm5zAKNkhldvBVKKG9NEMHclGqgF4uN9UYZVtuN/tTQDgQTYMO0tGiEQwFT+tAgQAL0pWeKTrdTuYAryEcMolhAIAgFTzW4NsDZMSESglaj1+Cf4ABIMNTardbtSdrCCJUAo2mzZtmjRo0MBMDtG+fXtZtWpVrsvOmDFDLr74YqlUqZK5dO7cOc/l77jjDilSpIiZlCJW/vqWCgAAAifecMmmUCrR/BZEAshbue+z3N4EXyhsqES1FGw3b948M7vp6NGjZc2aNdKqVSvp2rWr7Nq1K9d+fbfccou8//77smLFCqlbt6506dJFtm/P2V7hjTfekE8++URq1aoV17bxzQXw8JA+7TkGAIgtbPJzKAXAHypsOiY283P/oXgCJltDKVsq02xTYsM2CapJkybJgAEDpF+/ftK8eXOZPn26lClTRmbNmhV1+dmzZ8tdd91lZkBt2rSpzJw5U06dOiVLliyJWE7Dqj/84Q9m+eLFi8e1bTRER9QQpdLGTLc3AwBgMR1+Vm7zT2IjrwZPDOkDEERuztqXFxvDJi+yYfhoEBw4cCDi75IlS5pLuMzMTFm9erWMGDEidF3RokXNUD2tiiqII0eOyPHjx6Vy5cqh6zSs6t27twwbNkzOPvvsuJ8D4RQAAAAAAD6SyKopP1fKpUK5rVlSrERyht6ezPx5vTrcLpwO2xszZkzEdXv27JGTJ09KjRo1Iq7XvzdsKFhAfP/995thexpoOSZMmCBpaWnyxz/+sRDPhHAKCOQsfQC87UidU1JmW9G4exGV3X7K99VTQa6aot8UAMDL6KEWu61bt0r58uVDf2evmkqExx57TObOnWv6UGkzdaWVWE899ZTpX6WN0AuDby8AAAAIBZ8AkOpqGnojAYWjwVT4JVo4VbVqVSlWrJjs3Lkz4nr9u2bNmnmuf+LEiSacWrRokZxzzjmh6//zn/+YZur16tUz1VN6+f777+Xee+81MwLGIlDhVO9KyxOyni71NiZkPQAApNU64vYmAAAAHwla2Gf7BAK2KFGihLRp0yaimbnT3LxDhw653u/xxx+XcePGyYIFC6Rt27YRt2mvqf/+97+ydu3a0EWH/Wn/qYULF8a0fQzrQ1Q0Rbd/SF9hZ+or23B/wrYFQHAxtK/wvN4InYAV8Haz6mP1+M6P3NFvyl+GDh0qffv2NSFTu3btZMqUKXL48GEze5/q06eP1K5dW8aPHx/qJzVq1CiZM2eOqYTKyMgw15ctW9ZcqlSpYi7hdLY+rcRq0qRJTNtGOOUDGlKU2xSoIjgAQCEksu8U7EK/KQBeZeusfYCf3HzzzbJ7924TOGnQ1Lp1a1MR5TRJT09PNzP4OZ577jkzy9+NN96Yb8P1wiKcApLIb43QGdIKIBqqp4JbNQXAribSB+sXriFxPFU1DersTuljwjtD+rQyD/YZPHiwuUSjzc7DbdmyJeb1x3Mfxek1AAASqFnNyCaTyULjagCA39gUrABILcIpAAAApCzwTFWACwBBk+hwj35TSCXCKcCDQ/oK2wwdQMFdUdWf/S8S3ZuI4Wnu7zP6TQGIB0OvANiAbzEusn22NL/1SwIAAAAgVlfXMLQv2PtNe6chmAingCQg2AMQRFRPFRz7quD8Wr0I5KfCpmNubwIApAzhFBBAtlftAUGTVuuI25sAAIA1/FIFFOSKOIaLIlaEUz5BD6LgVE3xWgNIVAPrZPQooiLInX3kVr8pglUAcB9hHvyAcAoAACDgUjVTHwB/SsasbgQuBcN+gl8QTiFP9E6KDfsLAKieygv7BgiuEhu2WdtMmiFYANxGOAUAQIAlazgYIUxO7BMk248//ii9evWS8uXLS8WKFaV///5y6NChAt03KytLfvWrX0mRIkXkzTffjLgtPT1dunfvLmXKlJHq1avLsGHD5MSJE0l6FsAvqApyZ/8koxIOyA/hFOChqin6TQEAbOk3BftoMLVu3TpZvHixzJ8/Xz788EMZOHBgge47ZcoUE0xld/LkSRNMZWZmyvLly+Xll1+Wl156SUaNGpWEZwDkREDlPfFW4sVT+ceslv7BtxkgYJipD7BTvI2lbe4VRKWQN/aFze8hFNz69etlwYIFMnPmTGnfvr107NhRpk6dKnPnzpUdO3bked+1a9fKk08+KbNmzcpx26JFi+Trr7+WV199VVq3bm2qq8aNGyfTpk0zgRXgoNomtQjt4DeEUz6SrKoa+ijlj30EwMuovAluMFUYzNRnlxUrVpihfG3btg1d17lzZylatKisXLky1/sdOXJEbr31VhM21axZM+p6W7ZsKTVq1Ahd17VrVzlw4ICp0gJSgSAmdfuDkBFu4dtonLrU2+j2JiBgwZTbQ/p4zwMF16zmTrc3wRp+DWZsQbDoXRruhF+OHSvc0JSMjAzTDypcWlqaVK5c2dyWmyFDhsiFF14o1113Xa7rDQ+mlPN3XuuF9ySiKXoygw0CKsDf0tzegKDTIVaHNldwezMAAEhqQFVu808SRIRz3gxuT/vhlKQVT85JoRPHf15v3bp1I64fPXq0jBkzJsfyw4cPlwkTJuQ7pC8eb731lixdulQ+//zzuO4PO2nfnoP1c/YPgz/YXjXFzI+IF+EUClwdVGkjfQWyYzgfAFt6BpXZVrTQFThltyevQjPIAZXNVVP0m3LP1q1bzax6jpIlS0Zd7t5775Xbbrstz3U1atTIDMnbtWtXxPU6o57O4BdtuJ7SYGrTpk1mOGC4Hj16yMUXXyzLli0z9121alXE7Tt3/hwy5rZeIJnBzJU1N0hQUT1WeCU2bHN7E5ALwinAA8GU20P64tG70nK3NwEAXEXVFPKiwVR4OJWbatWqmUt+OnToIPv27ZPVq1dLmzZtQuHTqVOnTIP0aLQq6/bbb4+4TvtLTZ48Wa655prQeh955BETfDnDBnU2QN325s2bF+i5In46E9n+xtGDS1tp9U2DOruTtv6gB1R+Fc9MffAXGhX4jBdDDKQOM/UBcLN/UZDCmiA9V9ihWbNm0q1bNxkwYICpdPr4449l8ODB0rNnT6lVq5ZZZvv27dK0adNQJZRWPrVo0SLiourVqycNGzY0/92lSxcTQvXu3Vu++OILWbhwoYwcOVIGDRqUa7UXvIshWcGtmqIROtxGOIUCYwjbL9gXAJIhCLOfBSG0ScVzdLsRehDeq140e/ZsEz516tRJrrrqKunYsaM8//zzoduPHz8uGzduNDP0FVSxYsVk/vz55l+tovrtb38rffr0kbFjxybpWcAPkh10BG14m1eeL+EmCoNhfUCMCKYA+LXvVKr4uf+Ul8I3+k35j87MN2fOnFxvb9CggWRl5T10Jtrt9evXl3fffTch2wgkSlCG96UimKJqCjbwxrdYWINgJvUYqgkglVJVkeOlEMe25+R21RQA+wWlf49XKori5ffnl4iebPCPwH27oUlz4QU5oArycweC7Iqq/j8z6wY/BVR+ei4Agi1RQ7NSVY3j1wDHr88LyE3gwqkgNKlORaVNEEOaID5nAMGUysocP4Q6fngOAOBlfgtyUvl8EhUiFibUDEqlH/JGOAVYHEwlMmgsTAjapd7GhG0HEBTNau5M+WN6tYcQ4U7qg0OvvlcAeEsqexn5JaDyy/MAYkU4hbgFpZIoKM8TgB2COguaVwMqr263VwJbhtQC7vDqrGteD3ZSvf00QodNCKdQKH4Pbvz+/ADApqbbXgp6dFtTvb22NEIPaoAKwBu8HlABQWXHtxyPYqiTvwMct58Xs/QBCOJwLS8EVF7YRgD+Ee+MZLb08XGjOsdrAZVur9e22Q+VdrAL4ZRPpTrYcDvISTS/PR8A8FKljhtVSbZvVyJfC68HmADgp8DHrW1kSB9sQzjl0xn73Ap0/BDq+OE5AIAf2BJQ2RqWAYBXqmHcDEJsDai8Ep4BqZKWskdCYGi4U2ljpniNTaFUoivf/BB+AoitMqbMtqIJq9gpu929ShsnFCq3+SdXH99NtvSaAgCvckKgK2u6P8mCDYFUIsPCwoaY8Q4/jXe4K+zFtx0khdeqqLy0rQD8j4bT7lcv+bVaqrBD+nhvAoVTYsM2CSobhpG5Wa1EpRSQNyqnfEyrb8ptcjd/tL2KysZQikbogH80q7lT1mfUEK9zu3oqXHhglOhqKhvDKL9UTen/FwCknlalHKxfpFBVMcfq2ftd3guVVLYFUjaEhEA0hFNIWQBkW0hlYzAFADYO7bNV9jApnrDKxkAKAPxKg5EGdXaLLbIHR4kKq2wLpJKFWfqQSP7+1uoxfu8LZMtQP1u2I1VVU4V9X3WptzFh24KcfvzxR+nVq5eUL19eKlasKP3795dDhw7leZ+jR4/KoEGDpEqVKlK2bFnp0aOH7NwZWZWQnp4u3bt3lzJlykj16tVl2LBhcuLEidDtP/zwg9x6661y1llnSdGiReWee+6J+livvfaaNG3aVEqVKiUtW7aUd999N0HPHF7jhQoeZyheLJcg7XNm6QO8y0/9dWyu3HGG3sUaLoXfz+ZgyrZ9H2+/KfgTlVM+Z8PQPlsqqWwNpBBsGkxpULR48WI5fvy49OvXTwYOHChz5szJ9T5DhgyRd955xwRHFSpUkMGDB8sNN9wgH3/8sbn95MmTJpiqWbOmLF++3Ky/T58+Urx4cXn00UfNMseOHZNq1arJyJEjZfLkyVEfR+97yy23yPjx4+Xqq68223T99dfLmjVrpEWLFknaIwjv7XNiRxmxiU3D+/zOxjCQflNAMPl1aF9+bA6Z/BBMAdnZ980HgeFUMCUzNErFYyQKvaaCZ/369bJgwQKZOXOmtG/fXjp27ChTp06VuXPnyo4dO6LeZ//+/fLCCy/IpEmT5IorrpA2bdrIiy++aIKkTz75xCyzaNEi+frrr+XVV1+V1q1by69+9SsZN26cTJs2TTIzf/5y2aBBA3nqqadMaKUBVzR6e7du3UzVVbNmzcw6zjvvPHnmmWeSuFeQSFTKAABsRFDifQzpQ6IRThUSQ54SHyIVJkhK1HqAaA4cOBBx0eqjwlixYoUZyte2bdvQdZ07dzbD7FauXBn1PqtXrzYVVrqcQ4fd1atXz6zPWa8OwatR45dG3F27djXbvG7dupi2L/xxnPU4j4NgsrGix2+SsY8JKoHgYugU/BYGxjvMNcizZXoBw/oCwMahffkJWrCUrKopv/cxy67it5mSlpb49/qJEz9XG9WtWzfi+tGjR8uYMWPiXm9GRobpBxUuLS1NKleubG7L7T4lSpQwoVY4DaKc++i/4cGUc7tzWyzbF209sawD/sTwvuQh/AMQlKF9tjVH9ytbgylCU2QXyG9AvSstd3sTAHjQ1q1bzbA65zJixIioyw0fPlyKFCmS52XDhuRPXQw7NKsZ2aw+1T1+qJgBANjK1uAEeWNIH5KByinLaKXLoc3R+7/An/zYa8qvAbDOqKeX/Nx7771y22235blMo0aNTMPyXbt2RVyvM+rpDH56WzR6vfaN2rdvX0T1lM7W59xH/121alXE/ZzZ/HJbb26PlX0WwPDHCZorqm6QpXv81Ry1MKie8k7VVCICysIEpYUJaAEA8SP8g5cEsnIKQMHQUy0+Ogue9oHK66JD8zp06GBCJu0j5Vi6dKmcOnXKNEiPRhug66x7S5YsCV23ceNGSU9PN+tT+u+XX34ZEXzpbIAarDVv3rzAz0PXE/44znqcxwEYgpY47MvogTCAwvfZSdQQqmRVyxCgJAf7FV7DN6GA8GN1DvIWtH5TXqQz4OlseAMGDDCVTh9//LEMHjxYevbsKbVq1TLLbN++3YRZTiWUzqzXv39/GTp0qLz//vsm2OrXr58JjC644AKzTJcuXUwI1bt3b/niiy9k4cKFMnLkSBk0aJCULFky9Phr1641l0OHDsnu3bvNf+ssf467777bzCb45JNPmmGI2l/rs88+M9sIb2FoX3Dx2gPwAoIU72BIH5KFYX2AiwgNMXv2bBP2dOrUyczS16NHD3n66adDt+vMfFoZdeTIL0NqJk+eHFpWZwzUGfSeffbZ0O3FihWT+fPny5133mlCq9NOO0369u0rY8eOjXjsc889N/TfGnLNmTNH6tevL1u2bDHXXXjhheY6DbYeeOABOfPMM+XNN9+UFi1aJHmvIPtwqhM7yoitGN5XeFRNAQhyY3QEL+yjGTqiIZxK0NCnRelN3N4MeAzBFJTOzKcBUG4aNGggWVmRB/BSpUrJtGnTzCU3GjK9++67eT529vVGc9NNN5kL/FFBU2ZbckIQAio7g6lEVU0lojE/AOSH2fvsD6ZsqJoqzPBW2I1TdQEajkUYEhwM6QPsEoSG0FT/xI59BgRTiQ3bPF2tksyAwvaKHwDJw7ciwAUEhQDcqFxJdv8hwhZ72NJrKgjBLIDEIqDyd9UUQ/qQG75FBgyhCAqKmfoAxIOAyl/7iSF9gF1sGdKU7OFdBFSxY5/B67zxzSiAGJblX8kOCHnvAPBCRU2QJTuY4jUG4IeqFcIWe/aVDb2mvDqcFgVHOBVAVE+5h30PIAgVLF6pCnID+waAX6QisCCgyh/7CH4R2G9IvSstd3sTEDBBCab4/xZgf++dVFTWEMK4s0+omgLgN4Qv7u6bRIaQXqrcQ+rxzTGg/XmCEpQAANwNYwipfubF/eBmtd4VVTe49tiA3yUyIEjVcC8CqpyCuE9s6bnmddOmTZMGDRpIqVKlpH379rJq1apcl123bp306NHDLF+kSBGZMmVK1OW2b98uv/3tb6VKlSpSunRpadmypXz22WcxbZf3vikFCL2D/CNVYSDvGQA2Vth4MZjxYkBnW9WUTdWCgJ8E9Qd6EMMYt/eFH3pNIdK8efNk6NChMnr0aFmzZo20atVKunbtKrt27ZJojhw5Io0aNZLHHntMatasGXWZvXv3ykUXXSTFixeXf//73/L111/Lk08+KZUqVZJYBPfbIqieShEv7mevVQICQanm8FLfqeyCGFAF8TkDCJ5UBhhBD6j0+Xt1HzCkzw6TJk2SAQMGSL9+/aR58+Yyffp0KVOmjMyaNSvq8ueff7488cQT0rNnTylZsmTUZSZMmCB169aVF198Udq1aycNGzaULl26SOPGjWPaNr41AT4JpqiaAmB7pU2QwppUP9dEv5ZeDkIB+Dso8Go447XnTdWU/2RmZsrq1aulc+fOoeuKFi1q/l6xYkXc633rrbekbdu2ctNNN0n16tXl3HPPlRkzZsS8nuB8S4RvqnoAwKsY5hSMPlR+f34A4HaQEbSAKmjPF7E7cOBAxOXYsZzDf/fs2SMnT56UGjVqRFyvf2dkZEi8vvvuO3nuuefkzDPPlIULF8qdd94pf/zjH+Xll1+OaT1pcW8BUlYNc2hzhaQHVOU28UU60Qj+ACSDVrSc2FEmoRU3ZbYVdSXAKbvdX5+TboVSVE0B3lNiwzbJbFrH7c3wRWDToM5u8Su3QqlEh42JqNTzcq+18puPSVpakaSs+8SJn/eLDqsLpz2lxowZI6lw6tQpUzn16KOPmr+1cuqrr74yQwb79u1b4PWQSCSQl/v0EKR4e38ypA+AF/mpisovzyNRqBIEkisRP9QTPbTPrWFgfq0q8uvzQnJs3bpV9u/fH7qMGDEixzJVq1aVYsWKyc6dkcdo/Tu3ZucFcfrpp5v+VeGaNWsm6enpMa2Hb1IIIaBKDK/vRy+HrAC8Ocubl4MdtwM2t187ALCBlxuF2/Zc6DXlTeXLl4+4RGteXqJECWnTpo0sWbIkoupJ/+7QoUPcj60z9W3cGPkb8ptvvpH69evHtB7vfhsMkFRWxXg9WHGbG/uPqikgeJIx7MrtkMPtkCceXtvegmBIHwAvBxteD6i8vv1+a77vR0OHDjXNyrUf1Pr1601/qMOHD5vZ+1SfPn0iqq60ifratWvNRf97+/bt5r+//fbb0DJDhgyRTz75xAzr0+vnzJkjzz//vAwaNCimbaPnFHKgB1V8CPYAIHGBj639qGwKpNwOFAH4Izg4WL9IwgOqY/UyxS1e7EVlSyjldriYrGGs2uMNP7v55ptl9+7dMmrUKNMEvXXr1rJgwYJQk3Qdiqcz+Dl27Nhhekg5Jk6caC6XXnqpLFu2zFx3/vnnyxtvvGFCrbFjx0rDhg1lypQp0qtXL4lFoMOp3pWWy1/3Xuj2ZliJgCo2BFMAYunFsz4jcpYUW7jVHN0LIZVNoZTtwRT9pgDYFvjYGlTZEkolK5iiaspOgwcPNpdonMDJ0aBBA8nKyv91vPrqq82lMOz6puUDyerX48bQLQKXgu0jN/cTQ/qA1Lui6gbx8/Ar20IPZ7ifG+GQm4/txmvEkD4Afq3AcbuPU7RtsWV7bHy9EEyBrpxC/pzghSqqYIR3NEMHYFsFVbjsIVGiq6psC6EAIL+hTvsb52x6bMPQPhuG99lWTWVTGAXYiHAKBcIwP/uCKaqmAGily4kdZSSoooVJBQ2svBpEBaFqypbqRAD+DKjyCosSFVh5KYhKVtUUQ/oQK29+Mwsot8MIt4ew2YJ9ACAIPXlsG94Xz1C8vC5e5NXXBKnz448/mga0Oo14xYoVpX///nLo0KEC3Vd7ivzqV7+SIkWKyJtvvhlx26effiqdOnUy66xUqZJ07dpVvvjiiyQ9i+CwqUkzQULOIXeFuXiFF4bzFbYZOrzDm9/OLOf3oVFBDWdsCufcDioB2COZFS+EIfZI5muRyPeQF4JXP9Ngat26dbJ48WKZP3++fPjhhzJw4MAC3VdnVtJgKjsNt7p16yb16tWTlStXykcffSTlypUzAdXx48eT8CzgN14IQJBYhJ2IB+GUx9gSStgU1CRbUJ5rIkJVnQETgL8QUAHesH79ejMd+MyZM6V9+/bSsWNHmTp1qsydO9dMBZ6XtWvXypNPPimzZs3KcduGDRtMRZZOD96kSRM5++yzZfTo0bJz5075/vvvk/iMkOqqkmQGCgRU9uE1gW0CH07xY7pw/B7a2Pj8bAkoAdjDpn5BSDwCQn86cOBAxOXYscKFDCtWrDDD7tq2bRu6rnPnzlK0aFFT8ZSbI0eOyK233irTpk2TmjVr5rhdA6kqVarICy+8IJmZmfLTTz+Z/27WrJmZYhwoKMKQYLwWiQw5GdIXLDRER0IDHL80TbcxlALgLzr8aX1GDfECW2fvC4JkB1MM6Yuu3JafJC0tOVUkJ04cNf/WrVs34nqtRhozZkzc683IyJDq1atHXJeWliaVK1c2t+VmyJAhcuGFF8p1110X9XYdwrds2TK5/vrrZdy4cea6M888UxYuXGjWD39J1sx9XmiQHhRBCwlt6u2GvPFN04N9p2yunPH6EDjbt9/m1x4IEhtnE0t29RTVO6nHPve3rVu3yv79+0OXESNGRF1u+PDhphdUXhcdehePt956S5YuXWr6TeVGK6W0sfpFF10kn3zyiXz88cfSokUL6d69u7kN7qO6BAUVtGAK3sLpDiSFE/B4oZLK5jAqVfzexB9AYlBB5a9gysbhoDYGv8miM+rpJT/33nuv3HbbbXku06hRIzMkb9euXRHXnzhxwvSLijZcT2kwtWnTJjMcMFyPHj3k4osvNhVTc+bMkS1btphhgzpEUOl1Omvfv/71L+nZs2cBni28hOopf0pFMEUjdBQG4ZRHaQXNoc0VxHY2D/nzWihF1RTgP4ke2qdhw4kdZSSZCKiSj4ophKtWrZq55KdDhw6yb98+Wb16tbRp0yYUPp06dco0SM+tKuv222+PuK5ly5YyefJkueaaa0I9qTSUCp/Jz/lb1w3Eg4AqtbxYMUVFYPDw7RIpHzLnZihkwzbEg2AKgE0IT7y/bxNdNeWnflNepQ3Ku3XrJgMGDJBVq1aZ4XeDBw82lU21atUyy2zfvl2aNm1qbldaUaVD9MIvql69etKwYUPz31deeaXs3btXBg0aZGYEXLdunfTr18/0m7r88stdfMb+YGs/nFRUwHgxMPGiVO1nqqZQWIRTHh4q5eXAIjwkSlZQlP0xvBZIpQpD+gB/SdVQLQKqxGOforBmz55twqdOnTrJVVddJR07dpTnn38+dPvx48dl48aNphqqoHR9b7/9tvz3v/811Vk63G/Hjh2yYMECOf3005P0TBCUKhMCquQimIKXMKxPRHpXWi5/3Xuh25sRaHkFR3kNBwxC4OSVEFL/fwTA37P2ZccQP28GUzb2mkJi6Mx82g8qNw0aNJCsrLx/REa7Xaun9IJgSXbvKQdD/JLDy8GfV8NWFE5c3yinTZtmDm6lSpUyY9id0uBoZsyYYc6waNNEvXTu3DnP5eHP4CLRFVBBqYQKwusLcEzxdvhAtU/heT2YYkgfbMHxxNtBipfDFNukcl/aXDVl67BZJCicmjdvngwdOlRGjx4ta9askVatWknXrl1zzA7i0Fk+brnlFnn//ffNLB9169aVLl26mDHvAIBg8/IxJUizihUkXCGkih37DUgcLx9PbK42SXXwQEBVeOxDBCacmjRpkmm0qI0QmzdvLtOnT5cyZcrIrFmzch37ftddd0nr1q3NmPWZM2eamT2WLFkiQZCKfj5U1/hTKl5X+k3BbRxTkld54sbQLYIWu/eV7cP5CHxRGBxP/INwxTv7LhnhJUP6giumcCozM9NMT6tlr6EVFC1q/tYzDgWhDRi1GaOOic/NsWPH5MCBAxEXIEgIHBEEqTimcDxJPaqBghVMMaQPNuA3ir+qpxQBlf3DIm0ezocAhFN79uyRkydPSo0akY1b9e+MjIwCreP+++8309mGHzyyGz9+vFSoUCF00TJb5I0wwz9S9VpSNQW3peKYEvTjiZuVMgRUORHcAcnh9d8o9MWJjj5UBcM+gl+kdIqdxx57TObOnStvvPGGaVSYmxEjRsj+/ftDl61bt4qXEQIAgDvHFC8dT5JVgeJ2QEUY8zM394Ptw/kAtwX1N4pXqmQIX+wL75L1fmBIX7ClxbJw1apVpVixYrJzZ+QXaP27Zs2aed534sSJ5oP/vffek3POOSfPZUuWLGkuqdS70nL5694LxesVN4c2V3B7MxDACjj9/w8Qq1QcU9w4nthIw4kTO8q4GsyU2ZbS82HW8HM4x5A+2MLPv1Hi/YG/v3HJpAQSB+sXETc4IcyxepmuPL5tCOzgRzF9UyxRooS0adMmolGg0ziwQ4cOud7v8ccfl3HjxsmCBQukbdu2hdti+DLcQGpfO6r5YAOOKcH6sR+0Kipbni9VUwgCjifB6TMU9KF+Njx/t98DBcVwWe+J+TSmTtE6Y8YMefnll2X9+vVy5513yuHDh83MGKpPnz6m5NUxYcIEeeihh8xMGQ0aNDDjvvVy6NAhCZJUhgEEVN7Da4ag8voxxUuzi9kSUtgS2gTh+dnymvvt/0uwk9ePJ4nm9+FRNoQ0QXy+yQym/P6eRYKH9ambb75Zdu/eLaNGjTIf4Dr9qp5tcBoQpqenm9kxHM8995yZQePGG2+MWM/o0aNlzJgxYhM/DO1zMMTPOwimEGR+PqbYyO3hfeGcAMcvw/1sCaRSFUz5ucoP3sTxJHXcHN4XtOF+NgRSXquYQoDCKTV48GBziWbZsmURf2/ZsiW+LUOhEVDZz41giiF9sA3HlJw/+tdnRM445deAKnuo47WgyrZACgg6Lx9PdAhSZtM64hU2BVR+DKlsCqWAVPHWt0CPcyMUoCrHXrw2ANxi63AvZ0iczaGPF7aRqikAqRgmZWMljS3D3wqz7TZuf7Jfa4b0Ie7KKXgLFVT2cSuYomoK8IZkV0/ZWEGVXfbwx82qKpuDKK8EjwD8ybYKKkf2gMfWiiobgygvhJDwJyqnovSd8mM4oGEIlTp24HUAALsrlsIfi2AqElVTgLekoiLFC+GFLVVJ4dvh9rbY8tom4z3KTH3eROVUwFBFFdxQKlnBaLIDXcALs4wt3dM04euleip3eQVGBa2w8lLo5PeKKWbqA5BK0UKhZFVWeSGA8nLoCH8hnHIpJFiU3sS1xyegCl4wBQB+C6iCEjrZFExRNQUkl9eaontheF8QQiQvB1P0mkI4hvUFFGFJsPY1vaYA+LXqJuh47QDYEgBQaQOgMAinAjxMiT5Uycf+BYIhWcOSUlmpQsjhPal8zaiaAlAQBFTe5/WqKfpNeRfhlEtsqmQhpEo89ikALyKg8g6/vFb0mwLEd8OnCKi8SV83Xju4iXAKIYQp/tyPNgWhAOyvWPFL6OFnqX6NqJoCUscvVR+EHN6S6teLXlOIhnDKxaF9NoYGVPzEL4j7LihDYAG3EVDBwWsDwCuBAAGVN/A6wRaEUy6zMaAKatDix31l6/sL8CO/DU8iBLHv9XDjNaFqCvAXAiq4/fpQNYXcEE7Bs8GL22zfNwRTgL+4ERIQUNmB1wGAlxFQ2cmPr4tfhsUGFeGUBUOWvBAiOEGMzWFMqrAfAAQtoCIccY+b+z7Z7ze/VRsCXvmB7UblCs227eLWa0HVFPJCOIWYBTGc8Vo454XAE/AjP//YJqBKPfY5AL8hoHIXISFsRjhlCS+GCV4LbILy/FL1XqIZOuAON3sAUUUVnP1MrynA39ysYCEcCeZ+p2oK+SGcygc/wGMPcrwW5oTzw3MAgGRzOzjxMxv2LcEUEIzeOW4HVG6HJUHi9r5OxXuNflPeRzhlES9WT/kh5PHStgbpPQTA7vDAhuoePwna/vTzEFgA3glN/I4QEF5COGUZP4YL2auq3AyBbNqWRPPjeycIfvzxR+nVq5eUL19eKlasKP3795dDhw7leZ+jR4/KoEGDpEqVKlK2bFnp0aOH7NwZGVakp6dL9+7dpUyZMlK9enUZNmyYnDhxInT7Dz/8ILfeequcddZZUrRoUbnnnntyPM6MGTPk4osvlkqVKplL586dZdWqVQl89v6Uqh/dNgRUQQxV/L7/bHlfAQjOUCsCFH/vUxveY/AGwqkCYGhfakKiRIRGyVinFxBMeZcGU+vWrZPFixfL/Pnz5cMPP5SBAwfmeZ8hQ4bI22+/La+99pp88MEHsmPHDrnhhhtCt588edIEU5mZmbJ8+XJ5+eWX5aWXXpJRo0aFljl27JhUq1ZNRo4cKa1atYr6OMuWLZNbbrlF3n//fVmxYoXUrVtXunTpItu3b0/gHoBf2Bay2M7G/ZWqYIqqKcCuYUq2hAc2BSpeZds+TNV7iyF9/pDm9gYgetCwKL2JBJ2fwySvI7BNjPXr18uCBQvk008/lbZt25rrpk6dKldddZVMnDhRatWqleM++/fvlxdeeEHmzJkjV1xxhbnuxRdflGbNmsknn3wiF1xwgSxatEi+/vpree+996RGjRrSunVrGTdunNx///0yZswYKVGihDRo0ECeeuopc/9Zs2ZF3b7Zs2dH/D1z5kz5xz/+IUuWLJE+ffokYY8gnjBhfUYNsYkTuJzYUcbtTbGSbYGUg4opALZwwpWD9Yu4vSmeYVMgZVvoCe+gcgrwOKqmUufAgQMRF60+KgytRtKhfE4wpXTonA6zW7lyZdT7rF69Wo4fP26WczRt2lTq1atn1uest2XLliaYcnTt2tVss1ZpxevIkSPmsStXrhz3OoIilZUhtoYKNlYGucnm/WHrewhAsIME26qAbMQ+gp9QOWUpqqdQEARTkUp//YOkFS2R8PWeOJVp/tVhbeFGjx5tKpHilZGRYfpBhUtLSzPhj96W23208klDrXAaRDn30X/Dgynndue2eGnllVZzhQdjQH7CA5kgVlPZGki5hSF9gN0B1f7GJcU24eEL1VQ/sz2QSmXYyZA+/6ByyuJhTAQPsPH9EeQhfVu3bjXD6pzLiBEjoi43fPhwKVKkSJ6XDRu89QPtsccek7lz58obb7whpUqVcntz4NHKF5urh5LxPL3wXL3y3gGCih/ekYJeKeSF529jFR68gcopy1FBhWgILt2hM+rpJT/33nuv3HbbbXku06hRI6lZs6bs2rUr4nqdUU9n8NPbotHrtdH5vn37IqqndLY+5z76b/ZZ9ZzZ/HJbb160/5WGU9rD6pxzzon5/ghu/6kgVVN5IYjKjmAKgFeqp4JcTWV7GBWOYAqFQTjlAQRUsCWYCnLVVCx0Fjy95KdDhw4mZNI+Um3atDHXLV26VE6dOiXt27ePeh9drnjx4qYpeY8ePcx1GzdulPT0dLM+Z72PPPKICb6cYYM6G6AGa82bN4/puTz++ONmXQsXLozojYWCDV9auqdpSh/TSwFVbqGOV8IqL4ZRbgdTDOkDvMErAZVfgyovhVFuB1NUFvoLw/o88sOcShko3gf+ojPsdevWTQYMGGAqnT7++GMZPHiw9OzZMzRT3/bt203Dc6cSqkKFCtK/f38ZOnSovP/++ybY6tevnwmkdKY+1aVLFxNC9e7dW7744gsTLI0cOVIGDRokJUv+8mVz7dq15nLo0CHZvXu3+W+d5c8xYcIEeeihh8xsfjq7n/ar0osuD3t5vRomfEicLUPjbNymIL9HgKBx4we4VytgnGFvXhj+Fs6L2+yH90tQTZs2zXy311YdekI8+4iL7F577TXze0SX10mX3n333Yjb9beB/oapU6eOlC5d2vwOmT59eszbReWUh1BBFVyEUv41e/Zs82HeqVMnM0ufVkM9/fTTodt1djytjNKZ8hyTJ08OLaszBupMfM8++2zo9mLFisn8+fPlzjvvNKHVaaedJn379pWxY8dGPPa5554b+m8NuebMmSP169eXLVu2mOuee+45M4TwxhtvTGgj+CBxo3rKqxVUeckrDEpUpZXXA6eCIpgC4NcKqmiihT1uVld5NXyyMZiiaio+8+bNMye5NTzSYGrKlCnmt4T+3sg+UZNavny53HLLLTJ+/Hi5+uqrze+F66+/XtasWSMtWrQwy+j6dPTHq6++akKvRYsWyV133WVOtl977bUF3jbCqTiqp/6690LXHt8JKQipgsOWYIohfcmhM/Pph3xu9AM+Kyvyi4yetdAzHnrJjYZM2c9qZJd9vdk5IRW8yW8BVdBDJa8HUwzpA7zJDwFVrAFRYcMrPwZQuaFiynsmTZpkRm3oyAulIdU777xjRkropE7ZPfXUU2akx7Bhw8zf48aNM+1CnnnmmVB1lAZYeiL8sssuM38PHDhQ/vKXv5iKrFjCKYb1eZQtgQWSi9cZQGFQJQMH7wXA29ysEglaAJF9aGCsl6AI2vvCDzIzM81oic6dO4eu09EY+veKFSui3kevD19eaaVV+PIXXnihvPXWW6YdiZ781tYj33zzjWk1EgvCKQ9XkGhwQXjhX7y2gD+4XTFCKAG33wNu/38AQOERRMCm9wND+nI6cOBAxEVbf2S3Z88eOXnypNSoEVlZr39rX9lo9Pr8lp86darpM6U9p0qUKGEqrXSExyWXXCKxYFifD9CLyn9sC6ZsCWQBFC6cCMIwP9gVTAFI7A/yzKZ1XHt8Pw7xg/eCKS8q8c0OSStaIinrLnoq0/xbt25d13rEajj1ySefmOopbS3y4YcfmomYtOdU9qqrvBBO+QS9qPzBtlAKgL8EpQ8VCKUAJDeYIKQKJhuCKaqmotu6dauUL18+9Hf4DN2OqlWrmomTdu6M/I6gf9esWTPqevX6vJb/6aef5IEHHpA33nhDunfvbq4755xzzCzgEydOjCmcYlifzypJCDe8i9cO8C+bhjURWvifTa+xTe/9IPjxxx+lV69e5gdKxYoVpX///maK77xoA9siRYpEXO64444cy7300kvmB4dOyqEzOulZcQSXDSEFUovX3G7ly5ePuEQLp3TIXZs2bWTJkiWh606dOmX+1hm+o9Hrw5dX2hDdWV5nFteL9q4KpyGYrjsWVE75EFVU3mJ7KGVrEAsgflRQ+ZdNwRRST4OpH374wfxw0B8LOhuTzpqU16ywSmduGjt2bOjvMmXK5Jjd6cknn5QnnnjCTD1++PBhZnQN6NC+cAzzCwZCKX8ZOnSomVmvbdu20q5dO5kyZYr5THdm7+vTp4/Url1bxo8fb/6+++675dJLLzXHAK2Mmjt3rnz22Wfy/PPPm9s1CNPbdTa/0qVLm2F9H3zwgbzyyivm2BELwqlC/mj/694LxVaEVHazPZQCkPgKkqV7moot6EPlLzaGUlRNpdb69etlwYIF8umnn5ofHU4fkKuuusoMrdDeH7nRMCq3IR179+6VkSNHyttvvy2dOnUKXa9VVADD/PzNtmCKIX2Fd/PNN8vu3btl1KhRpql569atzbHDaXqenp4eUQWlM/HpCQ49DujwvTPPPFPefPNNadGiRWgZDaxGjBhhTpBoBa8GVI888kjUKty8EE4FACGVXbwUSlE1Bfg7oFKEVN5mYyilCKZST6f11qF8TjCltNeH/shYuXKl/PrXv871vrNnz5ZXX33VBFTXXHONPPTQQ6HqKa3C0qEZOkV4s2bN5ODBg+bHip5Fz96AF8GrnnJQReUvtoVSSKzBgwebSzTLli3Lcd1NN91kLrnRY8eLL75Y6O0inPJ59VRuoQhBVep5KZQCEDyEVN5jazCFgtGpvsNpf5BoPUIKSs+Aay+ocGlpaVK5cuVcpwhXt956qznLrZVV//3vf+X++++XjRs3yj//+U9z+3fffWfCqUcffVSeeuopqVChgjmDfuWVV5rltYcJUs/WgEoRUnmbrcEUVVP+RzgVsIDKQTVV6hBKAbC9eioc/ajsZ3so5YeqqbTNPyRt2m+Jcdrv4cOHy4QJE/Id0hcv7UnlaNmypZx++ulm+N6mTZukcePGJpjS/lVPP/20dOnSxSz3t7/9zZwpf//996Vr165xPzb8iZDKm2wNpRTBVDAQTgU4oFKEVMnhh0CKIX1AsAMqRUhlF9tDKb8EUzZN+63uvfdeue222/JcV6NGjUxYtGvXrojrT5w4Yfp/5NZPKhpteK6+/fZbE05pWKWaN28eWqZatWpmSnLtTQL32Fg9FY6QyhtsDqUQLIRTCeTVgEox5C8x/BBKKYIpAIqQyg5eCKUQO2e67/xoEKSX/Oi03vv27ZPVq1ebqcLV0qVLTeWTEzgVxNq1a82/Tih10UUXmX91qF+dOj8HIRp47dmzxwwHhLtsD6gU/ajs5JVQiqqp4CCcQr4BC2GV/8MoAKlne/VUOEIqd3gtlKJqyl3arLxbt24yYMAAmT59uhmKpw1ve/bsGZqpT5ua65A9neJbpxDXoXs6C5PO6FelShXTQ2rIkCFyySWXhGbjO+uss+S6664z04nr1OEaqOmsTE2bNpXLL7/c5WcNr6CKyh5eCaUUwVSwEE4lmJerp3JDWBWsQIqqKSB1vBRQZQ9LCKqSw2uBlINgyg46654GUhpA6Sx9PXr0ML2iHBpYaQXUkSNHzN/azPy9996TKVOmyOHDh00fLL2PNjwPp2GWhlbdu3c367300kvN1OPFixdP+XOEN6unogUjBFWp5aVQShFMBQ/hVBL4MaAKaljl9yAqO4IpIPW8FlA5qKZKHK8GUg6CKXvozHxaCZWbBg0aSFZWVuhvDaM++OCDfNer1VIvvPCCucBOXgqoHFRTJZ/XAikEG+FUkvg9oCpIgOOl0CpoIVQ0BFOAe7waUEULVgirghNKKYIpwB5eDKgUIVXieT2UomoqmAinkihIAVW8gU8qAywCKAA283JAFY6hf/4Oo8IRTAH28WpAFS1QIawKViDlIJgKLsIpuIrAyA5UTQF28EtA5aCqyn+BFAD7eTmgCkdYFYwwKhzBVLARTiVZ0KunYD+CKQCp4uewKmghFFVTAFIt6M3U/RhGhSOYAuFUChBQwVYEU4B9/FY9FW+gY3NwFbQgKjuCKcB+fqmeiiWo8VNg5fcgKjuCKSjCqRQhoIJtCKYAewUpoCpMAJToACvooVNBEEwB3uH3gCqWQMfW4CpoIVQ0BFNwEE65EAYQUsFtBFOA/Qio8keYlFoEU4D3BC2gKmwIlIgQi8Cp4AimEI5wygWEVHATwRTgHQRUsAXBFOBdBFQFR7CUOgRTyK5ojmuQ0pCAoACpwvsN8CZCAbiN9yDgfQQBsAnvR0RDOGUBQgMkG+8vwNsIB+AW3nuAfxAIwAa8D5EbwimLEFIhGXhPAf4JCQgKkEq83wD/IRiAm3j/IS+EUxYiTECi8F4C/IfAAMlGEAr4PyAgJECq8Z5DfginLEWogMLiPQT4F+EBkoH3FRAshAVIBcJQFBSz9VmMWf0QD0IpIDicIIEZ/VBYhFJAMDmhAbP5IdEIpBArwikPIKRCQRBKAcEOFgioEA9CKQCKkAqJRDCFeBBOeTR8IKiCg1AKgKKKCgVFIAUgr1CBgArxIpRCYRBOeRTVVCCUAhANIRVyQygFoCCookKsCKWQCIRTHkdIFSwEUgDiCSIIqoKNUApAPAipkB9CKSQS4ZRPEFL5F4EUgMIiqAomQikAiQ4gCKpAIIVkIZzyeZBBWOVNBFIAkoWgyv8IpQAkC0FVcBFKIdkIp3yOiirvIJACkGr0p/IHwigAbiCoCgZCKaQK4VRAUFFlD0IoALahmso7CKIA2Iigyj8Io+AWwqmAyi0gIbRKHEIoAH4JPwis3EUgBcBLCKq8gyAKNiGcQr6BCoFVwRBGAQhKOEJYlVyEUQD8Gn4QVrmPQAq2IpxCoUKXIARXhE4AEFt4QniVN8InAEFFWJV6hFHwCsIppDy4cTvQImwCAPfClyAFV4RQAFC44ITwKn+ET/ALwimkHOEQAARXQQMbm0IsQiYAcAfh1c8IoBAEhFMAAMA6BEIAgESGNjYEWYRMQO4IpwAAAAAAvkYwBPy/9u4EysY6/uP4FzMMyZa97BmEIiJbsoSIqE4yzhwkS+ickC00IpEzp5yk/BPR+VcThQpNyRJjLUvJMvbkZBSFIdvw+5/vr/+dZsbM5I658zzPnffrnOvOvfe5M8/X3Of3md/vWX7ultfpFQAAAAAAAEDuxeAUAAAAAAAAHMPgFAAAAAAAABzD4BQAINdpdwsX2wYAAADcgsEpAAAAAAAAOIbBKQBArtSx8G6nVwEAAAAAg1MAAAAAAABwkqcGp+pW2OP0KgAAgghHTwEAAADO89TgFAAAAAAAAIKL5wan7qn4q9OrAAAIIhw9BQAAADjLc4NTAAAAAAAACB6eHJzi6CkAQHbi6CkAAADAOZ4cnAIAAAAAAEBw8OzgFEdPAQCyE0dPAQAAAM7w7OAUAAAAAAAAcung1MyZM6Vy5coSFhYmjRs3li1btmS6/MKFC6VmzZp2+bp168ry5cslO3D0FACv+/PPP6Vnz55SpEgRKVasmPTt21fOnTuX6XsuXrwogwcPlttuu00KFy4sjz/+uJw4cSLVMkePHpVOnTpJoUKFpHTp0jJixAhJSkpKfv348eMSEREh4eHhkjdvXnn++ecz/ZkxMTGSJ08e6dq1q2Q3t2SK4ugpALktU9TGjRuldevWcsstt9j3PvDAA3LhwoXrlrt06ZLUq1fP5sGOHTvEbdyUJwDgVjOzua00xshLL70k5cqVk4IFC0rbtm1l//79gR+c+uSTT2TYsGESFRUl27Ztk3vuuUfat28vv//+e7rLb9iwQXr06GHDcfv27bZjo7eff/7Z75UFgGCjnYhdu3bJihUrZOnSpbJ27Vrp379/pu8ZOnSofPnllzYovvvuO/ntt9/kscceS3796tWrdmDq8uXLtg2eP3++zJs3z4ZGyg5GqVKlZNy4cbYdz8yRI0fkhRdekBYtWkh2I1MAwNlM0YGpDh06SLt27WwH5fvvv5chQ4bYHRdpjRw5UsqXLy9uRJ4AwH8LRFs5bdo0efPNN2XWrFmyefNmu6NDv6fuUPdHHqPDXH7QkbX77rtP3nrrLfv42rVrUqFCBXnuuedk9OjR1y3fvXt3OX/+vA1In/vvv9/uddGVvxFnz56VokWLypkzZ+zenLR+PFrBnxIAuMy5xGvSvM5vGW7jN9pGtC03QELy5s/29Uu6dlm+Pf4/WV6/jOzZs0fuuusu2xFo2LChfS42NlY6duwox44dS7cDoOugg0offfSRPPHEE/a5vXv3Sq1atWwHQ9vXr776Sh555BE7aFWmTBm7jLa3o0aNkj/++EPy50/9f/Tggw/aNnn69OnX/Twd6NI96E8//bSsW7dOTp8+LUuWLMm2/4OczhTfZ2Xb7jJS+NaM988sP3dXlmsC4KyL55Jk9H3fZanNTs6Tkk8HJE+SM+XkXFdkiq8Nfeihh2TSpEmZfn/NFu3QfPbZZ1K7dm3bSdG21y2c7KO0Lf1MwD4vAJxj2+vf37v5PkoA24gkP9cxu9tKHU7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", 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"text/plain": [ "
" ] @@ -420,13 +399,15 @@ "id": "35e51649", "metadata": {}, "source": [ - "The results are not so great, and we can clearly see that as time progresses the solution gets worse.... Can we do better?\n", + "The results are not ideal, and we can clearly see that as time progresses, the solution deteriorates. Can we do better?\n", "\n", - "A valid option is to impose the initial condition as hard constraint as well. Specifically, our solution is written as:\n", + "One valid approach is to impose the initial condition as a hard constraint as well. Specifically, we modify the solution to:\n", "\n", - "$$ u_{\\rm{pinn}} = xy(1-x)(1-y)\\cdot NN(x, y, t)\\cdot t + \\cos(\\sqrt{2}\\pi t)\\sin(\\pi x)\\sin(\\pi y), $$\n", + "$$\n", + "u_{\\rm{pinn}} = xy(1-x)(1-y) \\cdot NN(x, y, t) \\cdot t + \\cos(\\sqrt{2}\\pi t)\\sin(\\pi x)\\sin(\\pi y),\n", + "$$\n", "\n", - "Let us build the network first" + "Now, let us start by building the neural network." ] }, { @@ -491,11 +472,18 @@ ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 58.13it/s, v_num=3, g1_loss=2.02e-15, g2_loss=0.000, g3_loss=0.000, g4_loss=2.01e-15, initial_loss=0.000, D_loss=6.88e-8, train_loss=6.88e-8]" - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "9bb6d54ab360490baac01347c085ff0e", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" ] @@ -569,7 +550,7 @@ }, { "data": { - "image/png": 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" ] @@ -594,7 +575,7 @@ "id": "b7338109", "metadata": {}, "source": [ - "We can see now that the results are way better! This is due to the fact that previously the network was not learning correctly the initial conditon, leading to a poor solution when time evolved. By imposing the initial condition the network is able to correctly solve the problem." + "We can now see that the results are much better! This improvement is due to the fact that, previously, the network was not correctly learning the initial condition, which led to a poor solution as time evolved. By imposing the initial condition as a hard constraint, the network is now able to correctly solve the problem." ] }, { @@ -602,17 +583,23 @@ "id": "61195b1f", "metadata": {}, "source": [ - "## What's next?\n", + "## What's Next?\n", "\n", - "Congratulations on completing the two dimensional Wave tutorial of **PINA**! There are multiple directions you can go now:\n", + "Congratulations on completing the two-dimensional Wave tutorial of **PINA**! Now that you’ve got the basics down, there are several directions you can explore:\n", "\n", - "1. Train the network for longer or with different layer sizes and assert the finaly accuracy\n", + "1. **Train the Network for Longer**: Train the network for a longer duration or experiment with different layer sizes to assess the final accuracy.\n", "\n", - "2. Propose new types of hard constraints in time, e.g. $$ u_{\\rm{pinn}} = xy(1-x)(1-y)\\cdot NN(x, y, t)(1-\\exp(-t)) + \\cos(\\sqrt{2}\\pi t)sin(\\pi x)\\sin(\\pi y), $$\n", + "2. **Propose New Types of Hard Constraints in Time**: Experiment with new time-dependent hard constraints, for example:\n", + " \n", + " $$\n", + " u_{\\rm{pinn}} = xy(1-x)(1-y)\\cdot NN(x, y, t)(1-\\exp(-t)) + \\cos(\\sqrt{2}\\pi t)\\sin(\\pi x)\\sin(\\pi y)\n", + " $$\n", "\n", - "3. Exploit extrafeature training for model 1 and 2\n", + "3. **Exploit Extrafeature Training**: Apply extrafeature training techniques to improve models from 1 and 2.\n", "\n", - "4. Many more..." + "4. **...and many more!**: The possibilities are endless! Keep experimenting and pushing the boundaries.\n", + "\n", + "For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/)." ] } ], diff --git a/tutorials/tutorial3/tutorial.py b/tutorials/tutorial3/tutorial.py deleted file mode 100644 index 8595c89..0000000 --- a/tutorials/tutorial3/tutorial.py +++ /dev/null @@ -1,336 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# # Tutorial: Two dimensional Wave problem with hard constraint -# -# [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial3/tutorial.ipynb) -# -# In this tutorial we present how to solve the wave equation using hard constraint PINNs. For doing so we will build a costum `torch` model and pass it to the `PINN` solver. -# -# First of all, some useful imports. - -# In[ ]: - - -## routine needed to run the notebook on Google Colab -try: - import google.colab - - IN_COLAB = True -except: - IN_COLAB = False -if IN_COLAB: - get_ipython().system('pip install "pina-mathlab"') - -import torch -import matplotlib.pyplot as plt -import warnings - -from pina import Condition, LabelTensor, Trainer -from pina.problem import SpatialProblem, TimeDependentProblem -from pina.operator import laplacian, grad -from pina.domain import CartesianDomain -from pina.solver import PINN -from pina.equation import Equation, FixedValue -from pina.callback import MetricTracker - -warnings.filterwarnings("ignore") - - -# ## The problem definition - -# The problem is written in the following form: -# -# \begin{equation} -# \begin{cases} -# \Delta u(x,y,t) = \frac{\partial^2}{\partial t^2} u(x,y,t) \quad \text{in } D, \\\\ -# u(x, y, t=0) = \sin(\pi x)\sin(\pi y), \\\\ -# u(x, y, t) = 0 \quad \text{on } \Gamma_1 \cup \Gamma_2 \cup \Gamma_3 \cup \Gamma_4, -# \end{cases} -# \end{equation} -# -# where $D$ is a squared domain $[0,1]^2$, and $\Gamma_i$, with $i=1,...,4$, are the boundaries of the square, and the velocity in the standard wave equation is fixed to one. - -# Now, the wave problem is written in PINA code as a class, inheriting from `SpatialProblem` and `TimeDependentProblem` since we deal with spatial, and time dependent variables. The equations are written as `conditions` that should be satisfied in the corresponding domains. `solution` is the exact solution which will be compared with the predicted one. - -# In[2]: - - -def wave_equation(input_, output_): - u_t = grad(output_, input_, components=["u"], d=["t"]) - u_tt = grad(u_t, input_, components=["dudt"], d=["t"]) - nabla_u = laplacian(output_, input_, components=["u"], d=["x", "y"]) - return nabla_u - u_tt - - -def initial_condition(input_, output_): - u_expected = torch.sin(torch.pi * input_.extract(["x"])) * torch.sin( - torch.pi * input_.extract(["y"]) - ) - return output_.extract(["u"]) - u_expected - - -class Wave(TimeDependentProblem, SpatialProblem): - output_variables = ["u"] - spatial_domain = CartesianDomain({"x": [0, 1], "y": [0, 1]}) - temporal_domain = CartesianDomain({"t": [0, 1]}) - domains = { - "g1": CartesianDomain({"x": 1, "y": [0, 1], "t": [0, 1]}), - "g2": CartesianDomain({"x": 0, "y": [0, 1], "t": [0, 1]}), - "g3": CartesianDomain({"x": [0, 1], "y": 0, "t": [0, 1]}), - "g4": CartesianDomain({"x": [0, 1], "y": 1, "t": [0, 1]}), - "initial": CartesianDomain({"x": [0, 1], "y": [0, 1], "t": 0}), - "D": CartesianDomain({"x": [0, 1], "y": [0, 1], "t": [0, 1]}), - } - conditions = { - "g1": Condition(domain="g1", equation=FixedValue(0.0)), - "g2": Condition(domain="g2", equation=FixedValue(0.0)), - "g3": Condition(domain="g3", equation=FixedValue(0.0)), - "g4": Condition(domain="g4", equation=FixedValue(0.0)), - "initial": Condition( - domain="initial", equation=Equation(initial_condition) - ), - "D": Condition(domain="D", equation=Equation(wave_equation)), - } - - def solution(self, pts): - f = ( - torch.sin(torch.pi * pts.extract(["x"])) - * torch.sin(torch.pi * pts.extract(["y"])) - * torch.cos( - torch.sqrt(torch.tensor(2.0)) * torch.pi * pts.extract(["t"]) - ) - ) - return LabelTensor(f, self.output_variables) - - -# define problem -problem = Wave() - - -# ## Hard Constraint Model - -# After the problem, a **torch** model is needed to solve the PINN. Usually, many models are already implemented in **PINA**, but the user has the possibility to build his/her own model in `torch`. The hard constraint we impose is on the boundary of the spatial domain. Specifically, our solution is written as: -# -# $$ u_{\rm{pinn}} = xy(1-x)(1-y)\cdot NN(x, y, t), $$ -# -# where $NN$ is the neural net output. This neural network takes as input the coordinates (in this case $x$, $y$ and $t$) and provides the unknown field $u$. By construction, it is zero on the boundaries. The residuals of the equations are evaluated at several sampling points (which the user can manipulate using the method `discretise_domain`) and the loss minimized by the neural network is the sum of the residuals. - -# In[3]: - - -class HardMLP(torch.nn.Module): - - def __init__(self, input_dim, output_dim): - super().__init__() - - self.layers = torch.nn.Sequential( - torch.nn.Linear(input_dim, 40), - torch.nn.ReLU(), - torch.nn.Linear(40, 40), - torch.nn.ReLU(), - torch.nn.Linear(40, output_dim), - ) - - # here in the foward we implement the hard constraints - def forward(self, x): - hard = ( - x.extract(["x"]) - * (1 - x.extract(["x"])) - * x.extract(["y"]) - * (1 - x.extract(["y"])) - ) - return hard * self.layers(x) - - -# ## Train and Inference - -# In this tutorial, the neural network is trained for 1000 epochs with a learning rate of 0.001 (default in `PINN`). As always, we will log using `Tensorboard`. - -# In[4]: - - -# generate the data -problem.discretise_domain(1000, "random", domains="all") - -# define model -model = HardMLP(len(problem.input_variables), len(problem.output_variables)) - -# crete the solver -pinn = PINN(problem=problem, model=model) - -# create trainer and train -trainer = Trainer( - solver=pinn, - max_epochs=1000, - accelerator="cpu", - enable_model_summary=False, - train_size=1.0, - val_size=0.0, - test_size=0.0, - callbacks=[MetricTracker(["train_loss", "initial_loss", "D_loss"])], -) -trainer.train() - - -# Let's now plot the losses inside `MetricTracker` to see how they vary during training. - -# In[5]: - - -trainer_metrics = trainer.callbacks[0].metrics -for metric, loss in trainer_metrics.items(): - plt.plot(range(len(loss)), loss, label=metric) -# plotting -plt.xlabel("epoch") -plt.ylabel("loss") -plt.yscale("log") -plt.legend() - - -# Notice that the loss on the boundaries of the spatial domain is exactly zero, as expected! After the training is completed one can now plot some results using the `matplotlib`. We plot the predicted output on the left side, the true solution at the center and the difference on the right side using the `plot_solution` function. - -# In[6]: - - -@torch.no_grad() -def plot_solution(solver, time): - # get the problem - problem = solver.problem - # get spatial points - spatial_samples = problem.spatial_domain.sample(30, "grid") - # get temporal value - time = LabelTensor(torch.tensor([[time]]), "t") - # cross data - points = spatial_samples.append(time, mode="cross") - # compute pinn solution, true solution and absolute difference - data = { - "PINN solution": solver(points), - "True solution": problem.solution(points), - "Absolute Difference": torch.abs( - solver(points) - problem.solution(points) - ), - } - # plot the solution - plt.suptitle(f"Solution for time {time.item()}") - for idx, (title, field) in enumerate(data.items()): - plt.subplot(1, 3, idx + 1) - plt.title(title) - plt.tricontourf( # convert to torch tensor + flatten - points.extract("x").tensor.flatten(), - points.extract("y").tensor.flatten(), - field.tensor.flatten(), - ) - plt.colorbar(), plt.tight_layout() - - -# Let's take a look at the results at different times, for example `0.0`, `0.5` and `1.0`: - -# In[7]: - - -plt.figure(figsize=(12, 6)) -plot_solution(solver=pinn, time=0) - -plt.figure(figsize=(12, 6)) -plot_solution(solver=pinn, time=0.5) - -plt.figure(figsize=(12, 6)) -plot_solution(solver=pinn, time=1) - - -# The results are not so great, and we can clearly see that as time progresses the solution gets worse.... Can we do better? -# -# A valid option is to impose the initial condition as hard constraint as well. Specifically, our solution is written as: -# -# $$ u_{\rm{pinn}} = xy(1-x)(1-y)\cdot NN(x, y, t)\cdot t + \cos(\sqrt{2}\pi t)\sin(\pi x)\sin(\pi y), $$ -# -# Let us build the network first - -# In[8]: - - -class HardMLPtime(torch.nn.Module): - - def __init__(self, input_dim, output_dim): - super().__init__() - - self.layers = torch.nn.Sequential( - torch.nn.Linear(input_dim, 40), - torch.nn.ReLU(), - torch.nn.Linear(40, 40), - torch.nn.ReLU(), - torch.nn.Linear(40, output_dim), - ) - - # here in the foward we implement the hard constraints - def forward(self, x): - hard_space = ( - x.extract(["x"]) - * (1 - x.extract(["x"])) - * x.extract(["y"]) - * (1 - x.extract(["y"])) - ) - hard_t = ( - torch.sin(torch.pi * x.extract(["x"])) - * torch.sin(torch.pi * x.extract(["y"])) - * torch.cos( - torch.sqrt(torch.tensor(2.0)) * torch.pi * x.extract(["t"]) - ) - ) - return hard_space * self.layers(x) * x.extract(["t"]) + hard_t - - -# Now let's train with the same configuration as the previous test - -# In[9]: - - -# define model -model = HardMLPtime(len(problem.input_variables), len(problem.output_variables)) - -# crete the solver -pinn = PINN(problem=problem, model=model) - -# create trainer and train -trainer = Trainer( - solver=pinn, - max_epochs=1000, - accelerator="cpu", - enable_model_summary=False, - train_size=1.0, - val_size=0.0, - test_size=0.0, - callbacks=[MetricTracker(["train_loss", "initial_loss", "D_loss"])], -) -trainer.train() - - -# We can clearly see that the loss is way lower now. Let's plot the results - -# In[10]: - - -plt.figure(figsize=(12, 6)) -plot_solution(solver=pinn, time=0) - -plt.figure(figsize=(12, 6)) -plot_solution(solver=pinn, time=0.5) - -plt.figure(figsize=(12, 6)) -plot_solution(solver=pinn, time=1) - - -# We can see now that the results are way better! This is due to the fact that previously the network was not learning correctly the initial conditon, leading to a poor solution when time evolved. By imposing the initial condition the network is able to correctly solve the problem. - -# ## What's next? -# -# Congratulations on completing the two dimensional Wave tutorial of **PINA**! There are multiple directions you can go now: -# -# 1. Train the network for longer or with different layer sizes and assert the finaly accuracy -# -# 2. Propose new types of hard constraints in time, e.g. $$ u_{\rm{pinn}} = xy(1-x)(1-y)\cdot NN(x, y, t)(1-\exp(-t)) + \cos(\sqrt{2}\pi t)sin(\pi x)\sin(\pi y), $$ -# -# 3. Exploit extrafeature training for model 1 and 2 -# -# 4. Many more... diff --git a/tutorials/tutorial4/tutorial.ipynb b/tutorials/tutorial4/tutorial.ipynb index f1df1b2..cfce47b 100644 --- a/tutorials/tutorial4/tutorial.ipynb +++ b/tutorials/tutorial4/tutorial.ipynb @@ -5,8 +5,7 @@ "id": "48dd2795", "metadata": {}, "source": [ - "# Tutorial: Unstructured convolutional autoencoder via continuous convolution\n", - "\n", + "# Tutorial: Unstructured Convolutional Autoencoders with Continuous Convolution\n", "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial4/tutorial.ipynb)" ] }, @@ -15,14 +14,8 @@ "id": "25770254", "metadata": {}, "source": [ - "In this tutorial, we will show how to use the Continuous Convolutional Filter, and how to build common Deep Learning architectures with it. The implementation of the filter follows the original work [*A Continuous Convolutional Trainable Filter for Modelling Unstructured Data*](https://arxiv.org/abs/2210.13416)." - ] - }, - { - "cell_type": "markdown", - "id": "80e8bfac", - "metadata": {}, - "source": [ + "In this tutorial, we will show how to use the Continuous Convolutional Filter, and how to build common Deep Learning architectures with it. The implementation of the filter follows the original work [*A Continuous Convolutional Trainable Filter for Modelling Unstructured Data*](https://arxiv.org/abs/2210.13416).\n", + "\n", "First of all we import the modules needed for the tutorial:" ] }, @@ -41,7 +34,7 @@ "except:\n", " IN_COLAB = False\n", "if IN_COLAB:\n", - " !pip install \"pina-mathlab\"\n", + " !pip install \"pina-mathlab[tutorial]\"\n", "\n", "import torch\n", "import matplotlib.pyplot as plt\n", @@ -63,10 +56,18 @@ "id": "4094758f", "metadata": {}, "source": [ - "The tutorial is structured as follow: \n", - "* [Continuous filter background](#continuous-filter-background): understand how the convolutional filter works and how to use it.\n", - "* [Building a MNIST Classifier](#building-a-mnist-classifier): show how to build a simple classifier using the MNIST dataset and how to combine a continuous convolutional layer with a feedforward neural network. \n", - "* [Building a Continuous Convolutional Autoencoder](#building-a-continuous-convolutional-autoencoder): show how to use the continuous filter to work with unstructured data for autoencoding and up-sampling." + "## Tutorial Structure\n", + "\n", + "The tutorial is structured as follows:\n", + "\n", + "- [🔹 Continuous Filter Background](#continuous-filter-background): \n", + " Understand how the convolutional filter works and how to use it.\n", + "\n", + "- [🔹 Building a MNIST Classifier](#building-a-mnist-classifier): \n", + " Learn how to build a simple classifier using the MNIST dataset, and how to combine a continuous convolutional layer with a feedforward neural network.\n", + "\n", + "- [🔹 Building a Continuous Convolutional Autoencoder](#building-a-continuous-convolutional-autoencoder): \n", + " Explore how to use the continuous filter to work with unstructured data for autoencoding and up-sampling.\n" ] }, { @@ -74,54 +75,61 @@ "id": "87327478", "metadata": {}, "source": [ - "## Continuous filter background" - ] - }, - { - "cell_type": "markdown", - "id": "7f1aa4ef", - "metadata": {}, - "source": [ - "As reported by the authors in the original paper: in contrast to discrete convolution, continuous convolution is mathematically defined as:\n", + "## Continuous Filter Background\n", + "\n", + "As reported by the authors in the original paper, in contrast to discrete convolution, **continuous convolution** is mathematically defined as:\n", "\n", "$$\n", " \\mathcal{I}_{\\rm{out}}(\\mathbf{x}) = \\int_{\\mathcal{X}} \\mathcal{I}(\\mathbf{x} + \\mathbf{\\tau}) \\cdot \\mathcal{K}(\\mathbf{\\tau}) d\\mathbf{\\tau},\n", "$$\n", - "where $\\mathcal{K} : \\mathcal{X} \\rightarrow \\mathbb{R}$ is the *continuous filter* function, and $\\mathcal{I} : \\Omega \\subset \\mathbb{R}^N \\rightarrow \\mathbb{R}$ is the input function. The continuous filter function is approximated using a FeedForward Neural Network, thus trainable during the training phase. The way in which the integral is approximated can be different, currently on **PINA** we approximate it using a simple sum, as suggested by the authors. Thus, given $\\{\\mathbf{x}_i\\}_{i=1}^{n}$ points in $\\mathbb{R}^N$ of the input function mapped on the $\\mathcal{X}$ filter domain, we approximate the above equation as:\n", + "\n", + "where:\n", + "- $\\mathcal{K} : \\mathcal{X} \\rightarrow \\mathbb{R}$ is the **continuous filter** function,\n", + "- $\\mathcal{I} : \\Omega \\subset \\mathbb{R}^N \\rightarrow \\mathbb{R}$ is the input function.\n", + "\n", + "The **continuous filter function** is approximated using a **FeedForward Neural Network**, which is **trainable** during the training phase. The way in which the integral is approximated can vary. In the **PINA** framework, we approximate it using a simple sum, as suggested by the authors. Thus, given the points $\\{\\mathbf{x}_i\\}_{i=1}^{n}$ in $\\mathbb{R}^N$ mapped onto the filter domain $\\mathcal{X}$, we approximate the equation as:\n", + "\n", "$$\n", " \\mathcal{I}_{\\rm{out}}(\\mathbf{\\tilde{x}}_i) = \\sum_{{\\mathbf{x}_i}\\in\\mathcal{X}} \\mathcal{I}(\\mathbf{x}_i + \\mathbf{\\tau}) \\cdot \\mathcal{K}(\\mathbf{x}_i),\n", "$$\n", - "where $\\mathbf{\\tau} \\in \\mathcal{S}$, with $\\mathcal{S}$ the set of available strides, corresponds to the current stride position of the filter, and $\\mathbf{\\tilde{x}}_i$ points are obtained by taking the centroid of the filter position mapped on the $\\Omega$ domain. " - ] - }, - { - "cell_type": "markdown", - "id": "a2ea9c78", - "metadata": {}, - "source": [ - "We will now try to pratically see how to work with the filter. From the above definition we see that what is needed is:\n", - "1. A domain and a function defined on that domain (the input)\n", - "2. A stride, corresponding to the positions where the filter needs to be $\\rightarrow$ `stride` variable in `ContinuousConv`\n", - "3. The filter rectangular domain $\\rightarrow$ `filter_dim` variable in `ContinuousConv`" - ] - }, - { - "cell_type": "markdown", - "id": "ac896875", - "metadata": {}, - "source": [ - "### Input function\n", "\n", - "The input function for the continuous filter is defined as a tensor of shape: $$[B \\times N_{in} \\times N \\times D]$$ where $B$ is the batch_size, $N_{in}$ is the number of input fields, $N$ the number of points in the mesh, $D$ the dimension of the problem. In particular:\n", - "* $D$ is the number of spatial variables + 1. The last column must contain the field value. For example for 2D problems $D=3$ and the tensor will be something like `[first coordinate, second coordinate, field value]`\n", - "* $N_{in}$ represents the number of vectorial function presented. For example a vectorial function $f = [f_1, f_2]$ will have $N_{in}=2$ \n", + "where $\\mathbf{\\tau} \\in \\mathcal{S}$, with $\\mathcal{S}$ being the set of available strides, represents the current stride position of the filter. The $\\mathbf{\\tilde{x}}_i$ points are obtained by taking the **centroid** of the filter position mapped onto the domain $\\Omega$.\n", + "\n", + "### Working with the Continuous Filter\n", + "\n", + "From the above definition, what is needed is:\n", + "1. A **domain** and a **function** defined on that domain (the input),\n", + "2. A **stride**, corresponding to the positions where the filter needs to be applied (this is the `stride` variable in `ContinuousConv`),\n", + "3. The **filter's rectangular domain**, which corresponds to the `filter_dim` variable in `ContinuousConv`.\n", + "\n", + "### Input Function\n", + "\n", + "The input function for the continuous filter is defined as a tensor of shape:\n", + "\n", + "$$[B \\times N_{\\text{in}} \\times N \\times D]$$\n", + "\n", + "where:\n", + "- $B$ is the **batch size**,\n", + "- $N_{\\text{in}}$ is the number of input fields,\n", + "- $N$ is the number of points in the mesh,\n", + "- $D$ is the dimension of the problem. \n", + "\n", + "In particular:\n", + "- $D$ represents the **number of spatial variables** + 1. The last column must contain the field value. For example, for 2D problems, $D=3$ and the tensor will look like `[first coordinate, second coordinate, field value]`.\n", + "- $N_{\\text{in}}$ represents the number of vectorial functions presented. For example, a vectorial function $f = [f_1, f_2]$ will have $N_{\\text{in}}=2$.\n", + "\n", + "#### Example: Input Function for a Vectorial Field\n", + "\n", + "Let’s see an example to clarify the idea. Suppose we wish to create the function:\n", "\n", - "Let's see an example to clear the ideas. We will be verbose to explain in details the input form. We wish to create the function:\n", "$$\n", "f(x, y) = [\\sin(\\pi x) \\sin(\\pi y), -\\sin(\\pi x) \\sin(\\pi y)] \\quad (x,y)\\in[0,1]\\times[0,1]\n", "$$\n", "\n", - "using a batch size equal to 1." + "We can do this with a **batch size** equal to 1. This function consists of two components (vectorial field), so $N_{\\text{in}}=2$. For each $(x,y)$ pair in the domain $[0,1] \\times [0,1]$, we will compute the corresponding field values:\n", + "\n", + "1. $\\sin(\\pi x) \\sin(\\pi y)$\n", + "2. $-\\sin(\\pi x) \\sin(\\pi y)$" ] }, { @@ -176,7 +184,7 @@ "source": [ "### Stride\n", "\n", - "The stride is passed as a dictionary `stride` which tells the filter where to go. Here is an example for the $[0,1]\\times[0,5]$ domain:\n", + "The **stride** is passed as a dictionary `stride` that dictates where the filter should move. Here's an example for the domain $[0,1] \\times [0,5]$:\n", "\n", "```python\n", "# stride definition\n", @@ -187,26 +195,15 @@ " }\n", "```\n", "This tells the filter:\n", - "1. `domain`: square domain (the only implemented) $[0,1]\\times[0,5]$. The minimum value is always zero, while the maximum is specified by the user\n", - "2. `start`: start position of the filter, coordinate $(0, 0)$\n", - "3. `jump`: the jumps of the centroid of the filter to the next position $(0.1, 0.3)$\n", - "4. `direction`: the directions of the jump, with `1 = right`, `0 = no jump`, `-1 = left` with respect to the current position\n", + "1. `domain`: The domain over which the filter operates. In this case, the filter works over the $[0,1] \\times [0,5]$ domain. The minimum value is always zero, and the maximum value is specified by the user.\n", + "2. `start`: The starting position of the filter's centroid. In this example, the filter starts at the position $(0, 0)$.\n", + "3. `jump`: The steps or jumps of the filter’s centroid to the next position. In this example, the filter moves by $(0.1, 0.3)$ along the x and y axes respectively.\n", + "4. `direction`: The directions of the jumps for each coordinate. A value of 1 indicates the filter moves right, 0 means no movement, and -1 indicates the filter moves left with respect to its current position.\n", "\n", - "**Note**\n", - "\n", - "We are planning to release the possibility to directly pass a list of possible strides!" - ] - }, - { - "cell_type": "markdown", - "id": "71c13ef2", - "metadata": {}, - "source": [ "### Filter definition\n", "\n", - "Having defined all the previous blocks, we are now able to construct the continuous filter.\n", - "\n", - "Suppose we would like to get an output with only one field, and let us fix the filter dimension to be $[0.1, 0.1]$." + "Now that we have defined the stride, we can move on to construct the continuous filter.\n", + "Let’s assume we want the output to contain only one field, and we will set the filter dimension to be $[0.1, 0.1]$." ] }, { @@ -241,7 +238,9 @@ "id": "49ccc992", "metadata": {}, "source": [ - "That's it! In just one line of code we have created the continuous convolutional filter. By default the `pina.model.FeedForward` neural network is intitialised, more on the [documentation](https://mathlab.github.io/PINA/_rst/fnn.html). In case the mesh doesn't change during training we can set the `optimize` flag equals to `True`, to exploit optimizations for finding the points to convolve." + "That's it! In just one line of code, we have successfully created the continuous convolutional filter. By default, the `pina.model.FeedForward` neural network is initialized, which can be further customized according to your needs.\n", + "\n", + "Additionally, if the mesh does not change during training, we can set the `optimize` flag to `True` to leverage optimizations for efficiently finding the points to convolve. This feature helps in improving the performance by reducing redundant calculations when the mesh remains constant." ] }, { @@ -298,7 +297,7 @@ "id": "886cf50f", "metadata": {}, "source": [ - "If we don't want to use the default `FeedForward` neural network, we can pass a specified torch model in the `model` keyword as follow: \n" + "If you don't want to use the default `FeedForward` neural network, you can pass a custom PyTorch model by specifying it in the `model` keyword. Here's an example of how to do it:" ] }, { @@ -338,14 +337,8 @@ "id": "2d4318ab", "metadata": {}, "source": [ - "Notice that we pass the class and not an already built object!" - ] - }, - { - "cell_type": "markdown", - "id": "254e8c8d", - "metadata": {}, - "source": [ + "Notice that we pass the **class** of the model and not an already built object! This is important because the `ContinuousConv` filter will automatically instantiate the model class when needed during training. \n", + "\n", "## Building a MNIST Classifier\n", "\n", "Let's see how we can build a MNIST classifier using a continuous convolutional filter. We will use the MNIST dataset from PyTorch. In order to keep small training times we use only 6000 samples for training and 1000 samples for testing." @@ -358,8 +351,6 @@ "metadata": {}, "outputs": [], "source": [ - "from torch.utils.data import DataLoader, SubsetRandomSampler\n", - "\n", "numb_training = 6000 # get just 6000 images for training\n", "numb_testing = 1000 # get just 1000 images for training\n", "seed = 111 # for reproducibility\n", @@ -370,7 +361,7 @@ "\n", "# downloading the dataset\n", "train_data = torchvision.datasets.MNIST(\n", - " \"./data/\",\n", + " \"./tutorial_logs/\",\n", " download=True,\n", " train=False,\n", " transform=torchvision.transforms.Compose(\n", @@ -387,7 +378,9 @@ "id": "7f076010", "metadata": {}, "source": [ - "Let's now build a simple classifier. The MNIST dataset is composed by vectors of shape `[batch, 1, 28, 28]`, but we can image them as one field functions where the pixels $ij$ are the coordinate $x=i, y=j$ in a $[0, 27]\\times[0,27]$ domain, and the pixels values are the field values. We just need a function to transform the regular tensor in a tensor compatible for the continuous filter:" + "Now, let's proceed to build a simple classifier for the MNIST dataset. The MNIST dataset consists of vectors with the shape `[batch, 1, 28, 28]`, but we can treat them as field functions where each pixel at coordinates $i,j$ corresponds to a point in a $[0, 27] \\times [0, 27]$ domain. The pixel values represent the field values.\n", + "\n", + "To use the continuous convolutional filter, we need to transform the regular tensor into a format compatible with the filter. Here's a function that will help with this transformation:" ] }, { @@ -475,7 +468,7 @@ "id": "4374c15c", "metadata": {}, "source": [ - "We now aim to solve the classification problem. For this we will use the `SupervisedSolver` and the `SupervisedProblem`. The input of the supervised problems are the images, while the output the corresponding class." + "We now aim to solve a classification problem. For this we will use the `SupervisedSolver` and the `SupervisedProblem`. The input of the supervised problems are the images, while the output the corresponding class. We will train with `CrossEntropyLoss`." ] }, { @@ -494,11 +487,46 @@ ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 0: 100%|██████████| 110/110 [00:19<00:00, 5.61it/s, v_num=21, data_loss_step=0.723, train_loss_step=0.731, val_loss_step=0.723, data_loss_epoch=3.200, val_loss_epoch=0.635, train_loss_epoch=3.200]" - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "a70679a4feaa449db15d18c17588cf51", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Sanity Checking: | | 0/? [00:00" ] @@ -666,7 +681,7 @@ "id": "ab6f5987", "metadata": {}, "source": [ - "Let's now build a simple autoencoder using the continuous convolutional filter. The data is clearly unstructured and a simple convolutional filter might not work without projecting or interpolating first. Let's first build and `Encoder` and `Decoder` class, and then a `Autoencoder` class that contains both." + "Now, let's create a simple autoencoder using the continuous convolutional filter. Since the data is inherently unstructured, a standard convolutional filter may not be effective without some form of projection or interpolation. We'll begin by building an `Encoder` and `Decoder` class, and then combine them into a unified `Autoencoder` class.\n" ] }, { @@ -743,7 +758,7 @@ "id": "eb097e34", "metadata": {}, "source": [ - "Very good! Notice that in the `Decoder` class in the `forward` pass we have used the `.transpose()` method of the `ContinuousConvolution` class. This method accepts the `weights` for upsampling and the `grid` on where to upsample. Let's now build the autoencoder! We set the hidden dimension in the `hidden_dimension` variable. We apply the sigmoid on the output since the field value is between $[0, 1]$. " + "Great! In the `Decoder` class, during the `forward` pass, we used the `.transpose()` method of the `ContinuousConvolution` class. This method takes the `weights` for upsampling and the `grid` on which to perform the upsampling. Now, let's go ahead and build the autoencoder! We'll define the hidden dimension with the `hidden_dimension` variable, and apply the sigmoid function on the output since the field values are constrained within the range $[0, 1]$." ] }, { @@ -775,7 +790,7 @@ "id": "2df482a7", "metadata": {}, "source": [ - "Let's now train the autoencoder, minimizing the mean square error loss and optimizing using Adam. We use the `SupervisedSolver` as solver, and the problem is a simple problem created by inheriting from `AbstractProblem`. It takes approximately two minutes to train on CPU." + "Now, let's proceed with training the autoencoder by minimizing the mean squared error (MSE) loss and optimizing using the Adam optimizer. We'll use the `SupervisedSolver` for the training, and the problem will be defined as a simple problem inherited from `AbstractProblem`." ] }, { @@ -794,11 +809,18 @@ ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 99: 100%|██████████| 1/1 [00:00<00:00, 6.65it/s, v_num=22, data_loss=0.0318, train_loss=0.0318]" - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "2b5c90e63e5649a09132869ff4ffcd47", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" ] @@ -890,7 +905,7 @@ "id": "206141f9", "metadata": {}, "source": [ - "As we can see, the two solutions are really similar! We can compute the $l_2$ error quite easily as well:" + "As observed, the two solutions are nearly identical! We can also compute the $l_2$ error between the real solution and the autoencoder's reconstruction quite easily:" ] }, { @@ -903,7 +918,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "l2 error: 4.73%\n" + "l2 error: 4.78%\n" ] } ], @@ -922,17 +937,11 @@ "id": "c30996c4", "metadata": {}, "source": [ - "More or less $4\\%$ in $l_2$ error, which is really low considering the fact that we use just **one** convolutional layer and a simple feedforward to decrease the dimension. Let's see now some peculiarity of the filter." - ] - }, - { - "cell_type": "markdown", - "id": "f76db3b5", - "metadata": {}, - "source": [ - "### Filter for upsampling\n", + "The $l_2$ error is approximately $4\\%$, which is quite low considering that we only use **one** convolutional layer and a simple feedforward network to reduce the dimension. Now, let's explore some of the unique features of the filter.\n", "\n", - "Suppose we have already the hidden representation and we want to upsample on a differen grid with more points. Let's see how to do it:" + "### Upsampling with the Filter\n", + "\n", + "Suppose we have a hidden representation and we want to upsample it on a different grid with more points. Let's see how we can achieve that:" ] }, { @@ -943,7 +952,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -987,7 +996,7 @@ "id": "2cbf14b5", "metadata": {}, "source": [ - "As we can see we have a very good approximation of the original function, even thought some noise is present. Let's calculate the error now:" + "As we can see, we have a very good approximation of the original function, although some noise is present. Let's now calculate the error:" ] }, { @@ -1000,7 +1009,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "l2 error: 9.68%\n" + "l2 error: 9.72%\n" ] } ], @@ -1010,88 +1019,24 @@ ")" ] }, - { - "cell_type": "markdown", - "id": "465cbd16", - "metadata": {}, - "source": [ - "### Autoencoding at different resolutions\n", - "In the previous example we already had the hidden representation (of the original input) and we used it to upsample. Sometimes however we could have a finer mesh solution and we would simply want to encode it. This can be done without retraining! This procedure can be useful in case we have many points in the mesh and just a smaller part of them are needed for training. Let's see the results of this:" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "75ed28f5", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "l2 error: 9.53%\n" - ] - } - ], - "source": [ - "# setting the seed\n", - "torch.manual_seed(seed)\n", - "\n", - "grid2 = circle_grid(3500) # very fine mesh\n", - "input_data2 = torch.zeros(size=(1, 1, grid2.shape[0], 3))\n", - "input_data2[0, 0, :, :-1] = grid2\n", - "input_data2[0, 0, :, -1] = torch.sin(pi * grid2[:, 0]) * torch.sin(\n", - " pi * grid2[:, 1]\n", - ")\n", - "\n", - "# get the hidden representation from finer mesh input\n", - "latent = solver.model.encoder(input_data2)\n", - "\n", - "# upsample on the second input_data2\n", - "output = solver.model.decoder(latent, input_data2).detach()\n", - "\n", - "# show the picture\n", - "fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(8, 3))\n", - "pic1 = axes[0].scatter(grid2[:, 0], grid2[:, 1], c=input_data2[0, 0, :, -1])\n", - "axes[0].set_title(\"Real\")\n", - "fig.colorbar(pic1)\n", - "plt.subplot(1, 2, 2)\n", - "pic2 = axes[1].scatter(grid2[:, 0], grid2[:, 1], c=output[0, 0, :, -1])\n", - "axes[1].set_title(\"Autoencoder not re-trained\")\n", - "fig.colorbar(pic2)\n", - "plt.tight_layout()\n", - "plt.show()\n", - "\n", - "# calculate l2 error\n", - "print(\n", - " f\"l2 error: {l2_error(input_data2[0, 0, :, -1], output[0, 0, :, -1]):.2%}\"\n", - ")" - ] - }, { "cell_type": "markdown", "id": "8e720e55", "metadata": {}, "source": [ - "## What's next?\n", + "## What's Next?\n", "\n", - "We have shown the basic usage of a convolutional filter. There are additional extensions possible:\n", + "Congratulations on completing the tutorial on using the Continuous Convolutional Filter in **PINA**! Now that you have the basics, there are several exciting directions you can explore:\n", "\n", - "1. Train using Physics Informed strategies\n", + "1. **Train using Physics-Informed strategies**: Leverage physics-based knowledge to improve model performance for solving real-world problems.\n", "\n", - "2. Use the filter to build an unstructured convolutional autoencoder for reduced order modelling\n", + "2. **Use the filter to build an unstructured convolutional autoencoder**: Explore reduced-order modeling by implementing unstructured convolutional autoencoders.\n", "\n", - "3. Many more..." + "3. **Experiment with upsampling at different resolutions**: Try encoding or upsampling on different grids to see how the model generalizes across multiple resolutions.\n", + "\n", + "4. **...and many more!**: There are endless possibilities, from improving model architecture to testing with more complex datasets.\n", + "\n", + "For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/)." ] } ], diff --git a/tutorials/tutorial4/tutorial.py b/tutorials/tutorial4/tutorial.py deleted file mode 100644 index 1a1b999..0000000 --- a/tutorials/tutorial4/tutorial.py +++ /dev/null @@ -1,676 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# # Tutorial: Unstructured convolutional autoencoder via continuous convolution -# -# [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial4/tutorial.ipynb) - -# In this tutorial, we will show how to use the Continuous Convolutional Filter, and how to build common Deep Learning architectures with it. The implementation of the filter follows the original work [*A Continuous Convolutional Trainable Filter for Modelling Unstructured Data*](https://arxiv.org/abs/2210.13416). - -# First of all we import the modules needed for the tutorial: - -# In[ ]: - - -## routine needed to run the notebook on Google Colab -try: - import google.colab - - IN_COLAB = True -except: - IN_COLAB = False -if IN_COLAB: - get_ipython().system('pip install "pina-mathlab"') - -import torch -import matplotlib.pyplot as plt -import torchvision # for MNIST dataset -import warnings - -from pina import Trainer -from pina.problem.zoo import SupervisedProblem -from pina.solver import SupervisedSolver -from pina.trainer import Trainer -from pina.model.block import ContinuousConvBlock -from pina.model import FeedForward # for building AE and MNIST classification - -warnings.filterwarnings("ignore") - - -# The tutorial is structured as follow: -# * [Continuous filter background](#continuous-filter-background): understand how the convolutional filter works and how to use it. -# * [Building a MNIST Classifier](#building-a-mnist-classifier): show how to build a simple classifier using the MNIST dataset and how to combine a continuous convolutional layer with a feedforward neural network. -# * [Building a Continuous Convolutional Autoencoder](#building-a-continuous-convolutional-autoencoder): show how to use the continuous filter to work with unstructured data for autoencoding and up-sampling. - -# ## Continuous filter background - -# As reported by the authors in the original paper: in contrast to discrete convolution, continuous convolution is mathematically defined as: -# -# $$ -# \mathcal{I}_{\rm{out}}(\mathbf{x}) = \int_{\mathcal{X}} \mathcal{I}(\mathbf{x} + \mathbf{\tau}) \cdot \mathcal{K}(\mathbf{\tau}) d\mathbf{\tau}, -# $$ -# where $\mathcal{K} : \mathcal{X} \rightarrow \mathbb{R}$ is the *continuous filter* function, and $\mathcal{I} : \Omega \subset \mathbb{R}^N \rightarrow \mathbb{R}$ is the input function. The continuous filter function is approximated using a FeedForward Neural Network, thus trainable during the training phase. The way in which the integral is approximated can be different, currently on **PINA** we approximate it using a simple sum, as suggested by the authors. Thus, given $\{\mathbf{x}_i\}_{i=1}^{n}$ points in $\mathbb{R}^N$ of the input function mapped on the $\mathcal{X}$ filter domain, we approximate the above equation as: -# $$ -# \mathcal{I}_{\rm{out}}(\mathbf{\tilde{x}}_i) = \sum_{{\mathbf{x}_i}\in\mathcal{X}} \mathcal{I}(\mathbf{x}_i + \mathbf{\tau}) \cdot \mathcal{K}(\mathbf{x}_i), -# $$ -# where $\mathbf{\tau} \in \mathcal{S}$, with $\mathcal{S}$ the set of available strides, corresponds to the current stride position of the filter, and $\mathbf{\tilde{x}}_i$ points are obtained by taking the centroid of the filter position mapped on the $\Omega$ domain. - -# We will now try to pratically see how to work with the filter. From the above definition we see that what is needed is: -# 1. A domain and a function defined on that domain (the input) -# 2. A stride, corresponding to the positions where the filter needs to be $\rightarrow$ `stride` variable in `ContinuousConv` -# 3. The filter rectangular domain $\rightarrow$ `filter_dim` variable in `ContinuousConv` - -# ### Input function -# -# The input function for the continuous filter is defined as a tensor of shape: $$[B \times N_{in} \times N \times D]$$ where $B$ is the batch_size, $N_{in}$ is the number of input fields, $N$ the number of points in the mesh, $D$ the dimension of the problem. In particular: -# * $D$ is the number of spatial variables + 1. The last column must contain the field value. For example for 2D problems $D=3$ and the tensor will be something like `[first coordinate, second coordinate, field value]` -# * $N_{in}$ represents the number of vectorial function presented. For example a vectorial function $f = [f_1, f_2]$ will have $N_{in}=2$ -# -# Let's see an example to clear the ideas. We will be verbose to explain in details the input form. We wish to create the function: -# $$ -# f(x, y) = [\sin(\pi x) \sin(\pi y), -\sin(\pi x) \sin(\pi y)] \quad (x,y)\in[0,1]\times[0,1] -# $$ -# -# using a batch size equal to 1. - -# In[2]: - - -# batch size fixed to 1 -batch_size = 1 - -# points in the mesh fixed to 200 -N = 200 - -# vectorial 2 dimensional function, number_input_fields=2 -number_input_fields = 2 - -# 2 dimensional spatial variables, D = 2 + 1 = 3 -D = 3 - -# create the function f domain as random 2d points in [0, 1] -domain = torch.rand(size=(batch_size, number_input_fields, N, D - 1)) -print(f"Domain has shape: {domain.shape}") - -# create the functions -pi = torch.acos(torch.tensor([-1.0])) # pi value -f1 = torch.sin(pi * domain[:, 0, :, 0]) * torch.sin(pi * domain[:, 0, :, 1]) -f2 = -torch.sin(pi * domain[:, 1, :, 0]) * torch.sin(pi * domain[:, 1, :, 1]) - -# stacking the input domain and field values -data = torch.empty(size=(batch_size, number_input_fields, N, D)) -data[..., :-1] = domain # copy the domain -data[:, 0, :, -1] = f1 # copy first field value -data[:, 1, :, -1] = f1 # copy second field value -print(f"Filter input data has shape: {data.shape}") - - -# ### Stride -# -# The stride is passed as a dictionary `stride` which tells the filter where to go. Here is an example for the $[0,1]\times[0,5]$ domain: -# -# ```python -# # stride definition -# stride = {"domain": [1, 5], -# "start": [0, 0], -# "jump": [0.1, 0.3], -# "direction": [1, 1], -# } -# ``` -# This tells the filter: -# 1. `domain`: square domain (the only implemented) $[0,1]\times[0,5]$. The minimum value is always zero, while the maximum is specified by the user -# 2. `start`: start position of the filter, coordinate $(0, 0)$ -# 3. `jump`: the jumps of the centroid of the filter to the next position $(0.1, 0.3)$ -# 4. `direction`: the directions of the jump, with `1 = right`, `0 = no jump`, `-1 = left` with respect to the current position -# -# **Note** -# -# We are planning to release the possibility to directly pass a list of possible strides! - -# ### Filter definition -# -# Having defined all the previous blocks, we are now able to construct the continuous filter. -# -# Suppose we would like to get an output with only one field, and let us fix the filter dimension to be $[0.1, 0.1]$. - -# In[3]: - - -# filter dim -filter_dim = [0.1, 0.1] - -# stride -stride = { - "domain": [1, 1], - "start": [0, 0], - "jump": [0.08, 0.08], - "direction": [1, 1], -} - -# creating the filter -cConv = ContinuousConvBlock( - input_numb_field=number_input_fields, - output_numb_field=1, - filter_dim=filter_dim, - stride=stride, -) - - -# That's it! In just one line of code we have created the continuous convolutional filter. By default the `pina.model.FeedForward` neural network is intitialised, more on the [documentation](https://mathlab.github.io/PINA/_rst/fnn.html). In case the mesh doesn't change during training we can set the `optimize` flag equals to `True`, to exploit optimizations for finding the points to convolve. - -# In[4]: - - -# creating the filter + optimization -cConv = ContinuousConvBlock( - input_numb_field=number_input_fields, - output_numb_field=1, - filter_dim=filter_dim, - stride=stride, - optimize=True, -) - - -# Let's try to do a forward pass: - -# In[5]: - - -print(f"Filter input data has shape: {data.shape}") - -# input to the filter -output = cConv(data) - -print(f"Filter output data has shape: {output.shape}") - - -# If we don't want to use the default `FeedForward` neural network, we can pass a specified torch model in the `model` keyword as follow: -# - -# In[6]: - - -class SimpleKernel(torch.nn.Module): - def __init__(self) -> None: - super().__init__() - self.model = torch.nn.Sequential( - torch.nn.Linear(2, 20), - torch.nn.ReLU(), - torch.nn.Linear(20, 20), - torch.nn.ReLU(), - torch.nn.Linear(20, 1), - ) - - def forward(self, x): - return self.model(x) - - -cConv = ContinuousConvBlock( - input_numb_field=number_input_fields, - output_numb_field=1, - filter_dim=filter_dim, - stride=stride, - optimize=True, - model=SimpleKernel, -) - - -# Notice that we pass the class and not an already built object! - -# ## Building a MNIST Classifier -# -# Let's see how we can build a MNIST classifier using a continuous convolutional filter. We will use the MNIST dataset from PyTorch. In order to keep small training times we use only 6000 samples for training and 1000 samples for testing. - -# In[7]: - - -from torch.utils.data import DataLoader, SubsetRandomSampler - -numb_training = 6000 # get just 6000 images for training -numb_testing = 1000 # get just 1000 images for training -seed = 111 # for reproducibility -batch_size = 8 # setting batch size - -# setting the seed -torch.manual_seed(seed) - -# downloading the dataset -train_data = torchvision.datasets.MNIST( - "./data/", - download=True, - train=False, - transform=torchvision.transforms.Compose( - [ - torchvision.transforms.ToTensor(), - torchvision.transforms.Normalize((0.1307,), (0.3081,)), - ] - ), -) - - -# Let's now build a simple classifier. The MNIST dataset is composed by vectors of shape `[batch, 1, 28, 28]`, but we can image them as one field functions where the pixels $ij$ are the coordinate $x=i, y=j$ in a $[0, 27]\times[0,27]$ domain, and the pixels values are the field values. We just need a function to transform the regular tensor in a tensor compatible for the continuous filter: - -# In[8]: - - -def transform_input(x): - batch_size = x.shape[0] - dim_grid = tuple(x.shape[:-3:-1]) - - # creating the n dimensional mesh grid for a single channel image - values_mesh = [torch.arange(0, dim).float() for dim in dim_grid] - mesh = torch.meshgrid(values_mesh) - coordinates_mesh = [m.reshape(-1, 1).to(x.device) for m in mesh] - coordinates = ( - torch.cat(coordinates_mesh, dim=1) - .unsqueeze(0) - .repeat((batch_size, 1, 1)) - .unsqueeze(1) - ) - - return torch.cat((coordinates, x.flatten(2).unsqueeze(-1)), dim=-1) - - -# We can now build a simple classifier! We will use just one convolutional filter followed by a feedforward neural network - -# In[9]: - - -# setting the seed -torch.manual_seed(seed) - - -class ContinuousClassifier(torch.nn.Module): - def __init__(self): - super().__init__() - - # number of classes for classification - numb_class = 10 - - # convolutional block - self.convolution = ContinuousConvBlock( - input_numb_field=1, - output_numb_field=4, - stride={ - "domain": [27, 27], - "start": [0, 0], - "jumps": [4, 4], - "direction": [1, 1.0], - }, - filter_dim=[4, 4], - optimize=True, - ) - # feedforward net - self.nn = FeedForward( - input_dimensions=196, - output_dimensions=numb_class, - layers=[120, 64], - func=torch.nn.ReLU, - ) - - def forward(self, x): - # transform input + convolution - x = transform_input(x) - x = self.convolution(x) - # feed forward classification - return self.nn(x[..., -1].flatten(1)) - - -# We now aim to solve the classification problem. For this we will use the `SupervisedSolver` and the `SupervisedProblem`. The input of the supervised problems are the images, while the output the corresponding class. - -# In[10]: - - -# setting the problem -problem = SupervisedProblem( - input_=train_data.train_data.unsqueeze(1), # adding channel dimension - output_=train_data.train_labels, -) - -# setting the solver -solver = SupervisedSolver( - problem=problem, - model=ContinuousClassifier(), - loss=torch.nn.CrossEntropyLoss(), - use_lt=False, -) - -# setting the trainer -trainer = Trainer( - solver=solver, - max_epochs=1, - accelerator="cpu", - enable_model_summary=False, - train_size=0.7, - val_size=0.1, - test_size=0.2, - batch_size=64, -) -trainer.train() - - -# Let's see the performance on the test set! - -# In[11]: - - -correct = 0 -total = 0 -trainer.data_module.setup("test") -with torch.no_grad(): - for data in trainer.data_module.test_dataloader(): - test_data = data["data"] - images, labels = test_data["input"], test_data["target"] - # calculate outputs by running images through the network - outputs = solver(images) - # the class with the highest energy is what we choose as prediction - _, predicted = torch.max(outputs.data, 1) - total += labels.size(0) - correct += (predicted == labels).sum().item() - -print(f"Accuracy of the network on the test images: {(correct / total):.3%}") - - -# As we can see we have very good performance for having trained only for 1 epoch! Nevertheless, we are still using structured data... Let's see how we can build an autoencoder for unstructured data now. - -# ## Building a Continuous Convolutional Autoencoder -# -# Just as toy problem, we will now build an autoencoder for the following function $f(x,y)=\sin(\pi x)\sin(\pi y)$ on the unit circle domain centered in $(0.5, 0.5)$. We will also see the ability to up-sample (once trained) the results without retraining. Let's first create the input and visualize it, we will use firstly a mesh of $100$ points. - -# In[12]: - - -# create inputs -def circle_grid(N=100): - """Generate points withing a unit 2D circle centered in (0.5, 0.5) - - :param N: number of points - :type N: float - :return: [x, y] array of points - :rtype: torch.tensor - """ - - PI = torch.acos(torch.zeros(1)).item() * 2 - R = 0.5 - centerX = 0.5 - centerY = 0.5 - - r = R * torch.sqrt(torch.rand(N)) - theta = torch.rand(N) * 2 * PI - - x = centerX + r * torch.cos(theta) - y = centerY + r * torch.sin(theta) - - return torch.stack([x, y]).T - - -# create the grid -grid = circle_grid(500) - -# create input -input_data = torch.empty(size=(1, 1, grid.shape[0], 3)) -input_data[0, 0, :, :-1] = grid -input_data[0, 0, :, -1] = torch.sin(pi * grid[:, 0]) * torch.sin( - pi * grid[:, 1] -) - -# visualize data -plt.title("Training sample with 500 points") -plt.scatter(grid[:, 0], grid[:, 1], c=input_data[0, 0, :, -1]) -plt.colorbar() -plt.show() - - -# Let's now build a simple autoencoder using the continuous convolutional filter. The data is clearly unstructured and a simple convolutional filter might not work without projecting or interpolating first. Let's first build and `Encoder` and `Decoder` class, and then a `Autoencoder` class that contains both. - -# In[13]: - - -class Encoder(torch.nn.Module): - def __init__(self, hidden_dimension): - super().__init__() - - # convolutional block - self.convolution = ContinuousConvBlock( - input_numb_field=1, - output_numb_field=2, - stride={ - "domain": [1, 1], - "start": [0, 0], - "jumps": [0.05, 0.05], - "direction": [1, 1.0], - }, - filter_dim=[0.15, 0.15], - optimize=True, - ) - # feedforward net - self.nn = FeedForward( - input_dimensions=400, - output_dimensions=hidden_dimension, - layers=[240, 120], - ) - - def forward(self, x): - # convolution - x = self.convolution(x) - # feed forward pass - return self.nn(x[..., -1]) - - -class Decoder(torch.nn.Module): - def __init__(self, hidden_dimension): - super().__init__() - - # convolutional block - self.convolution = ContinuousConvBlock( - input_numb_field=2, - output_numb_field=1, - stride={ - "domain": [1, 1], - "start": [0, 0], - "jumps": [0.05, 0.05], - "direction": [1, 1.0], - }, - filter_dim=[0.15, 0.15], - optimize=True, - ) - # feedforward net - self.nn = FeedForward( - input_dimensions=hidden_dimension, - output_dimensions=400, - layers=[120, 240], - ) - - def forward(self, weights, grid): - # feed forward pass - x = self.nn(weights) - # transpose convolution - return torch.sigmoid(self.convolution.transpose(x, grid)) - - -# Very good! Notice that in the `Decoder` class in the `forward` pass we have used the `.transpose()` method of the `ContinuousConvolution` class. This method accepts the `weights` for upsampling and the `grid` on where to upsample. Let's now build the autoencoder! We set the hidden dimension in the `hidden_dimension` variable. We apply the sigmoid on the output since the field value is between $[0, 1]$. - -# In[14]: - - -class Autoencoder(torch.nn.Module): - def __init__(self, hidden_dimension=10): - super().__init__() - - self.encoder = Encoder(hidden_dimension) - self.decoder = Decoder(hidden_dimension) - - def forward(self, x): - # saving grid for later upsampling - grid = x.clone().detach() - # encoder - weights = self.encoder(x) - # decoder - out = self.decoder(weights, grid) - return out - - -# Let's now train the autoencoder, minimizing the mean square error loss and optimizing using Adam. We use the `SupervisedSolver` as solver, and the problem is a simple problem created by inheriting from `AbstractProblem`. It takes approximately two minutes to train on CPU. - -# In[15]: - - -# define the problem -problem = SupervisedProblem(input_data, input_data) - - -# define the solver -solver = SupervisedSolver( - problem=problem, - model=Autoencoder(), - loss=torch.nn.MSELoss(), - use_lt=False, -) - -# train -trainer = Trainer( - solver, - max_epochs=100, - accelerator="cpu", - enable_model_summary=False, # we train on CPU and avoid model summary at beginning of training (optional) - train_size=1.0, - val_size=0.0, - test_size=0.0, -) -trainer.train() - - -# Let's visualize the two solutions side by side! - -# In[16]: - - -solver.eval() - -# get output and detach from computational graph for plotting -output = solver(input_data).detach() - -# visualize data -fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(8, 3)) -pic1 = axes[0].scatter(grid[:, 0], grid[:, 1], c=input_data[0, 0, :, -1]) -axes[0].set_title("Real") -fig.colorbar(pic1) -plt.subplot(1, 2, 2) -pic2 = axes[1].scatter(grid[:, 0], grid[:, 1], c=output[0, 0, :, -1]) -axes[1].set_title("Autoencoder") -fig.colorbar(pic2) -plt.tight_layout() -plt.show() - - -# As we can see, the two solutions are really similar! We can compute the $l_2$ error quite easily as well: - -# In[17]: - - -def l2_error(input_, target): - return torch.linalg.norm(input_ - target, ord=2) / torch.linalg.norm( - input_, ord=2 - ) - - -print(f"l2 error: {l2_error(input_data[0, 0, :, -1], output[0, 0, :, -1]):.2%}") - - -# More or less $4\%$ in $l_2$ error, which is really low considering the fact that we use just **one** convolutional layer and a simple feedforward to decrease the dimension. Let's see now some peculiarity of the filter. - -# ### Filter for upsampling -# -# Suppose we have already the hidden representation and we want to upsample on a differen grid with more points. Let's see how to do it: - -# In[18]: - - -# setting the seed -torch.manual_seed(seed) - -grid2 = circle_grid(1500) # triple number of points -input_data2 = torch.zeros(size=(1, 1, grid2.shape[0], 3)) -input_data2[0, 0, :, :-1] = grid2 -input_data2[0, 0, :, -1] = torch.sin(pi * grid2[:, 0]) * torch.sin( - pi * grid2[:, 1] -) - -# get the hidden representation from original input -latent = solver.model.encoder(input_data) - -# upsample on the second input_data2 -output = solver.model.decoder(latent, input_data2).detach() - -# show the picture -fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(8, 3)) -pic1 = axes[0].scatter(grid2[:, 0], grid2[:, 1], c=input_data2[0, 0, :, -1]) -axes[0].set_title("Real") -fig.colorbar(pic1) -plt.subplot(1, 2, 2) -pic2 = axes[1].scatter(grid2[:, 0], grid2[:, 1], c=output[0, 0, :, -1]) -axes[1].set_title("Up-sampling") -fig.colorbar(pic2) -plt.tight_layout() -plt.show() - - -# As we can see we have a very good approximation of the original function, even thought some noise is present. Let's calculate the error now: - -# In[19]: - - -print( - f"l2 error: {l2_error(input_data2[0, 0, :, -1], output[0, 0, :, -1]):.2%}" -) - - -# ### Autoencoding at different resolutions -# In the previous example we already had the hidden representation (of the original input) and we used it to upsample. Sometimes however we could have a finer mesh solution and we would simply want to encode it. This can be done without retraining! This procedure can be useful in case we have many points in the mesh and just a smaller part of them are needed for training. Let's see the results of this: - -# In[20]: - - -# setting the seed -torch.manual_seed(seed) - -grid2 = circle_grid(3500) # very fine mesh -input_data2 = torch.zeros(size=(1, 1, grid2.shape[0], 3)) -input_data2[0, 0, :, :-1] = grid2 -input_data2[0, 0, :, -1] = torch.sin(pi * grid2[:, 0]) * torch.sin( - pi * grid2[:, 1] -) - -# get the hidden representation from finer mesh input -latent = solver.model.encoder(input_data2) - -# upsample on the second input_data2 -output = solver.model.decoder(latent, input_data2).detach() - -# show the picture -fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(8, 3)) -pic1 = axes[0].scatter(grid2[:, 0], grid2[:, 1], c=input_data2[0, 0, :, -1]) -axes[0].set_title("Real") -fig.colorbar(pic1) -plt.subplot(1, 2, 2) -pic2 = axes[1].scatter(grid2[:, 0], grid2[:, 1], c=output[0, 0, :, -1]) -axes[1].set_title("Autoencoder not re-trained") -fig.colorbar(pic2) -plt.tight_layout() -plt.show() - -# calculate l2 error -print( - f"l2 error: {l2_error(input_data2[0, 0, :, -1], output[0, 0, :, -1]):.2%}" -) - - -# ## What's next? -# -# We have shown the basic usage of a convolutional filter. There are additional extensions possible: -# -# 1. Train using Physics Informed strategies -# -# 2. Use the filter to build an unstructured convolutional autoencoder for reduced order modelling -# -# 3. Many more... diff --git a/tutorials/tutorial5/tutorial.ipynb b/tutorials/tutorial5/tutorial.ipynb index 688046c..ad41467 100644 --- a/tutorials/tutorial5/tutorial.ipynb +++ b/tutorials/tutorial5/tutorial.ipynb @@ -5,18 +5,13 @@ "id": "e80567a6", "metadata": {}, "source": [ - "# Tutorial: Two dimensional Darcy flow using the Fourier Neural Operator\n", + "# Tutorial: Modeling 2D Darcy Flow with the Fourier Neural Operator\n", "\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial5/tutorial.ipynb)\n" - ] - }, - { - "cell_type": "markdown", - "id": "8762bbe5", - "metadata": {}, - "source": [ - "In this tutorial we are going to solve the Darcy flow problem in two dimensions, presented in [*Fourier Neural Operator for\n", - "Parametric Partial Differential Equation*](https://openreview.net/pdf?id=c8P9NQVtmnO). First of all we import the modules needed for the tutorial. Importing `scipy` is needed for input-output operations." + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial5/tutorial.ipynb)\n", + "\n", + "In this tutorial, we are going to solve the **Darcy flow problem** in two dimensions, as presented in the paper [*Fourier Neural Operator for Parametric Partial Differential Equations*](https://openreview.net/pdf?id=c8P9NQVtmnO).\n", + "\n", + "We begin by importing the necessary modules for the tutorial:\n" ] }, { @@ -39,7 +34,7 @@ "except:\n", " IN_COLAB = False\n", "if IN_COLAB:\n", - " !pip install \"pina-mathlab\"\n", + " !pip install \"pina-mathlab[tutorial]\"\n", " !pip install scipy\n", " # get the data\n", " !wget https://github.com/mathLab/PINA/raw/refs/heads/master/tutorials/tutorial5/Data_Darcy.mat\n", @@ -48,10 +43,9 @@ "import matplotlib.pyplot as plt\n", "import warnings\n", "\n", - "# !pip install scipy # install scipy\n", "from scipy import io\n", - "from pina.model import FNO, FeedForward # let's import some models\n", - "from pina import Condition, Trainer\n", + "from pina.model import FNO, FeedForward\n", + "from pina import Trainer\n", "from pina.solver import SupervisedSolver\n", "from pina.problem.zoo import SupervisedProblem\n", "\n", @@ -65,13 +59,15 @@ "source": [ "## Data Generation\n", "\n", - "We will focus on solving a specific PDE, the **Darcy Flow** equation. The Darcy PDE is a second-order elliptic PDE with the following form:\n", + "We will focus on solving a specific PDE: the **Darcy Flow** equation. This is a second-order elliptic PDE given by:\n", "\n", "$$\n", - "-\\nabla\\cdot(k(x, y)\\nabla u(x, y)) = f(x) \\quad (x, y) \\in D.\n", + "-\\nabla\\cdot(k(x, y)\\nabla u(x, y)) = f(x, y), \\quad (x, y) \\in D.\n", "$$\n", "\n", - "Specifically, $u$ is the flow pressure, $k$ is the permeability field and $f$ is the forcing function. The Darcy flow can parameterize a variety of systems including flow through porous media, elastic materials and heat conduction. Here you will define the domain as a 2D unit square Dirichlet boundary conditions. The dataset is taken from the authors original reference.\n" + "Here, $u$ represents the flow pressure, $k$ is the permeability field, and $f$ is the forcing function. The Darcy flow equation can be used to model various systems, including flow through porous media, elasticity in materials, and heat conduction.\n", + "\n", + "In this tutorial, the domain $D$ is defined as a 2D unit square with Dirichlet boundary conditions. The dataset used is taken from the authors' original implementation in the referenced paper." ] }, { @@ -103,12 +99,12 @@ "id": "9a9defd4", "metadata": {}, "source": [ - "Let's visualize some data" + "Before diving into modeling, it's helpful to visualize some examples from the dataset. This will give us a better understanding of the input (permeability field) and the corresponding output (pressure field) that our model will learn to predict." ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "c8501b6f", "metadata": { "ExecuteTime": { @@ -143,12 +139,12 @@ "id": "89a77ff1", "metadata": {}, "source": [ - "We now create the Neural Operators problem class. Learning Neural Operators is similar as learning in a supervised manner, therefore we will use `SupervisedProblem`." + "We now define the problem class for learning the Neural Operator. Since this task is essentially a supervised learning problem—where the goal is to learn a mapping from input functions to output solutions—we will use the `SupervisedProblem` class provided by **PINA**." ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "id": "8b27d283", "metadata": { "ExecuteTime": { @@ -169,14 +165,14 @@ "id": "1096cc20", "metadata": {}, "source": [ - "## Solving the problem with a FeedForward Neural Network\n", + "## Solving the Problem with a Feedforward Neural Network\n", "\n", - "We will first solve the problem using a Feedforward neural network. We will use the `SupervisedSolver` for solving the problem, since we are training using supervised learning." + "We begin by solving the Darcy flow problem using a standard Feedforward Neural Network (FNN). Since we are approaching this task with supervised learning, we will use the `SupervisedSolver` provided by **PINA** to train the model." ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "id": "e34f18b0", "metadata": { "ExecuteTime": { @@ -195,11 +191,18 @@ ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 9: 100%|██████████| 100/100 [00:00<00:00, 289.72it/s, v_num=3, data_loss_step=0.102, train_loss_step=0.102, data_loss_epoch=0.105, train_loss_epoch=0.105] " - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "0b77243fe0274dada29b6bb5a15c47e8", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00.labels`. We can also access the values of the tensor by doing `.extract(['x'])`.\n", - "\n", "We are now ready to visualize the samples using matplotlib." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { - "image/png": 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gYDwo8NZchcLkTuKFIQfR5z73ufUMlbrhthwgOsDm07Tyq02OdJEtvFn0m6IAcmkxwpyn7+gn0967fp+CgoKClYiVKFsQnLwUTz755BG5J7d8X8xSITlsH3kUEat11IvFKPqizUOgyNOCIVEIxYIlg90gHoE8DlULHgcFWCT75d2W70o0uYOPQ5Mg44ZuJwrpJax2EhBhEtH6kYhY8RQJiw888MDG8vaqpNmZ4VIfCWnhqquuSouEnShJj5GxsdN2t7vdbeRxyVM0342LMGzfDwGVoFUDsyMldCJ39y8oKCgomB3h7ZAr1iohxoZYQIEvP7zmP/OZz4w87F//+tePEqpb8xk5rhVyIgqX2RwbJxN8Z9PKfXNZaxNuCDC6INKZRFuark+G8ZLIvSlmgeJoEtWT4/mziZooKCgoWM1YzbJFqG0ewTWEXeSYep81tTfSOCHUutifQ6LI04IhUXIoFiwZVAa2OMnBQKDUYZfCrlG+E5HvPNhZOfPMM3vd0/0IrhyuLQcgb8Mmj0kh0YG6yzYvSbkztCt32a5fv952RCTPxkVBpS4VvXgIvvzlL79uAd9hhx1GROprX/va9Y7n9emYWapKT+oDf8f4FhQUFBTMhrPPPnu9NCKUdnmRYh2XbiOMpwDjj8eDDbuQCaCKZw6RAfDYxz629f7O/cEPfjC6b0B6krZUIn0gXciRRx45CoeKPFRyaqkGaaMql+vkOA+ZeJZ5yTAVSm2IFhQUFKxmrFbZwm4jK9hyQXIOYRe5Bs9MFYtzW1I4eA5knui1Y445ptGGzO3PIVHkacHQKB6KBUsGOzPnnHPOdWXnea7d//73H5FtdrbOP//8kUs0yFVowVc4Ze+99x7tJJ1++umjXR1CrSs22WST0c4TASbk2mIqz4WS97wd/a2EPZIQ+SYs2fH+jnZwS7frdvvb3z798z//80joEIRtBWYUHpHbQTi1EAACyc7QvNyyhRFzJwf99I1vfGPUlz/60Y9GSYX1X0B/cvdHMsqF8sAHPnAkOIQs7LfffusVQZkFQpxda//99x+1jwBF4Jb8hwUFBWsFkrnXi3CFjLBbPyskUt9iiy3SHnvsMdqkY7gJZyLTwoiQK+pJT3pS+vM///ORAUgWxaYakAFkFUMt0nUwihgZwpPIiza4D3lIll9xxRUjA8X1Jc+fpp+0z3NoN292HhSiFPJIgBNPPHFk4IlykAje5tkpp5wyytl02GGHpSEjKnhT/P3f//1I3osw4HlDVwjPloKCgoKlQJEt/ftJbnw2KE/Cl73sZdfl3RvCLuIwo33bb799esELXjByZvHcZFieD989Tz311JHDx1//9V+nXXbZZRQ1J+e8IjVszTqx2RdFnhYsAoVQLFhSSNprcbWIWawtrHJEcKOXjyOElSSxdqa40SOlkHoqXVl499xzz873QySqCuY6FkrCDYmIHCTY5Di0yPEevM1tbjPKp3H88cdfdz4yzg6T61j05AVBErpeG1xHzkVknuOQi/I1ygnZtRJ1H6jSRTghLpGcQpwJSJ6gecUxsHtIoMgBee655448PlVxNh5ReW0I/PEf//EobD1yqhBgBAkFhLAuKCgoWO2wzjbBujuE0XfQQQeN5Kk1ljcJGUOWhdFlrSVzrMU2dnzuMwaHipSBN77xjaP2nHXWWaM0GeStlB6TwpFc76Mf/Wjad999R0aI/3k/MFAYVn37ySYiQ5anCwOWMVvfuBMmJp+xtjmPrGGoktt9irNNgs1Nm3KnnXbaKDk9w8fGnc06aU0KCgoKlgpFtvTvJ3YIZwd2Z+5oMYRdhPDkpKK9HFbYgaoSc2TJKyCDwp4+d5x78OjcaKONRoVtyLxZUeRpwSJwg2tK9sqCgoKCgoKCghUJCjiPCsr4zjvvvNTNKSgoKChYBSiypaCgoAtKDsWCgoKCgoKCgoKCgoKCgoKCgoKCziiEYkFBQUFBQUFBQUFBQUFBQUFBQUFnFEKxoKCgoKCgoKCgoKCgoKCgoKCgoDNKDsWCgoKCgoKCgoKCgoKCgoKCgoKCzigeigUFBQUFBQUFBQUFBQUFBQUFBQWdUQjFgoKCgoKCgoKCgoKCgoKCgoKCgs64YVoF+MMf/pB+8IMfpFvc4hbpBje4wVI3p6CgoKBgDGTa+MUvfpHudKc7pQ02KPtaTShyraCgoGDloMi1yShyraCgoGD1ybRVQSgSTne5y12WuhkFBQUFBT3wb//2b+nOd77zUjdjWaLItYKCgoKVhyLX2lHkWkFBQcHqk2mrglC00xUP/Cd/8idL3ZyCgoKCgjH4+c9/PjIqYu0uuD6KXCsoKChYOShybTKKXCsoKChYfTJtVRCK4TZPOBUBVVBQULAyUEKe2lHkWkFBQcHKQ5Fr7ShyraCgoGD1ybSS5KOgoKCgoKCgoKCgoKCgoKCgoKCgMwqhWFBQUFBQUFBQUFBQUFBQUFBQUNAZhVAsKCgoKCgoKCgoKCgoKCgoKCgo6IxCKBYUFBQUFBQUFBQUFBQUFBQUFBR0RiEUCwoKCgoKCgoKCgoKCgoKCgoKCjqjEIoFBQUFBWsWp556atp4442vqzr5sIc9LH3wgx8ce87555+f/vIv/zLd5CY3SQ94wAPSBz7wgfW+v+aaa9IhhxyS7njHO6YNN9wwbb311ulb3/rWnJ+koKCgoKCgoKCgoKBgcbjhAu9VUJD+8IeU/vVfU/rFL1K6xS1SuutdU9pgjdPapU9WF8p4rizc+c53Tscdd1y6z33uMyIC3/zmN6cdd9wxffnLX073u9/9rnf8Zz7zmbTrrrumY489Nj3ucY9L55xzTvq7v/u79KUvfSnd//73Hx1zwgknpH/8x38cXese97hHOvjgg9N2222XvvGNb4xIyIKC1Y6yDhYUFBQUrAZZ9t3vpvQv/5LSj35UfXb726f0l3+Z0t3vXn3/iU+k9L73pXTVVZWc+//+v5RufvOUNtoopb/920r+PfShKd2wsC4FqxQ3uIYF1REMqAsvvDB985vfHHldbLbZZun4449Pf/EXfzHRm4NB9d3vfndktDlnhx12uO57TTj00EPT6aefnq6++uq0+eabj7xGHNsFP//5z9Mtb3nL9LOf/WzkYVKw/GDB/djHqgX33/4tpT/6o5Q23LBakP/+71O6733TmsQ//3NK73pXSt/8Zkq/+U1KuAZ9suOOKd3sZsvfGCtGY7fxXMtzfCWu2X/6p3+aTjzxxPSsZz3ret895SlPSb/61a/SRRdddN1nD33oQ9ODHvSg9PrXv34kz+50pzulF7/4xWn//fcffe85b3/726ezzjor7bLLLquijwoKuqyDDKvf/x5xn9ITnpDSox61tmVEwerFcl2zbZgdeOCB6QUveEF6zWtes2S22nLuo4K1SxR+4xuVzPrVr1L67W9TutOdUnrAAyqZ9fWvp/Se99hITun736++hxvfuPr+z/88pa9+NaXvfa+6XhtuecuUNt00pa23Tuke90jpP/4jpRvcoLLz/H/rW1d//+AH1Xdw73tXn691u6pg6dBnve7FlV922WXp+c9/ftp0003T7373u3TQQQelbbfdduR1cTNvQgNWsjdHIUuG6TuLIyJRFGHs2tzhDlV/fvnLFcH4v/7X2iNcCLB//MeU/uu/UrrLXSphQqBddlklwPQRobVcSalCnnUbz7U8x1cafv/734+MKoSh0OcmfPazn00vetGL1vuMvHr3u989+vuqq65KP/rRj0ZhzgEC+SEPecjo3K6EYkHBSl8Hb3rT6jcd4AtfSOnii1PCT+y9d1kLCwoWgcsvvzyddtppo7Qe47CSbbWCgjpJ+H/+T/W3ackW/fWvU7rNbSoCEElHNz/99JTe+96KKPzv/17/On/8x5UOz/nFub/7HUK94gAQgY7njRj3mYSf/axyqvn4x9e1E1zrRjeqOAbXd10bcBBk4x3vWLXjdrdLif+Wz5zjWXhIFl6iYDmgF6F4MW0wA2+L293udumKK65Ij3jEIxrPOfnkk9P222+fXvKSl4z+P/LII9OHP/zh9NrXvvY6bw47Zq94xStGYWZw9tlnj7w5GGhLZXwVsmR6UjXvux//OKXvfAfLXfWhxc/CzMBwTa7g//mfKbHFLZRrZWHUr/qIsfVXf1UJFbD79ZOfVG71XOO32qoSZsuNlBqKPFtOpP0sbXHuO99Z7VI6z//OtaFjfO2ArrU5vpLw1a9+dUQg/uY3v0k3v/nN07ve9a70VwauAchC8imH/30e38dnbcc04be//e3oJ98ZLChYqXLtz/6sIhHJL94ZjDnT/yMfqXSqF7xgeciygoLVil/+8pfpaU972sij8Kijjhp77Eq11QrWJtiRvAa/8pWKEESw/fKXKf3v/53S//2/1d9+cqKQ7k235/nHucV51Kwg8HL8z/+kdPXVlW3GFnOMvxGNyD2qmmt3j/FsJh6dTx76iXtpJ2cScpQNXUfYFne7W0p//ddVRBtZyv7693+vbG3h1WRucYQqWBRmiubnAhnhYW2YhzfHvA2v4mk0PakafYcktOAhxyzcfsB19CdjwzFyUnAtdx4yB+G4FuBZ9av5FWQiweIzBpi8GyEQb3Wr5UVKDUWeLSfSftq2BAn5oQ+l9Pa3V//rF0rBbW9bXcNcN56XX14d57Mi5JcXpO248sorRzLtggsuSLvtttvII7+NVJwHeIYcfvjhC7tfQcG85JpQMIYeWWb9CxnHwPGZ45aDLCsoWM0QUfbYxz52ZF9NIhTn5XlfNsoKhgDyTuQW/ZrdyNuPPY746wIyiKzhMIB0hPA6HEcK+s5xIcP8jVB0rT5kYh3OrxOMrhf2FM6hzfPR5+gXdf6+/e2ULryw6oec4GSDiHITZi1zz7bbFllbsEwJxT/84Q9pv/32G+XQCHf4RXlzzNPwavMcW2ueRtOQqtF3docsbnJPyAehn+zu0CkiDEq/6lP/W6CROBb6tQLPGuRqgIDQH7w57IIhE0MP01+MtOVAvBLkCEVtayLP8nYizpq8/qYl7efh0ThtW4KE/PznU/rSlyry3N6Kpcxu6Q9/WI2p9EKWMu/Fq19dCfm16O28nHGjG90o3du2dUppk002GYWJ8dgQKlbHHe5wh/QfkeTmWvjf5/F9fKbKc36MPIttkOMqN+gYXncxIQsKVphcI9NDloUOBdZFxyAWl4MsKyhYrXjHO94xClcmy7pgXp73ZaOsYFqQJcKSzz03pa99rXJMqYcm90HIorhGV0LQcUFIskFmIRIDQRy2kYpNXpP14/QHW5G9kjumgPPZZ37e//4qd+M++6y7XwmXLlg2hKKdr6997WvpU5/6VFo05ml4NXmOBZYTqTMk6iSNZ5yGVHUN5AoihUFhofODcLLwWehsTiKieICFcYF08b97rxV4Vs9MEESeU/0S/Ubg6Tdu7wFEFxf9pSRezf03vKGaGxIXax/yOMizhzykyk+inXYBzzmnueCMnca+82seHo3TbiDknrjO1Q+KDJnn+oJHInJV+IHqb0h0P65jfNeat/NKgw2z3Ksih9Doj370o6MNtYDQsMi5KLcUUtExQSCSUZ///OfT8573vNZ73vjGNx79FBSsdLlGFoQsyxFyDdEolGstbSIWFCwK//Zv/zYqwEIuLXVuw7JRVtDVBiU3wg4944yU3vzmymYcAkHUkT+zEIKTPBq7os4v5NcnO7u2JTw0I79jU9vYJUjFSy+tahiQy+y0CJd+4ANL1FTBEhGK++yzz6jC5Sc+8Yl0Z+zTGMzDm2OehleT51iO5UDqDIkmksYGpESz97pXP1KVMOCFZTGUPJY9zjU8iLEIfbYAug/jwvc8ux7+8GpBWwr09Xqb1UvO+X6EMuv3v/mbdTkz9JV+IUS9DgyvAPJxKYnXIN94ThJG2hztjhB2zyOE3difd171LHWvP56rrtFnfs0rDcE0Gwg5CYk4FHbAQ9OOoDlhfkc7Pb9nRTYiYHkwuu5a8nZe7mDwPOYxj0l3vetd0y9+8YtRMvpLL700XXLJJaPvn/nMZ6aNNtpo5GkBDLUtt9wyvepVrxqFk/EE+eIXv5jegGkfzZsbjMhGIWaqX0byepWfJbkvKFitIAtt8thnJtuthaGqxYYiuUbOdZVlyynPbkHBSoC89j/+8Y/TX2MMsoJjbDY5EW2W/ZEXdAGe92WjrGAc2ANnnVWlBLIZT2ZY6+nQQyMvqtKXFHQOWRR2Qvw9BLlYv0+fa+bHtoVIR9vZIpwl/LCb1Df48IcrYpEzCHLRq/rpT1epSe53v5Q226yS1wUFk9BrmkjKu++++44S1jO4GEqTMC9vjkV6juVYalJnSLSRNDzLLDQIkKY+aCNV/e985Inf9BVeWRYx5yBXCAukos8RiRYvBgI7eymMhL5eb7N6ydUL1iBgGUubbFKRV3aPuKgjdV03d2Pn7WbhXyriNcg3BBjCkPCP/FgRwh55MQkvu2AEUt3r77Ofrc5FPDahPr/mmYZgmg2EnIQ0lxHovG2RivolwvcR7L5HNJrn+XiuVm/nlQiGF9Lwhz/84SgnlGqYyMRtttlm9P2//uu/pg2yibXZZpuNSEfJ6Q866KARaSjPVJ7644ADDhhVin7Oc56Trr766rTFFluMipottbdIQcE84TUhC61pfqzZeAhyH5kYXtrW1C6ybDnl2S0oWCl49KMfPSo0lmOPPfZIf/mXf5le+tKXXo9MXIm2WsHKQb4pFLo2G1HRLlll2DYILHYO+3EeZCKErRJpuJpCjuvHa5PXxd9RmCVCpun9ZFuXKs/160YbFoGcdDQG2h8FZshV/c17EbH705+uGwvPzWlit91SetKTKnumbOoVDEIoCnNmSL3nPe9Jt7jFLa7Lm8EI29AqsAq8OWKHnedTTl7Mm9RZ9C78OJKGoo4Uoo/wNKx7brWRqsgk30UIqPZHyJNF198+syhddVVlXLDZn/OcpTEO+nq9zeolVz9fhS7E4RVXVCTbPe9ZkVIIKt6LhJW/3cO8891SEa85+Yb09I4gzKL4jraaU//v/1XP5n9zuM3rTyJhpGJT5Et9fs0zDcE0Gwg5CRkhFOa3/wlffUIo6wsEo88RxsjX1eztvFJxhtiaMbB5VseTnvSk0U8byLUjjjhi9FNQsJZABqrgbN38wAdS+u53K5mBWLSGWx+7yLJSHK+gYDqwz+q57W92s5ul29zmNtd9vtJttYLlDbqxtV8hwo98pNKH2TM2lujt7D92JnLL3xHJdm2t17kgJxIjXVO0tQnaSXaRV+RQFBfFBTif7SEXIVuZI8gkchJB51xtaDo2iMY4ZkhvxrCd2C5RRNM9/M8W87eaB44LWet5jdFBB8mFWslhclx02WMek9KDH1zIxYIpCcVTTz119PuRj3zkep+feeaZaffdd18V3hz5DjsXbMnDhZ1a7Bj/XRThvuTgUuzCa5/7WlR4ylkcI4E6MstCSWm/+uoqvHUSqepaF1xQLZjIpEhi63ki54Q+sDhbgD3f4x+f0qMetTSLUV+vt1m95JyvEle9MjInX8TiF79YFe9giFnE5Rg0H8w580F/m3ddKg7Pi5TOyTfkGBd5bdQn7un+Puc2T4Fo8/oTLeM788s8m0TazzMNwTQbCHk/eGesCeGtqS3eAd8Tvrx9PWMQna5JYUI0UqS8d65H0frc54QPVSTzQx+6dGEGoQhKewAleXNBwXzzRVlHVoti7vnsL++xR5XOQ15l63M4RXWVZaU4XkHB/LDSbbWC5Qv2IM/D9763Wvvpt6Za6MbkHfKKrUPPJQut7eF0Mi9EfkJ6OtsLiYbotMlVL/aiLdpJxjgWkaZuH/sWIoqMbkxeyZX+vvdVzjLhOMPe5WTwt39b2TvCixWXCXI1PCZdkx6gfRHJx0aY5PnovKjsPMnbMicg2R1BcAIHCDZWtIdeEh6KQWz6jNxFMF52WUpnn13ZNkKin/70quhLkcVrG71DnidhtXhzWPSQBPI7gNxneNRJ3nTThNAuxS48ouPKK6u/w8sqr9QrHJUDqvYJW412NXnKhfJvAXQ+0swiJNTZbwuncyw+jAmk2VITFH293mb1klMZGeFqTjRVRia0hIDrE/1tzJcbKV0n37SfrqndlgZCUi5MgkUOrTavP+70vDE9FwGl78bNr3mmIYgNBO9al7Y09UPurakNfpv3xsLct47oDwoJwtC7TmFwD+dKloxA5rUZnrwUF+/+4x6X5hZu0jSvQhGkMBjPWPu23DKlvfcuHkEFBbMgrwwv3YX30DtpPbRBs9JDeZvkkA0Jm0wMsK4bXWuxOF5BwTxRt81Wi61WsPSIDXE2I136gx9M6StfqRxSgsBiH9KLg6gKbz+bT2RFyIt5bKRH3kRgQyhCIjruCU+o7k/3J0/IY+2U7osNTM50CfP1OecYP+Pw4hdX/YRMZQuENyDCkuOOv+M79gfHDK8pmylHhCvrLzYKm6NLIZc4L1KahqckUtLfvotxMQ5NXpLxmd9So/mxucfuExpdCrysXZRUm2MIPgSil9SiiDSJF63LuV3IwaXahddOBTO4nvPAtItSr9RrkUUWMQYsbuM85UL5t4gwGng8OicXHnZAXO+5z62Mp6VGX6+3WbzkojKyRd9u1bjKyHG+8e5qKC2KlM7JN0IRYRxVu/0gzDbeuGr3JK8/HniEeRdPzD5ehNN4abqXPgpDeJJXaBMJyRNH2IPdSf3inTLPfecYGxMIfN6/fghwv70rBx9cCXJzQ+gH5cE5L31pdb9ZSMV6zs7Iue49lc4gJ50de/jhlWe2d/baHOwjYtFOM2Xx0ENXNuFRULBUiHUakWjtj9QWkQKEfFnJobzjcjJbo3feuTqO9/O4TY21WByvoKCgYCUhdO2LLkrp3HMrGcYesG6HR2J40UVaoAjljRx98T99M0gtujN7cVqwD+jvbFuphmxm+cw9fcamZW/lcoeuPsTm/STohy22GH8MZ4IA5xv6AlKRzaUvw2OSPi6KiE7PvlAc0jPmXoqR+9F46GtyM4hC37HbwkaPXJD+D1K3a25Icph3JttBelVRaBxj9P9SRlsVLBZlmNNkgs8iZMEZR/BNQw4uxS587k0oD4JFiVKfV+p1T15JFoKXvKQyBsYRNLnyHwuU9sciEqXtI1/FuLZNIoOGCuvt6/U2rZdcXhlZn46rjNx2/rjnXTQpzdB97GNTOvLIau54Du1GThl/3nbmVRevP9fq4ok5yYvQ+7npppVA4wmoXeZhHy9N3+ujrnOrTkKa/4Q8wUx4aw+ywHgY94svrtoVZKMdUIqNQsIIBePlnlHcxjEUiVNOSWn77acTyLmBj6iMHKfxfiIVg3TeZ5/qWYRjxNyMuaStyEjfOaaEGRYU9EOs095BctAaEfmJw6vZ536vxFDecXLIWiIcjFemZ7aWtG1qrMXieAUFBQUrCbFRzYNOuiZkIHlFT42w2vBkyz3nIj9gEFWOJfcQZVHA0DXov3TlSXA950YUDTKLPYDQinDklSRH69B2BKOfvfa6/ve5fUhvp8/LWSkijhNU2Nz61A+bRB+TnzFO7DH2C5spxqpL+HQdrosI/uQn193XuISttAjCtmBpUQjFDLMQfNOcuxS78HVvQjtKXKx5JFLQLUpR4RnpYxGaRGaG8k8AuLZFymJOyFigIuzZItVmLHUJ2R0yrLdv7rxpi/V0rYxsp0m4cD0v5aTnnWbezULKOlcog+vqB4KJ8I9ciEFg8q7r4vXX5olZb6P+a7qe++p/xBvCyzzzGYIWidbHS7OPV2gTCcnbVLiw8c2NYAqPPkI4ErS8GY2XdhHAvqNMBQkabXEdu452Jiftao4z8LXz05+u7kHRAka9a+snIfiquwm5dp62h3IRibLlkvF8lMcSZlhQ0I6m9TXWae+R9y7yFUPIAQaANWJeobzzzLHbJofINpU8rSe8JyI3lGN8l29q5Gv0UhXHW6lF9goKCgrmBbacHPA27Nl5ZJWoGrai9ZiOa12Hej4/v5tCZ6MASZyb59wH+nuESQds2JOLovI5LpAnPOHk8VuLXnB1m4WTwlOeUunun/lM5bmoH8lZYeg29ng0+l5f0jfkd2TTsQnC2aBroZdAnEPGaxMPUOPuPtrwwhdW+SPZNCKx2LqctIpMXF1Yg69gO2Yh+KY5t2kXPi/a4CeKNgylpNa9CS3CPrOYhKu4tliwu5J0ofwTNowExpJ2uZbn8Rkiw2LXZCx1CdmF+jEEm3sKJZXbsk+Bl76586bJtdelMrL+QSrp6/z8rmHMfefdrKSsseNpol0IqCCdkFKukxOYOeGWFyBAXkdRmiaMa+PLXrbuHSAY5aXUFj/6k8DSn4gvoeTzTuCfC3Qhz9pLydG2IOJCKYoQZ/M2+iNCPCJMpD52nivClKc18G0auE6QGOaRNvCYNBeNH29I7dBWnyMfY4woJHZ9wbklzLCgoN/axejxv7XPe84YC4THhneSQu77od+xeefYbZJDnsv9PBODxqZZbHKBtYfs3Hzzqn35Gj2tvF0OpN5SFNkrKCgoGBrW0KOPTunkk6vUNznRZE2NAlzWePp3hNbmCPkWFZYhCoLQOa3rkb/PseFtx9tQ2jFkJr3Zmi9Hn+KVhYgaDzr9Ix5R/QS23XZdsUVyMcKl2UsiBRQHjUI5bJg+fRxjHuHTUVwn0sRxpGHPxriTiXSif/iHlJ761LVJBq9GlGFMw4TZTHNufRee0R9Vc/OiDX4PpaRGOy0odg4IgqhShUxAdESuhUnIK9N6FsSDxSkII4IAmeFzbSU8LFi5sdQlZNfOGIS3lWvy8ghjQY5L/++0U/XTtT/65s7re3ze38aQQHSMhVw/5y7nz372uvP7hDH3mXdD5FqUD4snIOUBQUZw5Pkged+Zn3kuSEJFKHSXudu1jfpIiLOdUjtexl97KCJ+IpScZ9+iEvh7D5Cs+ifCP4yt9nlX5JjRF55FpbQQovokjs/hufUvY3wWA19fBonhmuatdzPCLX2ub7y72ud/73BUeAuiw7X8lDDDgoLrY9zaZc3OvX6tmdYp3zve++ozOYi8X9YS3sPzbtdQORub5BB5EBsZPvd8vsvlme/J86Y1ehp5u9Sk3lIV2SsoKCgYCvRr4cyHHFLJpKbw19DxgwgMHTYnDSNPYhT+jCIgfoTDshdsZvuO0wk5Ql+W5ufBDy6e3UNCP/IKjBoG9Q03cur44yu7ik3dN+QZgjAMD1XXrpPM/mdTcEzh+IGwPuCAlPbYo4z1SkchFDPMEmYzzbn1IhdIGUp3ePZRxEG+OrAYz6qkuj9PwXe8o3rh81xpSAREgwVBmNI4jz+JeCnOeWVabs5+W0QsGCEkopIxA6NOqnYJ2b3iiup/5wnd1Jd2rCI8030Za1y8GR1t/eH42KEB/YCUy73euuTO65NrL+aFqrn6Kc9rgWDVH9ttt351sD5hzF3nnXNOOGG2XIv6j0cogWA8o1JYng+Sl15UcO5rYPUhUvM+QoLlXj8RQug65px+nncCf8/JW9LYek8RiVHhmccfss79fa7Yie+0DRjU3pPoz+gL/WkXTy7TWQx81/Uuerdjs8Jn2oAYBu1C9nuP9GMkc3ae+aD9nouyFwphEf4FBd3WLpt3iC2KOm9fa4KNNu9cJEOPnKveS2uJd21W8qmpXWHgaQfP8iHyojbJoZxAtcZZV3LZb+2xJjpOW5rW6L7ydilJvUXmMy4h1QUFBUODjELwvPOdla00qRAphEdhkIp+6I+uBbEuRVEW31mT2QlkHg81Ybc2zstatjg0pXiS+gjB+9rXVnnf2avGl+3QJQyazCPXjTGZX6+bUL8Gm4I9Loc7pxNcB5unYGWiEIoZZgmzmfZciq2XSY4BBINzKItyGFLQKdrhoffEJ647f1ol1TEIirPPrl5uyrwFILwJ3d91kTVtHl3IRDnytJerdFSmZSS5jmtoO+GgHyIRbxOp2iVkN0I0Q8BpZxCgzkW8OM51KfNN/cHIkN8Oscd1HyKR79579zMw+uTac6zKx297W9VfiDf39UyMSaTxAx+4flv7hDF3nXf+nrUAkO+MsWMRTJSI/FrmEWGkmrdj+hpYfYjUvI9i9zOIsrqxGqH8s3rWtRlx8ZyErxADZLy/Paex1mbt0FbtiiTUrkHwgmvG+2fsInXAvvtOFw6QG/jmtnmAPIjQFO8pojW8OZHy4UXkR3u8X+Ddc3zkzzzssBLCV1CQY9La5XNro3UIsRZpIrxrESLkM+8842qo4iz1doXndngte6dterjn1ltPf58mOeS5XD/I0/oabU2JHK3joj8mydt8XbZ+MoYXVaQsx6KK7JWQ6oKCgqEQ+faOOy6lj398HRHYFUih2Aiz5vux3vs8PBTzQpTCmHfZZZ1HYiEQl18RmNe8Zl0EIocejiT+ZrOO81ykxxh75wYZ3SUnozmHVxDd9bSnpfSMZ6z8gjprEYVQrGGWMJtJ51JikWJ1QoLhThF2nJeR8R/eCjwawoUc4eDzWZVUO0F2h5AcyDXtyb0J3UNewvAMzBd8C4Xdf+RYnlSVwu5vz81wQjh5Rt5Y4UXWRKp2CdnVJwgxxEZUkvLsDBILWOyeEFhN/eH/ww+vXPcJO20Cz/7e91YGz6GHzs9rIYqY6HdEk/brbx6S2s+rb4cd1vVL3/D5LnM28vvNUgAoCDqheFzVIxekOSFEz5yIHSfekIzUPgZWHyI17yNGuLmVF7wJYxV5NkQC/3FGnPc3nlN/yN0YRnsUItAORKt2mce+Cy9ez2XsEQyOM9/t0iETp62Mlhv42q6vKQMRRh25Uo2h+2m790H/aU/keoyE2o7Rz57Z9yWEr6BgHbqsXeTTk59ceSuqwmjdC48NMtc7Gt78jh2CfMrb5V0XZmRN8i5bB6zn1tQ3vGF2j8i6HCLzrTPWP6knyIVYo3PPbOuQZ51mja6vy5FawibePEm9JiyiyF4JqS4oKBgCdLszzkjppJOqlEH1HN59EDn3IsLF2k9Ht8aye6z/QpjZwIUoWhlgmxg3P2wR3MVb3pLSuedWf+dei/SV2EAEOgb0KfBiDol45KXIQ5JT1TbbVPURkJxlzix/FEKxAdOE2Uw6V840O0B1QoLiq/rRl75UKYcWY+RIGBZROStCiIZQUrWJZyHvx/BSjAISFNVLL60U/ze9KaX3vGf93W+7FF565+f9ER53FqEIiXVdgkr7HvvYamGoK7tdQnYtJhRp5GpUR46CJu7hd4S71vvDAsdjwc5H7JDFPSxYiBPfDRH2Nc5rAUGk36PgTvQ3o6pu4EwTPj9pzs6SHzQQ10AuBWmmLQxVpFPk10M0aztS2vNJ9tuE+lj1aWO9j/KCN9HPEUZnzCcl8J/FiJPvJTck3c87rA36CInsnXCsY8IrUTt5BiLujKe+NC/sztnBnTVRcd3A984ifiPkBGITwfsjP6b7b7VV9Z3nRX5on76MohKL8PYpKFhJ6Lp28UZ//OOr9/1Vr6pkkHfKd3nl5yHIp7xd3uEokJLLQL95Uft+iHe5LofywlkIS5tp9ATQT0HwdSmy0mVdZuj4n0zngR3kZWCofm3yWHftvjK2T+jyIkOqCwoKVn9+RI4BTRWY+yDyqceaykaxllmTEEKTHHEKVk7+RY43L3955dFKxiKO2YOqfXNA8sNOj3Re9Io+MHfMxyi0yRmHjKcvHXFEFUVRZNvyRSEUBwhrnXRuGyEh/FYoLGPdS2kRdm4UuEDaRHhQeOBNQwTV0UZYIWOiyIr221FigOS7376zk6C9AW2L3GxB5iABGRBICAozg4Gi29RXk0J2N9usUpQdG20lFINcjJxQiLqoLh394d7IWt/nBhv422faS7DO22vB/XIP0zYDZ9rw+XFztmnMo6J4jJFqm+M8ROrXcDzFxLhrE+GBoIoqnjxCzRefRz7QcXO3D5Ha1EcSPPPEdFwURNlkk/UVmr65p7oYcfJ6RtheGJKO0y/G1m/t8Z67Fw9en8WuW2wi3Ote1fU801BCs15p2w4jkhDJm5MYnjPyJkaV9rxoUHgTxTjO29unoGAloe8mUCjc1gUeHHVvumnk+rh2CVmKNApxL+2K95q3/FDvci6HeLPTA/JNjfBYQPb5u0v0R9d12Rprk8b67n7Wrrxv6/06bS7CJo916yxy1vrdZQ70DV1eVEh1QUHB6oO1jme8is1sz6FyipMpiB4yzbplvafbWodLOPPaqCAdclTYMg9Gdk+km+rqodgGtpLIClF8D3tY5b1oY7Zg+aEQijNikkLapvg61osSeQgp9UJvKdlR4ILyiEwLj6b6rvekQjHj2stjDrHgh4KKIORRhgASEuyFtXDUd7+RSAgQRGO0x8Lhf6RK5ITyfEGe8cDgodmm6E4K2eXhZddCH9kR4Wqdh7RG9TDtcGzeH8aFEQHhxZgjilI4Zh5FO6b1DIw+kT/Tro/jkIpIs2lyJdUJOOMtxNb/CD//3+c+1Ti1Xbt+DW3WZxSKuAaDKOY4IxU57pqbbjrZwGojUl1buJz7uU69j3KjzC6aOerHHM7fx2lyT3Ux4jyjd4Z3TE7WOo9novtEHseorqxNEW4cRN28jMLcwDffY3PDvbw3QVQLyY5+8p13Ot4348Bgzj1sh/T2KShYyei6CWQttAZ5x6wXduBtJFh/wptuGrk+qV1kO+9AspgOEDmTY81mDPIcnMe7XPdaDO9ofTNtDq22ddk6qh99b321XoUeUu/XaXMRtm0Q6+PIITZpI3Ca0OVFhFQXFBSsLljrX/e6dXInCuwNAWsaT0epeQp5uHYRNoZ6EM997rrci29/e6XjsBmmqRqdw5y1McpJRJ5F4fqzRnEVDIsyHDOgrpAyshELcg4EmdGm+FJ0kV+UX7nLHE/Bj7x0FG0Kvpeybuh38VZrIjrDmIn2eskRBjymoiKtRUFb8lChnOjYaadqBwrB42VmoERyd22IkKrwUuuq6I4L2RWK6Rruox99p60WGEaA56DER3h03h8RigR5Qvhc2EYbHTt09cRpK4drhz7znMY6dnlmWZSDgFOcBjlMsQiSyTN+9KMVoTwun2RO4n32s5V7O4Mtr+Yd0KfmsnHirYhgZLiOm7t1ktCc06Z4dsWEFD0Jo69reoK6AceQ1rfC+5HqBx3UXF2sqxHnnUd8hiFprnl/zVkbBsbdvYP8Rm7rf/2Tk7DzNgonkfcQ30WotvbrM+tHFHPwHMbSGM7qRVVQsBrQ5d3K1yCbHkKHyFKf2TwkTycVgBuHJvmlXdKNSD/i88jdmq/Z9JEhPCLnEfHRhLZ12Trqmayt0plYw5pkjrWsTujpFwYLYlB/PepRzXrVJI916z9PSePalM942tDlIdKWFBQUrB1Y44SKWgeHhHXJ+iRX+rR5vgtWf+7FbbdN6dhjU3rf+ypbcQiwn9iBrqk47ItfXIjF5YIyDFMq65EbyEIdRUcw8Z/4ROVVhgQUsoykaFJ8kWAMc27hlF/f58UcEF3IOV5jGH/oWiimaeddKA4PSC9jviPueXwfnl/CnJteTse7rp2uSLorhwKPANd2XcQog8hz1PMrdlF024wO9+B5Jtm6vqFMM5QYDEhYCjmjQdv32GP9/nCcfqLcR5XlPOTLZ8hInn/aKc+l5/Qs2sM42X337qXsmwy6SZ4rT3jC+uf47vTTU/rAB9Z5ggqL8x1y1fhPm3ydEhAh4owefavvzEV9gfiToF9+rzZjNkg8xvDxx1eEk+fKyVLEOMMMaWe+GSd/ew7Hjwtzi+sLz9CWUF7CMKx7cXSpApobcH7rxwjTZ1y+6EUpvfrV1fWmyYuFhEeYxntnfTB25q17gs+DZATvmRxq3idjov8WYRROImHzEOm3vrXqK++Pdz6KOVifeLh6lvAALihY62h7t4BsyUkk68nDH17JGzmIpE540IOmCwGGcR53yDGbgdZs7cnTHbRtbA29uTYtmtoxjlwj4+lf0l/43tpVL45XH4uICPGb7Ee+7rxzSk984vrj0MVjnU4oib2+auq7aUOX65uTEB7jNgXpBbw3ZvVqLSgoWPmQh/u882YPOQ1YY+jgQl2tb34XIqdgHMjOs86qnJaEQp9/fiVbo2jLLMCbvOxllRfkUUcVYns5oCwHUyjrDGuFSZARFlUKHSLGS2LXn5JHWZW7D4nk+7riy1POYuxzv/3P0yuKOVBKffeCF1SkBEzjiRU77wq/aJ8CEtEOvxFl2kgZRQzmocw5EDgWBfdj9FDauTW7D7IoCj0wXBArgSHCt5yHpGQk6fPwnELGekawG3LMMdcXcNrLkEJ+GiOEjvOMiQVJ+3iGKI4jN4Nn1F+eyTFIYvlGwq1/WoOuzXNFjimFb3KvUcRbeA/e4x7rqigbd5WTGT3TJl8XZof0dn9zNQwa42dM9Q+vPcfFvGuC++o3OS0YODmimigCW64+RrO5jLijkDzzmc3eH3XwRDQ+ebj0NAnocwPOfK1XOvXu+Z5wEn7IoJwmL1YQn3E/ZKjnj7yD3m27dB//eHUMIBKMd+QY1XdDhDpOwjgSNv/O+4SkN/94JkdlWO+g59J3xiGI3YKCtY6md8t62kQiRQEn67wNsr33rtbVvu9SlxBacpDsaUp3UPeInDYceGi0tWPHHcd7/tPRnvSkyqiuh1bXx6Je/do9yFoEr77JN++6eqy7J9nehGlDl/OwerpXrqf4ER1j87OswwUFaw82XqxtNlDOPLMiE4cCHdiayxusq3NFQQGQRyIHFXM58MDKxo4QfLKXc8IsFcbZ6M96VkovfGFK++9fSO6lROn6KZR1pBaCikJOEY2cgrn3G2WPAU4xjKIXFuL4nuIaYTEIuLzYgb+dh0jJDZO+nli5J55zkUZInXqVx7Y8cPl1hV7boeLJ51qIHQQI5TaUc4QoIgwh2iUsuytyRdoCpA+imjSF2vMgPdoWEsaAMF6hvpdcUvW5MTRuSDXPrbiIhU7fhScW4tFi5xmUsmf01YVpeE/w4iLAKfYMlyaDDmFV90REYuZhuEE2ua/PIidT5NU0fgyVafPseXaEmWdu8o4IT1bHjSMUJ+XidA3eiMhn46I/zWdEIGIXoTgOQyagDwNO24xT/V01FuaRdvOCVZkuvCH75MXK31FzwIaC8feuRAEhc9a6Yf4xXM0xn3sO754+muVdGRqe1TviXbGmIRLzym3mJE9thL/E3AUFBf1IJO+/dyzy0U4T5twlhFZ40LiQ7CDNpsnvNw9MasdjHzve85/O0CTD8rGIXLe5TNCfrmMNd+9842qIsONZrqHfPTd9hIy1oeNYXv+e5/3vX5eTs6CgYG3AWvn611d2jM3foUKc6cyIRB5g9NrlopcWrGxy8aSTUtprryoS7uKLq83UafN6kuHOR1jyVqSf4APKXF08CqE4hbJuwTZZKa2IOAa2xTYUecQbpTVIIUQVxa+u+DLSw0sKoTErCddGwiC5vKzIC8+RJyoflwcu2oPE8iy80fL2+JsHlmsRYE9+cuVVFsaKZ0bCyRUVyeCnfcnr+am0kyJdr+I77vxnP7siQIRqUsAj3NTz8Tj1vPoqJ5vcAzFMeX/zm6tQqboXh9+IJ2NImUekMRSaDLogv/RFPeyK95rn0jbkkuvp2yCjXC9y2DGI5pFnr0t4RN1rpCkXp3kRnqzTEIFDJqAPA0679F+92rf26/cI5fV+1MdvUl6sLkUagmx1fc+uXfpNn8X7gVhoqoa+VNC/3uOttqrGzMaCvtMX1jl9x6uVN6b3pBiyBasJQ4X9zjP/XZ/Nl0npDqbN7zc0urRDSLMk8OHh32Vdro+F+9RlQhR8c0xdXk2bEznHLNfQXh4ZxvqhD63aan2ODem+47NcwtoLCgr6w/v7wQ9WtpF1A2bx9gJrH/19110rksY6WFAwNDijvPGN6yqPI8PZfNMiZKMUcXJ7sve9F1F4tWD+KITihAkq55DiE0ieeriyhRtJgKTKi2WEQhqVUP1GtvHiysk2edce//iK4EJYdVWI+5Iw0d7wkEICdMkDF+2Rx9HztSnJQe4g0sILjyeYBOdInLe9LaV3vnP2kKmuBTiaoP0MD2Pz6Eevr8S7BuUegZcTw3n/+ckNi9x7IgxEJItxdB0eW0FMNpFoCMMvfrHyhEMwMQgir6b+tAgiuXwWAj2I6lkS6BtfXoi8FBGqdWOGh6nv87D1Ll4jfXJxdiEChzTAw4ATyh2eqfkzR3VT/YvU/eQn150TBYYm5cXqQoIjI3OyNdIbRNVkcJ8hKzzPinwcjJv+yueN3zYqzNVFEA0FBX0wC2EyZNjvEETUUJsv4yIdhvQMnwVd28HorXv+TxrjfCzIbDI3ZIKxIL9t7JDJNmLrfdelmve4+89yjegXz9AkF/uMz3IJay8oKOgP9qRQT1FysyB3nqC3H3xwVUyj6HEF84Y5JrJJxBpC8SUvqTYKZ8n7SZ6ztVxLjn9FiZ73vCFbXdCGQihOULaQibyKGM1IIAoXhS+8E0OJj5DKukLq7yDrkId1ss01m6pDD+kFoR3a6948ofJKx+PywIWCzig77LBu5I7zeV1xY24LVeJV4LNpjLxpq0WOM1C03Q8yp6mKcngB+E6b694T3K19hhz0PJHgXZ+7V92gi/AE3l6+Y8w4locXEs4zuhbSL99t1A6ht9opL+E0xqe+23LLlN773qrd5gYiLTzzGFCPfGRzH4/zGumai7MrETikAR4GHAWMN6qxdH/PHDnFEI0x9sgx76X+QAx79yflxepCghvvN72pUtqMY04mhvEa5OZyQYyD9cq8zj158rUOAb0IoqGgoCuaCBPvonc6ily1yZ6hw36HIKIWsfkypGf4LHB9eoR1WURIrJGx9uTt6KsT5GNhM9e6bx12besZPc6a11Yka1I17y7zYtprDDU+yyWsvaCgoD/o73vuOXtoszWH7JHKCumC3ClEYsGiYc4hsc0/3MErXlHxLrMWFCLfFNz0m7dtmdvzRSEUJyhbPBOFnSJ6EIBBMlA4/c2jCyGDQEHWUeRCIYU6WddGtiEwEBkM82knfRsJ4zdDyj2CNInqrOPywAWc05XcmRSqJJm4F1y/hvfdInbFxyniDBUGJsMliOH8+RgZSCVEGcOiTk6GByjjx98Rmhyh5blREnOLIeM+QcLG3DKH3M81whvRtZGOlAfX0c/TGJ/hrSN8VYi3fIGuH0ByKfrynOeM944Y5zXiOTyDHKPGM0K2+xKBQxvg2nLQQVXiXqRieIN6fu2LSsveZZ97T8HzIhFnqbycv0+8ZD2TZ4jwdeMbhHLTfZYyLC3GgXBHcGuf9iBjc+MbAb7cyNCCtYsmwsQ7JMeO1BVy65FBTbJnXmG/05JIk97/ITdfpiEn57E+kcVkFDniWrFGhtf4NCHi1lr6h2uT9//wD9V6TGZFsTabI3GPcX03S7TELNcYgjxeLmHtBQUF05GJ8s/NSibS9Xk4InFKfsSC5QBzcIcdquKxPBZFhfE2nAVseunFcDXmeykqND8UQnGCsgWIuKjE6nPGAG9CC7KKuZF7Tbgr4gMBgZigmOXEx7wVuToJg6AI0oTwsQtFYUYMUKC77qr3IXfaqlmC5w7izDUIsUXtio9TxLUTkcuA4bUXXpw5aYIwMUYUfp5uOTkZHqCejSESoclIq9wo8cxyO+gHYxEVnZ0TRVe0zf0ZPe7l2v5GNvuc8Ef49e2nureOsUKQIkG1V+iXcOVxxO4k7wgkHOIpvGERd/E+aHtfInAIT5AcBIlkwMceW72r5px30vhqOw9B4xxFlhCs5gOBNq1HaA7n63MKYVR1dy9j4H1E8EqAnd9nFi+roaCfzblvfauaA1GZPje+ZwnDLygYEk1y1tpq3Y7E39Z2a16T7Jln2G9fEqlLWOqQmy99ycl5hM26pkJP1kXjpf2Rm9c6Q+8ynn1CxC+6qCKYyfhIeyE5vGgJuQjlgI0N3UhDMqnvpo2WmOUa9fGB8HQnx8lIeaXH9ctyCWsvKCjoDmvgOedUIcnWv1nwuMdVmymFRCxYzh6L5BDZrAgZ+T+txyJ7Tr7G972vIuNVKy/VoIdH6dIOylZ4IzJQEAFIBso7gwCxuPPOlfIuLBBREZ48deJjEYpckDAqGl92WdUWiLx4EpVOE24c173wwip00/O6DmIsNx7aSKeopsiQo7BTfhE2QaYy9s48M6WnPa0i0UIhHsrzYZKhhFBSPVH/R/VEP7wWtJdHSxgWdXLStWKOEPTOcxwlPyeVGSgx/r7Pz3Ed1/U/ggYZLAxePxk75wiZl2uibx/o22OOqe7jOuFBaA6DQjKMK2TWOCNwHCnr2vKNImAZfJ5NglzPrD/vf//KcOtLBHY1wLt6ySAVd9mlyq3h+cNTUT8bN3OXEWtuRsidNgxZeTmK7IRw9Ds+G8rLapq+GQfzzjr36U9X55sHEYI4aw64goIhUZezeSXf8Iy3webzpo28eYf9diWR+oSlDrX5om3kAJkh3QudxMaBvqsTbPMImw0y2Pg84hFVkTd/kzeRo9gmLr2rvia3rXPIRAXRyFbjbwPJ8xj3Aw+sZMHhh6/ruz6brbNgmnU5J495WyJByVxz2g+dYffdx19nuYS1FxQUdFsn2Eann16ty975aWFd22+/alO9oGC5gxxTZAUJiF9BCn7gA5W3YV94b8g0oc9ISjqB6xZSfTgUQrGDsoXg4RFE2UQmKtyAQNlss/UVToQPD71w0UXg5YbDIhU592EI8A5j+GPjGQSvfW2l6PfNBReo7xDUcw62kU5ByFLmETZ5HsfwXPzSlyqByXBAogFCdAjPhy5eHPrF85x1VjXW/tYORmc+zk3kZMwRRtZ3vlM9OzIqN0okm83HP59X+gDZytCRY49H2LR5JnPoT2G+futDHhoRaq64hnHRThWaKRlPelJ7Hs82Utac8NzGilGub33Hm9K74jufS5I7za7QJAO8j5eMY9///uoY84yQiQJL4VFqTgTJp4/6eoS2GYo+00eM4Qh5dkx4+0XxF8c5ZxYvq2n6ZtIYPPGJ69qtrdoxRA64goIhUZezIXuCAM89yJs28uZZkbkrpolmGCIMVz/wXLEuksnkhX60eWFD6AlPqDak5IF+61urNckmzVDRFjkZ7Fq5fIy1knehzY18/Wpb5+hkSE9yyCadfrXW6xsbheTeKadUMuGAA9YPifa8Q3gxNMkD3vvTrsu+t/nJayM2P52PLDVWnsUmYZcq10s1vwsKCiavG8I+bXhYl+jpoZd29dRyrHf5Hveo9Hokit8FBSsJ5LDc/n7Y0RyjRMPlue8nId4Zdgu5j6iU0/6MM0oY9FAohGJHZQv5w2hmPCMVn/nMijCkXJvQlOZJSuIiFLl8h18Ia+715J7TKvq5NwKjK8g4hgUSNMiMNtKJ8eblR4IgaRh3wCBRpSzCKCn9juWabAFAvlDuGQR2KCjmL3jBdKRiVy8OAnycUdZGToY3oedrIuaaxj/mVYSl+87zMeBmhTGjQPDyMA76FWFpQdX/2uq3MYiCIMZTBWJ9UTdu2p6b4YlEdT3j5/2IJPo8PC3WDB/vTl/P20leHH28ZOpGOsMRGM/mJkMzvFL1lc89A7KvT5+3rQGu7zPvnn5oKspiM8Kzzupl1bdvumDoEPSCgnmgvs6GF3JU8iWDyJrY1Kpv5M2zInNXTBvNMEsYbr5eIKRsOlrbrRX61DqObNQua4/jrY3kMznWpX19yeBcPhpHnuNB+DW1u77OkX1kmvOiAIs+srHpuq4vlcM73rGuz2Pd5gk5a27nJnlATpKH1vtp1mXPwPvfuUjPKBoXOtUkHW85zO+CgoJ22DgW2vzRj1ZrovfSGuZ3n7BP6zh7QojzInNvFxTMC/QSHrscYHgrTptL1HuEe5Cz8XWvq96RgtlQCMUeyhZQtkAetLyoyMYbVzvD44x3Ct68Fbl5hFX39ZZoIp0ovfpD3riooJiTJK5F4UbQIqci/FSIpfMjDDUqVb/qVdMJxy5eHE1FaXie5se3kSvyF7WRK+OK5jAGXAMJPATpBsLeGVP6LghMfR3VLBmLyCkEIEKNt1uE/7YZN03PLTQ4vCTcLy804nmjSnJfz9tJ3nV952X+buinSO7v2SOvlr7S/vD+0z/edfebNN8mEXg77bQ+0eFdaNtQmNXLaqh8rfW55fiXvWzpisTMA8cee2y68MIL0ze/+c204YYbps022ywdf/zx6S88bAse+chHpsvklKhhhx12SO8nCJLQw93Tm8WmZ9huu+3SxapyFcwN9XU2L5rlvYnK5EHA1Dfy5lmRuSsWHZbatl5Yxzw/D5mjj67+179kMCKOxzWlnCdhTipO276mTTdtibUyCpfFWE1a5xCgwqMc7zw6hDXeZlGECJOJb3lLdc60BF/TetgkD9z3wx+u7inxfDxjn3U55Jj7NG1MT9LxlsP8LigoaIYUDVIxcFChi+ZeiV29scCaXLyvClYjyGORhDwNjzii2hCk300DclBOxbvdbfrIzYIpCcVPfOIT6cQTT0xXXHFF+uEPf5je9a53pb+jfbSgyaiCv/qrv0pftw2TUjrssMPS4ZLYZGDMMfAWjXHKlv8pXD6jPMfnQnUprpReO8ZtxjtvsXkrcvMwRPqSlDnp5HNeV47zwjIWPGdOkuinMPLAZ1HV2LME+WLB8B17XciPkNpp0MeLYxKp1SfEbB6KfFv75LbEdzCkeWPo/1BGGNiMKV6fjCufm88+1+eM7nHGTf25kYheX9dDwkWhkUiiT6Hp63nbxbuOgdhnXubvRuS95J0ZBF2Qie6DbJDDi8HZhYDvQuDxluHVrL8mbSi43yxeVkNsLMyj4MJyBGLw+c9/ftp0003T7373u3TQQQelbbfdNn3jG99IN2tZSBGQ/20QrsVPfvKT9MAHPjA9iWtyhu233z6daTv1Wtw4z/VQMBc0FSfjFeb98v5EZfJx+T+X2ht30WGp49YLQITxqqPfaI/1zvrrh+x2LvkV507bvr7ec5PaHfLNdxG+7DdiEalHRkX+wWk2XtrWSHko6YR1eeAZXMf9EQbkbr6x2GVdHkLHW+r5XTBfnHrqqaOf79oJH+WOvl865JBD0mMe85jG48sG2dLDOvWhD1XkBm9qaxe91NoEXcOdrS3yhJ99dtkUKFi9MLfl/jfPpUCR2sty14d0B++T1C677VZVg8YrlPdmQYTir371q5HhtOeee6YnSqo1ASeffHI6zihdCwZbk+FF4H1Ewoho2BKW4GlStsIOpPDVSUMGy+WXN+fbqSuJ81bk5mGITKPAhgcZ7wBEk7+RgsKVeDtQsin0vNvY5a5BEfc3MipCc6N4ixfcGCB4VMMVEt2nQMk0CdAnkVoqRPbNczjk+I9rH89OfW3uIc0YhPoyFBKGNUWFMYgE1Ab/B0k1ybgJUla/RtXiGC/n+j8qVyPcKThdPW8RZ3Jb8FSNVAGuWTfyuKqblwgCcywPH3Z8fV7W3w3tcz2Gck7S3ec+1e4u70Rt6ULAdyHwfC9VgutNIpRn9bKa1eisF/LRHu/kIiqyLxp1g+iss85Kt7vd7UabZo/AKjfgTyPJ67V4xzvekW5605teT64hEO9g0SqYC9rW9fo6G2saWWKDg9f0pEq+Q+QknBaLDksdt17oJ+uNPgwO3bqj3xBy+oUMchwZP0378nFU1MvfXTbdJrUbyDp6RmwkQWwi2UDTfmk+2tZt7VBwzDNP8kAM+RvFE4Qc5tclo8hJ8y/vsz5k4FA63lLO74L54s53vvPI7rrPfe6TrrnmmhERuOOOO6Yvf/nLI1urjrJBtrSwlrz+9VXBPWtSkCKRL7sJ3tM4zt/0Q5FyCk7Iw15QsFYgtzN7UJoSBOMHP1jJQTZLlxQB3iOFSvfYwyZJReoXz97+6M3a2eFq2+Vqwi1vecvRT+Dd7353+ulPf5r2MHJ5Q254w2VleNWVLYqfENJ8RzkQOWwo3XUFsUlJbFPkgAtvvahLHwVvHobINAosAakADKUZQRPKNoUayeg5kTV+9CmF3m/EkHZSxhkCXvScqEWouA9So2vY9jSeVpM8zpCiL3rRunx2fZOqz6rIT2qf3CsWU2CEaaN5yqDW5+Gx6LdngDpJFfPWnK6HfEdbPQNPC6HejKioWM1YC3LY/RB0XZ7PWCET3/nOatyRohE6He9eEJ0Pf3j1XB//eDVf6qHW2pDPy6Z3w5LjR794Tn/nO1RdjbOuBJ7cX10I5Vm9rGYxOqOQj3HV7nwMZim4sFLws2uZiDppOA5nnHFG2mWXXa7n0XjppZeOyMlb3/rW6VGPelQ66qij0m0w+A347W9/O/oJ/NwLWTD1uh7rbBRK8y5FYTX/d9nImSUn4SxYdFjquPUiPPh8H/xBeHgH2cjwjXQafdvXlmfQmse4Hrfp1qXd5FteFM7x5JJzrPv6tm19R0RK/i6vMm/MSR6IIX9VyEa21kOoYmPI8VEILEcXeTOkjrdU87tgvni8akQZjj766JHH4uc+97lGQrFskC0N6OAf+1hKr3xllReVHhtrpnc5CMXwbI7fYO2ylpALhvtpTyveVQVrF94FTkZ+pA0QCh2FW7q+i1K4XHBBSldcURU9Q1QWdMfC3QAZXltvvXW6m/jXDN/61rfSne50p3STm9wkPexhDxvltbpri0a0KMMrV7ZUFnLLJsIgvLI0I89zNk5JrCtylGqEpagDkxrI+C23TGnvvbt7A83DEOmrwI4ju3h3IixUHfNsXl6ERdjY+s5xjAjX9ncYMf7Xx0EAdQnbnrYwxTiPs6hKzUjRv8axb7GLWRX5SR5xyGjjz3hGYoVHDgUlvCTMW/1uvBCBOUkFQQCr5mmMmoz2INIY7qpm1ity6h/jlyfRnzRWPBOdyxDUzujryNMV5Jw28y70t/t4ngi1Rkyb66qCxbxseze8l0JMzCs7u7lC19U460PgGfcuhPIsXlbTGp3GQLJjZKL1JzxZ9Y8+9f5OW3BhJeAPf/hD2m+//dLmm2+e7n//+3c65wtf+EL62te+NpJtdW8OXvz3uMc90ne+851RKLXNuM9+9rPpjwxiDWRePfVHwWzrer1QWni5K/bVVs1+uWCRYanj1osIu7MeZ3vDo7XYmkxpt+ZqH3nSp31t42gMXYtHN9nRtkZOandsTNrkDY/A8LYM0tJ8aFq3yReeiY737IqtxRwjP6zddQ9EiE0vYVT6xXMFwrMzckHnDl5d5U3JgVjQB7///e/T+eefP4ouY1staoMsUDbKmsGmPPlkERLV2gSh3zUVXwlvRMdECgdr18tfXnlWlfe9oKCCAis4Bu+GCLquhYy8YzZG6VvPeU71/5iMfgVLSSj+4Ac/SB/84AfTOeecs97nD3nIQ0ZhZvImysvIqHr4wx8+MtJu0bBVuxSGVxthQOmkFCMBfffFL1ZKZHhUdVESne9xhE0TJhRo3l1253lqud5hh3U3IIY2RPoqsJPILueKbkcceXl5K7p29FGEGdnB1+6ockYnQXo5xv+TvMZmKUzR5nEWhWSMDwItQrL7FruYFZM84nga6h/eoH5iN5MBo83OpYz4zDyTiyLmbDynZ0EiMcj0eZPRnr8X9YqcYSx5N/qMlfmJwEQm5qHTkafLvXzO2GMoOo6OGp6R7mXOezY7TPX8j/V3wzXNNddyfuRR7GOc9SXwxhHK9TDOAw6ozvd/pAzgYTXOy2oaozPGAAmt78wbHjpRGVUfmwuPfvSwBSGWE+RSJHc+paR8RzC+HvCAB6S/FauZgUEW8P3GG2+c7nWve42MskfrxBoOPPDA9CJuz5nhdZecjSjota47Lrzkc7KKxyKiyabLcjfCFhWWOm698K6TFU2yxjpC1my+eeUhgzDr2r4u40gnknt6mrzE9CprOfnAuDAHyCLyyTH2tG04aUc9r601O/Q6/e+6edqNNg/EgD5xD+2Kc8Hv8JoNuUUH0k5/k3Vd5E3JgVgwCV/96ldHBOJvfvObdPOb33yU717u+kVtkAXKRtn1YRNFFecmbjW6Ms+XmK9L1it6mM1vxVtKddqCguuD08WFF1ZVzk89dXz6AIh3Lch8NufznlfJ4uKpuAwJRXk8bnWrW12viEseQs3oQjDyYDzvvPPSs571rGVheDURBiacCoeUV8pjFHag/DPGObgwyMeREoQD0lD8foTDUA6jeivi6tJLK+/FV7+6uyExtCHSR4EdR3bpMztzjAj946VHoHIxRpQgMyjVCC5t54EWFZ55FPAqoYDXPSKbnnOWwhRtBHIeOhWEV9drDolJHnFII+3RzkiNw2gxLuaYjWp5Ipx/3nnVfMvJNIYQMhHJZozajPaXvOT670WE/Acp2cXDr16BOfJzRZiz++p3bfrBDyoD0ffapu11z0jGoms0zcGmd8MzC2Gb1jgbymtkXBgn49UPl/4u73X9ndUOc1YfC5GpFzGOMXBN/Qx5ZVTvncquPHWQ6UMVhFgu2GeffdJFF100KjwmB1UX8PoQHnaE+IoJuOc975lue9vbpm9/+9uNhKJwspKTajK6rOveQWTQrFXOlwMWFZbaJuOls9h996oYWtPaZo3mIdOXxBqicFRbu8ObW7qVyBVs7DlTWbsilYfQZf1bz2tLttjwdHzutR9t0+YmD8SAtfKe96zWyHqf0YHMO2ss3Y5XPYJAW/Vzn43jkgOxoA0cNK688spRCo8LLrgg7bbbbqPCK5NIxaE2yAJlo2x9ICnYc21eU2HvBKEYv6OYk82K5z+/0t+XsNRAQcGyh3fmlFMqOclbsYnAD9nuWO9e5FcmlznbsHHpQSWdwGQsbDmSGPhNb3pTesYznpFuZLTGAOn453/+5yPDqwlLYXg15TTzm1JKGUQYUAgRYhRGvxFnUpCMy6tHGVS0AvFI2XS98AjSTZFQHNlhJ6pPZeM+XlBdC4p0UWDbyK7w7nOucE3KOgGJHEIA8e7Uhyo42xzVF85hADiOVwkCl54T5Mw4AiYItGkKU7R5nDFOLDRIOsRKHgI26ZpDYpxHnLFF0Oo3XL2wP4aPNptP+tK5UdSGp07diGQMec5xIV36nkE5BJHWVIHZ+EdORoqT98A9tYlHzNveVh3v+7pnpM+RX23j0PRumN/j5vakd6apunkUiFBBbJKh2DWMsw/BEO+sPD1c/40JQlbiYlWn87XJc+ljRIw54nlDsdX/5hMj2LrG8B2qIMRSg2zad999Rx4cjCMeGF0hlEw419Of/vSJx/77v//7KNn9HaOcfcFU6JKv1LtnrpIns5BVawHjPKLzdc66O6RH3BDViiflvO6y4WT864SkdZBc2WyzdV77OcJj07pMF2SohOxxnv6THoJnQ32jytwjj232aXds2Ggz0lY/90lxs9bnb0Ez2Fn3tjOfbApski6//PJRkczTvBgL2CALlI2ydTjppPFkYr4mWyvo7EFyWG+22abKDVcKRhQUdIcCqlKscZT+8IerDT/vWBD1kZ8U6AfhpehHuic55Z/61JTUIS7e/8uAULQzRvA0eRzW8ctf/nLkUo98XE7ICQPkl1Bdizz7MMJFkTMUQ8w2MsCmHnKmDRHG6PjwJAvZi9AhTExwL0DfysZDFinpo8C2kV1BEIG+ysk412UQUPq98F727bevyDCf6QsKuBdcfzt2EgGz007TF6Zo8zgzRs7jhVf3XJh0zSExziNOn2knL0Ten5GUPg9DNt/CmG4iih1/9NHdjD1ec7OGXzVVYJafKwxBBh6CWPEe3jA853j2xvG5ZyRof99xGDe3u74zTdXNGY+MyiAXu4T/xTMYM8S1Pp3Wo8p80Feu7fnaiEp9Zb2xHnnHvKvWHXOG0WtOef/6FNlZKWHO0nC85z3vGaXY+NG1Zb8VE9vQREtyuT0zbbTRRqPwrbo3B4/7eh4pMkyY10477TRKYk+eHXDAASMDbztl5AqmRpd8pVEBcwiyajVjkkf0PD3ihqpWPCnndZcNpzZC8trXv9UDMSJM9F1sBGuzvgvZl29Uua9KrgjH3PMfwrO26zo/zaZwwdqF/MB5LsMmlA2y+UHhFd5OXWHzP4gOdiXVY9ttyzteUDANyGTReNKtveY1VREkdjCbJ8hD7xaZHMtkpAmzYahyNH1JmoFC6A9EKDKUcs/Bq666auRWr0qYIirc27///e+ns7nA1AwvocxNie7333//UVUyYc7yLB566KGjnBy77rprWm4IxfNDH6pCkMlSSqfFP9zTERu8eXhJUIrHgYKJfGCk50Ik/mbEUxzZq30qGw9dpGQIssvLy/sJwZWTcfqNAk9JZ+TpDwI0iKUmMkwOokn5l3hguU49P1Lcc1Juy7ZQKm0HRkqOaatoDx2ixivHnIk21Mk2c42XWm5M18k0/dvH2JvV2GwioSMnI2LOvEUmHnNMtch7Psfz7uUhEpXWg6TuOg5djLI+70xbdfM+RYCcG0RqVK62nkgJ0Pf975NHNPKXem846fGQdp73MqqEx6ZJlyI7KwWqX8IjJVTLcOaZZ6bduWKOxudf0wa1ifEv//Ivo1yLHyIMaiC/vvKVr4zSfFx99dWjgmPbbrttOvLII4u3xozokq/UO4bIH4qsWo2YRhcY0iNuyGrFk8jKLhtO+bNZNz/xifFtQyjGOo1QDP3PdfPQqvy65KoNnlnDvJuIYOsyr8hxRWwK1gbYYVJJscl+8YtfjDbMeN9fcsklo+/LBtli8eQnI2v7neOdpoNJ86TKfCExCgpmA3mIlCd/qf0KjkZ6J3aWn6gKHXUH2GBRS4BexNEC91PexwEIxS9+8Ytpq622uu7/yI0hP4fCKoqqML5yyOHxzne+c+Ru37bThTy02/Vnf/ZnaYsttkif+9znRn8v10lpoplYkavO/8iP8FSsGyzjiIso7GEi13NiBHPuml0rG8+jSMkQZJcX03PYKYihjWIb4YWGvGDYeOGbDIEgw5C1k/Iv+V6VyHp+pKZw3LbxaSLK/D7uuCoxu2silbW7S4jv0F4FTe1zD0V8ZjGmtct1P/3p6m/HR/XyNmNvFmNznMel8RYGxjMx3g/Hb7xx5fkncT+OJsLNnGd+mdP6pa2Pu3gd9nlnYNYiQN4Bz2M+6W9CzLqAiOc4hxzv08d985QJ0VN10L3YFL6XaoCBrF+RurCaiBghz5PAGGvKUdV2Ls/GMN4KhkWXfKVSDFgb5kFWrQaPsXnoAn2eP46llH/969VPTmrOWq14VrJy0hyzNtrYpIf4O3I2RvE4pOEb3pDSq161fvuHCPNuIoL15TveUaWyQHTGpm2XqJOC1Ycf//jHI9KQPcbTXr5D8mgbMbNlg2yhkPbqggv6nWMtsa7galWbLe9wQcFw8D7xUmRDvuxllRNTvhziWoKT8TmnMfqI/9W7kBZGGPQQEaNrmlDkxTHOAEMq1kGg/ZqF3AI5O1YSKHQEhMnlRz4dRBePCDvfcvwhykJhnZTnz/mMdkph5LmD8FpEOFIQTepZDPmhkqBPS3ZFuM+VV1aKN4VYTkRTgyHj2fWF/JOIrIc//Pr5i4IMgy6Kud36SeG4k4ilnChzrNBz42W8Oeu6FyWed8C4EN9ZQs3HQfvMs7yf9TtjalrvPQaROez5hI/xkDM25s6kQkPTok/hH30p3xSyGckYOayuuqoSBN4dORaFozX1cVfvnD7vDMxSBMgYccP3PkQxGgiiFMnnvVBQpWu/9zVgCcgddqjCArQjUi5orzmVr2sFBUuFLmuFd2TW3K5dMa+1fV4YWhfo8/z1Y63bZIoUMta6IaoV9y2S1USGjptjCtWoPk3W5Gs10G1sgtmD4JGYp7wJz0n3IbPoEWSr9mnLpM2+JiLYmoyQjZxQ+hMZMWTUScHKQr1Ccx1lg2wx4EPTl0wMPYwHlbWjEBYFBcPDe7XXXpUuoFASUjFsxyhQGhEH5LGl0TFkthoF0hdIq+anyNcKpUZUT4RCZ3f6EY+owgP9HRUEGf2f/GRVNILCipiZlOcPWeiHIkg59Du8ICmbrm1ym7SzGPJDJkHvirrXmqSmFHoKMELOy4noCg8oZCzlPTwQvex5aHSQYcJ7uobkBhnS5D3RN5w1juUxx9PSMzjONXl3jSMT5xVq3mTMgT6se++ZT5SUccZ03lZ5GPWbvHpyTpkfiuZMs2vaxYOlS+h0blQhcQGR790zryz63iFzBClW7+M+3jl935lZigAhbIXZ8XitG6jOiWT+fQj/vnnK9PPee1fP4T7WNO9nVJ+fB5FcUDANJq0VfTYoZsEi0ogMhViD5YDWNv3hs/A+n0YXmFaG5sdqk7bw5hHiN4R3Z1vKEukc6Gc2aD07HW0cGdo0xzhx8Rq3ZjcRsn/6p5U8IoNzQjH0NxurZFQUvnI83YeeN27Dpk4ER6G72IRyTe3y+UqrZl5QsFrgvfZeHnxw/3PlzOY9dW09nYKCgjki7JlDDql0BO8ue4czBWKRnhD6EP3AZ+Q+WfuZz1SfLycdbylRCMWeoNBRihnnobQhufLCESYi4owSJzR2HHEhLxpFkBeYKkRCGpEjCpBQXsXum8AUzD6GfBN504dcmFf4Vij5b3pTlf/Oi+slzQvb6Cd9xjtONUYCNvcsQNyBStGE9t/8zfptawppagrHHSKclWIfydRV0Q3PmGnv07eP28KfPvWpasHTn+ajPtYnFkKEYNfiINqq38zJIJmMQfRJn3Z29WCZFDrd5F3DIPYOeVZemYhqPzwY633cxztnXMXyKL7kndfv2s1g5Z3inQ2v0LjHpCJAW2yR0oUXVtcF1+Bdimy3HiCwGYt9CP9pQv+MxwtesG68eAzPg4gpKJgVk9aKoQuJLGUakVkRa7CogCDYrJmR2iDkb58ck0OlhBD67Fg/4zyw++ol+fjTrchFmzLhvR7EH7kxjgztG7HRFsTzgQ9URgjZJBLFBp9nsmHH454MGKfn1Te4yAr9GXKGzHAM2b8U1cxXUth/QcE84H2TmpI90Nc5g57HM7HkZysoWBxwCpyEzjwzpYsuqmQqboJ+wN71P1vM5h+Z7YfMJmOFQOMzjj32+inr1hrW+OP3B6VUyC4Ek03xNtFMLr8ppJRDitQ44oLwoNSasMJ97JSbwEgfgoji6xhpT/p4hLWRNzvu2I1c0H5E6LzCt1xDEbkIRbIDkBMvjJrNNqvCO3lsUr6D0ECqyI0VRId+o8AGKdInpG1R4azzCjVvMuZiHJFZjAukqz6zGPo/jEhhrU1909TWPI+lceDuzUPDnOhiMEzyYNlnn+qzrkZIk9dgblh5JxFviD3wWd7HfbwOKXb1dybyfvrNG9JcO+ecKh8HIeM9dg0GY+RV9XtSqDnPHDWrPIc57/6eJch249enkMQsecrmTcQUFCyKrBiykMhSpxGZFrEGk5f0Cn2iD60DNi1tilhDVW/vslYtWobOElbuWW32yg2byyBr7Ic/XH0nV1lsGHUhg3m/09XIGRuedV2KXPC94wL62Bhou/bajOJZaF7T85CAxkAxrzbUN7ic47qRJoecj8qUi65mvtLC/gsK5vEOyK0mSm1CQe3rgZ73+tevc5goKChYHNhJJ5yQ0vbbp3TSSRXPw+4l28lPcp0NRqZydqI3sTF9zjnq61+viiext9cqCqHYU1goO85jyK4+ltrfwlqA8k2RM/mEh0rK7XteduHRFNWKKX6IHQouEgE77n+KPFKScKHQP+YxKe2yS3fmexJ5wzttXF4hL0NUqZ1n+BaSRx+6fpO3JJJRAQjhl44N4ydvm36VIxHBxdMTwSh0vKsn1aLCWecVat5kzOXEmjnHaPFdVOWNMO82o21cWxFo5g2jVJUrxHduMDQZ/MDIcC7PQcZbhNgx2oybuk4R8t/FCGnyGgzDSk5Tc5mxaM4i98xrRprnirZ19dSt5+IyL+1IuY5+1W7vLwVSGBsB5NkimS+B49m9z5NCzfUXg76tcrX7d81fOESesnkSMQUFq4Gs6LK2W4+0e6mI+dh4sg5Zl6yT1i36i7ZZ76IwmfXYO+/7+lrVtL4vSobOElbe5kVJPno++hY5kedCnERw+l9ECS8keoc1OjzKyWAej4rG5+fpW4ZI9L1nCLkVkRrIXsfxVGzq77rHubU8KlO6P32TrAmZsahq5isp7L+gYB7wHh94YJV/2vvfB9aS172ueCYWFCwl6ANbb13JUBsD9IKQr5xzwjMxosjoEL7z++KLK9l9+OEp7btvWpMohGJHhFJKAUT+CZMxuUwsE86EoswhHOxYC8OVp8jk+973KkWZskXohBejv01SxBoiAunD4Fc9GPvtXjzBKJVdDKcu4UdISx5h4eWX55WyM+bzpvPd2/PYQRMOSVGexSjqGorJUzGMnabwcfmQEIvahjTq07a++eX6HJsbA+YIxX+WqstNaDLm6h4LEf7Ulbxs6xPGqFC5CMfnteEeOVGtoEjd4JcXynnGDckexhOSz3yPQkaMN+PWxQhpmjv617WdhzhjUOXFkrTfXAnDrE8YcITpC0eWYNu1eJ8wQKMfGFTIW8/E05Ag8syu7fkIKO/dJE+aIC8RkUH4W1e6et2adx/7WLWZgVTVPuvUvPKUFRTMG8uZrJgkQ7QPieR9jGiGRROhsfFkTbQGRzSAfrSm8JKzdmmftc3ne+xx/SJWTYSu9X1eMjRf06y99Chrlv+tW13Dytu8KMlFhj8dzNyyTocn/iRZGblm6YE2mMLAAPqdfhFVkreHLsj4ID8hEr4H9L9xcNw4Aj3f4LLxpP2Kv7hXFGRz7cgPSS/yd/Tb0FhJYf8FBfOA9xWJ8NGP9j9XtJBCj+XdKChYHkDs81I85ph10RWRHoU9FilN2Jfx9zXXRia8+MXVJuORR6Y1h0IodkQopRRapIFJxeinbCIzKKbCX5BbFD/CQbiLqrMf/3hl1FNWkQ/OoXxBvpvsM4IpQld9l5M2kwynruFHu+5alUqv7363nR8hnp6XW6+2IExnMYr6VmEc92yOoaxSxv3dVTD3JZbqx4bXaeQW5FXQVNXb/GAkWGQUEemSx25aYzb3WHDtPPypC3nZ1Cd54nfXQ5hbXH0XXoYWT2Pj/NzgV2TEnMnnv7Yh+VxT23zHu4Ih1sUIaZo7jDR97b0MMtH1/ERKAe9TVNMU/u9c5L12O97ztRF35rn3hjcsL17PzxuFwea98OP4aI+5EB7JjvPT5pmTY5ZCEuadFAp+rCUMTfeP3Ghd85QVFCwXLJKsmCakepwMsd7L2WeTkV4QxP6iidDYeLKO5JtN2kJm+l+7I9G4NVnKFhun2jeO0NVf1kLPM40MHXdswAaJjRzPgFSMDalY19o8CWM8rdmes37dkJWgX+ohipNkpb459NCK7HQPx+ubNt2I3qivyZk2QtX3NsQmEeghI2zWkRF0z+hPfeGz73ynkjv64bDD5kdkr5Sw/4KCeYY5NxTOnoidd07p/PPn0aqCgoJZwF56xSvWOZKEswqZ5icnE+EG19rK7NsTT6x0GfJ2LaEQilN4g1EGhSbyikO2QRRkoChHYnPHmnT5ZAPkY4TbBHLShmJPQXQu78WuhlOf8KOmcMam88MzLZTg8GwYwijqQ57MI2y4L6lZD331tx0LnmD+RyBLus4YqxsDjEvXRL4Zzy557CahyZhFprkews6cQv4FYd2FvGzqEwskwsx8dC33zA0Hz68fkKV5Hirj9453VGOiHUFs+s1Ii4paDO2c9OxihMTcQZ4JETZPGU/uq28Ria4dRU0YveaW5ycUeOJGnlIeRM4RkuwZ2og748UARQ54P1V4914gQxmCfusLxqXni3VAv0mL0HVuTpO/MIx+BjfDWH87PjxArVfjjO+CguWIRZEVTZtA5LCNgTZv3nE5Sq0DNlOsuY94xLo1eCm8tmLjid6Rh8eSUf72rNZLMszn+hQZJUH5UUdNJnQdT0/pK0MnHRvjwrvT+m5NA+ubfo91zcZJXfbn44lM9L+oD2lUYl0OWelanj2XQV03+qzVwhy7rNVki8qtnp3Mq4eTe0ZzyebXJAL9pS9dtynG817+XjIpvBvJOKHVIjwit/S8iOx5pXQpKFju8N6K2lJoqU+YszXLZoSIqoKCguWJkO/0DCQh2857Tr7WycQcdJRnPauSvZtsktYMCqE4pTcYpZSCiKxAJlDITTRGSCCqBwp/ocxSGKMqLOWVEm5iRrhM5L6j5OeeZV0Np74hvJPOz0lOz+sl8azarZ1DGEVdyZNZn20IUjOOPe20ijgMklVIEUOSAXLEEZWykHsiOsb/yMQY5z6eZ30JUb+FQBk/IVHmYB/yst4njBTPinDLCXMwd70DkRc0h8/dx5wx77Ul+kSbvDOua8zC4O5rhOTXcy/jEEn486ImxojBpahSJOfngcPbEOmmDxl5wv4n5W5EFtTfC8+ivxmm+sH3+lr7ppmbffIX5l5c3h2kovFwDe0LD2PtKcZdwUrCIsiKugee91pqEISg3Wk5UimUuXfXpByl4Qn48IdXxM5Sem3FxpONF7KbXmItis0Q61Wkb9E2SrNnstHiM8dbK9sIXWv7M59ZbbB0laFd5G2sa9Zb42ydDo87a1ukmyFb8/W1Pp6en/4Vmy2xuaL9dA9RJHkIU9+Nvq5rtbZ6dmSgeaINQahao8nAJz85pcsum0ygk+82xTzPwx62bsPac/K6N69cQ7t8N08ie166WUHBcoZ1iFci7yVrfxdYA7yH3tFIfVBQULD88yqCDQD6gnc/kDuL5RD+vPnmKb3kJWsn/LkQijN4gwnhtGtO0UUC1r3BkBQURkoyMoPQoagTKggIinhU6oPIL+fzPBS6q+HUN4R30vl5gQ/IE34PaRR1UchnfbahPMIcx9DgaeAYinL0hwXk8ssrI62OCA/Wn3mhma557NrC8doMNMSYfjHveMf1JS/zPnFdXiI88+rEn7kbYXK5h0d8F8aM7xhN/tY/CEA/vm8ynnIjpOnZhRqH0WjuICv1P4PKPXgVeWeiqEmQnkIQ694f7m8uM7Yk2ffsTWMSc9A1wgCM/I2UQ+8tT0hGe+Tkcswsc7OvF1dUng/Po+j/aE/k7epj3E1bXbegYNb5NG+yoh5S7bfIA2QbWeed8V4j48K7C5pCUvMcpd69M85of+cXSeznG0+xyWL9yguC+E03CQ9v/ckr3SaYdVVfNPV/PIdw3qY0Kk3j2lXexrpG3toIimO1l+wwRmQbeaJ4XeRXjHyLxoY8cBxC1PMhR1VvVDDF5/rBhm9EhXjmWTf6xuFxj1s3fxC25hDimWeiHGxk7CWXTCbQPXfdczdCscJD3bzN80LOi8iep25WULAcwRtdOKQCLDY8usLm0tFHFzKxoGCl4VGPqtJe8UjG+cTGZk4u1kEWy8NIvzr22LTqUQjFjmjL20ZZiyrPlLjcG4zwiNBYAogCi3CIiUh5RTIKh6Ww+5w3GMW9HlbaxXDqG8I76Xz3i0qzFG/Pm7drqYwifamPwhBCFtntnyZsOL9+FwWbIm689UPdwIq+0p56gve8v5BMfUrLT6pwGgYar4WYi8KvKfDGfVoiKPrEeQxqBkOEvQcYcxZN/V8nG/MQZwaF+c6A0h6Euv5BfEUF6iYjxNxVjCd/ds/mOjkxGOHd7uE908/CFeM71xMaRhD0DZ/MCRDGp35gZHu3I6w6Uh6Ep6LPGHTaMW1I+zReXO4RIe/hhWOM4hht6mPcLdfqugUrE33n07zJipyMh9zzOO7l3RG2Ym1BVkFTSGqeo/QpT6nWh+XitZVvPElh4jmtvbHBoC+1xcYM2UUPibAea8YHP1gV3qp7W+bP0ceretKx1lVtjCTo1tZYV7XZOuu+CENrsQ0012Tg8xjyDIhhz4iwEzXgx7haG5GKNn6COOybYmJWUnH77SuyVj+Tf7ws6TNkeBcCHZo8d4Mk9gz6pZ4Xch4626x6Z0HBSsJFF1UF9sz3cWRCHd7Jf/qndZsKBQUFKwfk1047VcVHeflHobNJ+MO1BWXpLcjF1YxCKM6glAtboTQxHCi4qv0h3ijdUTXZsfLImVQIuQgf9X+4yVLCQrGnDCIt8rDSPobTLEUd6ueHpwYgayIJ+lIaRYwau/sIrjAWhLPuvvtiE9w3eRCEl16EwNUxTX91rXDKY6/NUO9DXvY1GMwv3h1C5upgEHkvzG1knpDpKFSC5PJs/neNqFCZGyHa/drXXv/Z5avh3RGhXuC353U9P4z/KDgQ1+N+/ra39QufbCJAjJ/ndZzdaYYg49h7b3MgSE1t3XTT+Xi6jPPiin4Ij9AQfAxmHjBdjbvlXF23YOVhmvk0b7IiX89zj/xYV4KMR2Qh24RBk9FNZFi+KQHLzWsr9wwU1kzJ1Q5tC9LOOud5I88i0FusJZ/8ZJUPMnSAeT1HrLn0D5uH1lhjYjPWuFtbyRD3N24IOb8j36L113fWPOuiZ0E8Rg5gc2/PPSuSOCcOF5lTlsyw4TUtgW5TrYl4jEIz+ojs1U90zvDUH0pnq3sZ08EYWzz8eYdGTs55eXoWFCwFrEdSFkTl13EeSnkopHfkzW+u8p4WFBSsTJBjhx9ebbaqldAU6twGHorWBB7KqxWFUJxiQhEgjBtehZRTvylqSB1Eg3xC3GOjKMLZZ1eKHYIjEqOHMky5892221aEi911yjsFcFrDaZqiDk3n2y0/+eSUvvWtqnJhvYjMoo0iBoOXmAK91Vbr8lYyBPOqlPPEuBA8CrvP9Es97Hma/upa4dRxTcTbkMRPG1HNKEPm6v8mg1/+sRg733k/PIfvjBeC2I6P73lXRhj3M56R0vve1/zs+s854UkY3zF05cfSDmS/ecvYDKOGgaOIS1evoTYCxH1jHmhbhL1HG5APQuJf/vLqnZ63Z0bdCI1+ME7WEqF8PmPAdvUsXGR13YLVj1nm06ybZF3X8/DuiirI4F0mryNvqh/PYuOAfKxvssWmhOstR6+tyC/Lkw9B55k9GznKo83zh7d1VKUGstYz5+HC83iOfM21+aH/fOZ+2mZj05rubyShfuV5GDoAfcfcQiIa2/DQjvF1Xb+lxFiORam6Euja3kQ8kkM8LxEfzkPKhs7pc3Pb+M2is7XlD42iPmCcHv/4dXpwQcFKh3X/hBMqOy+IhHGEQnznPUQmrLWKrwUFqxH0TfmL99uvCn+ma3TFiSdWXMpqXQsKoTiFUKknww5FjjcSJVAePYoUUH55ZyE3KF8UrggvohwyZiT5pADutVflBTGE4dQn/KjtfGTIc59bKfhBCC2VUZQbpELL8p37yH+XG6Tzyvs2zoMAGGE89tq87vr0V5cKp54bYbQI4mccUY0cbJu3MG5Oez8i/6FxCxIewdhUDCBIP+Fw9dByxj1jkZH5nOdUxB6PFe8Xw8p7qh2TCPJxBIj55/m1N8hGXiAKObgG442xft55iwkNbjJCPT8PzwjP1xd9jLtFVdctWBuYdT5N2iSbdr3P13MkSJ5/1JrAc887773yN289pIyfegX1+qaE55gXETot8nVNmK3fvP09S1Qp1W/WydBV9Kn+oJs0hQsP9RxNa65r2xzSNvqT7+hUCEbrfhBj2qiPbe4ay3yOGU/EcOSP9JshoArjcvScG0egi3pB3JFnIlnM+TrxSDf1zP6OTU5/kwWRbmVaXaC+yYZI/PSnKx2EzFNV2jtCFtm8M2eWYx8XFPSFwgpvf3v3as5khHfkVa9apwcXFBSsfJCf5CA9hazuSir+z/+k9OIXVxEG7MjVhkIopn4GSd0wonBHGGco3blh5FpRHAJBZ6c/Kjg7n5LsGAqYc2b1Lhwa8/QOmZdBSsmdV963SR4Exji87mbtry4VThkJiC0hR4sgftqI6nzeeh9i7jJ+zN+2hP3aFt6VniH6UhL+73ynuRgAowhpK+xZ/+TwPupz5D4j8h/+oboHMoAiaCy8e9oS5GET4cv7aNx8I0gYushQYyDdAa8Z/c1gY1T19RCdhQRve09VmZ3mPV1Edd2CtQPzxLpMocpDMPvk421be2bJ85mv5+5vQ0gkgbZpSyTP1/aoGA82M6wX1q0oHAJ1L/TlJs/rchQRaq20lnrG8FCst8+z20C1LjaFC8+jbWB9JRestdbHyF2L/NWvPLD1t3419jZSwrMS6ah9/vZcZINzfU8+Mwim9d6fd6GqpnnjOWxm5/MciUfnjHy94VnqfH/7XJ8ZP0YMksPG1w479G9vnfAFclrf0nt8buOcJ3zxYi9YTTjllCr/WVfiwHsmBYDCLauROCgoKKgcNcjTU0/tHv5Mh+LdqPjaapOLhVDsaZDkhjZl1jkUqaiWSMGjyIVhRNGkIPNaZHQgFAPhAYEc8XmcM6t34dBYDkZRV4KDgnvxxUsT/puThhT2WfurS4XT8MZcKuKnblhpk9CzLu/SOC/AyAtpseaRkpN6/tafnsu9GYl1T1DeKwceWF07Qr4iv2W8q5LiC+OLnKc58dZlvrneU5+a0jnnVMa4c9032trHqBqi+MmQ7+m8q+sWrC0gEZFWiHfz0fvnPY2Q4Wnn0xB5Puu5kZGFfmwOCLt1rci/F9cit93TGmANse74rMkLfVZ5PiR51bSuMZIjZYNncL/wwomNUsf7jmciMrHv83R5hqa2WUvdL0KctfVBD6pkQl7wigyIHNTOR6pFHlnnxEauucbz0jjyXJ+G8FpUoap83rgnUkN+QvfzvJ4n5J00O/rEM592WkVi6Od8s9sYG8NpNxjrhG946LuutpIT/o+ogeLFXrAagMSXN9EGdRdYa6xRcibWUx8VFBSsHpB7CjRddlkVNdAFeJ+Pf7zKpXjwwWlVYc0Tin0NEkoa5QxRQLkiZCjZBAfFNZKcM6AitEQuGVUSfYZwdKzzIoSKch1h0MsVS01ydiE4jMunPrX04b9D9VeXBO3aIQxtVuJnGqO1KZeStvASYdBMepfGeZ2GQeIZGS6umT877xOeoIwpxGNO6qqix63ceYwu75r3zN9RGZTSx6vCGL7gBdVY5c/blVDz23stV2T9uK4eokMWPxnqPZ13dd2CtQPzW25g8hFR5Z1F/ETIsNDN8DTrM5+GzPOZr+c2pcgRpCKy0FpjrYj8pBA5Sn1vPfFbuOfQXvv1NZaMswHJC0xqh77kYtO6FoShNdJaaXMk0rMg5hwX1Z55PPd957sScNE2OR3dL4gw80V/C7U2Z+hNPIDyTSBzwTWFb9PHjJ2xCi9T881zmCOx4RQe8n0Ir6UoVOXZkIQf/eg6T19AKiK8fWbDGunBqNFv2uVZ83Qgs24w1gnfes7RKGAUBemKF3vBSof3CWEQ79wkeOcQ7DwTC5lYULD6Qd6fe25lj9rw6wJ68CtfWdmpEQWzGrCmCcWmEI7Y0RVSQxkKgwQonhRHLqtCZqJyM6WKkhr5lZAVPB0iZ5nfPNYkQmecRC4f4VN52E4xzmcjOIRHMTgWlfdt3iRrlwTtu+1W7aDOQvxM43FRN6zMfbsuvD4slt4hBtw4436cF6DnQMgzDN0rJyjj2bmbN5G6qkA7B4HB+HQthrJ3Uzv9CANzvN9NIX5dCbUItevjIZqTt76Xa8oaIHSN4up7SumQJHhXwjg/rilHF2NfiLdrCJUsKOgiY5FRKgR/4QvV39aFIH5UTkaQ9c3H27YhEWlIrGOIFvIaIdh1PfdjEzCur3Iw4ia8+ABZZQ2yNnt3kTkIxSHfUWtdXmyL7sBjW39deGG1iYFo6+MZ17SueS7PYu32232tkT5HKBojxJ5z+45RFwIuT5VBL/rwh6t7hGe5NjmGvrT55ik97WlV2+obeCErQ78yLnQz+ljoZZ7L83vuvoTXUhWq+tjHquuSVZ7BmAC5Yy02F831vFjYPDzL69eOitKRczQKGPl71nsVFCw1vO/WJ7peV1iXjjqqynVaUFCwNsA+ff/7U3rykys9oAvYpjiL009fPevFmiYUc4MkciHl4csUN2GRFDqGEJJQyBYFlPJkB4pS6X/KvuPDO4vXVBBXlMu9964UQJ8xpAge98jDdlZiPH0fz7ZZQre6kGuMjbe9bZjw33nnSBoyvFq7pq0mOo3HRZNhxUsH2eT+FsrIK+a7NjJ3kvHjO0QAct/OD2OKV0Y9PLlO6l5xRZUknhEZVT6RDN5ZRqpn9Ntn3smm+RDzTXuREm3vbITa9akcnZO31hqfOUb+qVh7Ihx0CBK8K2HcdFyeo8v3vDFjDiicY11cROGZgpUvY70f4dln7Qjix3u6887rPM26rrtNGxJ5GhLvO7l88slVcbFpipq5P68362F4uNXbgEichkzMn9V7Rb+gN4Qnos/cL4qnqNjreRBryDfvpLb18Yxrk6PeccXh3M8YWcMRifoTCbfNNtUGTp8x6kLAIWvDy5yXp7HzbI6JVBfuhRS2gbHHHu3PWQ9dd60gFMPjPa/K3YXwyp9Vu6yBiyxUFUUAIw8iHTPu7X/zwXfyDWufTbh5eZbXyeggom3i+m3OmJs+L17sBSsd++5b2X5dYdPJu8pzvKCgYG3hfverInGe97wqBLoL6DzSZh1/fErPf35a8VjThGIYJLyCkAaUM8oQA8euK1KCcsg1lSJHMUZOCDmijFL2HEeZdh3H8OphhNs5zokKyq7QyjDYTaSlrvg4LULJzkPDeKQ1ERV9jp2VXEPu8PaadXd+UTmShgqvnrZwzrQeF02eQRH+5P2o51JqI3PHeQF6P3jieBfDMwixyHNoXLVizxS5LOI9Ztw4Pv5HfAbZWJ8PdSOfYc9gimt6tx/5yPWN664GXBN5671g3GsPhRRxqY0RDqoadRvp2QVdCeO24xyjTVtuuS6JsPkQhQ/mGepXsPJRJ/3Csy8iAZA93jPkUd91t74hgfxCJIUcD08pRP20BTi6bGRNsxmYP6u1TtERa6d8gd4v3oJINs/hufztufRfrDH61vF9cwG2yYsdd6zWLHqPttgctRbka26fMZpUSA1RaVf/3veu2q6P477mRngskuvW2Yjo6CorEW2qOetba3Oe37YL4VV/VnoiYtPGZZN+MY8QX89h/kJsYAf8bY6bF1EIbV7zFZqurWCO+amPyUb/IxZnvVdBwVLi5S9P6Z/+qfvx1pZCJhYUrG3c977VJgT78Iwzup1DNr/oRdWm7kqvBr+mCcXIhyh8ua6s+9z3DHs799ttVyl2BAdllJKGQKHsIhh5PPmh9LURV8uhuMmsCCU7vDXHVbaFrscOUXgiJ3ccR7GNPEwMgK7hv4vOkTREeHXXuTWEx0WTZ1Ae/lTPpQRN70Sb8eN/5LP3LHJ2BbmFMLbwto2BtnqXGTPh1aFNQSC6p3YxfvSF68R8aDPyzRmGvf4yL/J8Ol0NOKiTt57P/67hf9cPIsRaxFAT4shLc5qwsa6EMSNw3HHI1PPOWxfmvKhQv4KVjyYv5Dy3mzlPhiIVvdt91t18QyJI8fBuM/dtHNiEQMr7bto5Ou2GTRcZY73wfEB/ICe13RoVeZltOlhP86rYscbywpzGM65NXgDSzIYoqAwcURZNaS7oR5deWq0RBx20fkXTcSktrH3ubS2NHNKIzMhHbe1DLNIV9DXwyOzyjHnoumqK2ox09XlXcq1JD3ANuqKUGuRSeDoG5hHiqw/Nh5gLdVJR232e33fo+Zqjfm3jK2wL2esexnCWey2XyJCCtQvE4Ktf3f1476N1ppCJBQUFG2xQbUaQkeRhF9Dj9tyzssVWclX4NU0oUlaQgTyhKER176IImzRB/B0JqCP/DuOFMoe0oFxTeClYfrcRV/PMuzdvZSyUbMp+eGtSqhE3wrGESuWhTIwFx006tq+h19aHQe5Q+uWYikqVwBNGzqlxO+Z9PfaWm/I7aW61eVzIX9bH46KJJMjDn3yf51Ia5w1SN1AcpxoskkHONRWY+5BXYWQ/7GFVEnvPGOHOxtM77DyEomvHfBhn5Lun+YrYYzzV29DFgNPPdW8d6wfSQ9/pS0RoeO86Rj/qDx4x04SNTfIQCiJCWodxx2mf0MqttlpcqF/B6kCXXKQqYtp06uspnZP5SC1z0JocspoXrWs7btY5OtRmYF3GWAOCSNNmqR2sH9pOj7AWWMPoHXmBjTxf3bSecU3yos0DkfciQzva7Tei0286EA9Ku+wM8VCIx6W08NyiFTynY/ICH8bf8dZG33lu3yH0+j7jNORamx5gDt3rXhXZqp8ipQf0DfHtqjv4Th9FTk0ywpjTZ8gm/5sHxjHP8TnPzeuma0cBtVnutdwiQwrWHqwzciDmm+GTQC9abdVaCwoKpseNblTVNzjppO7n4EZ4RuMuVuom2pomFA0aMsUAUnAhr8Acnm15zppIQE2ZpPSEkkehDCVR6OKiQz3mrYzlSjYPsfDW1Bd+IneV/vQ9Aw9Ji3Efd+w8yYh6eNBQBEx4Vqwk5Xecx8WnP93P46KJJPDjM+8Ro807EKT7JG+Q3EBpK4LQlbwKI9b9tt66yvFnvlEQvaPeYcdsu+26fFzjjPzwlslzQja1YZIB1+StE6SuNcbf1hE/+RqkvQjFadaScR5CEEQE77BxxzFeY+Nk3HVKNc+COrp48CLr5ePs6ildJ2Me85jKoznWK6SUe/iN/OHp5mfWOTrEZmBdxgSR5v2yHseGh/ZaA+Sm9Vw2QEL3sI7l+er8PYRn3DjvfGOn7xBqvs9Dy/WzdnmuY4+tlOLw/G4jkyONA/0gvL9z/aru5T6L99+kqIb65216gL9dy/PLWRieeX3DiXlznnVWdQ/3N7au26Q7aI+w9vAYNfax8aQ9kR9SGo46kdl3vvbZIG269izvxnKNDClYW5CDXVSI96wLeMCbtyuVACgoKJgPTjih2oQV6dYVCvc6XhqYlYg1TSgCN3WeaxQZO+J5BWbCgjcd4YJcCA8sxAuFh4cTY5zij12OwiBPfOJilZ9FKGO5ko0ECW8CCI8C92cA6Qv9QuHOPQ/qxzIi7L4PRUYEMWTn3hjUQ54nhb11JWB4Zlx8cbfKlcvBe7GLx0VOmE3yuGgjCRiB3hNGjmshkruGP4WBEu9fVLLsS17VjVgGa3hOeCbzU3uOOWYdQdZm5OfeMnlOyLY2jDPgmvK9IXMj5Dm8aa1BUd2Uoakfpw2liZQOiApj4+88bDKMdPnrxhWW0R59oU+aUKp5FsziJWZeda2UXt84i+Il3kubEFHJPbyjYzMgQmeXeo7WZUx4m0mxgEyz7oVXtffSsdYE35Gr3l/XiGrFMETxi0ne+Z/9bKX70JXIv3qKGP1q3fQcuYxtI5OtuZ5Bm/NK06Ff5R6Y2sYD0lrubz99ZWkfb0welm3zUdsU4LEJ51mNRZ8Q34suSumII9bl5/VDJrlWk66m3XQZJIfNMX0iqkYfRM5EhKNjZtEvlso70HPw3pfrkneu9ATxHCWlRsEiceqpKb3iFd29E70jQhtXcohiQUHBfHDDG1YeirvvXuluXUA3evvbV67H85onFCm0PCSE9PGso8iG4U2pR0yA/8MDi5FCgXYsQobi4+fZzx5fMGIemLawxiyGkHvm3gSAsNAG4ZOUY0qyewtrCg+M/NjwPmgqjDEtcmLIs+YhYtDVu40BZ+yDjAwSxsvuf94wkypXItYQdcvBe7FOmAWxJqTOePoRZswgR6KHx4VnkDOPR0XXQjA8JZ7whOqa01T+dl6fqsl1NBmx+TMxSnkm5t52TUb+0N4yOdHJKGUcRmV4v7XbfbSBgopM0KeMxWmJAu1kuDLGw2Mrqkf7HUSEKrLSPrSFpVrz9Jvf+nPIyqEFawPjvMQQCl3e+aY8i1G8xHnhreedzddl8tpaHPlYF4163lrti2fVZmsAMsXvIMuCTNNP0j9EeCuyMfIQWy+scU2ecX3TcUzyzvc5GWGTSP/nGxNAF7K+OI6MNabuR/bvtNO6CtYhJ2y8ys/of2tI7uFuvKy9npOnuF171/dMhx02jCyd5I1prW+bj8ZDKP3ee1f90HXDkBw98shqznq2yIvI2CB/oElX85yHHprSaadV1SMjL1NTgbBpNjGXyjswSEyb9ldcURHM+j2vxF1SahQsAu99b2XEdzX8zUseSFJBFBQUFDSBLUzmSwdDh+kCsph+txILtPQmFD/xiU+kE088MV1xxRXphz/8YXrXu96V/m7Mk1966aVpK0kmanDuHWy1XovXve51o+v+6Ec/Sg984APTKaeckv5WyeQ5IycgQtGjUEWlOjvyQKHxnR1Uu8W+o/RT5hnksTsdO66L8kzrE6Y7izKWe1jVvQmioEQIYwYCRZzi7TMEXRRkcWx4H1CohyQjunoYhmdZXQHXPkr6hz9ctdO1/A4vMQo3r0vP3dbfnjkqV1KMl0PoTt4vjDXKuzkaxUWCXFN8KPJW6QvjKBSxjRSdNU9Tk1eE6xkDfTWpavJQebPq3oPjvGWmJdBindFXyDuGk+WPEa7Pwf8MTM/ufXHvaVMn6NvXvnad94/r8oTSF+YAD2w5IV3fs40LS9UOu2zm9dCVQ5cDjj322HThhRemb37zm2nDDTdMm222WTr++OPTX4wpKXvWWWelPTDTGW584xun3wQzMJqv16RDDz00nX766enqq69Om2++eTr11FPTfbCzaxBtHrxd8iw++MHVZlV9IydI+PCeRUrEhp9zI4+voVyKOdrmUWnTjd7gOaICvDWBTAoSKwqT2FTQB9I0+G2Tblzxi2m8zSbJTmtTFMyKIleBPATbceTLa15TbVrF/ZGHz3xmtVEScgLBSHmONcWz2kxxvn5xH2Ouz+TEjeJcs8rSSZuwiD/ttlZrT5sM4qnYdT65pzBnY+dZo9BMXoCLHNAXTbqa55SfclzBnGk8DBe1IT2OxESkm1tRBJEuaZM/SMWSUqM/yBk/3zVhknl8v3TIIYekx8gP0YC1LM/IDqS8DfYu8I4ceGBK++4775YVFBSsdDz/+ZVe9OQnV/J2EshE+RdF0Tl3VROKv/rVr0aE35577pmeKM6iI/7lX/4l/Um23Xu7qLaQUjr33HPTi170ovT6178+PeQhD0mvec1r0nbbbTc6Jz9uXphEQECurDHE7bD7QTQFibIUYSN9SbRpUTf6cm8CCiEyFhgakVeJkRGEjDaGoec83m/aNQtpEghi0PUoB1Hooo7cs6xprBBZlHXtC7LNtSm5jmfUGHN5VtoqVzJ0eJLor5juSx26E4SZPmKs6acgPxltnj+8RJ72tOrZLrigUrAmeSxMm1eszSviyisr4svPLORVH7KzidBo8paBNo+gLtCmnXeuvHWieAQyL3grc44nkvlmnuU5HvuQtrmRiLTw2zz3W796Lsb/PvusTw5PImF5Y8+jcuhS47LLLkvPf/7z06abbpp+97vfpYMOOihtu+226Rvf+Ea6WdvCOnqv/2QkowI3qO0wnHDCCekf//Ef05vf/OZ0j3vcIx188MEjuea6NwlGoaBTnkV7i015FhEyUTjNvLaR4xwef9Y174I5vxShzm1rHDJRG5Fl1hvPR/Yg4DybNcFa4B21DkUqCd4wkeOvbS2Y1ttsXAEVINPoPUDWh/dk5HqNEGz3kANIm/INNWHS1gz3z/PONq05u+5aecYLD+YVOXQYbBdvTM/gGYfaQIl7hsd7/Z6eSz+SCW26mvsZgxiHITwMh9iQnkU+Rc7ieIeDXM1TsJSUGv1x5zvfOR133HEjsg8RSAbtuOOO6ctf/vKIXGzCWpVncrnb5OkC7+7++6d09NHzblVBQcFqwU47VekUpDvpArrAy15WyWVejquWULTD1bbLNQ6IwVvVY1Cvxatf/er07Gc/+7odMsTi+9///vSmN70pvUyvLgCTCIhJ5MRShY1MMgSGUsaajL7w1rQJynijDAovjdxOUblTu5zP6LBDH56dPC9mJSNyYpARxssOKZhXCK57FugT3lv5WCEheSZGSFp4i2i3/5FKzkfCRX8HORqh0e7h+TxvXb9aytAdc9X8PeecypgFzxOeo9E+ZB4jDUGsjfPKZ9TmFaE/zR99ZFz0kRC7acmrrmRn09yue8sYX8ZeUxv6GFQ8dJAedqz0fYTUg7nEcPe8iF33mGaTom4kei+9bzFX/Rj/Olc2aQ2cZ+XQpcTFEqLWvDXIK174j7CQtIDBlXvZ52DE2Rh7xSteMTLk4Oyzz063v/3t07vf/e60yy67DPwUazPPonfHmqxIhnltTbM2m/fWfwS9IaKgkc+L8hAf5/mF5Ecmgu89V8gMz2v9zdcFa1J4RI9b02bxNuviJardO+xQbUQg+iKXYxCfSE8hudreVXa0rSn+R7C6br2ts8rSLpuwnoFHAW/FITZQ3NP4uEae/iUnKsgXz9pHV5vVw3DWDekh5FM9IiDPWey7klKjPx7/+Mev9//RRx898ib83Oc+10oorkV5dv75lZ3SBd4FXsK8GQsKCgr64NBDq+g0BWu7gC7LE5rO1VYQc7lhYc180IMelH7729+m+9///umwww4bucvDf//3f48MtwP13LXYYIMN0tZbb50+KxN4A1zHT+DnrIUBME5Zn5ciPyu6GAJDKWN1oy+8NYXeIPHch6dFtEHYiuOQWI71/HJM5p6dMG2IeBOJy8CR4xBHYOcxwqTCswDbr/JSfazCQw8pGXl8eF8wZL3MQRYiHT3vJz9Zfe8zvxkE2s8ooK81eUguVeiO/jQWb3zjuoI6jJr4LvqAAi8hrHmrr+aVz6jJKyK8EoyLNjJYGSX1MLk+IWZ9iK9x3jL6rq0NfQ2qyInGI4MBnsN+i/7wufkz7SZFk5HourGfY/y9r03zcIhKtisdP/MijHKU/enY4375y1+mu93tbukPf/hD+uu//ut0zDHHXGesXXXVVaP0HeRY4Ja3vOXIA59cazLA5iXXVnOeRe+GYyM/jXUtKnRaU+RFlu/OerZID/FJnl9kj7ZHHj4eMuEVrq152pWuHnGzeJt18RKV10faA5st5F2kP7FB4n+58IwDT/4+JGDTmjPPyIuum7B0FLzMEBsozg0vVGlg8oI2EBs9UR27qzyb1cNwlg3poeRTPSIgPF+9C8Z4pafUWGr8/ve/T+eff/4ouuxhXs4FybPlLtfoQS98YbdjzT264F57zbtVBQUFqxEbbFAVcaLzfeYz6wpxjgNdTESkEOiVgLkTine84x1HHod/8zd/MxIqb3zjG9MjH/nI9PnPf34ktP7rv/5rJPDsdOXwv5xWbTmvDj/88LRcsKg8hk3oYgjkyti0ibvHGX2RLD3yKlGaw2sPeagdFMWXvnT9vEOzhIi3kbj614vKA4SBw+MLyRieBcicprHS3kgX49oU2tzL0Geex7muwyMGUYps9Dy+95ygT+rzAJYydMfrxZMkqomCdkd4sedliFOyIsE+b0/jZgzDa9OxCL9ZSNG6QeEedomNVSS5107erz7Lw+S6YNp5ZV7Ti5tyVLXdp69B1XUDwHss6fc0mxTz8lpeqkqgiwRjar/99htteNn8aoP8ijzoN9544xEB+cpXvnKUe/HrX//6KNyM8QVNci2+W+5ybbnnWfS+mIt+I+Gt+2zVKGric95+ETq5SA/xroSY9Q5R5wf5OUtKgVlJuHFeokEmWo8QiNqqSr31StEUr0pUYTZWUcwpL2zWdP82fWSekRd9NmGH2mBxLf1LrukTMs9zIWL9r1/0KcOhvp6PW3f7VEiftS8CkSdcVdxpKjM3jS2CNTaghdST+74X+r7SU2osFb761a+OCER5EG9+85uP8t3/lcFZkDxb7nINOejd6AJrmLWxkNoFBQXT4r73reQmUhFH0YVUVCxKyp+VIAPnTigSVHlye0LqO9/5TjrppJPSW97ylqmuyZtRzsV8x+suLPolwqLyGLYp4bq3SxGKoQiBupKtPdpwySXVdbWLYhpeWH6rRlgnE2cJEZ/k5eYzLsMMyqc/fV31bSRV01hFZdAIc45Q4EBU//b9xz9eGQH6L7xhEG2MWJ9Tpnk31KtuSk8TRlfcZ1EwT4Lo1E4/2hzPFh6aQJnXv76PfF8UfudE2BaPGkbmtG3Jw8aNmXuGJ2RsYDOwjGkfr6K2eaWKu3F50pPWz3uan9fn3ZjWK7nrBoC/2zYp4j52ufzUiwPMw2t5qVI6LBpyKX7ta19Ln+LmPAYMtdzbg1y7733vm0477bR0pLJuq0CuLSc0vTc2RpAP1mreX3J8es+9G2ROFGVBbPHOXaSH+DSE2KwpBbrckwzTH+Rg0/Wb2tC0ueH6nJVsHlobnCMUUI4g51pjHB8e/ta1KEYSzzxuzXW9WdawcRunfTdhh0B+TzAOkTORzkDWMRzq0aiT1l25mWYhXvv2Rb0ys2P7RjK0ySfn0xddm570gheM39ArGA9215VXXjkiCC+44IK02267jfIFN5GK85Bny1muve51ledPVzz60dPruwUFBQUBMh6puM023XK3ks2csdiTy10WLklkturNYbDd9ra3TX/0R3+U/qPWs/5vy+eh+pif5YJF5TGcpIRLN9mmRM+TEECU+eGxEMSbfuAZyNsrvDDCk8/u9utfP93udh8vN1NK6Owb3lAdg1RsG6s8j4/25zkLooplhHoxWnk6qvich0X7zjMJabr88nVJ6fUv5dux4c25aM8uc4GS/ulPV8+jvUGg1ndJfB/Eof4Mgphyrx8Y8sLzGEHTtD83KORMNCf1v3sZR/3n3vrMeNnJ6eJV1EbyMXgYbrxKFQcQAqnd0f/TvBuzeCV3KYDSRnwHaY7o1U/ychBQQvmDNB/aYF7KlA6LxD777JMuuuii9IlPfGLkldEHf/zHf5we/OAHp29bcEZVce9wnRzjpR/wv/QfK0GuLTfU3xvrexQLMQ+RiGSOdTg2f2wqRbTdIj3EpyX1u3jEtZFlk+7pPYXTTlu3IdYkh+ptIK+b1jp/R65ZTkrOQ+y+733rvBKNCXlBrrqOdSqqWk9ac6ddw7psDnVZg4dGfk9tjJyJPueZWCcTu1Sjtomrnz1Drkv12Tzq2hf5mBmLaSszT5JPd7tbSs997vWLzxT0w41udKN0b+7ESb7yTdLll1+eTj755BFJuAh5tlzlGj2cw2TdaaANNtbPPXferSooKFgreMADKpn78pd3O56c/9CHUtp++7SssSSEol2zEEqEHmH30Y9+NP3dtSWVhZ35n4G3ErCoPIbTkoLzJAS06eSTK5It8gYy8pAdjDn6DO8QBAkCTv7C2N1m/E2bp2+cl5truD9lljKA5FPcw24+RbZprPzmuea+kYcrQp+RaAhE3o6exXOZvvoqvBQ9h/v73vkiQ+QAcj0VIxm5NoAjp+OiPbu01etlnBni2svYC29Jzx9jb15Fle4gHylf2qv93K/7eg62GRT6hxeRcfKe6EO6p4IK5geji7GKCJxkaLd5rQbRzPvBcxiL6H9LTFNOzUnvxhDhheO8kZqI7/xZwLOY28h8OUMl7+VK79pDGsxLmdJhEZBwft999x2FhF166aWjCpZ9IW2HELMdDEKy1t1jZISRY2Fw8cyQ6uN5z3ve4M+wVpC/N+akzSIEBNljrcqLO1i7rV1RMGuRxR3m5QU3iSxru6f/3ddn+qbPhmLftU5fx0/T/131EbvyfdewPjpSV4/QrmliuhzX5gFqbOpeo+PWXc9nntO7fO9vx8f87jvPJvXF0JWZl4LQXetgV+W5DNeqPDvllGq+9gmNposWFBQUDIUDDkjp9NOrjdZJoMu+8pUpbbvt8nba6E0oStwbu1aRrBdBKIH9Xe9615F7+/e///1RBTBQGYwwktxXLg85FD/2sY+lD6FbrwV3eO748izyXnSOBMJR9Xm5YxbjoY+yOi0pOC9CINrkPPfkbRY5gZAdlE79QDnkZfa1r1UvBmJu2t3tSV5uocxqE4UXwedz1xIe6rqPfWzzWLkG0s+YIbEYon54YWizHfMHPzilj31sXTviPCRPkHM8/lyHSzOyVd/Mq2JyH/BgQ6q+9a0VKZqHOusr7WaA6zNjI4ciRHi2H+1G9umXWUikMCje9KbKixTpymiNsGoeeJQ47dC3PCslyG/rJ+eE11KQC5ATzT5D8pqj0f9vfnM1B/u+G0N4JY/zRqpvUuTPol94Wxoza4vf5qtcZvpQqFiQirxSvXv6BcmtUmvfimGLTumwFGHO55xzTnrPe96TbnGLW1yXE0rS+Q3tJCTFgZ6ZNtpoo1E+KDjiiCPSQx/60JEHyNVXX51OPPHE9L3vfS/tdW3WdhUz5WI86qij0n3uc5+RDDz44IPTne50p+s2zgqmQ7w33hGEinfEO5gXd7B+kEHhaOpdX3Rxh6FJk65kWf2e4RykL7z/fTcUu6513n8bQA9/+Lq8ydbbqDQvJN3/1qOu+kifMPBpdKRJHqFdU2H0SZmR39N5wsn75EeMjSUy3FrueNezSatvzX0yum2etemc4/piHpWZZw3xr2PW/OCrCeywxzzmMSOb7Be/+MVIvtksu4SryxqWZ+bIO97R/fgtt6yiqQoKCgqGxA1vmNIrXpGS/ZioazAOKkQffXSVGmXVEIpf/OIX01ZbbXXd/5EbAyF41llnpR/+8IfpX0n1a6GK84tf/OIRyXjTm950lPT3Ix/5yHrXeMpTnpL+8z//Mx1yyCEjY84O2MUXX3y9BMDLGdMYD32U0FlIwT6EQB+lLNpEseQphdjQlihm4oVhQHhZEEa8+hBtXXa3J+V6avJyc5zn1BbguaItEfrmGpRe1wzPtKaxcvxZZ1Xf+VsYF4PEd9ol/wHDCfHmXM/nc22K/H9efgYUT0lj2qfq5bygDUKJ8CUKqDNYEKXaHO02F4J80ydIRgQW0ta4xBwagkQyx+mzdmgk/Hc/1zVv3NeYydGlb8IDo6mf8rxOxsycMNeEZOdEM6I7PJby/jfGbf3f9pxdvJJt5Lt22xzus0nBYGMoanssr64X7xrvy8h9GUYzz8X6+mJe9g21X2RKh6XAqV7oJM/rI9f7/Mwzz0y777776G8ybYNs8H7605+mZz/72SN5detb33rkZf+Zz3xmvfxUBxxwwGhj7DnPec7ISNtiiy1Gcu0mebWngkE38mz+GAJEozXE+2KtXirPp1lJk5DHZKGNILJSaOw4sqx+T+eKcqxXFu4qh7pGYIT8dW/rJpnsf8doh3EyHjY3+mxQdC2MMvTGaVcCd9rIkWnyI0Yhokjtoh/teYhI9b9zyT6hVDZA+xR4aXs3YrOO3hCbdfXKzPQIelDfysxDFb1ZCwXD+uDHP/7xiDRkj9kYY3chE7exy72G5RlngNgon4SNN17feaCgoKBgSOyxR0rnnVeFM08Ce/2kk6pISqljVgWhyOgSItYGpGIOQsjPJAhvXikhzkMYD+OKR8iN84hHVJ5UEKkkKejTeAl1JQQo+vIftSlldbKRMuk4vC+iJoi1gPY7VuJ89+i6u90111Pdyw3hInQ28klFX0Xom+uEUbHrruNzTh5/fHNYkjbyUlSYBRHGaKVM6xtKvuczB7RbX047ZvOCPpPDUd9edtm6PE7GTd8ZDwaKNhlPfYZM9B0SOMZ3KBIpwsaj4nTdWI15FMV+xr1HCGQErnEytxhAxiGMIKQpY8t8Q1Qaryjc05csm+SV7FkYWvo63iVVo3kIeV+6EAv5JgUCWJvdI+a3dtffNcSiPqEIv/Odw+RMXVRKh6XCOHkW4N2RQ1ExP+PAq4Pnh5+CxW7kPfWpVWqGru/aPDEtaZKTJJE+w/rlmcKbv40sy+9pQ8M62FUONW0qdonAIDf0vXPpMJFmIvIoOlZbycQhNija9JEh5G1Xb0ce4NNEjnS5/he+UMkM6T7iGM/oHMeFPKPfSEnuc30bhN6ee17fi7Iv8Zlv1tmgchx9INLUDF2ZeRovw7VSMKwPzjjjjLHfr0V5Zm6JGIrN83Ew52x2r1UP14KCgvljgw2qUGb+dXS8SbB2yf8qE0XfSLNFYBk2aWWja1L1tuIRlG7KuKIXYedGTjmkAW+xphRf45TwLoQAI8E9TeompUyYsKIrOdnIsAmvr5wgjGehYCLcECuuF7mc67vb2kwpDqOpT66n8HIDirdzHBv5HHMiyWfaE0bFuLEaF5bk2YyJ8WMsRU475yB/N9lkXYGWGJvl5Nmlz1796ooQVTQn8KpXVf8bH4SYMQWGomeNPhySRGI86Afzm9FpHuhffalfwnCKEPrc2w/q75HfxtY1jUsQka7p3XEf4dNhfLmnueady8MBYdJztpEZrudd8H+8S55TqI1MEDxHtKOLZ4i+9+4xXLXHfGPYxfwOBGnucxsD733vcDlTl6IqakFBF+TviE04a4N3YGgCcdHhlHWSxLoiD7ANIOGueYqQWTcUbapYX51v7RA2Sw7UNxUnRWDoI2vKOedU6y0P/vBmIw+tXeQKDyHHXXnl9BsUTR5poY8MIW/D29FaR+6EzA9v9yBw+4Rv57pGF29K3z/zmVVfx7pLppFb1ntjTo4gHvNidDZW6ULmT+hL04SDN23WaQvyME9TM1Rl5mm9J9dCwbCC2YFjtdHaJbzQ3F7uBRAKCgpWR4GWww8X7VvJ9SZEShL6ETnJlnz609OyQyEU0+KNjrbiETzGfEeZouBHWLBJxtsKYUAgyiVHkeyqhE8iBCiEkV+uSSmjNB95ZHUeIyFCYYUxI04izImS6XpBClFyI8SU4un/UPSbdrcZNtPkenIPu/GUXyReFElxPjIKkUQxrScL7zJeiCaEJSXdeDkmqhH7jBLvHAZTvnNv/BhPPtPvQ3l2DWXYOgexlVdS9HzHHFM9mzEw/3jGGWdh3wwG/TkkiRSFcxgsjFnPFLkco1IrQ9p3dY9VHkj19yifV4wfXn3GyfHeGdeKeWiehkemZzLPjVMfsqzulezct7+9OjfGXH+aR54l5qZ3rotnSBhX+iIKBNW9gXPSPMLF3Z9hN1TO1JJEv2C5YRwBMSR5sOhwyiaSJIhTP971PEXILBuK1kZpEKz1HJSQfWSZTTHrWn0zb5xXf2yoWautVcjPPMWE48kQZKWqxtaoaTYo2jzStJ2eZIz6bg7V4fn0jef2HOR5bJzqS6H1QcBO4xXZNQ0NkjRfd+lo2kKWCcm0uZQXo4sQaPOSXhX6Ut9w8KY5GJt17kfXM3bCr7Rz1srM03oZrvaCYQXDwEb0/vuv2/wfB3qUYgmFgC4oKFgEnv/8SrYfdVTzhgf9hV0XqbsQiqJwltsaVQjFJTA66spksM6U06gwHCQVsiUmWBBiDICtt14XqtmV+GgjBISo8JxqUsoA0Uepc22hxaFcRzhTkDZy1lFiPZ9n0H5KnLY5pu4FVt/dljOIIJ8m11M834UXrvMOQ4JRDoLky40K/XbccePHS3tf+MLqGM+JjEIg2lFQZCXIWH87P7wXwPUp9shfoadDeHbN27CVm0uS2LiHcecNqw/di2E1NInEyNRPjDzzxg+yL4r7GEseGeZb3WOVhwvjmjGTw3H61gLtuCDBkc28LBDMkVtRnkPHIhPB533JstybldcnIy/epTznlXZ5Jv3oc9c19yX9zj072owr75jPrAf6hPHu7yDNGY7hFek9HDrUfugk+gUF02JRYY7T3GfWTZ/cO47cdG/wjvs/TxESXoDTbCj6/5OfrOQ5YsjGh2tpP9lHv7Bm1SsvtxEz+krNBzqLtdVaF5sg8fxkKOy883QbFOM80sgvfR66Rj5efeUtXcxGGuRh21FEzr3CK3Ka8O0+eWn1d6y7kUsTeapNeY7gfGPJvAhZEnOxD/HZRNTVN4H1D2J1lhDnWb0MV3vBsILZ4R3Ybrtuoc7eN84T3u+CgoKCRYHtLQqUrAvyMKJU678vv7xyLsMDLScUQjEt3uioK5OURIoqxT4mjMlEefIbmeI7f1PyHUPhi7yAoYRTuBAabYZMGyFA+W5TyijnlEfCmGIWlZwp1+E1SVFH6pjg7odYpOTK/xM71gibNkU/drc9Y59cT3V4vgMPrJTeN7yhIsS0QZ+F96S2IgRf+9rx4wW89VSmjmTj2ucaCCMEKEODEcYDgwIfyA08lZX1x6yeXYsyoJvmSOSPHJJEyosNMMoYSDwO9a1njJB085I3hnoZ9SrZFlWGn3GuhwBH5WqFcYSNCcMzP2OhRmJGSHd4X7jv3nuvCx0bV020jTCoGziR8yqMvsh16N2xa+7d8k4YQ8T0jjtWxYKajCtkPHhe5KJ33dxGLJoT5qJnQmLbIJhHqP1QSfQLCqbFosIcpw0TnXXTJ7zjXMM6Y/MAImTYdSPVhjZNs6HoHLLNWmBt8pl7Whett66de0FO8vSKvrI2Wc+Rn65Br4lQHb/pCzZUzj+/KhwyzuOxCZM80owLostGGNkwjbz1LMLKrdXkhd+uHZEW1lm5rnfZpZJZ1mshxq5ND4h2jSN6w2vUdegHiNcIqYb6efm6qz10gXoxuno0Rq4v9S2s1UbU5Zt1yOHnPCelbbed7T2bxctwtRcMK5gN3mVVVK1Dk2BtlTZDoYSCgoKCRWKDDVI69NBqk5eO4X/6Rx1kIh2KDoBfWE4OHYVQnBHTGB2URETXZz5T/U0Jp1DmLDTFO66VK1k+p4BS5PwOJRwRM8njro0QaFPKTGqkDdLDxI5KjRRKijPlktLuOBMbKXT/+1dEW+6tB10UfQTJrMqh58Pa5ySe9se9VEdqI2xivJxnXD1PjE0QVMbG//obueo4yq4dzTZviCEqfeZzDCKvkzboyyHzBDXNkSFJpLrRHZ6I+gbZG/kSzTXfqQzeVCXbO+Q8Y8FLoi3EjceGa5sDxoXRHBW5Ix9ZhLCFB2rXttffs/q7pP2RvgDMHf8Hie9Y3zEEkcM+N+cQoW0Gs3lASfZu6iOKMMT89nzeT21EUuZ9txqKqBSsbSwqzLHvfWbZ9Mk3KZBTrmUDjryP4kuRO48stm5Yr8jarmRZLodUFeQdbY2yXpDh1iP3iOJo7hNekEFO+b++aQl0GekxbG64TqRCgUhj4dqxyeO7SR6PTf1zxRUVmdW2dmknYk5+IfeNHMFkRde54D5kirBv67G+Ca95/W+D0RruWSVUd4/vfKc6x5wgPyKNRq4H1Dei6Ep0Eeu4NvtxH+NtI7aNIG4qRud+eTRGPTem568XeBknE8YRdaELIY7db4i0J0Feaks9Z+W4jeTVXjCsYDZcfHGVSqoLzGmbBMvJQC8oKFg7eMADFCiuQp+b8imGgxldAvH4kY9UG3rLBYVQXALjJrywKINcXClOlChKd3hQ5YRiXoSUsKNwUqLyoiGzeK81KWWUaGSL39rkvpEXETvOkKHAUmTDC0ubtSkIjlw59BmFnKJPSWwi1oZUDttIvC7jxdCKXHfxUms/5Tzy4Pmb0aQPLAL6aZw3xCyeXXmb9bO//Y7Qc/OBB+hKyBPUNlcZFAxoJK73QT8Kw/O7bbw9N6PG77aQ8iCQfRYh05F70G/jpj+N4SSyust7Zs7lc9g9Iueh+e99iHcodprMKWS78GtrgnnVRmqGcaVv5NDI57e2eNbwNnJN3zOMtbdr6N+iC1AUFPTBosIc+9xnFq/JfJMC6Yagiop/kaMXrCOxweWalE4bIX3ez6gQH5730oIE+UfGhZyz2UL+8aRGKFo7/C/cNvIGWi+dDwg1KSi0x+aIa1jb/A1kpmez9pCL1sKupG9TtWuywnqZF6bJNx2t6+9//3SeojHuxopsCXnrc2NAzug7ZIX7eSbe42SX9VWfIQt9FnpA0yZaRHi4XvS38xGVigyNa2e9GF3dOzLPjakYBT3NWBnfLulXFknUBXlpLrhurttol83hNtlcCoYVtMGavO++3Y+nSyIUCwoKCpYKL395Sh//ePWTgwz2E16L9JF/+qfKgWq5yLdCKC7YuMlJCZ5X8rpRhkLJjDBnSlsQiRHuTBlEUPA6CkVuiPCvulJGgfMb+RFh2H7cn4LKoJGLzsSmqHpGin2+ox1ETSiH2hmKPjKkSztmVQ6bSLwu4+V+jB/GW7gdhwdpVFvymedi2GyzTaV8T+t9OIm8iTYjopCdUdEx8joxshgnDIvlTCiO87TUf8aY98rTnlY9n+MPO2y8x6rwPCHNKl02hZSbnz43/8MTMnJ0+om5yoh/+MPbDaSu7xmPm/q7xJDzbFEwJcK5GdvG1bibR57B/T2XdiIBm545jKt6JfI8jF8aAQoyjx6eQ0gAfTXJm2nRBSgKCvpiUWGOfe4zrddkfZPCei4MNnIZRqEnstfaETKIHoC8m2a9D+ImKgK7ZxQpi2rxZJsfx/Jss5ZZo8gca1RUrn/f+6o2PfjBFaHlXORY6AvaTF7533pncyOKlo0jfUMukmnnnVet3frHOIg4QGBG8ZUgFd3Dukt2KOBlfIIU7LPBmo97hPjmXnPuw8Mz0p3Q4SKntJBJa637vuQl1ef1MdYPjAXPjzwUNh05g/32uXQYO+wwXo/Ii9HpE/Msxgy5GyGcIVPCm51MojNM2gBdFFGnfWTke9+7Ln1M6DaeC1ErFUibbC4FwwqagPA3d7riKU+p3qmCgoKCpcIGG6S0666Vk1A4Y9GH4icHD8Uzz0zpWc9KywJl+ZzBK8c5FE3kE8WH0lU3JupVhXNSwu8ovsI48H8YDBTDPDEnBQs5wnMpr2Ip/AjJFHkCIwdPKMDuSyGc5AmQK2Wux7vJ/Uxm7Yfce1L7oviK3XikQ+xoU8KRI0F8OZ6S7ZwLLqgU2jYlb5JyOClP5KSxrBuJ9RAboDhrK4PF2HgOzx6el4EgFz/4wenyCHUlb7RZ2xgZeUVHiLAghOKnP13lz1suuxXTeFr62/NEpckuXhLC7f00jbk+07fh1Wus8xA29+BJ47txBlIfwqA+h6PKaeQSM5cYlWFARs4x7QqvHoZcfT1p8wxpIzulF0AsRtGjvPDLUubpLCiYBYvynupzH6Gx9AAkCFkX63Kc0+Q1aa0Ttooci3QJCD4ge30PrhmbjdYtcsjf+bXqMm9c3lufuQbiht5ibdRO605slPntXtYjIbnIRMdL7RE6iesHweZ7cokcQjbZELG2Icys7dZda4o1aRLpG3KR3uLeCErXiY1X5yI+5fDz3Ig3ctHxNjo9n81AOlVsVtWLy4zbYG0a98iR7FmRgdZq1zeuQX55dm3VR/7WP65VX5v1lfaFZ6KIlS22WDdX8mIqkwjjkDUIVKGdxktfg2cwtsY63/iyseQc/ThO1100URebfPUE9Oaj/qP3tcmvUjCsIId1gQdvHt01DtZqxVgKCgoKlhqPfnSl89AhYnO5aS0jw484otpYXQ6FpAqhOKVXTpzjN0VH6DLvKsfnO+a50VEnVIQUU4QjHyHlj9IWilVUfKa0Uz63377KnRhtcm8VYnkhhWLLEAHGDUUsFKou3muhlNl9f/Wrq3Be3hIQ5GG0yQSPcKwIv9ZfnlGoDUU+qtDaDafQ2omniE9S6NuUwy55IieNZW4s6PMIP9dXsRPAhdjfruH/8A4NT02fMZIYYIwKhk7fcOM+5I0260v9akzqhq0+Mj8Yccs57Dk8Lc1NhmLd05IxlHta9vWSCBJSHzDwzRvH594mUaUyQtgc7/P8vWoy0r2X2t3VE7k+h5EMdszPPbcaPwax9nmGyB0V3i4Id23q6hkyjux0nHZ4B4MAX8pCFwUFs2JR3lNN97HmW6N8hpiRUsFx3m/pCqw7semmHUFm1Qk06z8y8Z3vXLfhFuGdUQSELPdeypNL/oT3DMLI8+bXqofTWqucH+kj6nleo/gK+ef4yIvn+axXUYQkqslrU57XNS82Ze3yt8gDBJm/6TJRcdm9rCOeDWEaXni8Feukb8hFG5rWLP2C3NSv4ZGtPzy/sUbGfupTlQ7lXp4VWecYx0dVZuu+ceiSX3Pc/PIZ0tJ46JfYZMwLtri2sfT8TWtz5NXVD/WK3dOG7Bt3ugHCVpv1eZ4jODYhjYENJjqpOTGJdFsEUefaZD9SNUKe3Su8ZM1Lus/++1fROW16eSkYVhBgk1nbuoJR7n0sKCgoWGrc/e5VIVL2YuhnbZsjdJL99kvpkkuW3jZb84TiNF459XMoQrzDhE36bLPNmpNyB6FCaUea1L3NgogUOnPve1chmM6juFLq8t3ZaAMCwvWi0l8IUZ5JruOeUVVR6NKkXeUgCN0zyDOGB8UOCUJh9xkCKMiVzTdfV3xk550rJTY8vxhBebJwineX3fe6cthlnKDLWFJIEcAIHgZB5IGKMG4Go743Lrl3YoSjU3A9h9+MDd/1Uf77kjd+zLELL1znfRAJ4qOyI89V/d03b9gi8+WFp6W+b/K09PwMwA98oBp7xqo+6Ool0UQmm/PG1/jr2zyEzTGeXd/ycMxRv5b5L3xGX4eXTY4mj5t8DhufIAmNu7nmvXCMc33GEPa3vhBC6G8khTHyDG2eIUPklFtUoYuCgiGwKO+p/D7kGqLLe+mdIuPlLLUuXHRRJRP9kJ2RY9c6ExtpsbEYsgwZRj6Sr2RMHG8dRKa5FpAvCDryGCHn/0h7UpeL1lUFUsgCawbZrJ1NeV4RcdbCICHDC9KzIZ6859aMLbes8hHm60u92FSEZseGTXhaRr5ha5gw3LiPPtp99/VlTcjFIBM9Q3h1x2afcbbG2sjTT9ZH5KH2aovnkazcGurcIPmiYnVXsq5tfimWEqlgYhMyECk06A/ap51Na7O2hc4QOkYUsOkbsh99pr8UJtPvdEDn5qlnPLs5Qv7oXxvGxqBLOos2om4o3SHPWek++lcfaqt+in7Uh8VbvqALTjqpmvtdIPVU2A8FBQUFS40NNkjpxS+udDR6Yj3UOQf9SHQCRzBOZ0uJNU0ohjJG8FBI7caH512bV04TGURxQ0BR7g0+clHC8LpxE+G2DIfY3c+NdwQRosj9GBPcXtsUuWgDwyJyw2k/Bcw1wzDxXV5VUegjotP3oQhqR1NxFJM58ibqn9g5dh/EilBNCnueE9FnyNAwqrqEfnUdpy6VmbuQdH60zzN4ZkQOw45B5jtjePbZ63IPRcGcCEePnUyGYF4VsSumIW/0sdDyIJ4iQXyQtdrUN2/YovPlTfK09Gw++/CHqzmKEI/2vOxl442XNsIZcR/FBnJvE/dhhCHe8xQCbdfS5zYMvBP+N/Z9wyy9Bww77wyPG9f3bjECvafmL+PfPYXVRRVvc1i/8YZqGpdJud7yap+T8nTOu9BFwcrASijMs6gwR/fRH95Z65b3029EEA9+cgWBRAcg+4URew8RejzsEFyIPboAhCxz3fDAyz3cnGud8L5FVIB7xYYXgtKalV8rctJa77zriC+fW7NsmDTledVvfjwbuR1F10KWIG+0BWnK4yffTMmLTQXhF2lDyCnj4VncmxdmhIHHcyJIkZQR1QHaYu21XsWGkw0z65J1UjvdA6Fk3QZefUE+egY6lLZoV6SayL0A/d8mJ+tz3tyqyx3XQCDrY8+Ub4qBdjrWHImolPrarI2xiRSRDzbZ/G3c+4Ts13WJnKyMnNvGAYmob7XfOHo2bZ2WoBtSd6jLL3JSqhJ9rH+NubbSB3xX18tXwlpVsDicemrl/d0F3oVLL513iwoKCgr6QQgzXY1spg+NA31HyoZpUq8NiTVNKFJCeB1Q7OTjySvLUY6aiJ02Mig8nxxHgdt778pTMR/cIOoIMBMgdveBUkl5ZqggD7SnzXjP2xAehUgJSjVCwmdBglG4fU+xlOTzwAMrIyP3tGB88CwIZTBCfsLg0D8UvcjlFB4TEUqUK74RThUK4BAJ87tWZgb9P4mkA32lmEpUcw7iM4wyO+QMQEQe5ZXRkuf24fkmZCv3POmKacgb19fXDFjkLqMkbzMlu087liJf3jhPS/1o/psX+jfmkOfNPWvCcPA7DIcuhLPx937y3hjnzdR2Lf0swT2vVgQBsj+S/XcNs8zD7ZEC5rS2ERaRp9T7jziIHSnXQ9Az6BVdaRqXcbnemqp9tuXpXEShi4Llj+VcmKeJPJi3x6x7ItWsU7xZ8vXFWix9A90h5GNEBXjnrBF0Cp77+s57HLIsUh7khaJc04adtcn1kGtCeQFBKQwm0jPk14rcfLFRGfkW83Daep5XOVWNLY9w8k5b3cN1rGn+jmgL+ki+mRKbI1Eh2v3J4PDmj9Qh+sUY6bcmmZUTQ9FvfjuGbHB8FLHSH1E92t8Rdhy6DFJXX/vbT+SgdZ2QueR4k5zsOuf1uf5wfpCmkY/X87m+vxkD+lkb8rXZeMgvDZ4t8vs6j1yx/tPHuobs13WJnKyM0PlA6Lc2qYyt76ZJZzG07hDyK3Qb10XKxzwJvTg2pvN57F1ZrmtVweJh/sudmHv8tsFct2FQQp0LCgqWI/bYI6W3vrXbpofUd3Qh9uJSYU0Tioijr32tEih5ZbkIPeL9RzDlxM44MoiyQ1ljBIRSnyOIOp4OiA0KJaMiD12lDAXB0Ga819vAGKHA2jHX/kgOD5Rf96L8e1YKcHgseWbH2nF3vVwZzA0OyqZrRHJyirvj/egr3+X5/oZOmN+1MnP83YWkC0W+XmiFMWUsjI1x4fVgzCj75oQ54hz9rS+nydc1DXmT53WKAkCeSVv75g2bRMCZnypHRbXlIXf8mzwtYww8cxjR3k3vQ4Ttv+EN6wjBuuEQlZzHEc4Mtn33XWe4tnkyjCOvGdIIUd4TjmOcmSe8diK0UN92qaZu7iBCzEnvU6QTiAIH1hGfMZ59Ns7wa8v5pY1IAM8R+crG5elcRKGLguWN5VyYZ6mIznFrgnfUZ4gmJA1ZTGZYY6zN2uh/P3VZ5rx6oShrCplsI8CmxROfuG5zwSZWnvakLhf9TXdwjSjk5hgkZ1ue11e+stJzFBbTBrLF8ZEeJdKw8L7kUch73N8IHuuM9dh6ZT0NueZ/xCJPf7oFL8QmOVffsI3K9Z6DnqF/rPnWbn0CkV86CFznhh4V55uvIRe1P6ojOpZnY11O9s1nnG8KRQ5mfao97mse6Cdrr2M33ri6DrlKXyLfPBfkpLN5oF/32ef6m1xdiswZtyArfWYMYl6Yn+SM/tCmmMdtERFt95xHrl3H6SPnIefBHHLvqGaetznmMR3BBt9yXKsKlgbmpjVsUjEWc0kqh5e/fFEtKygoKOgHshGpyClkXNgzkP9vf3tKBx+clgxrllA0OBS+CKuICr956BHiwG5xTuzM6slDwTnooJRe+MJ1CdEplRG6StGc5G3W1AY79RQvyrfr+R5TjawhYCNZPHhm5Ij/XcuzUobrBVPC4KAkh5dT5BGM8OD6OfNImN+lz8Ooyo/JKziHF2KMS9v18mNjTugr3mmRG4qy67l5b0yTr2ta8maovGHjDGTKOaOHt4A5k4cdD6GcN3la6m+hgmEgMyYjZJ7njN/eFX2lLXXDQd6ILh6fzpHLcBbyWvsZt896VtVua4j+etvbqtC+SX2Vj+FnP1sRAHkhpfBwYQzqe88eSXnH5TGszw1zSH4xz4EAiBDtcXk6F1HoomD5YjkX5llKonPcmuBd9d5ax6xbITNsxOg3stdGX5xbl2X1QlFRTE3KFIrkuGeqk0nCZl0jchdrm02ZaFNTYZhYL4IYte4gGG36xPiTdaIaXNPfyDLPak2IFCvWMeShtczaRCZZf6yN1txcFoeXYp3gDLnoOWKDxX3cN0hRiHBm3zsXgedcsiIKr1iz4pl5fPvcZlB9bZ4mn3G+KeTZjJc1WY5Iz4RorG/ePPaxVZ4jcs/zmE/6yXWNU+gdeW7qPkXmXNe4GwfP77f2efa4n7HStiCJA/VxGHfPLpt3fXPtOh5ZTX+lY5KB2h1pe5DbeZsjzzDZuxzXqoKlg+iXINLHwZx63evK3CgoKFjeeOpTq3yKZN0kyKNok2Sp1rU1SyhSeCigFCDKS+TbgSDaKKU8j3JiZwhPHt5tkgZzzWdsUKQo2JQ3JA7laZzx3tQGilSQD0GcUf7iWRRvcZ/wnoQoNuF4k5WnVSiDeVVqBNrjHledkxsEkbOnrkAOnTC/S58zghgHdq0jtCiMNEo6JdQ1/Hb/tuuFcm8Mop/A/wgez4pUfOYzKwU7Km/2wSzkzRB5wyIPpn6J3FaeNSqPa4fnQvjxnhjSaK97WrqH98+7SBH0PLx5Iu+hvtDnDExGTBDAueGAjPQMQ4TrdiGvvVf6RxjkNARHjKHiCa94RfXsrucHeW8ORh6xnKSYlMcwnxvmPq9OHjn5PB5n+C2q0EXB8sRQhXmGymkW10EsCPtAkJCdiyYPJq0J4ZVc93bvKssiXQo5q3+RicccM1m2xLUQVUgY64X12toeHm/aZu2s6yZNBC0dgf6BGLShExurZELkNNQP+pnccBwZYuMSEUSfCEI05gtS0b0iHDtPK2Ptt7Zpp81b/Uyu2rzUVt+7r3vEmAdRGp7c2h3F0aydeQ5K/5PZ1i1h4gpv9fFI77pOemZrvnW2bfPG8zEMQt6TIfUc2voGcZsTe12LzLkuj1DPGzktkcnaYLy1Uz81hXfm8nHSPbtu3nXNtZsTug99aPWZcZWeJzbHzTW5v6PSpblBV0VWlyJiBfn7Y+2YBPPj8Y8v+kxBQcHyxw1vWOVGPOecycfiJpZS5q1ZQjFCgYRaCLOo58KhjBrIqGAcGMqTh2G0yy6V8ib3UORUpDipfjip6l69DZEc3XeIGc8S+QGj+EOEU/kbiUFZp9CFQuaZ/Y2UM3kpoY7jHYb0oRxH6NYkBXLIhPlNz0tZ1jafUeB33LE6Tlsoo5RNfRJhpEGqRB66tjF0PmOKYZbD/IiiO/r2ve+t8kpN67k3C3nTVnWxKyjoDL3wWjUvGCLmgx/PF9XI52G0x7OfdlplDBsrfR8esDm8i7HjHGH8dcPB+cZMWNes4bpdyGsVmM2xJu8Iz+Z9fv3rq5QBeYhiDp8xoII85AkdBQVcj8HJsDIPg8ToQozG3IiiPfV5vMj3tmBlYYjCPEOFJefXQSz4nxd/FAJbJHkwbk2Iysjek5CfuQ4RXoiRkmOc/mCDRXgwz8QuG1WuRe7Z2CALEXDWbNc2RvoeYUee67vYqISmYnQ2HHn7OVe/kwl+B5kY0RT6AwkY50WosXtbI6OyMM9LzyEM1zqUp5XxrMgz1yIHXDvmCv1Hyg3ruj60/kc6CXAN/ayPfW7NzCtMW5d9p91SbDz3ue1zr+uc97zkS1PBlq6bN8hGfeqakza++nhOerYnPWldQR7vS16wjU7q2mR+PbdcLh+184QTxt9zyM070KfkZeTk1n/moQ1iRLbPzJUgF0PHppeLCihFxAoCr3pVtQ5Ogvn57GcvokUFBQUFs8N6de65k72vEYr0gEIoLhjhdUAhzRXRMMQp1hSXvIJxYAhPngjzoJRttVV1T8ogBape/bAJ9TZEtcjINRPhk66LbImKjH4oZRTWqAgYyrdQIwbGeeet8wij4DFQQjnTV/XwkzYFclbiq+15KZp5URljyKhiqMk/JJxcP/rOc8pHl4eTR6XLpjGUa45BYwzC4NOXvMmEFEWiesbTrJ57S0HemHcXXLBuLkRosefwfJ5XWyIJ+ixG+yRPJcaN+5hz+pdxY94ZC58Zv8iVZWyavCvCcBDOhpibNVy3y4aBsDFVwOveEWFIR4oB12AYtZEprmfumlNR+Mj/jGjtCE9I/xuLPsToLKkZhnxvC1YOZk3nMVRYcv067mnzxvpk7a/LoHmRB/n65Z33d31N8Jl303NZf3IdIvIMWtfyPptWf8g9NmNN9RvJ6n55buTIy+feiDkETIRQk52qyGtrbCoha6xDUa1Zm4xZFHnJi2MA3cJaaK2LIiqQV1Vm3McGSXiXQWx0Gk/tJZ+FIJKz5orr8twmg8l167+10PO6trbSdbTPOe5Nl4kwbP2jfcbHpo7NmlnmvLbykKVj5SQ5MjfmgWMmkVvu1TW6pa/nJD2VZysZGcVscg9I19QGx+vLJvno70n3HHLzTvttvEkmH56mURAxUgF438xX7795Hu+IZ5BipBQRKwDrCJnRBZw5lrJwQUFBQUEfsG9xBeThONB9OE3xwF4KJ5A1SyjWvQ4MWOT4oZBRvqKQwSxkUBOpArH7nIdwAaWtqzdYW4gjBSvPV+T/j360Oi7IRsq3a1MCCeMIh6ak+ztyKPmews9wQDq6D6UvDz9ZVLEGz6s/GUEMG4qv39oVRutOO1WKp++aFOt6pcu2MUToGiPHyo3EmKonqh/Cc2+R5E14PTC25ITkOeJv88OzMxaMc4S7hceAvkOg8iih/MMk4nOcp5K+inZsuml1HwZDJPM3nt4/nqfmJMM4DL86Ip8Szw/hWPIqMWRnCdedZPB7X+peLXlooP7UZ74fR6ZE0nkEtee3HnhW5+pbz68/9JM29CFGS5GVgr6YZc4MlX+x6To+QyAE2Z7LoHmRB03rF8LNRke8jz6jN5AL/kfaaV8ud12nLR+uvkDMWFfzoivj2lPfTNMP+iqqMef3tq7asdY2m5bu5zpHH13lb9V/nsF1nEOuOt9YR76eyGVofYuicT4L4tLn4YkZ4xFVla1pzkXGmjtBtmo7cs51/FxySZUD0HExV7SFZ2HkKhQhQQ+JuaONSFPXMe45oelvz0y21Puzro/VqzDX57y2kEvhmRlEHM96ZGdsyEVYN1KvnqMw5qd2dY1u6estrG3mVNtzkEvyOEZhsyb5KCy7yz2H2LyLTQNh9uZVeLlGQcTYNECU0keFrBunvDhMkW8FAaHOXbwTbXDYZCgRFwUFBSsFN7xhlSJPoVSytw1knwKycimyhxeNNUsoNnkiUVApJlEdcJJiNI4MovB87GMpve991T0IMgo/JYjiPFRi62gDxYlSHgoWZT8QyjfShQJO4Y9qkJThyFdHwTRZo8JitCcqUbaFnyyqWIM+pcQzQh72sGajVX9HwvOmnFZ1RbxtDPM8d8cfX5E7xiUfr5WWqyf3etBnuWeu+QB+Mw4YF57L+CJoKf6U/Te9qRqDcWGMkzyVkL75/GdoRSJ58w/h7Xh/m7PaGuHXOcLg81u4i/MdhwwWXsYYmdbjcxzZjATIvVrcvyk0UNs9WxuZEiSpNucbGmGc6e8YD8ZxH2J0HkVWhsqNV7A8McucGSr/YtN1vEPu7X0w76wr3hVyalbyoGlOI1ya1i/94p2W58+aWD/e83lOxzg+1s+2PnNel/DwWE8RifogyDzrZIQFIwiteZGSJPeWtoacfnpF3DneOhy5lbVLX5Kp9AIy09qlX5B4znWsMQvPMcQZ3cF3yB5kZKSMcS7PQz/aQm7qI+e7D/JU2GwUVgH3df5HPlL9n4cI6z/3RDCGF3eElBv7KM6iDybN1bZNrqjCnKdT0U9BZnqGfOPXGk0Hity3j3xk1SdkpO9yD9r6/NSeLt6pfb2Fu7y7SLlxm+Bd70muIr+njdDJNw148Osz/a3PIm9nhNwHMSyH1DxSDxWsDlx00eQqqGB+STVVUFBQsJLwhCek9MQnVtFx40CeHnjg9WXmIrBmCcV5FiGg/CI4eAVSfBlEPOkob5T58HjjTdiEaUK4JilYwn64wcpXRJmOioAMAMaJ43lgyA1XJ+ImhZ8sKrlxF6OVUg9DhMLoU2OHCOYdUb9n17EaukjBLMVYcg+EKAbA0KPQX3ppNS8j3xWjD3kmJ4M5Ib+n/IG5R2jd866LpxLSlzEc7XCM+STknrHs2fxmUGiv/jfmYbDHvI5E9BGyFzA/zXlGzywLahvZXPfk0n9NoYHh3dlGptSvk28COE5uKX0+Lhfjota3oXLjFSxvTDtnhsi/2Had+qaWNSaIrlnIg6Y5bc3wLo9bv+RcljIj7te3z2KzUUSBTRMkjzW3KTw81lMki/XYuqgtkSfZWmN9JM+DwMyLaznOBou1BmHneCQcItAa7NyIUoicq9qEQLP2CI3WBht4kdfRumZtRg7qL2ODHDUWoVcEWRlJwhXR0F7HuVeQl64dmyoITGQjRRhhZw7E+mgT1rnh5ehc90DmaUOb113XTS7ee+RP7gFKpngWxzqPvMw3j3ir6ivH8kw0h5CM9DvtckzT/OwS3TKNt3DXedhG6Pe5p7ZOm64l1+McH+92kNKuhQgn/+jI4wrUlSJiBeCd6wJzYppCigUFBQVLjYc+NKW3v/369QTq4BB0xhmLzxW75pfWofPY2Sk74ohK2aY4U5QplnkuJiQNT8G84nKOaUO4JilYjAeusJQ1MCkp9owDfUAhJmzttlPY83DhceEni0IXo1W7kX+MhCFCYfp4CrR5uwxdpGDa6zQ9S3gIWoB8Z86Gpx+DCiHueGQzTw7zY1wYY1fS11iYh5HziSHmugxa/ed7nzN+3DNyYLq2d8u1GJ12YyLkLRL+M04Y/Qx2xP7Qc7RO3us3/RSeOhEaGM/fRqZM2gRgTAn7G5cDbBHr21C58QpWBqaZM7PmX5x0ndjUYjja/PA+kVvTkgdtc5pHuuIVuQd8YNzmQNc+c+6FF1Z5bK0V1lVrWHj/1dfVWE/1hQgEazOSLtIiBDFn3bS5ok2qL1sDrYdRKAoc7zzfaZv1lw5i7Yocy0hGa6/P9bVzrLPyKusTfRVkW6y51j05yYyJ4x2DUKNvfPjDVRoK/RsbmdZH1yBrIo+zv92XHOBJqT2nnlrJHPfwTJFvl5x1Hc9gs2VSv3fZ5CL/bLj6O9KpuAYS1nxzbV7k+js2j7RLPxk/G2KU/Ziffo+bn5NSnUzrgTfLet/3ntOma2na2GwqqIPQHldQp8/zFu/61Qs2F/K5C7bbbt6tKSgoKJgPbPTSQSYRijaSX/Oa7gX+hsKaJxTHKUZ9lRCeichE5xhEClPkLKQwA4JJfkJKp7+FcwyZ/4WCRRHjaYi0DEVXe7SPwu6HshgTE4Eon57/HWeXvp4k2++28JOhMK6/fReVJRlC9fBjoPgyYhgGEnYPEQrTddfe9Y877vo5t/S1l3vIIgXTXqftWcI7gHHHmGLwMSL9RAg8gzUvihLGtT5mhDOwjJlrTSJ9tZ2nDAPZ//qRd4q56jreDX1n3rq3Y7XlMY+p5qofc4QBbRydF+FzfjNQzBEel8j7voRcl/c+J+8psxEyHgWAuhYuWoSXxSx5OofKjVewstB3zgyVs3Pcdazd1ie5CuWSiVQJro0Q6koUjJvTzuepFoRhXcaM87Sc1Gd53jhrJHKsKW9cTlq6DwLRM/oBMjryA5OH5Iv3z5rn2jzstDOq/LpmFG2L9dTf7u8c61PkpfPbj+vq71izfCes2nWEACMMH/CAqq8iz7Bz6Db5+idX78UXV3l99C09iIyOHMxkjc+0KUIWo3I2YvGDH6z0ENfOi8e4v43NcV53sY5bV8PbrYkk1g/0H/oYOaP9+tzGFVkTm1f6SYiu9sZmm7EI2eOZtUtf7Lnnuhzc066L08qGWdb7Rcijpk2DPFqia0GdPu9d8a5fnfAuHnxwt2gu76kxLygoKFiJ2GyzSqcg0yaB7sM2p4MtCoVQHEgJobyeddY6hZuREJ9Hzh878YgbyjwSBEnDIKfQRoVnypQJM23+l6Z2S1isIqHcdzwM3T9Cn8LLATFFwedpgERCNPqOwaHNjBPK3bzy0ozrb4gCKQgiRkxUwW7KVfSoR1V9OoRS3GXXnmGlslJO+OlD3hmIJslRQ3EeR8RMKuAzK6HT9izmHELPvGUEhWJv7Bn2PmdYMfRyMPIYT3JMMhL1sXkdeQCbPJU8H28TyewRAuaZsXO8d0a/maMMN79BG439G99YHYswdyxCErQzqkKDPgoyl1HYh1Ds897nhRVOPrkKtdbufBy6kClLUe27K4bKjVewujFUTrNJ17HeR7Vi8+6EE/oTBePmdBD/1o7I0zhE9EBOYnq3EX8hf/O8cfopJy3pEwhC34NztJk+QY4j5KyhriuCYJttUjrnnCoM2BoYz+e8IL+QYeS/vvUT67q1KjzDI8WHfrVOb7ll5blZT8Gwww7j8wz7jGcfwtfarh9c09ruvp5D+z2Le/veZ/qXfmSs3Mfx+t1aTlcie7qu48YSWUjGkZn5Zo9+Nc/ICfcF3u3xd8xX8k0fR2il7/PUFgHynmciOTrEejiNbJjVG2/e8qht02BSQZ1xaHvm4l2/usH7WUqeSTAXeCeW6s4FBQUrFTe8YUovfGHluT8pZyw9ixNZIRSXGNMoIWGkUNgpxlFYIhSlMAKQisgZirbk7tz1VQwUwgOMAMbA0O02sSI3EgWbFyJShiIfiiJDgyJHYY/wkwiRojjvs8/0ytc4JXdcu5GHEF5+vFMYMAyAvLpl3WgdUiket2svUSqitk74mQPuZbwZM4yYXHGuEzFtRNaQBXzansV46zveJWFshSGt7VHAJzwxwhAzDowqc5kBasyQheaXZ+BhmLfZHEACug5PDkRmFA7QV84xTp45N/rMW4a1Y8KjN8L+GNTeK/3v77z/F/HeaxMj1wKfF2boS6Ysstp3HwyVG69gZWAWMmLSOmmdzj0JoelecR2hwarKR0VjZH2QhbMQBePmNELDZgfyzDE5ZokeyElMfRwhxkEQ2nyJYjN59WWRBlHpOlJSkNPhIWdtpDNYjx/96KqQidzNvs/X3ihsox3Wdvc1PrERhGyLtpD14UEYpBlCjzy1ZocXYz3PsOOisFSeLkVf0Yd23z2lo46qZIScivo3NpEcpz/CA9EGkXH0ORmKpIsK0XQA49+2kVafG9rhWrFOhSeoPqMHRZ/rz5BD+ls/RSXqkCfaGiHh5on7xzMjYt0jPBOHQh/ZMJQ33jzl0dAFVdqeOTbRi3f96oWNjC66Hv1UBFEZ54KCgpWMZz0rpde9bvJGCl2R/b5I9CYUP/GJT6QTTzwxXXHFFemHP/xhete73pX+jvRvwYUXXphOPfXUdOWVV6bf/va36X73u1867LDD0nZZMgv/H3744eud9xd/8RfpmzSEBWPaED+KajDGyI/Y7acMU5Qj5t0g2wG3s08BpwD5jcyhwDI0KFUU4j67p3nydso4Bd5nlGntFq5EeacEI+Mo/OFl4Fj3pDhre4Q4h6IcSnUbqTCLkqsf2/rbszMqQXUjbfU5o8k1hbxK4i4hepP34ZBKcRtB2ebtot+QoAyxvCppExEzzjieRwGf+rO4Bq8WC5Q5m1dXzZPvhyeGY7QZCe464ZVibBDWrok0R2Lnz2Nxiwrd4Zljnjk2QvSRgnlotXu5P7hXtE27GLFRWADpqc/NrQih7kPOzxra2ydUbCXlcxoqN95yxrHHHjuSU+TNhhtumDbbbLN0/PHHj2RQG04//fR09tlnp6997Wuj/zfZZJN0zDHHpL/Fhl+L3XffPb35zW9e7zxy72IxoMsQQ5ARTeukOcKwr6eDAGtI273qhmLI11nf1XFzOggw769nsLYMUT02JzGdG1WrY6PJmhfHIO2sG2Dt8xzkuv4gU2JjEvwfocCItqjG3OT9Fd7U7k/PiI2a0E3oBH70j3aQO3k+2DZZ43hrrwIurhkFXiJdirZppzbvtVeV1xapGOu/+zjH9clLXu6RR0//hzdmkK7hXVnfSDMvPJ/cizxAw1tcvyEUouJ1VBD227hqa4xnRJOAZ3JP8ilIxsj1SBb6TWZqj2P90K8Qp0uxnq8kb7yhQqu7bKKLZllr3vVsLj/f9UKMcm/dLx1yyCHpMfLGrBJ55j2VSqEL2FfLZe4XFBQUTAu6hc0Rm/STcilaH0MfWwR63+ZXv/pVeuADH5j23HPP9EQsTwcCcpttthkJp1vd6lbpzDPPTI9//OPT5z//+fRgJWOvBYH3ERmwo2FLVIpr2hA/SnUkWI8woVBEIRKP+zEJKLenn14ZD/U8ipRYytCZZ67LFTWJdNAeu+0UK6GXdaVeu3ldyCWEhKl7zDnWORTPIG6CAPM5w6YraZUTJgwWCeg9Z5OSu9NO7f0duZ7i72hPGCK8HHiq7b135Q3XN5dWXzQRlG3eLhFi5pn0Xz1cOIgY573jHe3GMfJ5HgV86s9iHCj1dY+BPPm+MfA5QxiZyyjLi4+Av7VbmJ7x0fYwFoTLmRu594bjI8QZ6W08zZWoempM/R0pAgLmgvYjKeMdi8UVeWve8ILsaigMEdrbxSt2peVzGio33nLGZZddlp7//OenTTfdNP3ud79LBx10UNp2223TN77xjXSzll2USy+9NO26664j8vEmN7nJiIB0zte//vW0kR2da7H99tuPZF7gxrmb7zJCFzKiq8d3vra4bj0dhGu8973VXBIO67r1irvvf391jutEW5A31pJxMqPLuzppTiOdtIGMmVQ9uCvqJGa9sm2E+2pzVLZ1rDXC/9oRUQ8+I1PoFNpuHfZMQp7HeX+5l76OaszaZB1F2sXGp7XXGhweh3k+xDZZ43Ne6fopz81MTvic4W/tVnXQdXnw0W/cJzbe3MNmFCIwqisHgRwEaJCuzvHMObkZ6yr9hlerZ86L3eRVwuleeBa/3dsrGdWuwwMxPEijffqbfoeYdA0yUT9GZWz9wlPffc3dSMmyKCyXXLd9NstmjSKZ9MyxiS4lzVrzrr/zne+cjjvuuHSf+9wnXXPNNSMicMcdd0xf/vKXR7bWapBnNqnqXuRtoIsWFBQUrAZsu23FG4kSbAM5Sk/GLzz96YtpV2/Wzg5X2y5XE16j1EwGxOJ73vOe9L73vW89QhGBeAfbuys0xI8ipPmU0Kj6GlUVKT5+ohojTwKKO5IO6VE3iihIkSMOoeQcCrGd7wZdYATGls1FSjcjISreRsJ3SrzPKNH15OTaRWn2bJ6r7k3Xh7TKCRMGEBJTO8Tx1/MIMire9rbK6Igd/7qXH/isTshFaJb26stpcmkNgTZvlzzEjLGS6105EQPjjGMedvMq4NPFYyBPvh+fG1fPKtw8D00OmEee1yKmH8JY8A4cdlizZ5Dr2EVGCPveuxFGvOc+++zrV6c2pxmA+idykJrj5rONdUn7uxonQ4X2jvOKXQoPklm8IeNcaw6DtO5xOovH1nJC3cPirLPOSre73e1GXviPaElA8jYLV4Y3vvGN6Z3vfGf66Ec/mp4pl0VmcC0HuTYrGaFiehBsTWts1/yvsWZZH8gFawpZ4ydkwimnVNcw75ra8r73VWvQtO9ql5BLa8c4sqPve1UnMfPKtog+HtXuSzewT6tPkV76GWmljWQ3mUdWB8mlD00vG2rR521rOU/+qEKPI4jK9LFRRX/wt8+00ZjkKST0l/QO1lltc7/IHW3NtTFk08lY0UOsxeS/60UycX1Gr3FvbdAuY+m+Npy01TO5XhB8rucadIBIvZHrJPm6ahz9+DwvdqNv9Uuk2LDpirRE/CECyR2/wzMyitS4T7TH9+7pczLd89GlVKL2efTjUoTSLodct9Nsls1SELHLM5t/5oFjVqN3fRs4beQ4+uijRx6Ln/vc5xoJxZUoz2wehMPBJCwyj1hBQUHBPEEWPvnJ1RoYERX17+kndCaE4lOfuhhdZOFugH/4wx/SL37xi/SnEfN0Lb71rW+lO93pTqPdsYc97GGjMLS7trAkQqf9BH5Oi13iED+DxdtCiG7kUKQMhReBwbW77Xd4WjGeovpzIPL68CCgDDNwnI/QkWvxkENSetzj1j/HNT7wgUoR1i7KvHOi4q1rMhboARQ9183De3SfNjm+7k3Xh7SqEyYUcfcl9FVRjNxFOWnqc9+7R90jIkg4bWjaCDUW2nr++dXvpQjzGZdgPELMwtNC39aJmPA4aTOOc++8IfINjUNeZCTCjBGaFH4h+qHgmz+nnVYZVU2Id4SBlRsL+mGcZ5B35klPSmmXXapr5MSEeVI/z7Pbk9B/YZjopzzX2nIJ7V0KD5JZvCHr53q/jA/PU+/i0JU/lxN+du0CWZdR4/DrX/86/c///M/1zuH5gZy89a1vnR71qEelo446Kt2Ge9UywiTDHAHF60pCe/Onvsby5osNh0n5X0OmkVXmE9lE/kR1dGsGwmmrrdpJAl5sMMu72jXksonsmJY4qZOYCDibNdZa5z372VVBsXj/c9kSufqsv57Z2msjzr3DozFfN5q8v2JDx3Wb+i2qMFtDI69tjLU2i7gg048+el3YurG79NL1vfGRo/630ec4092z0mnoPNoRFZ6RnK4deo570wusN1HEhQ4VxVmMh7YbA2OlH20mxroam0p5sRsei+6lPead60URL/0fKTzoQ/qAThT5r6OonjXP8Z7Xs+hTclkbHR+5pqPy+KJDaftsiPUlw7scP+RmWdf3a9Iz0yd95/71YkGrxbu+C37/+9+n888/fxRdxrZatDybh71mTtoE6ALvZIdguoKCgoIVg002WZdSLTiGiDaNDVngBMCm71OcdMUQiq985SvTL3/5y/Rk9Oq1eMhDHjLyCpGzSl5G+RQf/vCHj/J53KLBKkA21nMuLocQPyFHvKwMMEWWwkMZpdQg8wwyI4pyGjmQKKEhj12fEkUhj1xEFGxdQGl17yOPrNz3Y5OR8vWmN1UVhR0jNxEdIKpFar/znavaMOFKsXZ97TP5GHMUe8q+9rhOE/k1SemsEyZRSMP5UYDD345BmmpDEE+MldyjgDHAcIh+qhtA4TFBoWRAtHmzzNtTYFKIGe86Y8+YYqTVixToE30dnhj1pPauEwV8kGqzVq2eBIvPJGXeWKscXn9HjIlxNCfNJ33Rta9invm+aeGrn+c9olA6zxzxTminfs2N8qUM7c0NMeOqXxblQTKLgdd2rraZl5Zua91yzv04y4bXfvvtlzbffPN0f4t5R7z0pS8dbYhtvfXW64WHSQtyj3vcI33nO98ZhVLz7v/sZz+b/igWtgVtlI3DOMPc3Dfu3reciIo1Vu5TMsk88f2k/K9IsCioFIqP9TvWfu8x0qot44nrO4fMMo9neVfNf15xkb8VQcTTb1y2lVneqzYSU07gpnU8Xy/JEs/qb31IXpAfplt4U1Ia66RPvpZYLyeRTvF+0wWijaakdZ3HIo++CFvnKRpeg2SUjUHH+d99rX+RQ9N9wyuQbHcemWi89LkxAPqSviUTnet7f5szvnPuxz5WzSkbq84T2ur+eWRA5Kc0t9yX4u1zuo1jo+AMeRIejHGOZ3QORFEYhKS+9du460vPaSxUmnWfSDFjTnneRYbSdt0QM8+NW1cyvAu5N+RmWZ/3a9Izm2t0CcfNezN2OeKrX/3qiED8zW9+k25+85uP8t3/lQFZkDybp71mretS3RnIpzwvd0FBQcFKx0MfWm2a0Q3JQYjoFT/kMr2ErmjTetURiuecc85IsAh5tssVyEOoN9544xHBeLe73S2dd9556VlK2tRw4IEHphe96EXrGV53aYpp6Ik8xI9C3TfEjxJPOeVhwbNLwRDnhrJj4E0ASi/jCfFHcWJExQ63Yyi9lDdEo3Oj6qNddQqsvMiSciJ/KF/y2VFmKdkMgNiJ13afu67fCEUKm/bVQ54o2M5FYFL0KdsMlq6kVZOXS+QRZBBEQnUGh+O0z33dJzwnI2yV8oew0J6w6Zuq50bYnH5fyqTbk7xdxhUpYKgjgRko5kP0g34z/hYEYcdIMj/zLObRpsybL8aE92AQSeMIPm03d3iO1A2VaZOx5+cho3m+6ift5GXiftrzzndWc7svyTrvypP6hxLMi7nJ+Bkyn9MsBp5z9SEvsAhpjGJIEfrsR0TVajTE5FK0kfUpLEFHyFX1jne8Y+S9wcM+sAtX22vxgAc8YCTb7nWve42Oe7SSvAvcKBuHcYa59ZjMiTxxdVBWfE+5qZON9fyvZEzkAozwZyBvyAAywVoYMqMJ2uhdN//M01ne1SayxEZJG7nS9F5F7kNrtXdGhMKBBw6XN66+Xno25Jh1Tx+QCfqUPjCJJOpKOlnjXVsbjf9b37r+pl0eth7nGa/II0iHCdI4iGO6hn6Lys95PsTIu+t7YxucunljTtAZnO94sgipZ3NO7mTXof8gO62vnjvPT0m/cK7rRg5gm1360fVdO+aQjVzXhUgbZ0zDmzIiKPQFgisK2kSIdaSYcV863SJDabtsiHnGcfms62R4V33A/B8i3Lqv3OryzNYlm4yhb81zM3a5gYOGYpg87i+44IK02267jfIFTyIVh5Jn87TX2GbkziRIIbHvvjPdqqCgoGDZ4YY3rGQYWzjCniP6I+B/uhD5vpA2LeY24rjfkfbaa6+R632+69UExVv+/M//PH1bApQGyOMxdDLgIUL86h4FdrsZS6E8U0opQ+HFJVyTchoKLeU5vJkowJTeXEmKKozOpTyH8qU9lFvfUbJ85r4UOIYaYyfCQylg2kdxDkPMtYQFmZRBblKe+3h7NXm55N4C2uAYbYtk6IbXS8EgiJxQXgZ9zmji3RcFxJsIKHqR1C9tnjUUfP3ivHl7U00yFMcVKdBOXheR3xKxaC7YVdCHCLP6dYZGmzIfniTGyI4wY8yzmudNBJ85pb3mepuhMm0y9vAoYrB7N/2f5/ma1St1npUnja2wUJsMPJLquSeHzOc0Sz4t8xBRY9wZ03lhJ21ezZUx99lnn3TRRReNColJat/V454BpqAYA2sc7nnPe6bb3va2I7nWZIDNa6NsEsYZ5uFp5b2rF4Uip5A05E49j0tT/ldkoXkTpFTkeXEP70eEqFoDXXtcmCK5hPSZ9l2dpghNnTjRVv+HR53vPa9NxXEqzrg8q00Yt15Oeo599lmXG9lv1+E5OsmzM9pINyBD8007YxPkYOQZRFLxGnVMeNq7JpJOu+hA+sh4g/kS+RBB28g790UCecYgs0M34QTlhydpeLoiMCOfYR7h4EcfmBcRih1h9bH21ouHheciuId1z49zzd+QNZ6ZzPbcjgty1rna4p70ro5LyCCYtCFG/9I+49SFrMv1AfPPe+7vGGv9FvoAfcVY5J7I02yW9ZVbXTcBtd/PPDdjlyNudKMbpXvLU3Ft1ebLL788nXzyyek0+WoWIM/maa/Z74swv0mEYkFBQcFqxDOeUTmYkW1N+WSDUxHFwTdv3jJvIYTi29/+9lFVaKTiYyVcmgAh0Vzqn6G3FoBxIX6MlNwzqwvpkRMtFF8/lB0/lLDw4jLQFE8KTpCAFFXKcbQjR3gUEqSU71C+nB/End8U40hizkCwEy/ePtqfkyaenXJI4ZdexTGeva+3V5P3AyUwvAX0QeQ90a+Rd4iii3zyzI7TPoaKMC6VjKK/6waVvhTuhFgKcjSU0DD0fI6YU1DArvq8i7RMMhTbPFw8k3Hz2xwA/eGZzRN9JodhKPpDKMb164SxrB8j7Nq8oajrY+NkcTJPcqP7gAOmI/j6GtUB7w7jj+dqGJ15iHgfwqupL+dVeVK7hNLFe5tvFgydz2naAjP6zbui7Yzv8ADODXVE/2qrjKkK5r777jsKCeNtIaSrC0444YRRsvtLLrkk/Y3EnRPw7//+7+knP/lJuqPdmgUZXl0wzjD3Hlifm7zAvXd+rPtNzc7zv/IosYFk3fdOISjM+zjXWmO9Jjsi5HaS9+G072rXIjTWPO9reP1Z24I4iVzH4WkfCbA9g3On8ZKeNEb19WzSc5CP+Gn6QIwT8gcp19Wzs2ktca2cHDS+5EJUrA4PU+Prxxj5Pion+9v4R7QGaEPIt0jV4lr62PM51+faYq64d4TzuD/5gyh0rPWVJ7iNLSQ2HYluk8umtuJh8ZyRw9dvG4B5Tkl/a0dUx7ZBbH2MfIo+8y7JLdlELA8lw/tsiEVhs65kXZB73n2bYEEmIog9n3cjPE2Fh9MhvetNS2fXzbJp5FbXTcBp9Y3Vls4jT6kxb3k2T3i3uiA8jgsKCgpWG+5+95S23DKlt7xl3We5XRn6xsc/vpg8ir0JRWRf7jl41VVXjdzqJe9VRIWXxfe///10Nu3l2jBnrvZ2xoQy/+haP/UNN9ww3fJabXL//fcfVSUT5vyDH/wgHXrooaOcHLvuumuaN8Yp5dOG+OWGDgLRbhovDRV5KNqUesowJZ4SRDGlAO+1l4qjKX3wg9fP4xQ5fxj0kSc5lK8g7nSt68XOHeXWvekGuaGQF984+eTqc8fE99Pkvql7uQAlW1vcD0Puf8olJp1Savj1B6HPAGMQBAnIu6WNgKL4CqcNT02eX8iaUB4ZIXEfnzMAF1Wkpe8OfHh7UMY9vzHmServCAkPRZ/RNG2RjUmhfuYVo0AfBbHtt/HTf+YozwQGRD43nvKUdQRfPYxuHmHnYXSYI96t8A6KCurmke+i8FCfPsj7ctq2tnlZ+Nt1tdfyqU+RdpPCNKcxPqcpMBPrIKPYXHAPP3lhJ8/FSF9tlTGFOZNTUnHI2Rsyinwip0Cly4022mgUlgzHH398OuSQQ0bn3f3ud7/uHLmq/JCTwpd32mmnUVVMG2QHHHDAyGNku+22S8sNbYY5Dw9rsf/JoHxOWwvYpwiruvci5PlfL7mkygEbmyjme+THs67FnKbwyI3H4aWL9+E0RMEkTyhD3lSExjnWSM+kTZEPMC/E5d3xDo2Tm9MSSm2bQPXnCC9/ZJp2m276KDYKoyiJ9XySZ2fTWhKpTMgI99I/kaLE+mY8yV6FdSKXsPvRW2Iz1Tn6Ng+hdm+bF1FsjcxGLFuftTnIuiCiwXfgmu6tbUhf13Mt7Xdd49K1eFgd9fciNtjIQV7cCLUgSj2jfkK8NRHLsxTKmmVDLPqxK1nnt37047zwOo37IlGd45ltVpNpn/lM1Zf6eprNsmkLo826CbgawQ6TSopNpggmOWWzDFm40uWZdcDa0AX1SJCCgoKC1YINNqiKH15Lt42QhzzH/3gVNvuyIxS/+MUvpq1oitciQrSQhgqrKKryryT7tXjDG96Qfve7342MNj+BOD52upCHdrv+7M/+LG2xxRbpc5/73OjveWOW8MBxCEPHD6dMXlwUM8SR6zE67JgzrBAy8k1RzhxLWFLCKKMRToZYsluMNKHIMvKaPAIDlL5IKN7WPj8UXwptXflyrvtr14c+VB0zTknLvVx4Rng+bWYYeG7t0RfarYAMgyOMAoZZeIf29SZFxNpB50niM9eMSo/6hbJJyfX3Ioq0jEMXb4/IV2du5Io+8gzZPGsVxTZvXGS3sGX3teFsfBgTkVvTqxghavl7ER48fb3h2jDJ2PaZPmO86Ddjy5jTVsYdw0n/yfvlfWpLND9NYYUuRMA4Lwt9uNlm1XxlZEdRojZjflrjsymE1Th6L1xHPyGA/Y+Qd3ysg94N/RsFCiIPmj7VZuMtZHs1VcY89dRTR78fKVlphjPPPDPtvvvuo7/JtA2ywXbOf//3f6edd955vXNshh122GGjDbGvfOUr6c1vfnO6+uqrRwnut91223TkkUcuiRdiF7QZ5pGr1/pJJkSu29gIaUs5kYcnm0veTXOIzInw2Fj//G3Oma/xXs2LJJhUhMYaQCbVi9DYdNMe8i2IqJw4Ca87Mq5NZ5j2nW46LzwmtRPBE17l+t3x4fWn35GkxiA2g/xtnQtPvLa+bVpL8lQmntszI5HCk9X9bYodc0xFtkW7Q3bQSVzLOVH12/V2263KdXfZZdXcMk/Cy9Ea7/kiTN7aHjLTNW3+Ru5GfeG3zxB8EUafP18XoivWe/Mz0sfpL20WNarNrh0kovZEZAjUieVFVkKuz7u+ZJ22Rf5T72qkAAqvTO9QRFeQCfpIX4hqce/Ia9wnp+kshdGKB+L6+PGPfzwiDdljNsaELyMTt9lmmxUvz849t1oPusDmVEFBQcFqxa9+Vf0ml5vCngGHJD/4vNfD3oQio0uIWBuCJAzYFZsEodBLhWnDA6cJ06Tg8qarezZEzjzKK+X/Fa9I6eijK4/DyJtI+UYmYpgpZ5SnUL4okOGZ6DPKH6VVODVjzndNRNq4Z6ccMjx4Opx0UmU4TjJ8fI4QVVUt2k5JpcBiyE1qbYzqxZ7ZMZFj0jG+0zfxkkzyJnVtBAcFm+HrPAZOJFAPTnoIb7lZQ5W6eHvkeaXAsf7naTprFcU2b1ztshhFPiyGkfb4npHIkGA8IqHCEyneC+hiqESuznF918XYjgIwvCe9CxHyrr3eD0a965q3jLe6kTZtwZKuRMAkw42RJe+UggL6Mu+LfH5ZL/ok0B8XwmoMXdc7qd8IHWMhlJ63leewNnkufZgXNfAM3k9tc67vVltlzHHyrE2OfVcHjgHPxvAGWUloMszDexGJguyJtAzkFuLAuj4phDZIqCAWvX8xt8A8N0/zSIB5kQRditD4vF6ERnt4Y5kK1pkoWpRv+Hk/vEPWpKaUAiICvIv6gky13k96p9uIKGuRH2tFrN1IOPCOOw7RY7x47UtZEHlQyUrPY/ymCYf32ysQodRyr0YIPL3jEY+onq1OUmurtrg/IqppQ8X66zj9GDoDRNSGtd44+R7MIfd0H+3kmUn+G0d9Rha4v7HTf12K94xb720KUc5DJrtOyOw2YtlcWYpKyLOSdXFc5AjNN6h9ZqPTXAt91rvlWvqeviAfZtf8w0MXRlvLOOOMM1atPFP4qgusx9ahgoKCgtWKm960kolthQwDnIaiyOaqqPK8HDFtmEUXBEEgqTiDKSod554NEISaMBrKokjvN70JObuOKGS8UQRz5SyULxMl8k9FNUSKGGXT37xKmoi0tmeP/FCUdtehGEdlw0keXAhT96VIRs5HCjkFnCHgfC+A61K8kYpRkMXzU3opuE393eZNSpmlbOpX3iNcgD1n3eN0FnJ4iFClcd4exi+K4QRpF4q+vEQIvWm8aHOSyng6rn4dnzM6zROeHdqi/x1jzIxPeKzGefFeCAtkGDMs6jkU8+qS55yzfj6yet91NZJcDykXnieRtyo8ec0t13dPz1E30qbxSO7aNn3tB/nvHnkagbrhxihtIyyRpELI9D2FuF49t4vxmZNAH/hAdU3vMINQ/xhT/WfsIrQQGeC5vE/Ihyg4Ye54Lp/LbbqaK2OuZUzaMPHuWp+QUNYoBI/53CWENl/7rM8IpZhbMSflm7MBttRFaKwpTUVowPtvXbBOarv3RT/kG1jW06aUAt5FJJQ+zQseeY+9i03v9LgNEF535F1sroQsDc9PsBZpG/lBT3AN9zVWk9JCtIXDG3P3sQlhTXetyIXp+RF9QsYjDUlODJs7xrhtnllbtTeKtQXX73t6kt/WstBz3IsHXYxVhKLrE9d1X2scHUzalSi+Mq54T5f1nuxS3MZ9PPskYnmoSJhpN8T6knVRcMa89BPepeaVsQ9PTH3tWv52PZ6p+sFz0Btf8pLrp+/pM9fWUlXmgm7oUt0Z6KZ95l5BQUHBSsP971/JSHrrOHAgmXcexTW/3M4SZjEOOUFA4fY/5ZKiVjdUouKhz8NQoXgff/x4Ay+ULxF7CAFtD3LObxPIfZEvFMA6kdYWGqnN4alGuXe+7yaRGaE056FiIATJtRwfRoDPHBdKKfIEicHwaevvcR6VQXiFN1VdaZ+FHB4qVCmUev0klByBasy1m1dFGBbGLlf05TFrq2Y9qchGToIyxCworpePT4Qdao9x8NuxYGwYpeZneITkRKHwE0Yl4w9JEFWeI9wJWWBM/T2ummpXI8kzmsueAYlJuYwqntoXbfdOhZEWm+/aqZ/dp+19rvdlVwPOccL19LV3OLxiYi6P87Kozy9jIPzcPJB3LjyL+hqf+st5FGvXtR547+JaDEVt0peewxxxTURBkPQRJu1z6QUWQfgULB7jNkzi/STHFHfI19ZIJTEphDYnNMw7a0SETruu45HVi/A+mlSExtrVRPyAY7T1/2fvT4C2y8r64HeLCYqJGj0mGqd8JpCU0TQQR2YQaJpJUjIjMjQ24AcUkyA0NPPQTE0jIM3UzGMjigK2QDPKYASicaSOFokVA1FPRIPnUw+2p37P7j/P6tV7vIfnfd73XVfVXfe099prvNZ1/dc16Af3+ly6P4/JDCz4APsIj4oVeBIeWXNDa3oMiPKcWPixSuRarD+1Dc9Vtnfglna6xrtneLbfp8JC1BRLQ+345V/u64XH4bX6T1tZCUa2mZITpixPw9/1nzorz/wowdJYc+PxeD7wF5CnffibQy39mf5yIAd8Bai69qEPPcwSXFPN71ESfwEu7Q3a9TM/089X/b4EWN6VJ8w2wOQasE6dAa9ARfPZmkXGmzzovljyovwPuDVO+vF97+vjd05lPB+iFhOx0Rhl3S+hs87ad20aNWrU6MTS9a/fYwj07yki09ArG6C4R9qHm0UNECTGEdDFZqj8BAkvXWQIpCXgtcTli/D1sIf1daVQAEzcp5wI3v4jbDqdL12chtpOEQF8EgoJiwmcvkRgHROaays8/aEfCKHaSlnwTjgn+I/195w1qf4j7FJALJpdgMObWgRMkTZQJIHASJ25bZsTLB5qVzAKrthEa6xoh0BQ/c+CVPxBzwuwFLdr4+A61qXaSWFIMHf/U1AT86oEClmiULaUXbo7AcKAaxSXqb6T2GWpkpQ5oE/OOONwDlGMYzURt3Ftcd8TntC3Q99aI9qp7hhxHaa17sslChwrIYzanHadORyrGP/pgzGrmKH5ZZ2aS9aMuVxnhV6jfNpkrOG4RJbW0bGYxn/UG0Cg7eEFQAfPwB/U/w53aErdyURLQzTMHZjc8Y7za2CJC20NaAS4xIs2tT7aNAzFGLgCNB9LQlPuIT/6o332X/zHmgrghT/iKeUepo5AOGCMPTNuo2XCo7hB12t6bE8NHw6IiB/mXnt4XGCU7Xtch5NIB6joQGYoLMQYGWP7kHmSQ8ZYiquPssNfNg0vEv6e0BVJTmbv8oy0A5Dof+MdK0F7vrbaj+p5mpic+GnGZSgER8nvkzE6ib9yqIanu87hipBzYuLmICixHSN3sdjz2XxSBiuCsQRG+8qEvAlYVx42O3AyHpEHsofqD+3VTv/bTzw/Gc/VY9OM5y0mYqMhsmbJR0vmz33vexQ1atSoUaMTR/ZhB6hzgCL6pV/qZde91WV/RZ88tOTkdqniMgZAiZtGEASaEcAIXwTQuMgQ8jx3E2tIgpf4QG96Uy/oUXySoTdWE07tuTETgoesHNN2m7Uy4q5UAy5TAusY4Jcs1FE8lMEdNLGUKGKeifTDptak6iWvAsVtV+DwLpP2lIq7epbJDSiE55zT17eeY4mNudSKdmwOqqtxBViqS0AqCg6rGb/r/7gte6cwclenJJgbiQFoLEug0HizRACcK1s5d7lL1z3lKfN9tyaxC8apbEpcLCcpNeZdCc5rE3Dd2CUBEAsaxJ3YMyk98ktljg/15ZwCZ+0C4jzzetdbbxUzNL8C8JofAf3MkyTq2UT5jFKcRAZlqAX9YJz9z/JKH1iXyRLrfuPOAlP9m9vZ8aelIRqWHJgEDNtFnOFdWh9tG4ZiqC54kvBigBBW5MBFIFK9hyReMH7+6U/3e7m1Za3L41M+X/mAWeUkI30ovBNYg5/Va3psT9VeFnyJHYv/5KAH73A98MrLd+Ocd9fjWwEcN4m/65DEnAi4pD7AOv8lq/Im4UWyx3MNj6Wl+cXKOrF88So82n8PfOBhLFo8UuzpuXkKSBWCY2jeaE+s+VmHR17x0j/kKmOlDHV1aPaRj3TdBz7Q/5/1o+7+109PelJfHn5q3xHGwgFNaNeZkO0f6s0ifcxaeE5WKQ+brTPrwhgo20FZkuPYb9Xf/mDM9V1AX+M0l/G8UaM1ZC5aU3NETsS7GzVq1OhUp8uviDM9R+SUfcZRbIDiAkVnjeIyFeeP5ZfBZKkI1AAQADk8h2C/adBp1xNsX/7yXskgzBLwUDIsqwsBecwVJm1Xd8oUMGTtSfoU4KdtSZZC4CTYJ06PZ3teYnKNWU0ssSblhoR2FYNniUWAZ3vWlII8prgD8oBP2uP0gCvVkIvYGivasTnos/argznoucYj7u2Ji0ZJUD5lwImwe1inJXaatlCShsqnVBDmKF3m+BKgEC2NYwroslaUTZFNAiLtoAwmfhUlh+JDkVMn86wE+7Tfs81VoKKyhvpyToHTTv8Ngaa1VczQuh6aX2UWVfMjoN82ymeZ/CcJBBJqwTizLvU8hH/EGlS8O32rfzbJRtro6GlNiIYlBybi/aFdxRnehfXRLsNQlLFSn/3svj/wQAco1gTeUVsYu1acQP2Bf+QAAJBTxg9EiRNpr1dmmZAN4b2uiTdDaComq7WbRF54Hp7h2QEQlekZ5AC/JeGX+nq++uBLeGGZOCTyT/hRXNjVo5wnSQCT53teYufpO3vc2JyYOpwtw4J4JbmctmqHsXDoYU4Cb1nG56DGXjW3j+Cjb33roTX5kDUu/sgK0f6grfpV+dqpvq4XgoRLbxLjaIs+8NxYygMPE2vSc9wPfJTbgiXs0gQxJVmPUzGLyQdIvM4kzFkb63nuoF2Mb2Pwznf2cSnNA88yn7Q3e516atc2ifCOirZNuNfoaIiF9JIMz1zt2/g1atTodKCvXSh70533GUexAYozis5axWUKgCLI3+Y2/el7stUS7AmC2wadVjaBNoHLCczeCbiEOsI4S6qxQOxpO0GKxYX2uXeN2/AU8OU39eAiBCS55JL++jpxRWJyjZ1qL40DtCsrmDlAyTOAW0DYuKwPCfDbWjquiX80Nwe5+rLwS7xO5bCYBBgClpSvLnEtoRi85z193Uorjl0BhU6Sl1hgup6bobXIGjBKJ1DP3KZgmk/WAMvAWFVRyMsyWeiYD9zozEvB9c3Job6cs4p1fxIJTPXFmKXO0PyKRW8yztbu5rXyOaYMlXXXpoCUsciMm5r1ZqyB+qxPWWhFkVe3ABGbuvg3OjpaG6JhyYGJuWd+m+u7jDN8VG1cQvU+by3oG7zB8848s+vudrdDK788v4zVh/Dx+vnWJGBP/yizzJ5unx7KcF0eYlqbwCkvYR6s5ViBeTbe5d36TmKluD3jfQGWuJ4GgHJvgE7vpdWefaHk/cBU9/ldrn7+VAABAABJREFUv2TMI7vE4lKdXOf5ZIh73OOqc2LJ4ax3Ft3+E3eSAIxn40f6DSiX9jvY0s8ALmCWuniG73VCLPM38XW1Iyf15bxx6GqM7emJNalMZWfs/K5e6uR3pJ0OXYCJ3JzxfN4oxiEJzoC31hOLf/us682LpbJf+m4sZrH6J7YxHr8pyL70oF0/As95JWQNxNVen/lfKBDzZ5NEeEdFu0i412j/ZF4BsOfI3LPWGjVq1Oh0oLPO6rrXvW7+OrKgfa4BiieAphQXggbQ4qKLruzOOAdAESIJswThKHRTVm1LQTHXEG4Jk4TaxPxJdr5YT8wJdtvGlBwCvkxighrhmlt2Yj1SjupyloJrc4DhJlYwQ/09BShRsIDD+seYxjVuSIDfRVD2ut2lFQmlK30wNwfjtszFOq7mQD39BfAWeB9AGgu7ul2sOHYJFHru3JwT94HLbbkW3WdOA8ko/ohyrn3ARYpOEgLVxKKHwqPss8/uQwYMra+59UBZ8jz9uIn11tj8ohCyDqzdzWvlc0gZMmYsloEByjBfXAdQYE0CSEXqZG0m27M5EVfJZO3F41hWB4jYNDZao6OhtQcXS1wozTvrj3XIrkJJbGMVtMswFGP7vDXhGVxcrZnnPa/nsXif/ljz/LkM1/boW97yMOFRCW4CtHI4aL9hFQeksd+wzlN3vEc5nq0f3YeSEdn44ielNVusk8kMeIADPu+ep+3GNjEk8QYAm0Mbn4GUeAOQ2bXl88ukcNpajqf4e894Rn9PrDHHLJ+9X3BB193udr3Lvf/VSd8AYh0oxaLy1a/uuuc/v/89bVPfXJN5qn3KUU/3Jct2kqhk3IxLHT8zFpLKiGtz3MZ91+fGQ3vINspQZrJpJ1yF/UJoEM+/3/36Zy+R/crDNNav+p5Lc2IWA7aRNiQG8lKQfW4dDslS7gGKarPnB0SMVax74u2gL8fknhNNu7J0brR/YjUcL4opwk/F8G7UqFGj04HudKfeO9PeNUX26SUxaDelBihuoLhE2aCYE5IJHiyjkhFzKYgypTytPTUlCBKGXEuIdH353FhrLTGNXWMNNwd8sXygrBAuCdWETv3nRSAGVq2J0xiKBVYE4bhsbWo1NdXfQ4AS5QLYY3wlFYh7+JgAv0RxX+I2GOFefd/85vGsrHNzUDtYelBuy/u5NrPScF2Z0bVsl9iXngHE2xYoDBAxN+eGlPjEefSiYJVKGoXnkY/slXAKnfsDrqNkCjT3gInq6p6hQP1TdQvQuWmW+CnA0hrhGmezoMjXyt6QMqQPgPaveU1/CkWBFcsKQAgc8V29kPI8N5aJ+sJm49lxn1QHSiHFUb9uGhut0dHQ2oOLOQvczF9glzm0q1AS21gF7Spj7tg+b87jccAhfD0JTySzUq7TYPspkMl6wVfKZEf189dkuC7BTesRL1YP69YaNB6u8Z/xUm/l4Fv6JPHs1CkWkK4nq/gfzwWEWdMs/hy4+N2hhfJYrmtbLK7VN8nSgGkshBL/N9mqAUrKscdrs2foDzwrRE56+MP7/Ub/6LeAeWOAl3fgm7mnfS94QS8/xKtB3YS18K4+2q3eytav9mfl67uAhXiaftRPyV6v/xzA4G2J5+ueJLPR//qkjEOpHvojVpmu9Uz3qY/ytT/uwCWReZRjPQ0B3vXaMJbaZH4FLLQfKz8xi42lvS6xJMv5OAWyb7oOc0ilv92TWJf6JRadscA8rrQPS+dG+6OESZoj64oXTqNGjRqdDnT1q/e6Oy+TKUqyuH1RAxRXKi6ENkBMCQwREMsTzbUWflOn0UtPTQmQAASn47VLFeXBZ24AQ3ER9xE8P4CfCZ5Mk6wGCP7a630og+1ScG1MELaohhKbbHtKXQNKSXABjCoDrIc8mwLqRbhZqrgvcRtcUt+pOVhmaK7vd72+G8qUWWZ0vde9+vu3BQrLeTw154DPUyBCraRRYAPKaWsyQ1O8lGFNuD6WiXOK1VTdvLbJEr8JgD9mVaXdccOz9in96uHdmFFC04fG++KLexc9c4Jy6lrrMpYmyDzXhxRVljBr4uU1Olpae3CxxiJ9VwlVtrUK2tXhzNA+jxdbg8CQxDq01gBR2qrODhDsZSwFY4lVWroNPX9phuuAm8YhbrGpR5KrqQuAMK7IQLBYIVrHAdTULe7I2pAQF+rlZV27z16mbXii9gWM0g6HEGQK/Df7Nndf8gR+ATDDF/yufr7H6lE98AsW7ywI8SZ19mzyQHgKMK8GvGqZCClbH2uXZyUsh+/GDugXy3W8UD1Yyev3t7zlMBu2vitdxtXBGALrXAPAA6Aq27MD4iZmZQBYe47+MkY+JyFerBv1X7xE/OY5+sXLb0Pzc2htqK8917gEaC5jFtvTgKf6yjXqVs7HMZB9jcVoTQ6KHSjqC+3R1+aPfogrvPFwmGXPWQIEHRVlbllnLPCN9S4snRvtl2IJO0cOPKy7Ro0aNTpd6Ba3mAcUEU+jxz1uP4dkje12yxUXArmA2oQ6AnVACVSeaEqssRQgWHIaveTUNBkH41pMoYi7SdrBBWlNnKttg+cTxFh6UBwIAhF2EzeKQkJwLV2CCHuEZy6rCUpfT/wxhfRDH+r7xqm5flxy2r70lNqYPuYxh0qOMX3lK6/an7FeNVe071nP6l2vxiwd17oNrqnv0BwcytBc3s8CxXixohmiKCaUhF0AhUvn3BoQwfwAyCfZTOJmeTalNFZHLDB/7Mf6+bYE4Bir27YWvWvc2cesqqJgxzqFgqc9fs+8kLW2TPrjHTiijeageUFo11/J4kk5ZNFkPflfbDSx5I4qXl6jdbTJwYV5x5WXa6lkF0nqNTR/t90TdmEVtMvDmZq3qF8JqpXuwa5JYo2AWvi2vS3gmD3WOhl6/hI+GHBTmTW457v3/G9/cYiYDMQB8kogK+6nriUXAIz8h7/bl/SfBCPahc8AK92nDHOBDKFP1NV9ylFHv+EV5orPObDxDCCkayWJM6eAXUAxfAVP8Z86A7uyX5J1ktwMWCWUiPIT/7GM4YhilRmgKhaEymCBaD4l5qxy8HhjpWz1T3zoZHQGrqmXwz9jmXA02qIO5D3vASETW1ZfBYz2n89+d71yEu9Se4yf/lFn8zfzreT5b3/7VdeGsvzn3voAVv8BtmOFb5zUXX/rL4AuwBGVIPcmFqMh+4zENgEQzR3t0I9+S/xOv2u/a47LAVQdm9Q7mUCbN/GUaXS0Ls9LKPO9UaNGjU4X+pZvOUwIN0X2PAfiDlt3TQ1QnKBScSFsUCQIcAQ8gnEyKBO+CEzlieYS5WHNafTcqWntVuXk2jWJmZbYSMo+qpgwhFxxlyg/LBMiBBNsKQZcqQh12knoVF+ARRlwvQYExxTSZPtVnvFxSrnktH1tPK70eQLtlwBX6SpnYVOCtHvK0nEt8DRVX6QupWVkCYImW6d+1a5YTJQue8rFbChDPk8Bd/piW6BwKS0FEbRLplbzTtsCYkfRiVvgzW/edeee29f//PO3d3vahfXWEnf2sZicrIjUNUBD2kGZNg+H+Ib6sSCRXTwAPLIWAQuU6bg16kv9p3wHF80F7HjS2hi4pYINEEAOZLjyczXdxTiXoAme45nbxD/cNs7vFG8x32N9jvAKvEOf4AkAKesOb5UYw8GY391nrQHPhCkYe/4cHwy4Gas/9dAue4X1B6yy73imvc7+fpOb9OtYvbhIJxQEsm7VXf2UaW3bex/96L4N+pmV8gc+0K93fNB1wEnloSR7S/30tWs9JweqSVDilUQt9kJ8RZvVwdiYA/Z3luTK0Q7PNP/w7Oc+95B3k30AYuruf7JL2k+m0d/6JHzLs81hbXJP4h7qJ797jmszpuoRjwm/sbi76137vku8Sy7VgLkAp9qiraV7u3KMkd/iAeCzNmiLurovz46XyFOf2isB+jIgcWJLl2tDH+ZwJ+OjjjlEcr9xUa+AfMrzu7Z7hrqL0xlr/Gc+s+9P/eT6OYvRUOQvbePFYAzIltpv3SXJm/lC9tHvXNRPxAHUnOePcchhmmu0u5S311o6N9ofWRuXXbbs2iQEbNSoUaPThf7dvzuMiz9F/mdI8qhH7b4ODVCcoCguhJL3vrcXLGMBSAAhNBGUAUg5Za9jJ40pD2PA2NRp9NypaSylXvrS3i2JMEdYjDuL+wCYRxFoWvu4YsUirKZkxiWQ6gMvwjfhuQymXgOCQ4Ba3NS0l6KibygShO45UGjTeFw1wIXiKmfMtEf7COZozNJxLfA0Vt8py8hyrLmuuUafUjiSvCfWCXEJ9r+6z1n/bAsULqWlIILPiZVlLNL/sUTBTP2nnQEA42I4BLAmayuA1m/7BE3XuIOWVlXqTPHV3lgS+S2WN5TGqdiH2pmECtat9gdQSGgCCm0SPpWx0RodP1pqMTs218wzbhF46bb7RG2Bb06yLLvBDYYtjZdYBZmjQCWxDGPJtvZwpgYbZFi2zll7JYmY9QygAZjgjT57lj0Vb8dztCsJVqw760TM0037LfuKdiVTbizb1MMa10fWK1nBd+1IVlO8TT3w6sT+s5Zd65UDFW12H77CEtEzjLfr7R+xnkubkuBF240bnhAgSnmem7i06m2MjQee6bn6KrEo1SEJZ/yXgzj/5/na52ALwMbi0LOyb8UNPdaCsYhLkhl1N1YBQtMHxg7I5dlxiS6zEyvHenjEI/r6ugagmfr47pmJR5tkNEnO4jkB0oC2+olVlb7CM/2XWLT67NJL+7HkqqR9xmEotrQ+VB9zPLEby0Mk9dDX6kjecl2AV2Oirkh/2g9YjepLz/acuHnXFqND6zD7pXmqTfo5iWqSyMfzMtf0nX127iB70wRNY7TE80ddrWNAqrqX8vaJyF7faJzIX+b2EmoAcKNGjU43+r/+r16+SFK+KSJr7IMaoDhDhCCukW9722H8jri8EHgCmBF0WQksOdEkPNkguZfW8fdyGp3MgaU78JJTU8IbwfCa1+wFoQj1EZJKcA3tUoirhTltVLaXeqtXgLAkhiCcP+QhvSu5Zyfg+piV2BCgpo/iHqbvko1xidXLpvG4aoDL/4R04xdlieIQhWXM0nEtDdW3tIz0H/CotoyMME+oBtzGXU9/ldYJ+psbHUVjlxlddw2U6EuAdWK73fve/TtljEKTeFLpf8qVV6xRKA+Z+1MAK6WT5QqA1v1L3eg3WVdr3EEDPLDoVW+Ko/rlHvXGj7RHW7k41vNYHd3LosrYsqQxFxCe47nKpVTpDxRrmEbHm+YsZo8iIcGYBb7YgPYG8QNrN8O5/W0IKHA4YA5f+9qHbZxag3UZAd9j3WuO46nKxf8Siw4gpTzhOMJbrIscRCR+YQD3TfhAeYjp5ZlxYcbfkTUKTPKbz0AiZScGZOL1xaLOXqSu2qgu9ofXv74vG29LzNTsofbP1D8HDHFX1t7wUGWbL8pXFhCpdH91jf60lwAY1T9eHd4T9xb/zfzzGfmufP2Kz8dCMAlRvCPPiEtyZBxlJvuyF8+SJFLDE7XTtYn1l373m+dLavXCF3bdu97VzxWkP83heE+YD0mq417PVzYrNyCVfvR/Mj7rN0BWZLkAxqmzz+73cn0JbnmZg+Zk5pr+BlbGIlHdjE/iVZeHSuqnPtbdgx7U18H15qprjW/6PBajiTtcr8NS/nKt9qqr/SMu+fpH3blUec7cQfY2CZqGaKnnT/pVn3q5JodnJ1rWaXRlItctiZ+IxsL1NGrUqNGpSle7Wu9VZJ+foxja7JoaoDhDhCNuToQcVgCJBZTA4hFGEnOHu8pUAOoIT8BEwjzhnrAdpSWn0Z4Tt5nQklNTSgjBSXk1QFaCawKlc4/alRA3JMxRrABbQFdKmn7z/Ligek+imJxk58S7thILGDcEqLk+7mEE/pziJwPnlNXLmCttlCHPFXdwaAGWAJfxdH0yDpcB0XcZj2dTy8gAyJQQyo95HSUs1gmUKQDVPe7RJ7dhFr2LjK67JM9Wd3NKf/tM+VHXZNP2bk6XQHzI/NBe9xmLKYA1LnXmUrKsziWP2EY5Wut+r0zjy/WSIqqu1o/5H+U/WdUp5QCckm9EOTQ3lKc/zQ9rNVleKVj61Fr0rLiVD2XDbnS8aMpidu1cW0tjgKVyuUqaj8ovLfDn9rcxi8rE/gNgaPPUGkTKsCbMaf/bL81llrwsJ5XvgCYW7/Zoe7y+AJipW51pHpVx7LbhA/5/6EP7e5ShjYljqix19Rx9iX9Zr5JLOIxzT5KnxPIMuBSLRv2Ed+F5qTfgVN0T/y/gW0A7hxPaZL9Nsg0UPoNvINcEuMy+Yl+KfOR/ddCeWKr6rvy4KAfg81sJfgcoDQhXU4A+5cWNWZk3vvFhkjp95mQ+oFcoz1GG5+rLF7+46253u36fwffVtwwBgc/qL+WyYlQeIKP0xkiyEnurawMO6i9zDM8uDz/d61rzLOBhxsg6wZO91FM8XO3Qp8bPe8ZPO5OQz7u14n/zRpgZv9361n2Z9rmAa8h/rrMOb3azq67DWv5yr3K0iQxEbvV8e00Z33fsgGLbBE2bev4Yx8QHdZ0+B/7qH3LrcZB1Gq13YzbOQkA0atSo0elG//E/LruOXLsPaoDiDBE0CFeEJ8Ia4dLmlhg8yaiaU2AkTssY2BDhKRkalVnGriGglafRifOz1EJsiQuverzsZb2gtwshbkyYQwRSv+snwrnyCcAE42RWjHXfmJVY6a5JeK8BwChNBHN9qV0sYJJYwgm+soasXoZcaSkPTkT1dwR0cfmGlMFYAnkeKzbjWrsK15Y327j31PVNsiBlz1lGIoq8zMasWups4PrdOIkdpZ/jYr4tcLRLd6YkXNFWlkL13H3wg/v2O6XRpsTXQomdZT5R5tw7BrCaL55lTlHUM6ZDFlxI+xw8XHJJv/5iMbRmXdVrt8wMqk7GFsDHvRl59p3v3D/XuAU48MJHzFv3WneeW/ONWjnUL9oKTNG/iX+mH7VXn1CarYVdH0Q0OlraNNTD0jXu+xBg6bN5Yn4Bwh0o2Qvm9relFpWuK+OklWtQ/cxXYBpgAS9M4g9z33XcQlk7AhXEQ7QP2A+sJWAj0FK/JJNvqARDy1ht+EYsH1mlqQOwcAmoeMEF/Xp82tMOw6woC++Ktb/vQDv7pv4MaJI+wxMCtqmXfnWPfrM3+j1JM+wj+sEax1MArekbZeor1yc5ifv9Z88NmKgfXJuDmYRSCAgHEMRnk4Ha9b4n4UsAxdIiMRanaZP/YlFYWipm/4r1oWdmPgJeWbDi97F0Sjl5juvd63888KMf7cfvutfteW1kguwV8QTAJ4GjsVwNlWCuMgMc5gAUJbFL1gZeil/bm/F646nf7R+eJWSKPYGswXPGc/2f9ns3x/U1sp6SgCagonnAtd/ht7JKOSDhYsyvoXU4dACbF35ij7LuynU/dkCxDyvpsYOS0vPHGL7vfX0/RNbUz9a2RDXa1w7JjhfRu8Jfpsga52HTqFGjRqcb/Z//M88n/b+vRGMNUJwhHU/wpGAQSgla0F2KR6wAvPuduan3IUGoFp4Sx4gwmGDWcXOpT6MpPkstxOZceBOkXL0IpLt0dRsS5uJSEisLSoaytT9CKwWNkodiAVC64QK3AsYNAYCJYUTgD7ASZZmAH6sEQjCqhcXS0pAiQdhWnrIpV8qfAoWUJcC9mIV5Rkm1sikJyDaAzJBlJOVmiWVkLNIokXX8rzpG3q5iAu7KnWmJAiLByL3u1YMB+txa1SbriJIFGND2AN5jAGsAl/RLDYrUlr4+szj2DBZY+lBZa9ZVHRcx42MuesVdUBIFFpn6EfjLgjYx0qxv400Z9Yr72TnnXLW/h5RDc8fBhvYAKEq3Z2uBG+CurEkanTjaNNTD0jUevpswA2X4AXMMvwTYALGSyGFqf1tiUWmNJbHIEH9g1cUKyf5iPQXISVKJgA32HOCN2Haee7/7HYIMyQg/Fg5CMhtrM26VDjayhskRytMnz3veMvdn1uJAIwAI66+4mpbgXSwz7ZfAxhyK6PdYGgaYUwcAqb5Phuq4vRojbVE/PDEHgMl6nH0Z4aFldmXP8b86ebcPAzpjLRirxpB6xBIyByd121EtGKd8pOy4Rqd/lYl3JkFKrErxcfMqh0bJxBywNUBn4sjG2jvWf/ocT8cTjYXr7feADv1jnPVp6cYfb5OMeeabd/fr3yQHCbkXn1VeXNKNiXYpQ/xD8pDP9jbv6mnvUq62aZM+iAVh1oHf9UVC9BjjuCybo8pJBmoJy4bW4VgsY3uN9lg35YHm1AHF2gRzQ+ulPsiIpW19UJKxsP5zaK2u8WpRhv5Ul6OICd1oHQG/k2l9ihwoNyC4UaNGpyP9k3/SywHRGYcoctI+qAGKM5RsvpQJQksEN4JIlG3KkKzCiYc4dBpbCk/JahghzHtAMYKa5zhlszka+DWWXXPZcAEoCLCxa1e3IauXABRJGJJrCIiUR/V4+9sPhfnaDVd/c8O9290O3W9qAJBgS9mKsBELCAIy4VFZnv2EJ/Tgi/trQMtnFgaPfWyv/PjOgjR95DtXqIsu6i1M9E05FkuShlAUxqxn1gIym1hGooAIcVUqLeB2HSNv1+5MYwl50gbrUd/f/e5dd955XfeUp/RKmbZ5AV0pwtaWuacuYwBrsocqc4j51pa+UfKT7dXci8Xx0nWVtfuhD/X1MA8pQuoSpcn3zK1YXXkmZc16p/RqXxQr/7OscthR09icTTwwAPVd7tKf+id79j5j7jU6OlqaNX0uIcHQGjfnxMS1DoCKUebLww57Kl78gAfMJztaalFpb3O4go8P7W3mNH6pLsCDJJEIGO+7+5PdODH+XJs1O5fwRrv8bj930ABUS2xf61g/AeVve9sesJwj/XHHO/YAk0PMZPfF75IwBjDkd+ATN93Xva4/oMM/kqDFs+MpEItAsgdAL4dnOUhJiAeJRXy3JySDMmHUGLLiNM7a77/svdqpLvokByBD5J5Y0cXCrQQPA1yi8vcAZgFJUfluDJMoJZaA2mhcjL82mJOeHw+TgIuxJIxVZxK4xPWYLOIAz5h6+QxQxPPixl/HPvQfQDh1jJCfsajlsCTT4bbpef6zrpL8z3p1+KVt2ccjX7keJVmMe0pr92QrF18bKGrtAid5iZRWkGQgv4/R0BrQLu3+3u+9alzUsQOKbRPMDR1k2P/SN+VBScZC3xlb9QiYGODYGDuQ9Iy2hx0vcnBqTk+R8SevNGrUqNHpSDe4Qb+PwZTGyF7tYG0f1ADFFYqXTY2FAsErAgygggJfmtkPncZGeCLQspQg9BFwk72QUOMaisCtbrUufkt9Siv+3RiwFXe0WBjUtE2svzGrFwIm0IPgxzqSBRnhkOBO2NanY264FAsLgNBcWxVqh3sIy3FZc33uMzYJUK4fokyNAVr6R/0IxWX9I+ACLT3PvVzRhkDJMWWztFzZFSCzxjIywEANIiRGU+Ic7Sqr4T7cmWoFJOMSC6CUw13PGuBO+epX99eoj/Xm2VlbyUQ6BLB6URhRwNYpS19r2PzSn9ZB6hblMutK+Yk/mHYkFpZ+V2/9omxAhrlrDBMTkqIct8z0o7ltfZXr3TNtKkCBH/ux8T4em7PWY/ppKonUrmLuNTpaWpo1fWptDq1x8x6PjMup8ij5ZVgPZYcvjVkebWJRGffVMdAxmXzj2mpt+S2gUsJmJFvxmJXmWMIb9J73HB4o2ONLC7EkkCHMveENhzGT5w4KPe/+9+/ju8VlVV1Li3R9iwfc8pb9mOh/6zAgJv4e4M9n/Mpe6DPekrAZSYRiTsRFVLn+84qVEG+AhMkAeAW0C/AYK8IlFPflJUkX0o4hl578p7wksNHnabM5py9ZGSbxDEo/JP4yWUJ98Fqgq/vNa8ldElYkskTmNStR/+HNeG7i7brP/mDcAbNkCP1onNybA+py7elvpD729nrvtL6MGWDUujXnySzI3ONanzniv4BmCYei3q5XZ/tMeL6YiUvlznoNqP8b39jvvVPhAErZYm2COc+SQT3eQhIl2uPKw0prS7/qn2RzDmU+Wy/6xb3lOtIvbQ87niRUQXnIMETWpOsYdzRq1KjR6Ub/+l933c1v3u/FU8TLjReCPW+X1ADFFYoXYYeVGUWfcImAFJTvUnAZUkR8JjiyNCgVDb8B9wilhCRC2qMe1Qs627iUsoDwrBrYIty+9rW7cXVbavWi30oXSqfAlCP9GlfOpW64IQIhgI6QHkExIG3crVyjLf7PabQFNAZoDZ2YlwJurNDUcwyUHFM295UEYS0wsC2IsDQ24j7aW7sEZ1wo5eaKueCFWbLCYGXBumGsjkPzNQBr3OBQvU6GLH0TLytAdrJlxroldZZd1TqnwHtHSV4UF2YKTrKVa493ZbhOncpy9SPFCEifJEtrk+hMZQSeSyK166RDjY6O5qzt1iYRSvZ0a9J8xmvxFfMzSRDMIfO7jNG2JMbqEotK9QUmjO1tiZOX5B+JS2p9WVdJ7BWAqQRBhupY8q2sE1bsAB9lxrq53E+SdIyFGB6gX5aEgGBhDEzhVuvZcStPv6eucf+1ByZWZFyAQ4nJnHg7kUESQ9E9ZJwPfrDnP/Ge0Ac+J+mMcgPSGnPl+T+xHgPMzpG6lvEMSyot0ctxHPsPBXgo4zAmpmeANfUDgOKl6Z/0A0DQ+GlTrBeFQdFnPif2o/tjuYiXA/8cvPju/nItDfFXB6lDay8y2tje6XfAHXnKfIsFvvmm/g6b7PHKNAbmdEAze7y9H9hGzjRvNo1tXIdEYUnrmUtlizUJ5vSpMCb2fNag2m6cJd3JWk+CHO1h2WgdlmCjOWvMWAYnvnCZ/M+caHvY8SQg+dyBg/9d1wDFRo0anY50tav1MoQD66lrHDySPe56190+vwGKGyheTuAJkrGcKxXrsdNYn51SE4oISbWgSPCDLhOm3L8EZJlzKeUyLQZTbUUBeNjW1W2IxhKcELIpJsA+FillTEJC6CZuuIRzwiUF0qm/Z3uWMSFUu5dQSVikTCQeXuIMDQFa9Yl5qSCrmzoRzrUjWW+HrOyGYg8OgZWlu25iW20izK4BBrYFEeaAbBZ22ihxCCBhbB5tAkBFAeECb05kXLxjkHFvB1o84hF9UgMKxthamgNjY/WhrfV/5hiAL5a+cetM1szSfTDWn+aj+aMcClJcLs1HZVkT6u4e1iKUUnPb73hHFOSUW/aj+x/zmO2S/dT9tDSJ1LYHEY1OHE2ByXNU8zRzwlyJgp6YfEAz1wGOzB1uGfe9b//spTFWlxyc3Pve/SHT2N6W7OXWYCzh1Q3/YIlmzZrjZRIiPLEEfobqWK4TYJQ6+k251iZwLvEC9bM1pIwydMFcCAjtZ2msrUn2oj9rwIblIMu1uDonaVxAtwCQscrU1sTcU4YEJBRysWFjPZc9MxmJk9wjgGEsPZH+mbMkGqLUsyZ1HYunOAYolmXmYCggorH33X/mud8BqSgJZ/wHcDJ2SbqVeZ0M1T6nX3J4hH9OufHX/HVs7cUCcczSNm7beH5C4rjePLBPPOQhvXX+M5/Zt41s6HfzsZzXxm2XlnhrZYulCeZ8JrNmbLQ5/MTvtQxuvZmb5DT3ph7GxrgmDmnkL8+MrNn2sONJY1bJJZX8rlGjRo1OR/rf/3v6/4TAISs2QPEEUS38xeViyGVl6DTWZyfH4gUmAHncenNqzvrRZFgCsixNUCErYK0c7tJKbUqoLBNVcK/xXwS/1BEoqF9dt8YN1wk9q4H0YzJWJm4TwdH9UUgI05S9BEAfArTqE/NSQUaJQRSFeY2VXQ1Wlu66sSLRBu1K/KI1Sv4aYGAbEGEKyBb7D8Cqj8Kw9LF5DSyfs+Kdoygg5gQLBWCAcszlZGKNC5i+pVA97nHTIOmcEoSmrEgynsnQmayZZYZkCiIw0bw2r1gZqa9+Qq639gAtLE7wFuVmHQA0knRAeWVm0LIflyTRWZpxeyhjO8tEgFCsR+LSjbY5iGh0YmnT5Es1T0vMuri7mqt4Q1wPA7D9+I9fFYgLHwFasTKxH3DzZZmX+bkEsHDt2N5mbtqHPBd/cuChvtZZQIqEySjX/9yhXR3KQj1YB8ad2PpWL+sO5UARv1oTAiLt//mf7w9VkqyDhwSw0b2veMUh2GIc9A+wtMyInPITizB7qLpY3y98YV+3xH5MQjUveyAe597sre5VTuIGrgUUhywTh64pM0Brt3d8taQAqV7KTNbjWBVqg7YF+ExsSeWbByw0yWABjmP5nrh7Kdvek/1M+/WL+eAgaKkb/9jam3Lv92z7qnlrD1LnHEqqhzXh/9vcpt/7slZ4hGxycLiW1soWcwnm7C/4Ad4Rt3F7p/L8Zw1nH8qelNiLDvuUQe4u4wBbu+RQ+2qZMMk84Ire9rDjR9btLq9r1KhRo1ORvnZGp44ctY+DswYorqBS+Ivr8xpLL0INqydCDMUpbr1lDJelIMs2LqW7slLbJmFI6kio465J4VsKcBL84gJByEyWScJEYgZF8C+zjpbZB4cArfrE3P9JukMpzIl5ylhjZVeClYTZBOw35t4JxsqVSEQcLqfrpWKzxC1uDTCwKYgwBmRTaPwGDDMuFCF1N77mIEWe4qvtay1haxCMVSvglTLoeZ6tv5RtTGJpQrFYEqdxTgkai5dWW/qOZUgGpqorVy2KZ2nFhWLhEuCdUq/fKIyl5aP3EtRe249rMm5PZWxX1yQ6ShKpbQ8iGp18VB/AlG7/AVnM1SS3StKiWI0PxV9McgkgGBDEWvfK/Jxbq0sOCACEnsGKK9ZqAAhA053v3O/TWU/nnz99aPea1/Rrs1wnypUYBqioncqOFZ9y9U/WMFp7ODVmmceq8LLLDi3dExcyVom5PqCbtnslXqB22Iv0jTEDyKgjHpa9KslMUlZAtzIL/VqaszzSb3GtTl2TgKW2SIr7dAmg5uA2ngvap4+1yVgBvPExMkSsEzNn8GPW9q5VJl5eu0MnriU5Z4oHLj3MmXLvN5fwfPMl6yoHT+mrzKOptbK0LpvQWtliSl7U3uyXiYedZEmRM/wvdqL1aFyMsT5RjkMw42Uc3WOvEwro0kv7eUJuQPhNLKjtvfsCXBttRub0Lq9r1KhRo1ORvuM7dnvdGmqA4hYUQYjQkphqBJepLK4AB9YFcctIDBe0JinGWIa8uHEEpIo15Fjd9ylUahfhXIDyGvSs3TXXAJzqzMVVHwI1KBhJyJITymSk1B+UgIBZ6aMxIEafUGB/+Zd7wTKKRBkAfxMru4CV6s7tPVmJ1UNd1ZsQTTh+5zt7gfhGN+rrs01m5F3TWKblhAIgoBPu9QmQyRgQ6IED5jsgPjGSlgBQY5kcKYI+68e4MKU+iRuljkuV9CklaOy/sQzJLCy4DrJWMe/8zlrSeywiyqQFpXs0wCWu1CkXOEEJBlDoX9+BNWssitdm3F6SsZ2yp17J2N6UsNOL6gMY/Nj8NC/N7/IApua5NR8pY9Vm3zAHgQz2g3J+zgEWU0lT/HbWWf2BlD3EmsNHJNmq57B9fcmhHXBGfcoQFuQA+5E1Yr1bs3hgYuvZE0tacjhVrmHPyxpmzckqzbMSrzJJSUrwrxw3dUsyFJQ4gsYs/AjAou7qqtwyhAPC24E0Jcg4Bw4O0dw9sbZM7EvP1M9lLMUSNC3j36YP8NN4BmgjXiY5nn3EHM1hSR1q5e53718XXtgnXDFPYhWXWM/G1P2yI4/xwDWHOWPu/Z5Ddsx8G6J6Ho2Fslhal6OisQRzsXo25vo9MRW5fAP/Eps1slodexGV1r9eDqHNAc/Up8q2xv1nfqxNFtdo/0S23OV1jRo1anQq0j/6R4cH5WMU2W3nz959kacXzcVXGhMUxUaLoLgWHJjKkBdBN/EEJYGgIAwJiptaqS2lJZk5A8ipx1KA0//aqn1OlikaAQ8TuJlSwMKLIpHslAlGP9bXpaAdF1rKFGWGO2p57VLrsNoSgGsaxVldzIPSui7xnJKpUvmUa4qN+lNw1a8WdvdpbVDTENAUqzUMSj0SGzBu3MbAPRQAv0suoB/mlJcxEAxgCQyIBY42l+BmLKMoDsmMug8asobS5vABrs2sWwCEflf3OnkLKt2YY+lSJllRHsVXm5RrPqyxKN4k4/ZUxvZk6TVXhVRY4+LX6NSieg0krhx+LHQDcB1/qHluyUfqWLWxLqPs42Xm7Volv97bahAlGZfjDjnEM8cO7UKxho47c+IbBgCJS7P2A0O8kmGalRQZIIdUc4dTU2vYGAilgqckzqm6qYffvAe0i3Wa7+qSvSYZmvVLmQVb+5NkR5n4WFyaA/IlVuHQoeEuKBmYU3d9lfqVgGkEZHulz+ZPku9kDMPL9D8AFu+zX9SHhfrM+HiWQ7Cf+ql+L0o8XVaN9jNj7j4ZExOqZNvDnKF1pQzW+Nqrv91rD6zrrc1JLjIkC9R1iWWqBDz6Aig61o590xCQGldkbY2XiesCAPvd//pEW8rYi5mPpfUvsn9ybY6MUiZm8bllej5+RMZ485uXXdeoUaNGpyt9xVf0MhDZbeiwNv/vQ15bDSh++MMf7p7znOd0n/rUp7rPfe5z3S/8wi90/ym+RCP0wQ9+sHvEIx7R/e7v/m73Hd/xHd3jH//47j73uc+Vrnnxi198UO7nP//57trXvnb3whe+sPtBKU+PMe1CUNzU3bh2i1GHMhsxwZMCJ87gE5941XhUR0FLMnOWgNxSgJNgzVorwiLBkiCtzQRQljLG46Uv7QXGJX09NpZJkqNvtWFNvMkhSwAKNuWMMitmUGld55okaPHi1kvxSfD7gIqWhUyFJ8LaYAhoClgWy9gotNqU9hDYKWbawOKD1egUTSnQyeSYWIOUAPUq45HqA3VZE6dxE2C2tIYyXm99a69ou7cGQI0PC78yeQsKAKptxtP8tFa9yvqY65tk5dwkPMLU2k2dCe8NTGw0FF/4E5/orfa9hnhuyUesuzoMQED2JC/ZRskf4+2lO+TQHF5yIOYwyHoHyMTVMkAbwAr/Y60c9037Ht4P9ElyI/zcAdnU4ZS6iq+q7u4p+8paDDDo8EZZ6o3/qU/4c9yB1c+1OcVWpvrGii+Zj/GpJKBzf2Iz5voklMr+tIl1YkmxMhwicySxGgNae26yT+f+gLza4t343P72h4eJgKoceGlrALW5JFNjchsr9Cm5bZPDnHpdcWV/2cv6/81V+4x9oK63Ax7eD8b3la/sQeJSFqjr4l1ZiePscNzcSTKz45IAUT+rn3WS8fHuu/YaW+vY/BjyJKmtNs1j80N/xio1a2qTZHHHkV7ykpccvP4bxtEZz+/pnvCEJ3S3vvWtR++55JJLuvPOO+/gnmtd61rds571rO42gnFeQf/wD//QPfGJT+xe/vKXd1/4whe6G9zgBgfPcO2+6ZxzetDeOI+Rteq6Ro0aNTpd6ZrX7PfCMWttso//XXfCAcW//uu/PgD8zj777O7HmBnN0Gc/+9nutre9bffABz6we8Mb3tBddtll3U/+5E92//Jf/svuVre61cE1b3nLWw4Ax4suuqj7oR/6oe7CCy88+O8zn/lM9y+gL8eQdiEobmNVVp7mSvpAuIziQ8HIaT7hyIksS62llmG7oiWZOdfGXdMm4F7iOVF2ojQROgmGFFGZKimfyp7r66mxZIlAOUaEbQqye/WhrKJTLk5DSiwhGcBESCb4l9Z1BONYWHqW+lJ4kkmYgqgdz31uD5qitYD2tjQENBmLZADN98TuorRGOJcUJ9mNtwXBErNN/7k21pBlMPc1IQS2AWYTG+2Nb+yVXMrYEAAaixjrgGUtCxikDcZTHeo1UQMomwAqm2QY38faPa70zGc+s3v729/e/cEf/EF3jWtco7v+9a9/oEz9u6R4PQkVsKOgMQDewUENhtc8t+Qj3BbLMACllTElH5/fVMnfZp8eA9XVz1q2Xlk3hu+VgFjANuQwQVscArE6ZqmYDNP++8hHegv4sfXkOS95SW/tbA3qJ+svwEkyvuM91ifeEvDPf4AlazwxgfWJfSWCZcC6JFjyOVblrsG/1JmLcBm7MK7FASc3ye5c0pIsrtqv37QpCezsi3G7jvWl7/qc0JzwKPrRPAjwam7hgdpt/5pLMrWJ3LZNrOuQOaNNPC6y9yVuo/qbw8pnEe86oVLUq5YF9FnqUh5AJ/mO+eH/Zzyj6x7/+BPn/rw0AaLvLIy93vKW4VjdQ+Cwz0MWxcbe/adCpudv//Zv784///yDvcY+9JrXvKa7wx3u0P2X//JfDsDFmj72sY91d7/73Q/2wtvd7nbdG9/4xgNDkU9/+tPd9wr83klo8+zuZ3/2Zw/K+q7v+q6DvY+e9nu/93vdV+u0PZLib3vbfpyHyPg97GH9dY0aNWp0utLXXpGgE0UuDZWJao9FUhYnXFOnXDUBCW0+z3ve8w6+f/d3f3f3a7/2a93zn//8LwOKF1xwQXfOOed0973vfb98z7ve9a7u4osv7h7zmMd0x5G2FRR34W6c09yLL+5j68RFibJCQKaUERZtsgQzAich6ijj8K21yJyzEvOfk3Sx6QCphErtpQShWC44tc99c329BLySZIMSlthNAFzZPYcAS2M/psSKwZTnqXPp+lrGPYiLF8UninaC0bPOlOlTuZsoytvQENBEIE+8Lf8b3yFz6lgbLGFkS9wNlfWIR/R9wTrD+LH+oSSpWw166buheKfm07bA7JI5ZNy4LlOQKD9RoHNmsq8MnFMZxmPh43/1AgYdVfKm40If+tCHugc96EHdD/zAD3Rf+tKXunPPPbc788wzDxSlfzIyAY+7ArZvqsNDWP/mPmuwWMJP8dySj4iHlkRKKCEecmiySUb42rIPH60t++b26SFep63iFdpHk9zEOjLk9tzE1UuyNYdd+AjwzzpPDNLyOi+HfUPrKQdT+shUjLBYWqfZP/RdsjnHaj8W4+QA/akOxsh+ojx7Wiy6hfaw/+ANrOjxxsSpwy991j4Wf3iG5yk7IGIOwvZFCWcifITP+H0sIxPHMfUwV9Qf/8fv7Ak8NcSaTDIa7UbJ9q0PfDau/hs7MMnhUfZ771Og4pJ9bAosH9pXyli2DqXsK3g3wPDGNz7cT2pZwFmHumgry8QyxACyRozrruMIrrH8r6+Ffc0lQIz8VcZenPKEMYfFyI6rcyyKzXX84kd/9OTP9Hx7jLigpz/96QeHWZ/4xCcGAcUXvOAF3VlnndU96lGPOvj+1Kc+tXvve9/bvehFLzrQx4CSDD14lwEm0Wtf+9rum7/5m7tf/MVf7O52t7vttT3iiuPjGauSzCVxzyU0bNSoUaPTmf7n/zwMaRNPkpL87jfX7dpKce8xFD/+8Y93t4h/5hVEqXqY46QD4OTvDtynHyt4yxV0tatd7eAe9w7R3/7t3x68Qn8V6fAIaRtBcZcx7ygh97znYVB8QiWFR5eU8agoZZvGo9qWlp7sL7ESS78rjwBcK2eUKYIixWNXY0mJBF66huJYAk5ckiksZUZmz6aEyepbg0vaTLhl9Zh4e+638I1ZkhFQkJJBs4wjRUlQBqsW9aAEb2r5sCnVQBNlBpOiPGtPQNKABD5TYgj2XMSWCOtL429yJzRHUheWuEOgl77gAv+hD/VjFcWCAjYHzCo78Q3H5u4SfqAMa5US4/pcO1XuplTyGM+Jq1yZYVw9zK9k5mYFgoeUwMa+kzcdB7pUys+CXv3qVx9YxtuXbmyCDNBxV8D2SaX1deKWsQJjwfYrv9IDFw94wLQbqPlkzlEE8ULKPNAqhLfHtRNvYXG+VslXz4suGrfsWwLolLyORRdgSr3xV0BHrM6tByCP38q4bNqVGL9lDNLSOtj6G9qvSutKB1GuT6gErxwMSGQR13EgpjJjtW9P0a/GCVDot2S0FnZCohG8ABipz0sLb/uNkAaxjNce9YyLOtJvOfWeCwS+LcW12X6sXWUilsRQRj6z5lNX/BsBVI2JPtB+bSut6fWfMoFzZ545fmASGcW7fSTx/ETwGXITHtvHYiEOzDSfxvaNsX0l88j9ZBBz+4wzDhP8DckCLBfVxRyqQwyUYQZ2KTussfyfu3ZqH1pqTZ85lHlTWhRrf8KmJDbqqUB///d/f2BNz7vsepjFANG1eInVepq9Kp5mwlGVutzXf/3XH3iUuXdqP9tWX7M+WM0ay8Rqzbgllqqxj6Vpo0aNGp2u9GdX5JcY8xhJ3GvX7Zr2zn5tQpSokny3qfw//8//0/3FX/zFwYY3dA0XtCFiFfLkJz+5O5G0JuFISbuOeWeDJWARfiLMEzKXxqM6qoQecxYrS+NRlv1OUATwaS/iCqXNBP011ixTY0lwAdBaoJ6f/70T6mER6krOopApgyLM+iNx8WrSxyws1B+441TcvYBFL4orihFTLEIoDZaJZ0SRWwJo72OMSwHfXBbjSRsAqUA9Sltc5yivCey/1E12TfzNObd2cwu70NeUTX2MKNHWoutucpNhYFbdL7mkPx3PGhpar0v5gXW572DvQzwGeKqdyTAeEDvul4njNnTYsO/kTceN/pKmfwA4f+PoNftQwI7DQdkclSBXCU4DsPAz4Nhll/Xz7qEPXQYaALsBi696Vb9OzM3wUvwk8VdrvjHF10rLPmDakGXfkmQoSBt4qTvzBGb5rr2JiwikUgeWztwvSz4SV+4SaPO/+5G64DFDzy+t08pEFLHK10dOmWWsVoZ+sp6VFbds45HEVaazvcz+6DM3a+36wAd6GcFpdWLPAmb0j+9i6rlHOdqvP93vuhwgJbvyVBzEXZD5kP70vNI60bNjza+d9koHJA6R9I39R5+4Pn2U2Huusx+Yi84IhoCJzCmgo/sC9gH08NXzzuu6291ufh8LEOxdv+rnN71pOBzN1L6S9mpb4kZOyQLKUhfxPo1Z+qoOM+C1i2Rma2KML712bB9aak1vTelz4Gpcnr0Sm8891oO1fvbZJ7cV/m//9m8fAIh/8zd/0/3Tf/pPD+Ld/3uTcIWe5vf8n9/GrhmjbfW1j32sX2PZGks3vgDBZG7XjZz/NWrUqNFpQd/wDfPZ7slurts1nZTnOawZS2WO4iXZy1HS2oQjmyZxmaLytBwoZdMN4JST6ql4VEed0GMXca7S75SEACI5mQQorrVm8WwvCp5+YAlSKq4UEGNpvKIEpl8pkK5VD8qB35KJkEUjYJCA4zdjEMsVRLl50pN65YT7jfGPhYexotwoz8KP6zOFPZYulIPMnykAi0Kp/H2McYAmfc3l3jxm3UEp0zexIlEXzySkL33m2hh+Y6CXsZUBlWWRvtfvmV/6QvnmEOChtvY0pu7zDtAQA3JsvW7CD9bQUlB4jMeob1xTrZEABGUQ+5bhUj9ffmA9L95hXJePSgE7DgdlcxSQy3q039RukwGaXFeD02Nzkyuq+QlINAetR/zP/MRLzFcAEcvHsqyxvcszl1j22S+WrkvX4aWmRMlv8XZlaq9yAX7ZJ7L3Au38Xsd3m+MLtXVa6eqaRBr6Ghim/dasviQL+D0uwcbEc1kj2itZJrofOAcABYIBxOxFCVkhNIM64Z3a5Xdjg3/EnTqxFEsAcZ9gYsrX7sToLU/h1THxE8k46qi9eB3rQf1hnPDPJGlJ3EnjpJ+Subnmf5FR9JH5GQtvY60M9zz1qX2/lZaK9T4GjDWXA9bZj+wtxm0oHM2SfcX1ZQztqcMsdVEP+7PfyBXbJjPbVqZDm8Y5LWmJNX3p4WKMxbNmweyZ+IF55bAXQIVXHWV4oF2TGMC/+Zu/eXBA9ra3va27973vfRDeYwxUPK76WvaZUL0GkP9d1wDFRo0anc70+c9f9QA7Mb3DL/0/cw50PAHFb/mWb+n+F0m8IN+/7uu+7iAA/ld+5VcevIauce8QfdVXfdXBa1e0iQXXHOBBOOF2A1iai6u3Scy7WjljbeCELgkqCIdepaAYcCdAk9hzR5nQY9t4lBQlfaPPCPYAEgK5/iVQTFmzDFGplBIilaku4jOqi/5wDSFTmWXdKCvGOTGHeOfHGi+npoR2gKS6JFYWQNB8u+Ute4GWclcmMDAOr399H3xa2RQW92W6q6cynLCrD0VkTNHQb9xYKUDak4yWLBTMNwDfLrI5lmtBf3kuw6woZxRhGfrWPmsXMfz0K4UhCXzKfvI5Vj3qWYMBnmlMKJpe+n1sva7lB2usRJcC/3NKnDlqLrHG1B9xy8x1p0qGy21ILMXf+Z3fOYjzezoelM1RFHKAzJDbJGsv15jvtSX82NwEiHGXtmYAXOXhSw5jyrLmDuZYO05Z9ll/LPtYHTskWGI1PeZ6qh3KB4DizXhJrCvD++51rz77u/VXxnmdSm6kv9TZHqeuASNLl2nP8hyZTfWH63z3fHxM/wBj1dvz8DT4dvZQ/yvHHopf61/v+CU+JUawdgPt1CMWQtnf4j56VGBi+ZwcjNSAZgDGuOHHCs9pPJ5r7rBGK7NUJ94Q/q7dwKQaUNQ3ubcG0fFjc9jzXvOarjv//CuPZ/Yx8lZkLvWJBah3dahBtsgErMd9HjtYkxzOWI2BjtYEOSMxRH/mZ/q5Sj4xpuXB0tpkZruIMY42jUc+JLuXnjf1fltafPpsv9NHYoh6lrVChjNm1tNRhwfaJV396lfvrnlFkKzv+77v637jN37jIFTHS8V+WainRQfLu98k1Cyvuc51rjNZj231tYwRSginmvzvukaNGjU6nSlhXkJlWI+p604KQJHJ/bvf/e4r/SbWVGJ52PRsdrI/C2ofKxHfH/zgB++7eltZ6Y0BHgQgg/fa1y6Lq7c25t2QckZBADKZJARLFleEqNICKUCTuHPiVh11Qo8xWhJ/Tt9ceGFvbUD5TBwogmGEYvX1XluzDFGtlFIsjRFliuKXxBlkJc/xKonykBgElBEKtHoQ0lGybypfvwPzlB8rMWCba82h2rruznfux0A7KQHALPdRWt1LwaA0I+M5BmB5LqXTmKoHRSmWLZ6t/tzZdgEqjq0FMRO3SeCxbQw/91ACS3e4kijfZN3MwVAAiCjxZWyqsfU61geUTaDIC17Qr13j6dolPCbzVF2SYMkcYBFaA/9zSpzfWSmZS0M41TbJL04Fst+8853v7D784Q8fZMmcon0oYLs+KNsHRSHHf8vMzKGE1zBXgRYBp6fmpns02xrxKkH9WMKZ6wBA6yegzNjexSLbHB+y7EuWeaAQfkzEWMKbplxPlc9y0b4TN+0cfDiIYjmjH/B860+9ADw//MPDvDEyibYoS7vxGPt2LKz1L/5i32JdqFxhNvSZ+sUqsUxigA9mWgf4DUiIDxqvF72oHwP81X7jfn1lrAFu9sG4G9cUC8F9Aos5vMnzy1P3sk7qTA7Sz8A742JemltkCG3I3NEX+kXb7OuS18lpUVu2Jat0DaIj83fMwlu9lO2gUuxj+y3gbixB0Pvf34cSqENW2Efs50MHa+o6dJjlu7VqDjz96YfyrXnv0NJ6cD0WNZbMbBMK4K3d2l/3WX14tUk88jHZXSxJa27MejkWn0DE8lCk9OYxT7T/VLLYp1eVITVKoo/RuRLbvtbTJBWzp7km+5cDr1//9V/vfuqnfmqv9S7zl03xlpM8z1mjRo0abU0xnJnilWXYnRMKKH7xi1/s/pD0egWJFcWsXryp7/zO7zywsviTP/mTgwD06IEPfOBBoPpHP/rR3dlnn929//3v79761rceZHEOscpgjv/93//93Q/+4A8eBLMXQDhZn/dFu3BBrgEPOmZpFZYy5+LqrbEOGlPOKDZM/gmflBCgEoUmGS5zog2QMjybZqjeNc3Fn1MP1oMEXq/o8WQjL4K1MRiyZhmiMWsZ7koUNH3HTU0MMODVs5995dN/C1X5lBJKlvoTnAnnvrtGPSkqCRhPwaWsUHC48fk+BtqaU0984mESkZgmG1fu3Pe//+G8HLPgYw2XMdZO7tdx06Ikus49gl0//vG7sUbdVwKPbWL4qYP5H1e5Gq/xW/5Xb+NoLcbtkgIf694l67XuA4qhxBCU9SidFDzf53hM6WannuJale79yi/n0BwwD+Pyn+eudb88lUkClYc85CEHMaY++MEPHihPc3ScFbAx2kUs1bhgMuDE18o1VSrkiTcacHpqbmZdhJ+juCWbk9aiex/3uMPEYkCDsb0ryV3K/SQHavguYE27rUOWXT7P8b8511PlOggSGjPWT94BdOrrINFeDFS0/vAc2WSHwMQyTp8xUzb5gXsm62JAiH7R/8rDY+wRrlMXfQX8igVf3F1dE0AswG/GLjKF3/Ba/wfMRbGsLw9d6r4/KkrYjyRWGSL9gF8aB9dLFqTP9ak55rP+8Vl/AB3NOaCd+8RGjjWr/81b80T7hwTxgOKJaT0Eeul/B3muHQIlc3AqHrH61yEr8HzWroDwev0OHWYlAY/6mn+1fHv3ux8Cb2PJzDYhbeBl4V259tQ6GVJ9eLU2HvmY7E5eesMbej4AuB2S6UtvCmtGuca19uY5mS326WG3vvWtD3Sy//N//k/3xje+8WBv+9Vf/dWD/+91r3t13/Zt33YQZgM99KEP7W5yk5t0z3ve87rb3va23Zvf/Obuk5/8ZPcyk/FgfX/FwV73tKc9rbvWta51sL+dd9553bd+67d+2RBkXzRztncVvtCoUaNGpyvd5jZd9+hHL7vuhAOKNpmbMTu6guKiBRCUHfNzn/tc98fxY7hCsQIePvzhDz8wt2f58YpXvOIggH3orne9a/dnf/Zn3ROe8ISD+FIUMJk36/hTu6Q1MV6WuD/HzYJ1RKzCyjIJaITJBAuvhck11kFTyplyPUt56k6x4LpRCotAiU0zVO+DppQ1fcoai4CtTUCexBSkLKkjoRgGsFQInLKWSYIPYxhX5dqVlRKdGF/qR1gmvCf2UCxrfOZxQmgFgno3Huqr/qxEx4BPY8h6kJs3KxUEiHRt7U41BOIlKzUBmTJau2l5fty1d2mNugT8O6pEQEjZLEP0IeWqjKGYbKVxIQf2us78sUaS9CdK0NL1mj4wBuRxSr95A2DO3IliPtX3+ggQ7H71CRisDMqp+VfOoTlg3hzQRmO/JC7l6eTmTOF6xzve0X3t137tl2McSqIiLMfJpoAN0a7i5ca135zzsn7KLPX4jflsDZXg9NTcNK/9Zg5aI3iSeW+dAIAAMEmqAizEW7MH1GvTfLaegZp4dpkIIwlk/B9euvTwcElMV/9bX+EtXF9r+cKe497IF7GyL8OiABPdZ7+IJZv9w5703vf2buGsGx1KsGLHs7QLb4g7sPHI4QMA0nPcb4w8q4yrrK762/WAp1j6xOLQe8Bj17qupn1bJpbPQUnGMmQpWV5rrw2Aqp+1Q/21X5+Yr+Ze4kT6L9m8lR9rUoew5prylFVbTSkPKOnQL3tCDXqph/kT+SSJgULmunFWDweCQzKp8eayPMSjS1nAGgHqmROAtaGyyKIUD/N3V3txaVFvfpF39HOZDMmcrg+vIv9pQxnyIHyhvHZMdld/c9Rz8CTf471TyvT6z3q/+OLestc6UsfSm+dkt9j/0z/904M9iz5mHzvjjDMOwMRbirVzIFv8cXe1YqCvf/3rH+yBj3/847tzzz33YM+SYKyMI8wohKHH/e9//+4LX/hCd8Mb3vBAT/vqPZsG4kn2hcSEHSOW2qdSdu5GjRo1WktLYyO6btfhdFcDije96U0PLDrGCKg4dM9/IS3MuJsdhYvzJjFellpHTZXplFiZhKNkhtzUOmhJRlnACQu7WC6VwiKQapMM1fuiKWUtJ/qURwpWMnMSHAjL6kgQB5qJ/7Sk7ktcrEtQsj79J/RT4Ag63uNORQHxThg2/uqRhC1R7vQ34YhyZ0EPxWsq+4UyEyV1qv/qMjJHCPJDsc5ioXLU1qhHnQhI38ieSXkCKADXrT3PNsb6wdo0Hvo5FiDmwBvf2I9PYm0tWa8BSyk1L37xIZgYmZuSlMQQ5q35Ptb3ygAumDslEJoyzEP/X5GUeFEAf0AEyyiWWZvGpTzV6CUvecmX96mSXvWqV3X3uc99TjoFrKZdJwNzrb1FM0QzYTmH31DizUFzuwanp+YmSpZ7cxRfDJAY12VrCPhj/SKgg/nrOWVZ2gUcMMe5RltfrM68Wydxx1aHAJlrkj4sjek6J19oC08GITZizYnv2O+0PXuda613fcBCzZoHfNzlLn1Sr8Tx1Rbti5WOfUf/eU9mY9doH54B+GKFrx89M5Z3sViM1ag90H4VENFvyphT7vdFAUz1lzrV4GbpEu2VBC7mH+BIX4SUYxyQeRBAL5ms9YfP5jdwO6FPYuGtL5LQxO/msHnlWUOgV2L1mcPkhnL++i8Hh+bhpjJpZAEynraoy1RZQwloNqWyzUBM8xk4W4LYYj6bv+Z2+IP7ALYAoTe/uf8tdTafsdSSl4ytrbhZ2ysTHzTWpHX/WatXnA0d7PFl5vZTwWL/la985eT/rBVruvOd73zwGiOHZE95ylMOXkdJAernFGVgO952RdjIRo0aNTrt6Nd+bf5w1/+uk7+hO92zPO+C1oJK25ZJUOHyZFMk1JTuGGutg5ZmlK2t2dbef5SC1JiyRumJZSKFiHJD2Cf8EzaT6IQSS1kgrKfuY5ZwSwDZGpQsT//VjyES92gKhe+eS3nRl5QL5VI4KDFxC0zMsSQbGIvXtA2VgBaBngAfpSrJFPQX4Z5yQ7jnlnQU1qi7BjaWUu1CHosM/UD4ZDURS07zTj2Ai+JU+r7Umq8ESyk2ykuflxSrCWOQuFxD5HfPq5PJpAzzzDjn/qWZsfWHV5kICLmOIrpPi9HjSFMHZCejArYvS/whC2oZgn/plw5dcHXlEMA2Nzett9vetl+f+IFy8Hh8Mq76KK7+OaipEyll7yIoARK1XQgLiqY1jueVVkhrDw+XhnWYkgXU2wGHMQGWeGbCogD37HE1UBqeAYiy17CswpvwEM+wr3jZjzIOXsBGPMazAC3q7jf7m9/LPdb37FWepw75DQ/zW7IHekaZSfAoKUBibZ1YgkHlf8ZB35hjAEJ95xr9wRLQnDIe5Af/u9Y8iWUmq1jgnN+NDYrbur4CePis/OwJ+GgNeiWBT7JkG0f7hHLNW3NJvZW1rUy6D/l2jmqgr85KntjREgiKZmQtZc8EPLLoD4CtLzIPl7bNvDYv3EterMMF1m0mE5199mFCI+PWLPaPH9kDyLJzgKJxFaO0AYqNGjU6XekLX9jtdWvotAUUNwGVti0TAECBIMBTcFxHgPn+719nobUUOBgThLa9f180pKwRsFnDEEQDrJQuxgT+uGMRTlkNqjvFbMwSrgzMvQZQzem/37lh534uaBYn91MKAoGYEuy5BFUKQqwsla9tFEH9rl1DQdw3cQmurf/i0hywNYoYwV5dhHaLm/a+rVH3BWysBUCsu6c9rY9nKskBZTB1KethjVqvZ53Vn+QQZqcskmqw1HXKMobWmTEsFSBzhLIegHuI/O6exHmq52mUqhr4XmJFlbms3qxCjspitNHR0j4s8UPmEKvwMkv9FL9aMjfV07qx9gBs+GgZG8u6Sfw766fOqlzuXdlP3vOefu37nGQl24ArS8I6jMkCZfZ4vAeYlezx6pvELlfk9BmN04digRfeADB1DZ5e1jVAGMBL/zPELd1clePAxd4AiIllpP1W/QIGxQVau9RD30+5HO+T7G31OcCY23XctNVbH5ljeLI9OCCpfViZPlsT2mocEv7CGOkL/Q2o1nf6x9wxp+wdJX8dA70Cspnj9iKHecCSMu7xLmTSKVlUH5FL7CuAzV25iQ61OVnJEzdYf4qYZC2W7tHmmHWcxDPmq1Al2aNK2WCsbeYkkND8L+ODzh0UL7U6bnRiyH5iDs2ReYyvNWrUqNHpSv/7fy+7bkjG3JZOW0CxtNJbErdlbZljQBWhvswYizYRyrcVhLa5f58x8GplzbP0aRm7iMBK8CSEWjyER30NIEsenzlLuF0DsvqBwAt8Mo88N1kT9VOsRwBZ3n1PIPixIO5rAJ4x6z/lUxw8gzKlr/xHYKfM6D8K5r6tUceAjTLeJJcVlh1zLt6bUmJimlOUt1rRCsACGH7sY3urFGOAJ2C+gONrX/uq8z1gaYL6629KKAUpseWMi/5P25OAwpiO9T0+oS+43Ck77vJxszOHxA6t+clSK6oTZTHa6OjoKCyVpgC2eq8wLx/zmPG5aS4Dbsxt6yVgTsjcV2dWKDmUK7MqD1lG4p/WrzKHLJ72EeJjTBZI9nhUZ48HULGMwydjnTkWp0/7XSuMQ1x0UR1X0HfXA3E8F48FANd7rD4D+JgrJa/xPPxBP+ojPA0P9czEfzxRVGZ7nrtOnUNxDw8opd3J+m2u+V9/a3eSdmlv4i/yLvEf3vzjP95fX/PXWNgB7vRjvBJiuWcf0bcSrJkn2QOM5y48R8bmn7HF98khxpjVPlfjXRwgjQF9+ipeHPr55S/vXf397pVEOHG5N6/VE1+yv9WHHmNtC+/AD5Kkb0n/7SuZXKPdkHEg21922fR1Oexo1KhRo9ORvvSl3itxjsjCu46feFoDigGFAFVvf/uV3XeG4rasKXMMqEpWxsStKTNAx9VybSyrbQShTe4/ETHwhDEj9Oo3wiehU19SaNRXvYE9Mha7figY/lhg7l0Dsne4Qy/YAOoIz0keE1BP3Sl4hGfWIE7uAVfc4TcFeKaClAeARd4J2bGYVGf9KN7YvoXnIWAjmVzVO5Y1L3iBzPD7A7LmABbjJCC/dzwgYwDopORL5lD3lf8+8IFeMY27ZoC/uCabD8bcmAAS9b25fO97j/e9uc2aRX0ptiw31J9ynEy6YiIOKZhzVlQn2mK00clrib+UxvYKPLJef3WoBmAhcIBlcCzmAqoBB32vsyqP7V3bhPiYOjyb+m9MFrCG8YKh7PE+81ZwgFACUTlAABri3Q683vKWnh+h7DVJxpK+Spn61F4zZo1a1hUp1/P0vf0prqex4Eucwtw75Hq87wQtyk8W61J2K92ey7rEVbm0bhRqRMJ1AJQQJvgzoEsf+l+fxiI01pmJd2l/1j/20yE+a07a13lKxCU9mY694/8Otc4888pzdleeI0Pzz572sY/184UMcv3r93NqVwdIQ+ssCZa0wTjxIBEqRj24nl/vev38TjiYjBlelTiI5nx56DElZyvDmBinhANY0n9LrI4bnTiS3Z6V+RRfSUiBRo0aNTod6ROfWGalTaZugOKeaReC8BjQ5IQN4OAkNvH9CDFzCvycNeC2gtCa+/dp0TTVThYB553XdUKREeITML6MXcQykRA5FLsoNBSYex+ALIpy/LrX9YkLCO7qW7riJN4VgZuV4Bgo6MRenV/1qt5dl7KZ2Hn+9+7/sSDl7qccUdATK0s9CPaE7DFwbZ/ARhQN9aIApE+sD3NsX9Zxc65gXA4pN56d/6fWqH4HZIuFWcYXixKuTP3rP4q651JogYnmtLk9RqXipL+sU+OWLKVlYPvj5Arb6PjQHJhmbuGfeMUu42eO7RViJFpDAHFrxFoEbiB8KaEaksXcy77pOoAIYAhoYO6XWZWzh2jDEC+2zqxfcdrK+kwBDVOHZ2juYG1IFrB21d0BUpnhN5ba+KFy1G1or/OeQ0lWivhA+GgoY6w9QDJ8x4GceJfqOmSNWtY1617ZwF2HGkA3B5/4mLo6JEnysVCSacQKHDC3b9Lv2lSDislOba7o88yJ8jBHwlv97JCIe601EhBb+yKjJTGQe5MZ2/PGLHv134te1NfDtfrBnuD6ZD8u4y2WtEsX3HpMWS4YU+31X+bfrg6QaqCvTIZkHOLWH4tOh/nm2Rln9HMm8TuRda5vywR3S1yVyVHWlrKbC/OpQ9bfkkQDRyHLNmrUqNFxpD+5Iq72HPGQ2Ided9oCirHQIRjKAlu7PNdxW9bQENBEIGcVR/gV5JsAlRNrgt2QAr9Pa8C1bsv7tGha0k7KEPcXScRdpz5rYheNufjtC5DNbxQISQuSQIagbJ7F4oSiy4rByUIN8JQWfJQaffzxj/fCOSVbGQngT2m80Y2uDJIlSDklFHhJcNe3mef64qgSstQhBrSLEhylRlsBnyx0tll7c/PcOhsDWFjjUNSNQRI9TIFsPrOoFAg8SmOUaf1tbOKCmGcDBbSfZeIUmDimOBlnY0gB3kZBOhFB+xsdPU1Z8/huzpu7T3/67vaXsb0C3/Ebyy1rg/KvXr/8y70yiH9Z8+pmbrKqw9uSfEW97QGscodimNZ7yBBQiY+yfgyYOQY0TB2eASuQtV3+J66uPmU5mdAItSzg2je9qQd3kj0+fN572swix1r3W/Y6YxNXUHxTPYxfMqBG4S7BtGREVhbrO/VRhxp4LWNO+u/CC/vr8BnXuYbldsJ1KK9OjOIzHnhUGaCT7Ar4p83GtnRxzuGRsS8Pc/SXdr7+9f09yfbsuoDY5pvy3ae94e363X9oyLK3nPvmadx9vSvDvQDFBz94fI3t0gU3ZbEIfNazestYPKC2jJ06QFojK5b7VZIhmUfaXCZDSt+Zt+QScx5QHmtkcyjy0iauyre5TXNhPpWI1fYur2vUqFGjU43+9E+vmgR0iOQP2Md+eNoCiqWFTk7yS9rWQqcEmpTzilccxlijzFDiCFAETBYAQJ9Sgd+nNeAmQOW+LJrWtBMAQyieEhRPpIvfELHwYI2QbJuly6o+N+7A5sTrC8BTW/BRRjALCisFKGPgc5ROc0qShAjthHG/s1JE5l2dEXXXgdmXABsUDVaWxqcEV/WH63ZlHTc2zykwQwCL640NC4ehWGslyBbF0eGAPkwczzJJkD722RgCxB/0oOF4W3O0jxhPx22dNNofDVnzWHfAKPyAG+IQ3910zg3tFUlGYq0kqYUXHoQvhR9Z7+YjMIY1Id5597sfujUPrZ+hPUQdHOR4vnAYASr97nnATNey1hoCUMYOz/SlECnIQWTqEf4uNh1LPh4Jrs2eWj7Dfdqa5DOAOn3hOQAfoRbIBqzlJCSzhyR5ypOe1PNKsfbwFXUCkCVDMcJzElMx7qSxkNOfwMKEYPH8cu+PO7Py7COAKP0QC8gAhmPWQrEU1JZ9uj7HBRl5T4KU7KH6G6gLdLXX5DBHm8yDxJ0MwG0PwsMdagG37LVJ2BL+aIxZsBs3Y8HCsQa5hjIdK88em7i59oYpS6pdx6h2r3VjrLVvbm/bRlZUd8+Rsd06B8gOJUNK9nZuz/ok2a/JMtpsPNwT8Hytq3JzYT61yDzY5XWNGjVqdKrR1RbKCeSAfdBpCygelYVOlBOCFQEpAjulhqAU6wQgRhT4qZh4pfsrV8sy2PgS2hSo3Ed/zVk9Uii1sw58PpUAwItyoU9Zu5ULbG1g812QMaMkUg49P9aBCdCe4PCUxgA87qkt+NQ7MZwCSmY+xVrENaxQbnWrvk+NNYsXwrkyKUMZ230FZl8CbLzkJf3Yaj/rj9p6YRdrb2qeU9bEr6L4AwSjWAMBvHsNUQmyRXF0rXWhH40XZdHYRPH22biZixTcORpTJnetIG0TV67RyUclKI3nsM6y9hzSBPgx9/Apa+Kii3q+xXp6rXX80F7hmdYivhcLtyRlKJNguA7/VqfEqXPo4kR16R6S+ZuwAyVQqU14HVCIy3ANqM0dnuGlAc18Vtfy8Ef/4cUOc8b21PBBwOTb3tbfj5fjf+GD2qCOkqjwbLD+8W9AWAA+/QsMi2toSeqA9+hr/+FF+krSMLwJuAbQsb7reioPoJYkLYlJl6z0id04ROn/TYHEHMpkLx8CEf0fsE/7XIc3x1Ix8wWQZ2+5wQ16GQI/fcMbeit/n7VbPyWZBxDXWFzrWl33kIf05bneOCgXAKkOiVfpeuujHNuhuZ+M2RkXB4hje9u+vFI2OUBaKyvWddfWuHjr35L0iblnn7fe8CZ7pDluvcaDZ1tL/EanBi1NttKSsjRq1Oh0pWtcIQMtuW4fdNoCikdloRPlhMBEsC/dOhJ8mtBFyOTyRcgaUmhq91cnuybO2WcvF7a2cVveR39NKW7qqK+4kQGfCKRTgnUpzFKEuNoon0Cq/E0Cmx8lcMMih6LrOqBxFG3XG+9Y8VFEEqsK+ZzswZRG7SfAAwVca0zi9kYJoKD7rj/0qcDsmMtRZfZV9sMe1rebgqIOaeeu1t7UPLf29DMAgGUW0t8C9LNaevazl4Fs5mQyQKO42AVUjELsNwrwEmDuKBMezSWQOup10mj/FFCaSysgypwsXW6tFyAAfsMCzpxjwRceghcv4RFDe0XCLyTbfSx6y2QMNTC25GBhaA8JeAnEKYFK61K7PMPaTObnHDLc6U79wY5nJm5eTamfsli+Kd+6zeGP7yzCAYpTe6r+Y3npAMhhIkCx5INDVv/61Tjg4cpXzxxglLwq1uaJd5h3v+NXytXvASN/8Af7OZB6BqhkpZiDsBxcum9KYK3/KxPYLCG80j2xrq+TrqRM4+Y91myuyX7n4Mb9+t6YiK+sv9/3vh7ENbbAUWMJfNRe7fIdWKocsgdLUuWZr/5zOKd+xopXiXvqsd1GTtqnV8raA6S1suJQ3fUluRaI7Tswv3ymNcOS0V6TgwsWtABgr4QNaHtQI3MkhxVjls9+d12jRo0anY509avv9rq1dNoCikdloZMTaxYBpVsHwcygehZBlaAYBb4+5a7dX5VFmSGoeT/33GXx2KYAPKROXJy8AE2lILeP/hqzekx7CaQUmYAdUyfjpTAr2QjFkLLGGoFyRJg9EYG5lwI32pnrtIfSQ+nQP/pDOcY9CVUoUEnqEiWMguxalnf+o/gYD20HsvoP0Gjs9MU+ArMvIcoxawTjWYOJu1h7Y/Nc+wMo6D/AK8VUn//8z/cuWktBtiiOxgIgm/FKwH6Kvnf/UVoBM1PWiOYoayVgxK6VyTHaZQKARicPlXy33luS2ArvzeFM4soBl9w7xyOG9gpAljKSsThWS0nGENAqAP3Sg4WhPaQEL8trxIvVTnwSH3WNOpSHDKwWrVuxuBzUiNlYUiwrtUP7WFTZv+03yYScdsyFAtG+JMfCw2uqAVX9ijfgYQmroI7eAyCiKNtJQoK0FS9Sz+wZ8ZAA5gA1U0+HlUBL9fPsWHAro060EqvBIQU/B19DmaCHKPVK0hd9SF5KLD08NpaWiVEbt2LzDHiV/sBHSz6mbTI5a29AB9dqo5dylBtQwnzhMm8N2HcTqiZeBuaSZ9Zju6mctM8Y1ZscIK0JcaMtQ3XHT25846679NI+zvDNb973ZfnM+99/9+E8Gp16hGdHzho70DBnjip+a6NGjRodN3r3u5ddR1baB522gOJRWejk9JuSRnlhDUCAJ3wlFptnnXPOoQJfnnLX7q/eCfsB2wCKj3hE111wwTyoOAXgRXlklSBO4fWud2XLqH3019BpfmJtRcFVX4LEmGA9JohTBClq4vVxYRKLitB/IgTVpcBNrrv44l6pcx2lGCAVyx5zKUFXzQG/UXS0y3hEYaYYl1YvAC1jFwtHCqRyT0Rm332vvaF5Xs6rGlAo5xX3wiVjFcWR1ZZ5hkEHAFHvJGnRrywf6/4srRFjceweCthQdmmWNWUsuV0pXfuIz9joeFP4bkDD7C3mahJYIPPSf3ipuZnMyxJITfGIsfUNTHCgYf1ZOywIk4zB+mQpjF+tOVgY2kNK8DIx6wBM9rlk3Q3oVx8yqJv/hiyrXKs9sbB0bTIz2zvxaJ+TCXjOynKtNZt+ZUkN6NIegJi6KBsvK4G7WE/Hws67upQn0/GQiGWqexxGcfNVjntiaZ3ENjUwOAUU4n85XKkpFobqFjdn40z+0Ldx0w5omPEJ6Ode9UuyHtf+yI8cWpmWfKwOOxMANBnDE2PYfAzw6oDHmBqDWJzrb/M1XiXmt++R48JDyXg+r9nb9hWjetMDpDUhbqbqbu2IYQp4d52xHdtP038BKdse1ChkvzC/eB6NZY83X4Tx2Xc88EaNGjU6bvSlL3XdZZctuxYGtQ86bQHFo7DQIQCyfGLtQGgH4FDcKPAAHQIb4Yl7B2E4VJ5yl+6vlBV1JBgnqHWUwmc+s+se97j1rmilhYr/1JEQOGQZtev+KkEZFgBRAGPBGUuWKGdDgvWUMEuo0NcUhsSh25Y2DZi+FLhx3b3u1SvtQKbE4qM4UepKBY6CRek3j5LpWbkUo9rqJVZCxivu0Scys+8+197QPC9juJWAQj2vAP8JKg/cG0sEUYIm+suaMT6eaVz0vXHgcs8KYyqJhPpwoY5LJne6WI6qG0WW9SKL2yhku8rGW85HBxJNED/1KXwXYBaQLbzTHLQXmL9+xycCSJmTgBZKXTLdrlnfeBShx7pIBnTrzpoD8NgDEo5h6cHCkEVYElBQLlN3WZXV2XrDM+0reMNHPzp8yFBbVlmD9kn1stbV374SnqrMACHqk/6csrLcxJqNnACgASpqm7oHHEMBAMPvgbgBhZO4q7QCdZ/1r2/8bk7YR4By9mKgWjIhz2UPrN2bEyN36N5Y2Wdf1j8J7xHAzz3mgHlnL9TeJNDznmRYsYQU93DoUDUygkM1gCWenfLLmI/KM2/8by4k+ZnrfNYv+sQ8NXcS39OakKm8zjDuOnNkyd42BeCpm3HzHM/YBmxbKoesAbvnwEfl69v73a/vk/qZRxnqo9HJSWR9XlN4+hhZI3i25HctIU+jRo1OJ/rEJw4T880R+WQfdFoDivu00ClBA1llk8nRc7hIyeRo8AE/ZbbIGqyI+yvFIJaJBDcKEKUvbk0E/7WuaCgWKgR3daVoUfKQE3aCHkUjllHKf8xjdtNf7tE36i34vOdQRvQPpTBCubYlkUkNeh1Vcp1dCL5LEmt4xs/9XK/AUqQISV4UnPpkNgpWMglTDoHTfh9SBKJIUlBKpfJEZfbN2gMoxAR7KOvqWhpS1OMGSQGl5JVAdeaJvn/KU/r/zUPzL5lah+Z3CZrotwAt+ta6pvzXc2PIopai6N2a9mzzKzGDAD6sO1yPZ+ibXbhCNyXu9KXsL0A2fCWWaPiGeYbwn1j5BQwyHwEu5vgSfjq0t5q773hHP+8AZoAaiiLgCX/DB9YcLAxZQ9ov7SEBnOKObP8ETAEVzXUHVmOHDKVlFbBfG+wjsQYPj0z244Bj1nQOA2pQcOgwaq2lts/3vncvPOIN6hMviFifRyYAdilDPcSjU2YZw9nv7jHG6iBRlT4yZuYFa1KU8ubGXHmxpE+fxD0xh1vpJ3uTdsYF1nUBdHOt65LUCsiLTynbveah/U5bEj5mTAZIkhltxF/JULG+TRDzWD/6PRa62hIwz7WATJ/NmWQw9syhUBWepc4OB2uLySEaA/DiPcITRR24bTuA3YZPL5FD1oDd5vQc+JjkR0OW+kvjRu46+3Wjk4eM81ln9Ukap8hasWYaoNioUaPTif7X/1p+rQPzfdBpDyiiXWdQHQINCM7Z7Ai3FJU733lcMKzdXwmUpWVihGcCNsGXMDbnElMrX4Q/dSEMqislsrSuIARecknvNrxLy6iQ+r7rXYcuvQTFAITqQGjkghUgiHJEkC9Br6NKrrPPgOlD80aSlmRq9owxNw/3JCsm6wzu7xT2IUVA/0RZK13MAQSltexRZvZler1rYGsIZEgfUZitoXKeI+vRPI+Crh6sWaKIjo1vnT03ys6QVSMasqiNi6Z5HhdEZSnDtcq0Riio2rFtXK0lc7m5QZ/aZN6ynBULzhgnnh/wI8BR3GjNOWsTD/Kf+bKUnw7trZ79/vf3Vl3mm7KRfQ2ItzYZg7l6xzv2VnsOJ7RJmQB4BCTSFvVOshV7ibU9dcigDq5JIg57baworU/7o7pai/gHfhHLtxoUnOJzay21HVRI4CYMQoBYfZVTZ2Pkd3VMcgsyhLqQP7zyf6z38SJgI56gf9QdgBWrwSHrxLHkCHEzDsCYeI+x3FY+y219ply8DWCpz8Kn3QckjIeGPsP/vPBz84Y85D3zhKxQzrUAUMBXfYuMr/v1AQATqJy2qGMS9iR7dPomY6ru+lf/GP+4TI/FPSyzdJd1qvnqEIAX75FYvUsi5qDqKBKorQlLsk3cSB48gOsA7ollmWzz5vhjH7sfOaHRyUXm4RiFF1mndAqHI40aNWp0utA/v8IAaY7IieTlfVADFGdok1PRIdDAYBPCIsQTzO52tz6r3RgRlLgyI65IidsUUMgGGrdgv0c5nKLSqkrCEkoQgV4ZBLRYVxBmWVV6555NkF0CoC3trxo8QwG2CNEESCAqIZpikaya3MfvcIdD4fQokuvsO2D62LwxFsYa0JWs4Eh/xA0r7lqAgJ/8yUO31TFFIEo2UAmATGj3u/HyXbxJfX8UQvo+Qdra5ZJSTAkxj8S4yjzPyY6kDMbZfAPwuY6VU5IaTI3vmgOJIYtaSm5iySXxhecmgRNS3xLs2DSu1pK5zAqmzLzZlLdTkwBTBAvZb80v/NrBl3lnXwhPsD4SrxU/SvKnTcm8AiSYg+Zt1n2SwbBSXspH61ikAb8kfQqv055k8GWV6VAhgNDUIYPrtd3eiGd88IM9z8UfktDEngQExZMBZNpRW1mi8LlkWFYne7q1K75vbfXvOnVUZr2PercHqo/66r8AMco1ZupovNTFu3qqeywIyQ14nHrqb22PNRyLTHX1HHWt4ySWQGLZX0neksQpyg8QGZlFP3lFtvB/3N9zEKNu+E72/Vjg4436Icl1tFF7EvfzrW/t25IkLOaFd4CiMc7hmXL1kbkHMI7beGI2qkusc9NH6mAOJS6k5wJ1XbM07uGcVXgJ4AGuvauvZ+HPrtE/Ph9FArWlYUk2jYnsUAEf0K/kkMSHThIoc8ieiN+QgfZ5mNvo+JP5N3aYUX4ur2vUqFGj04H+6q8O9dUpEhKiZXk+AbSpW+CYG65NkNsMpS1JHOaIYHX22b1CECtFgneUglgVJgbiEsuRWFXJ5iwBC/cuQmCE4iSw0A5oNsAxIAeLARv2kDC7pr+GQFd9E3fcKD6emWzYJah2lMl1jiJg+ti8AT7rgwSi1w/ejXvcFBN/jCXKEkUAvfSl/RgCzVCC3wvqSol+4hP3K6QfBUhbu1wmk3LpKmg9aTNFBrhPIUYlaOCz+oyN7xoQnYII9LCWs+a8kgE+iS8orsaeFY31WYMdm7rzz81l88oJv6Q+ntmUt1OXkhzMXBSbyr7kYMIcACjiGfhRwJsktDA3rSM8Z+1c2OW6HzqQAEoCxLwDIqxh+wrSNteImxjL/LFDBu1MGAZ1Ub+A/nEZjjWxvrKmeRw4JCwTJ6Hzz++vc99//a+HSVD0o/WI5zzveYe8Rbue/ezpfRSvd9DnfnVKnMMkU7FnG7MyTAowCq/wfG3WZ0BXr1iaOcyL1Z5ykmhmSHmvrRPNG32SGJz2LfUK6Bn3Ym23b8XqM8BdkpskO7d+ZFkZK0H1wcPtWa7DH5P0BdiIV5s7/nvRi/rv2p5M5Yk5qW7JXm2cYuWffVaZ6cvUV7uUkbii5suP/mifwGZJuJWlh2fZtwFoQmi4rj7sPcoEamtiP6+xtE3Wbf1BptTH5LXEsdRHxkQ5F17YX+PgeV+HuY2OP9X8eYzaPGjUqNHpRJdf3ssXU3wR2VMZzeyLGqC4B+upXbvhes6553bdwx/eK4EEX0J3BE2KDsFqjSWeTVfsKtmctamkWEYFYGAlQXjP6THFs870uba/xkDXAC4sIilDykhWzcR3VJfy2ftOrrPrOI1jANTQvPE5Vh551x+xkkhGzFhvLFEEoijFtYiS5H+KGeVYYhDCPiV3X8LZUYG0pfUgBRwIUs6TuHWmH0L6R7/q38RZGxrfKRC9BjOtGesX2AFYwNiNE0HZi5LKUtK4ut4Y+129S2F6G3f+ueD/6mv9mStD2aab8nZqUMmv7QHG3ZwD4JjzQOxY+wVIzLwxTwPerJ0Lu1r3Y8CkdZwDsDIWaQhYcZ3rdN0DHtCv6aFDhhxGBWyy35Wgf5KG6Sd9pL7WsjVfexxY6+phH8VXAVqeG1dl9QfgSwJ1i1tcdR91H8CQNaL1x/2TFbr1KdGKvVn98AdAW9yU7Z1+1wZ1Up7PgBkAG97ieuOtTdqWeIU5tMoeMSekZuziApy4iNoZwDYyAb7nGvPLS33VNRmkjZt6mHPapB7+c7Bib8KzUx/XoSQaUw6vC9cmG6znqYux9Uo264DlDtLUV3+6Ni5DSciS/VaZrlVfYy2OpUOXJXKedr/5zctA9Ozb73lP1z3/+b3Fpb7YxWHSprTUAn8p+Fhm3bZWtS0J54D/1hQZz/wwNv4b6t+jBFYbnXiy5p773Hm3Pmu0ZXpu1KjR6UL/7b/1IV/mKAfE+6IGKC5UVkoAhnuG/8eUqX244VIiCJhcoCkEBHQWGCYHgXQTS7wx6z7CHGWDQEjoY7FQKkEEPMJ7YhZtYnUyBromeQZBUvu4rkUZUAeCPsuRWpDeV3KdqbpuAuzMAVD1vAmImPhCodLl2akDZbRu65gigPkArvQpBbOM5UeIZ7FEgXXdlEv+NnSUyXSm5olnUOCtgWRANZ7msrWljymUSZ4C3AtNgeiU02SOtV4puBRSscPENWMdbB67F7BPGQdUcJ+8050Orane9KbeTTMWukv5yBrQOhQLSWvPNSU15e3UoSF+bTzLWKrmn3nne4B1vCKWUtbJJnNhV+t+DJi0R6if/60nbYqFYrlmrDnrYeiQIYdR4nC99rWHa0W5MrC7LvxBW9zPdRxfGWovgCTXx7oR6UM8Ap8VT/KmN73yuHi3x8ai0GGENl1wweEhmbLwlVjgBTTz8lx1SxIUbY8rsjWevQNgqZ8c2OF3QExk3H1fQp6hHkA/skisAeNC7KWd2duTWdx422NymOVdHfVrylJP/aE8AKpnaaff8TPXqDM+q4+0Ba92veeRW2J5mEQv5Di/GdvId+oVq8oStEz8xyTu8czXv/4Q7LN3TMl5aA2Iro7WmTWYup/oBGq7DAuUtWu96G/fYwWdsfWdHGqc9D0ZtFzLJwJYbXRiSTge64kV9RglRNA+ZddGjRo1Ok70B1fIpHOEP8KS9kUNUFygrCS2UFyVEtuFpQYgp6Z9ueGaCI973KHyI5bQtpZ4Q9Z92hiBm8BXK0GUE8AD17Hb334zq5Mx0FX5Jj1AU3l1mVOC9K6T62wKEJsfQ5mLKTtzVpx1HCXX6o8ASvmMoiC57pa3XN4e9QJ0UWaHxovVAIXMdfsSynYB0m6a9bGcJ+4z1ykr5lwUlICLcYXT56Wb5xSIbr386q/2ICH+YDxzIMEdEygh/pY1wdXUOmI1NbSOZYA3v9bwkbWgdci1+pLgXlprhprydmrQEL9OOA5k3rJcAzCxxrIf5EAn1286F3Z1ODMVVsT8tpYBTECJWMyNrZmxwyjEqrBcK4mFbN2KgQgwsxe+5jX9tXV4D2Xh0/hp2X+hgHt4RJKHGBd8heJcWjTqF/8/4xldd9/79jzcAYR2JbmNa5SXeiX+ofv1iXE0vgEg8beEdlBGYhoCs/wGyEncwClSZsDR7N3ql1ApDqkS38chpbp5rvGLRVFe6mp8EsszQLb6OKhRN32SrNzpU203J417DuDicp12xb1aWZ6hLsBI3+17AT0DMsYaKm7Rng1oVmdgr9+8pviz72tB9KOIDX2iwgJl7ZqnrjUXkpE9FrK+6z+yk4MNc2coPtRxAlYb7Zes1/vcp090VMd1DcVN3nxsgGKjRo1OB/rjPx7niSWRXxym74saoDijrCTTXinYE2xsWtxCx+JI7csNdx+WeHWZ2v3iF/cACqWyFmZdQ3gGquaetQLzGOiKLAwKjDpNCdJTgNKmYNMQrQGICdjiE37oQ71ChVgxSNOuLXNWnDJClnGUKGIE75gpl8Go45p2s5vtFkgdsojYNW2rMG0a33SoHq6nhFJiEhxen5uDFE5jJIGFsYul7RiIru6AY+PiRSE3D8wRvMN4GlfxoIAB3BY9mwtmrKbm+Agl2n0sHZNYIvctCT0wNpe1iXKtT467VUyjzSlWc8ASQNcQWBgAxZwFuO9qLuwKKJkCJgFV4gKOJUkZ4g9jh1FDa0W5H/lID05Z1+psnQ9lhNcO9wEb635MUrUkWjMWeJk1CKyqLRpjQUcmYdFoDPWlensugFP99If/ADWuVx4+ZrzJK0A6YF2SXyjfOCsjgBueVSbHqAHF8JvEksxBK3lBfyiftXus6JWjr9QH4Bj3bP0D9I2FoPsCAMalOVaICX2SjN313EksS/+7J3GYEw8xFpcRvH1OHM3Ers28T5klIAugyJ4AfM++bXyTxGpIzgNSrgXRjyI29IkKC1SuXfOb1X5iRScmtDmrD/U5635trgPJHydgtdHREHkn8wCvLClJpLzwz9vc5oRUsVGjRo2OlIRUWUL2ychV+6AGKHbjAg/BkRJfC/begUT+n4ojNRfHblPAa8oSbxdWWwgApm0E/JwaJ0A/5ZOrWCwQNrU6GQNdWdsBKxPXinBJ4CekUlIEQye8jwFKaBdg05K6looDAfvJT+5PUJMNFekn9+ljwjPFs1TiayvOMo6SvqM8OKV3H2Ep1ooYgzrojzWKRVy1KHWJPxVStvr633X7om0Upl1mhy7rEVe3uMJFMb3JTfqTHX2VMZqKAape4Q9eyqGkm8Pui+UPyxvWgIRkc2FsDEs+QlAGHFgfEgLIkllaHy4JPVCC1uVcBlAa88QpO65WMY22o8RKZC0bPmK9xZ3Z3Dd/Y3G2SwupXQElc8DkWJKUtQBMzffV+VOfOkziBFhKRvgouKVM4IU/X3ppv/6BirGUS1I1PAyFx1jbidtatiuAmj7Tfyh7bqz53Zt+xleyXye7MdBOGcC39BWe5D7XBkwOQOh/dSqtBwO6eSVMhr3JM1j5JfFcEsK4P7FiAauJl+idl0X2MWOmfPcDPn3OWCrbPdrqmYljmb5M7GX/+c21ys3/KK7XmQMBCc25X/mVw/GLJ4DrEubFd3XUR7GUc516OoQis9gnkqm6nGubguj7jg29DW2TXKnuD4dj3s1p91sXromFWcLfaL+yjhuw2ujoCK+JS3z0qFD5mbV3i6PYqFGjU52+9KXec2MJkev3SQ1QHKAIPBT3gD8EmAioBB4n8ZTvuThSQ+DfrqyratpVuYkVqR8onwRmwjqipBDifA9IuI3VyRjoGsCQdagTav2fTJEvf3mvrFAOhmLXoaH/ts1SOwcQA3d+53cOMwSnHwBHXOTMJe6tFjVFpVTiayvOMo6S68TXMr4UPwqSeagc/yW785JxTd2ve90+TmKtmJnbrvO8pVaPm4LYmyhMu8oSW9f5wQ/uLUvN9bjcGRd9S4hF5RjNxQCNVQ5lyHdzzzPNDeQZAc0pVHOWXupjzQEmxoBUcdyWhh6YWnfA2uNqFdNoOzL+LM+BJF4UdfMzcfSScMUaBITJljs0F+wPXD+BkmvBul0AJUuAyaEkKZtQ1gpw9alP7Xl8EnLUGeEBaHVGeNbNrGXe975eEU7iETKEctPfrJbFtsWXjU0AtfAUIKB+dp8y7Ctl/L4yaYz7XUsOsH/iQ0Ax9VOeMvB8QCjrMLwfECYcA7BZGQEU8R3X6nPPxH/U3x5r7D3bwUgSyKgrnqashM3QR8DExE00Tsr2HsuixHr0fxLhqIM6a4e2aWsyL6t3+hII6X/J3FyvrxKXL/GGlaUdCdtijqgbi1N9E1fnxFsM0JkELYmhGB6uj4y1/vVMaynyVrkWtgHR9xkbepv9fJvkSkP9QZY2r8ib5BrziSyif4yRpEVku+MGrDY6WrIWEqJmij796RZHsVGjRqc+fexjvfyxhMocAPugBigOUAQewj2BiGBf/kd5IDgSerkwrokjtUvrql2WGyGytIAizHlP8PhYURH0XEPhjLC5jdXJEOiaOHUUVsqPNnlX5nvf2ysLt7pVf402q6MxoaQm9lyetwZsmhOmx6xD3UOIcX9tWZLg/QmUH+UuSjzFi6JTW3HWQK24e66nELqeYM3icYmVUA02K8MYRVGLKzWFCVBw//svU1q2BbFLhUk90u+1K+8us8SO1fl2t+vnq35J1uex+J1LYoC6hgVLxp3SG+seyrcxpIwme/kULQFS4wa5NPTA2Lo7rlYxjbajzCFADAt0AI/P5pD57pCGKy9L1Yz10FwwV/EKCUs2PbjaBVBylHM11obWn3VUu1/G9TchDurwHkIaJOFNeAteq87ZH33Xh9YyYD97B2ER4JdDKDwKfxS/2CFW9lzWgeIss6CMFwV+hL94/+xnrxw7V9lxccaTgHFiuYaH2p9ygKrOiVfoN3VSB23Dy+xDrhHOARj00If2ffD0p/fPl33Z85StXuQmoF+sBvFIbuoAAFaLOejCz7yMrzkmhpqs2DmISXxH/ao+krgBRAMiBgyN63Xq6znK08/q5bc6GUvuTyIX/eCZxi6hcOxZ7jWXjc+YvLXNXN1XbOht9vNtkyvV/aEsfWuueKZ5WvcPUP4ogdVGx4+sAzyO3DRF9jJzuQGKjRo1OpXpd3/3MHnrFJFhHv3o/dalAYoTlPhCNbARZX5tHKldWVftutwIkQRk1hcmJyCEgE5gp3QQ/rXT/XGB3qdyp03veEf/7Otd77BNUQoI+1yCCa6xJkiAd4oP4b/MCLgEbNoUHFNX9xBi4pYWUt9kX6JwxJWMEhKrFvdSBmtwcAiojeUGpdL9SyzGxsBmbQR8BSj2uzoAY5eM167A8VjfURT1hc+xMKU0s/BJG6PI6D9zEjBauo/PKTJTdTYv9L/7azCxtrRdGgM0FjRxP4zbHoprtHmm7CmlcQmQyroSbZvw4kRYxTTaP5VzyPwoMxZnnnrJMp51W88FFkQsHAGRuwg3sC1Qsqu5usQqy3+us4aStKkkwBUgJNnU63oC2bK/sFYf2h+9P/axvcLMci4AHj6BJ5WHefjiUIbqu9+9H1vW7eqBN+AvDgtf8YpeALWvKzMHcuqc7PZJPAMsw7OAbmec0fePeiW2prkCnHTqrY54K1DygQ/sFfnEDqxduM0ZFp7agocrz3PUWZ28gKIAUH2ubPNVWZIElXKG//3O4t6eoOxYairTvuqZrtM/6pvYtQlPoWyfjaf+SBzGuD7j3cY7ZaOEwkn2c3V2/ZS8ZWyBrdwxrSPjwyp1aUyjuTm6bdzoNfv5LpIrDa3dzNWhNhwlsNroeJI5YM44PJ0i69dhC8vWRo0aNTqVLRT/ocJjhojcQ0Y6doDii1/84u45z3lO9/nPf7679rWv3b3whS/sfpCv1ADd9KY37T4kQ0VFt7nNbbp3QRA6p8736V4jTWJBt7rVrbpL+fedAApAF0GVgBOLAsItgWsMBJqibayrpoTFbcqNEAnY0i7to1BQeIBNBHAgGUXJ/b4ToCkylMqyzF0CEWNtAiAR5An9PhNmE8cKoKeeLCWGMgJOgU2bgmMBIVlmAHTiUqaflJH6lhkpKVGZS35jUWGxD4GD2wK1U2AzZYZySfn78R+/auynuaQ3uwLHy77H8LwbS7EoxbZimcDCR1vVQ59+4AOH8QnLGHBDlp5L+qIMsG/+lCCh53DdA+ay3lwTA9R37ec2TYmMFaj5yxqDgllbNA3REosQym/tBrlp3LumvJ16VM+hEjiyppIYBNAxNBesH4ocvr/LA7Ftadu5uvQgCU8BHOHf9sYyrAVKJlr3rAnvMcTz8RnrFa/Al/Eee1ySVqwtU//4Hd8E1CXDsTFVtjFXvj4wJ5L12zuQ8OEPP8y8nDiwBNnsuUN7Uqy4SxfukvSVvQe4yB3cs1kfOYyxZ0Z2YXWofPPraU/runPP7brHPOaqQNSzn31oMV6C5fYI/UZmASR6KTuu5OQ470lg41nxKMi9xiBu4uY/C0v/+V0by/jaY/LW0DzjBbPEsndujm7rKbB2P99VcqWhteuejG0O+dph1jp65jOf2b397W/v/uAP/qC7xjWu0V3/+tfvnvWsZ3X/zgCO0Mmiq5WWyTWVSQtZRZfJnRo1atToVKK/+7uue//7l137xCfuuzYbAIpvectbukc84hHdRRdd1P3QD/1Qd+GFFx5sKJ/5zGe6f5FgYwXZ1P4uUbE7wtj/5wCEvLOI6QWdddZZ3ate9aovf/+q+vj/CClgFkGGoE2wIeDmJHYOBBqjTd1E5oTFTcu12V58cR/fj7ANNKFExOIrSSQAbH4HsBHufbeZu74uc1dAxFib4m5FQfE5wdPLOFYsH2qXNBQASl/U8Q83AcdKIIzSRbFiVULp8py4BiagvTpRoCgtif+UuFF3ucuVBf8azGOqPHZyP0VzYLPfjbPxnlN+yjmXcrUxgERpKbjE9TjtTN8naL+1Zr5RbAEcl13W14GFj+uBdRQ6z9Cn5kLcx4GB4j8OKTJLgHfjcq979fVwrTaoA8ILuHn6L/0wFwMU0ByXOpY81pk5nb4yV5dYDS6xCBlyg2wxEBtNzaEAR8j6MYfG5uKu1vxxojUHSWVG+GRbTvxZ3+0r1ve9770uvEdN+s9eElARj1A+QG7oMG/pnptyHXgkNqO627PsAcZdPxhbc6IEhvKcku5wh2HrMuWFD+KTDq3wQ3PF72VCmhwCcXcWR089JCDzP3AxBzHqhc8r5xGP6LoLLuj/L6m2GHdgZl/gQg2EUF+Wj/mf7OBgxzX2FzJNaVlnD09Sm1vcoq8fmUd9/G4vJx/Yt+bkrW2s+efuZYUF79nGU2DtofS+slDvK7746UaAwQc96EHdD/zAD3Rf+tKXunPPPbc788wzu9/7vd/r/smIonCy6Gp4RRKz1FQetuAlrIHpaY0aNWp0qtE73nHoATlF9mMHp8cOULzgggu6c845p7vvfe978B2w6PTq4osv7h7j2Liib6zSyrz5zW/uvuZrvuYqm5RN6VuSFvcEUwlmDbmGjYFAczQFCtgIgSRlRkPPWSKIbuJ+olxgIvDBCR73pAR9J0gTmgnwnkvGSHbIWNmtdfdeS3NtKjMdh5LhUb1rE2BKIGsAStkrX9krzhFUfV5r4TkEQlJwKJmJq0lRAXCZS8aShQOL1tIqSN96lYlVpoTqtUFVNwGbl8w5c0Sf+k5JrS0FMa8p1+MhkELQ9TqjOvbhN9e9/e39b8qm/FE6o9CbL55HSRzLer20LwCHWBmrmRe8oP+dMkmZVxexMilRWJhxs2aGYhEmkYMyKLXA+LJeayw5llqEjLlBbhtXblt3uuNMH/7whw8s7j/1qU91n/vc57pf+IVf6P6TzhqhISsN9O///b/vfhd60nXdk570pO7JUr4XxDqExciJom2tioz9Ltb8caG1B0kliIISWkNf4OXW3XnnXRXoWktck4FqKFY41px6AMbGDvPm1i4wDRBpfMt9E0+I+zE+bwon3itAbwwYKoFMewYLwaE9i0UhC0dgYIBRe6H/zR39DPx71KN6AOBZzzrM5poDJqCe+/zmGc98Ztc97nGHsZa1z3yUmEroFs8qD4PwcPFB7ScBZM1l7SYvkAHsI/F8SMxKIun1r98fRlobDqvcw3XcIaJ61VTLRttY85f3ZpzIGOpnvWmjuWK8ANBl3GjXO9C66KL+MG4IFN5GTth1mJt9xRc/Ham2GHz1q199YPBhj7uxALoDdLLoatYjeREPnCIy9rvf3QDFRo0anZr0G7/RywJzRJ4aklVOKKDo9MqG9FhBfq6gq13tat0tbnGL7uPsyxfQK1/5yu5ud7vbVU7JPvjBDx5seN/wDd/Q/ciP/Ej3tKc9rft/QWMG6G//9m8PXqG/ImXtEcyqXcOGQKBtFDoCImGKpaDnyTYL/HKiHgR6ShAliK9RFCO4eR7FwmTTVsI3dyigTDLSam8SsQRIXOs+uQmN9ZV+jytx2qeusXqIRWncp1xLGBV3yrUSmyi7FFTPOmu9MD10om+eUDgobvqWW5xnmk/KIMfFmiEWIMZwaGx2JVSvBZuXKj+A0QTGtkwpX6WloL5fAjhHkaEMlnG2QpQ813iGfkXKNv51/DcKnnU6No5r+sI4PPe5vWKqPM/m0m5+ARCML8VfEgPjMWRBYd2wYhFTzJgqc1NLjjUWIbuOgXiqW4389V//9YElxtlnn939mACiM/SCF7ygO//887/8nQXIkCXH93zP93Tvg0pfQf/oBPtebWtVZH+w5vEt19ZrHn/Y5yHTtlSD4ol9Wx8kaZ/2aAuBrcwWWoIo1kViJvqdZeK2YKIy3/rWw0QoQCN9rD7GTL0T1sHYqdvUGi/XLhDNd8AhvpW9yDsZgNcF4CxZnIF+rAGXuOPO7VnPf34PAgLxXAOPABRqU5mUBv8H7pWJXMoDpoS8UI59KLGWS97k8OcmN+m6X/3Vw5hrDkTVSX306z3v2XXvfGdfvnrHvdy+rPzEbjSn3UMucj/+rzx97R77yJy8tU1ImtzLmvOjH+3LJlfEojIZr9WLDIQvl7GZHW4CiLXBgdYYz940JuIme83Q4RTaR3zxRj395RVpkWvQcN+62j70Nev07LO77vGPn05GYG1ccknXPeUpze25UaNGpxZdfnkfEmwJiT29L6ympFVs9s///M+7v//7v+++uQqy5PsSy4v//J//c/c7v/M7BxtVbUJPkfuu7/qu7o/+6I8OzPNvfetbH4CUXwndGogPUlt/7BvMimvYEAi0jULnRFwsIoqJvd7pG+HRswmCBHyTYUoQJWQuVRTrE29KIsGU4Jbsi7qcUOqdMpNN2/2Ujgj5+3SfLPtKP6gfoYAwrU6er776Tx9FAdJ2ChOlQtu0X50pKQC9eOWXgipBHXi6RpgeO9FXL9mn9S/XLwHyjR/rOkK+5ywZm10J1eaovjDHfNaOgHabKj/qQTlN9kzv/ivdzlnx3e1u82skiowxM8/qOFtJcqPOlEh1juVwCfKnX1kCjlnuLLXQMjbPeEYPJpKTE7+M8s6KMllx1Vfb58DeXVlyrClnV6EHTgerEXuN11L6+q//+oNX6Bd/8Re7v/iLv/iy1X4JIB4Xq/tt5yLexHrMfE/4hnLNW5vW/D3ucTSCyy5Acfu5ejuICAWIiWW+ve7CC7vup35qPFHNrix2w//xM3tG3JBLvqod9j1r8Y1v7K10xkB++2YJ4gER8VkHI57B80K5+Bzg1G/4mn00IOaLXtTfe7vbTdd5bs/6mZ/pLQozBvj00LzLflAncgnFclCdzEdJ5PxW8iYWe2J9Gl+Wj0N1gvOTJYBs+jVWpjmcRGQLVo3kIGXZRz1b+X7zWgLMb5MROVbBXsYj4V4S31Hb4qptf3JNXLMTpsc19rApnr2p9fJay/Wxwykh2DcFXRtN0+WXX9497GEP625wgxt038tfeAHtSlfbl772yEf2VsJk+ymyJvBJYWwaNWrU6FShP/zDXv6YI/vxT/zE0RzEHem5jc3pP/yH/3CVBC5OwUL+P+OMM7p/82/+zcFJ2M1vfvOrlMNCUhzH8sTrO0gix8SSY0rIqi0cEi+IEOi/WA0Q6pzQE6zH3FxLQdQ1SxTFEjBSN23xDM8lfPpMQM0JOIHeuzZ5HiWHCwHdeS7z8bYKl/LFBwJoUFYT2D0KlqmR+FJ+U399GvcpY6WtL3vZsHtSBFVtpvcTPpYK01Mn+snMSfCFU3jX30vHZkmMsjJw+VT/UhYpZpgPMMy12horTeVrc8pcovxQViimrBQprWUsMcpYFB4K69yYR5FhQRoAOyF59L3xpeAmizdKn5fx31CsisYspJasa+7SLF60yX8UMfcFSInS6T9KaKxY5sDeXYEQR5mBeV9Z6U81sq+x0v9XJTLVAU3+3923fuu3dl/91V/dXe961ztQrL5zAm3bt+X9NnPItdb92Jq33u0TtvbjNhfGQHG8lsWl81GuxNrEXTYutniJOY93ur8EYvaRtKiO3Rz31vQzvsgyWv3tWXjWGMhv7cbN2P8O1/A3UxR/T6xCh2wOmwBV2pzyEHBR/7zwhb0V/5CVjzrrX3UEeiV2sTmhvtyLs2ctmXdjiVzsBeptDO1fDga5Q9sbrne9K/MmzwSQDtW33Ef1kTFUD/xM3+rHWIAm9IxX5CF9Uifwsi6G9vTIQP6zPtLHNU2Fj8nYJYGOV8K5OCTFLgIq+k9Z5nBkpLiYJ0v4GM/eROZda7k+tg7Jdg51yRTqmHA2dT+cTOEUjhOJpQgc/DVC1hHravvS16xtcU2nAEVz1bpwmM8i+bjtS40aNWq0KT3oQf2eP0fkgDKZ6LEBFL/pm77p4BTqfyUwzRXk+5wlBrcyMTmewv58hv71v/7XB8/6wz/8w8FNSgyPfQcC3tSSY4mQFcGaIJ94QQS4UoiK4GvDpDwM7b+1ILpEYC8BI89QN4IzxcUmrTxCaARrAh4B3YsAqx9kBJ4CE3flIqkcwcYpCTe72WFmN0KverBQ0EfqTfki+MZy0m+UhbjDAoaGKIIqkJTQvlSYXnuiv3RslsQo42rr1HWuf0sBntLl2RRJc4oLlzFV9hve0MfSjKXAnOtTrCnVX7/Wrsf6z/Kss8UOURQZdfOKwkiZTOB+/abdwAxEEd40s6SyxNliwcJSx5wyr7Ouy3iaiSMa139Ag3nhXVv1gTrWivMY0LArEOKoMjBv46p3utD//J//s/uVX/mV7o0WZEESlolbJW6iuIwsNG50oxsdKHZfO4J479vyfps5lH0j7qPbrPld0NIDqylQnHVaYgu6X5tifY/siQAr15nn+wbPl8ZutifjR2MgvwM0+0htYR3XdG2IFaCsz6zNHcxod9y98UXj6jfWhPZa3hN1nyfeo3roO3so8kztAGSZFwGC5uZd9oMykUuyj+O1/lev97ynB6DsVzVvCpjp+iSYKUm9EqM6+5y9z/Pcm4QssZhP5mf/2y+TSMv+QahXn3oeljIQS0f7LeCx9JJYs28ZP/2rL7wHLNX2zMck5iI7pI9zILckcdIamXet5frYOjSP1Vffut9nsYrjuh3ad8zuU5Ue/OAHd+985zsP4gR/u8FfQLvU1faprzEcYEBpbQxRlG3r9HSWURo1anRq0d/8jcRby65NiJZjByhe/epX777v+76vu+yyy74ctJ45ve82rim65JJLDqwv7umoaIb+x//4HwcZxv4lSegE0lpLjjVCljISL4gAVQvFSPMTA7AGHMcE0TmBfSg+ZBQX7s4AO0L0ta7Vv4A7EUaTRXcquOeuXCRLAVRcqrLt+oLLEiEdOBZLBvW9z32uXP7S2EDiYbISXQogb3KiPzc2iVE2FZeQAC4ujPep/h0S4D1bOcpj/eozhSzxpZRhrlMClTUG2ilfGe6p44tGbqQYLBX+lSdovP4WRNu4lpaUFHvPSHg7ddjEcrhW8rLGWCVKZuI+buqYteeW1ruUy8QVxQv0U9ydYwFSKs6nAm3jqne6kOQs/+yf/bOrJHEpXahZcQAYWTC+9a1v7e53v/sNlrVvy/ttqOSju1jz29CaA6spUNx6d0iBF3JtxX/tEdpUHmYEQKrjKe6a5mI3e3HTBSjh5UMgv4MN1n0B9GJhXbpNa6cYg8DAWObhZdZyLPEAV+rifs8FuorrXPY5nmf/TV+pd9yF/aYMvBx/9MylCcWMYRK5cGnWXnuPPgFYA9OUW1owlqStOQQqDH6/TOqp7qVXgvZrqzq7BzAaC/iEf7HHkDvSTvUi63CHL9s2JAPpH3NMXEeHl35fsm8lbmOAN/0eMDQHjvrAy7iU7tDGOpm0M1fmePYSmXcTy/WhdVhaBOtj886+TA415+OSfxQxu081+od/+IfuIQ95yEGCMdaDXJSX0smiq93gBr0uMpfl1Ly7IoRko0aNGp309LKXjR+k1EQ2OSrr7NUuzxSee9/73t33f//3H5jDX3jhhQcnWokfda973av7tm/7tgNri9qEntJVB+/94he/eGCVccc73vHAylFcjkc/+tHdNa95ze5WgtGdYFpqybGJkDUHdhG0KC+u2wRAGaIhy7ooLpQVgI7ybnObXogOLRHqdukiWQugsZyI9SRh12eWd3HL9j+LRvGnoliusSRMAPelAPIusxzqO8L1VFxCSh3wmfJQgqxD/TskwHvXV0Az5WqXPjDOZRlx5Rqbc5IPcAsu+zRWIJvGGNVXF1zQx+r6pV/qn6Veyqv7c1PL4SGgG3DKOpMi7t6sSWuvtN5NdnOKZixBKKT6jXJJwVVXSnoSM2zqlrxpuIBdZ2LeNFD/6aS0XXzxxd1P/MRPHBy2TRHQ8d/+2397YMkxRkdheb8pDfHRTdf8NvN07YHVHCgeS2QAkzWsXclCzJIsISMCIMnYLsnS2rihS9q8JHazawAuY+0BJAGe4AfJYJwppSzrWHu0GY+3nwR4S5IPIFXcfLXbZzw5sRs9Gx9873v7PgF4AeZcF37hd+94OFCLRXgObZb0Bx76vOf1sX8c6qirstVR2caGZSXA0fPLfd0ep532kHpZlnu+gyQxIvWrsj1fWeQg93uW5/hPe1l96t/8Fnd4c+JOd+rv1TdcLGsZyHj4Dygr9Ig2lJbxY/NJ33heQmxkPCIjZGyNjXrnf8Ac9/ZNLP3mZN5NLNfrdWgcSotg3/Wx9kTWMy4Oeu3xm8i6p7ubM6v5d7zjHQcW8Z/nmnJF/N9rmHingK5GN7rudXs+NEXm3ROe0MusjRo1anSy08eX5UA+oKPMcr8aULzrXe/a/dmf/Vn3hCc84WCTus51rtNdeumlX07U8sd//McHmZ9L+sxnPnMQv+M9/FQq4kL9X//rfz2w9PjCF75wEHPqzDPP7J761KceW+VqV0LWErCLWX/iui0FUKaE9SnLOoI79y6UWH5rAMxdukiWAmgZKJ+CRLAuE8nEzS4JQ0rQcq0l4VpXwF3FtHM/5XUuLqF5ofy5/h1TpAnq+lG/EeBLC46UQVETxFqMqrE5p32bxhgdI9eLi0PxnOrPtX2+Buiu12Ssd40HSvZP1rCx7FSuOalcSjBLJp/9ttblf9NwAfvIxLxpoP7ThT70oQ8dAIRjFoe1MkYBAz6ejLRNXOFyPwJkOTjB69bO020P7XyuY9P6HWDzkz/Z18eaxhvxXPzP9fTvAFPcf+t4ilP11W6HDMKX0ek9e6zNS/r49rfvute+dhzkjyUOoDDW6GWWZO0ANHoGK0VjkniBiRWbA7zExgSwqjuLoPSr/30uE7cFyMp/ftN3+lo2QnXH35fyKuMVoCyxnT3Pbyzr9a12cH0WDqQk4+jAx96lLkNztTwQ/OQne3ALkSf0fcrWJ+at9rnX97jDA+1YHprT17xmX0fA9BlnXHWPNs+0X72xDG2ekxXCg8UZVF910l+Zq/o74WtiaWl8zW1xk8qyjYv7ATHGGwi8iayyieV6fTgVOSTeL9aF+wIgAs15axhX7ahl3eNy6HZc6SUvecnB+01vetMr/f6qV72quw83nlNAV1N1PGwOUEQMJaxvhxuNGjVqdDLT/2+hdSJ5YGGkixOXlIV785iLM/P6msSRYs0xRE7LfpUfyElOmwhZS5U0ChLBXAwexDUX6DUkCC2N4Thl5YU2sbrbpYtkslvqF/UgcOoPvxHmLSjCvr6aAy3r9upbgj/gk5Kjf090TLslMcooeFGO5vp3zLpMPwaYVG4tB6YMStVjHrMsudC21pmb9Gd5zZySsBbortckUJ9CCxigwFFy9B1A1nV+sz6TSIGFCkbuZMh4LnX53zRcwL4yMW+bnOpkIWBfaTn42c9+tvvN3/zN7hu/8RsPkqhwRf6TP/mT7rWQnMqSgyvzUObMn/7pn+5uf/vbH7g5i7P4xCc+8UAhu7u07ycpbbLmy/2IhReQwNpwcLJmbWx7aCfejD3DYUlcRRNWgs4tPiDQT13wS/q02FtJhBHLNACSdTZnaZ92A5pY0blf/QBNeMVYm+f62DMBnWMgv/YB3LRryMI67rza4rDElAbiAMXsiV6Jkeuze/DUJMiKVWosGvFC+7Br/K+d8WzQx3ii+gCvWCkC4VgFLuFV+K0x0F/KSL3sk4DdZMLW1ywaS94ENJPQTXxHYJzf/W/eCZ1Rx7NWvyc+sR8v7ciY6SsvbUzb40qsD5MdW18AMNPfvADs46V1IPKbfmERv0RmKHmw/c1zk4ka0BpPg7g+s4TUbp4a+qXk2Xi4dlgHT3/65odOm1iu14dTkUPUuUy+pv5e5rExvv/9u+7MM7dLBrPtfScjjelbp5quhi/kAGSKzDWZ5iWYatSoUaOTlX7/9+fDPISoJvTXo6IjzfJ8KtOm7oFJEsGlaChJBDr//GVC0BpgYcjKi/BJGPc9ydxi2bHkJHeXLpKuZRVAeSKsE6TzjgjQ6qO+BNC5GEFp7/vf3ys2+sMpOIXKM060ULkkRpmxQkv6d8y6LEHuKSOuqeNhlmXMAXtHmXF4GyVhLdA9ptQDCK1NShCFJxZHgAnj5Rq/KU8/m5v6b8qCKmCo8WBUwLrFtfoyLopT4QL2nYl5n8DxcaFPfvKT3c1kfbqCEsdQaA+JVSRVYc1R0l/+5V92P//zP9+9gL/jSGwp4KH4Uv/8n//z7oY3vGH3iU984uDzyUxr1ny5H8XiC+HjrLADuCydp5se2gHxJJ7CTz0PCIbPOaDD/8SYsZ8EuKFnqw/ghaKarLPWKODN3J+ytNc2XoT2r2SC91z3A6AAeVNtnuvjKZDfvg/YUgflsJrzzFj4ebFevMtderBPfwLfWIwCdXxPe5OM5AoPyQNeF3fUJKWqrRX1rc/6zv/a7rOx1p5Xv3oZr0IAXkCAvlOPkOuBdtoLSHS9vh46GAVKpo5jpL7app76x+dYPOoPIFxcjH0HfHmmPmP1pL+TRA3A4aV/8Ev7Qgn6bhImouTBAE+gvLoGRDT+ZCCKQ3gysLXk2doUUNR/2xw6bWK5Xh9ORb5I6JrEK43MAzAF2HpODSYep0O3RieWrH/rYInFzmWXHcYfbdSoUaOTjS6/vOte+tI+7vUckQ3OO+8wgdtRUAMUd+QSsYmQVSeJcB1Bh7UE1xi/LT3N3wRYKAEjdXn2s4eBmaXWd7tykVQX7VaPxLSK8FkKoAR5wE6ZyXFKYKcAiJenj7TpOAmVS2KUcUc3zgmmPxcPckjxRLE+MRdOZjfWpUrCHNDNAoUySPHKmh9S6vXbk57UA4jmHIU3GVmTtIhga9wAiurlN6CF9zqxQ2nFVIJ1nmm8Ev9qKlzAUWRiPg7A8T6JW9iURQdQsSaxqP6/8ZEcIFkyT1VaYkFc70fmP9DF2onLaAm4LJmnmxxYqYeYdcoHoNkvAHuELJb+9hbWZGIGm+ccL+5xjx4oyt6jvsoNj7D3sFQcsrQH5EkmYq/JwQMwLeBp2u1wYqrNU308BvIrzzR2qEHgZGWXuIZARG3yGa/gguwgM+0CoAHKADle2hz32Sjr+hfPS+gR/cjqFICGx2mrNruO7KIN2uYd4KVc9RUuYo5XIe3wWyzxyljAxthexQ37Gc84PAgNb9L/2RvKvZ7FomuHZCd7olBwiZupX7TLs/1HLktSutJlN+Be3OiNszYY61I22WZ/LXlwAN20SZs9t/YgKK9//euXxV5ewtM3tVwv561xRngCgJMsl37Xn8qy/5UeKJsenu370K3RiSNrEvCMB84RA4J9JtVq1KhRo30S/sVIPPokjGSIyCM8DKtckXunBijuyCVirZBVgyGEfYoN9xxWEO985yGg5uR5TgjaBljY1entVB8k9o+6q8MYIFELf4QAgn2y8lJKCMYUNH1BIE0cwCmBfUyoJIxTtvTBq17VKydHieivmT/+R4SnJXNsTPG85S17i5W4wm3qxnoiXYi2iYtYrg8KsUD55tQrX9lb45RtKNeKZ6acuEuaP7FuiUJtbnoGpY9SbF2XiR0uvLB34+KWxtrEWCRjqTnMksScLzNdjlneHlUm5l249Tc6fQ7f6v2odHEsk4MEcFkyTzc5sEo9AClDMRQBZuW+aP0nkYl1rL4s7+JWp36siLms1odWyrF/AEbwh1g12ru0zT1lu5W/6dqsQX4Wem97W8+DAtBcemnP4/Ed7aFI6z88Hn90kKGM8DO8KgcY2upe5eCRygCWaot+S2ZhwKVnAlj1i7aZF0ko47DGnFBGsh0v5VXGifWo+IZ1TGH9Z58GKHqv+fQaAKmcq8muXc4TfWGP0E59WM5nz/Y7MDbxAPWxcVfnAMpr9texdbWWB+d6Soj5sST28tLyN7VcL+etg9FLLunnBvDbuJof3gPCOliO/LmpjHsUh26NTgxZf5L53fWu89dag697XR/aoFGjRo1ONvrMZ/r9fAxIzJ4GTHzKU7ojpwYo7hBUq09guVQR6vwuM+6YNaH3BAUnmBJmAWkELYKV/0tPuSEhaFNgYdent0OCJuFb3ShqXM9YCY4BT6Xwp27qHZcrAjxLgViiUIAIFBQ+fTYlsKdc/VZmi3YPoZ+iJIwa5eHss4/GUrFWHPTxEiF9jSA/Zl2GMW3jxnqiXYjKeYKAcCVQMBcXUX39x+LGnBdbS79MtaEEfYUnMGcAgsmGah56ASnMWfOVEm7OqlMyg4oN9YlP9GvbNXHr82zzOZk6fY8V15jlbcvE3OhE0NxhQr0fWZdxTfMZMBRr8zXZZ9daRpX1KK2+x/ZFezYQjNWd+wImIu/qGNfRErjMPgpEUiYQyTqOW6p2xvU77U55m67NAEaeLYyHfSx7uN/wHJaH+JG+KZOqqIc9QPKtWPepK5lDnfC2WCmKw2O8gVJAUe1JojBAos+ejRJ3Ub8pz8t3/ZKs0vrbPfZa9dKXrqnngM8ApiTGKmMKJ8yE+I81rQWQ6rlazxP8mXWrMc2804/usQ/o59LaHy8HhLKMjWv90v11H4d0c7KhPlbHT32q/77U+nzKcr2UbfLcMnyOfvfiks+iNwB7XPJL4Dvy56Yy7lEdujU6MSR8w3Oe0+tQU2QdAxQf97gTYzTQqFGjRtvQRRdNg4nkBfuvffVEUGOrOwbVCFnKc0JN8fCZBZIszQEXazDEZ2BimY0xsZcI7UOxeGohaFNgYdent9oLTBEY/MY37hUJlhOUEILkHPBUCn/6S7uTqVL9E5DcPcAa5VJ0yriTQ4K3cilLnqlv1cEYUXyAuNwm/O/UfGkWz21oSnGYSoayiQvqkGXDNm6s+3AhWhtqIPPEujFm5hklWF3MGQqd/xPry/w466zDbKuUaACyeXajG/Xjv6QNAcwxdrE3E+w/bn/mKiUzwcLdm7KTGZTLn/Izl91nrVPsgBk+a1cOE/ARBwxDlrctE3Ojo6Ylhwn1fmSOl7w8YFsswJbO07WWUZvsiwGUtM86TNxZYEdAxutdbzzxk/0owGm9pn3Wbt+nrOnX8MKhPTyJQrRD+zy3TKpSJt+q4/MBd8q4fLLsSmagLspRL2OmP/FHoKXn42/qnvZFaQ94aN81dzwjEQbwZXuTfnB/2R8lX+MinoNAZat7DoFqWgsg+Q5sCN+OpWE5R/Bw4Cuer59YZpIfkskaOOsec1vbjPWd7tR1cjANxaEeGmNlCMnqd4CpsdGHvFbIOoATAOracBNTa0CfcwO3Li++uJdT1wCYQ7JFnYjJekDak7iIKV/f+93cNa45EEz/l/LnpjJuO3Q79ektb+m661xnHhRm3fO85/UJWho1atToZKHf+q0+VM0UkY/sYycqVHsDFBeAak7lxT6T+ZEwNCXQJf4fZQRwMKRsEUIj8JaxePJsglUCnRN0StewMSFoU2Bhl6e3NUhGOCRMLnXbHhL+ykyVvmsLYVx9KBmEdgLpnOKlHlFkEgMPKUvZiGJAyAXe7DOmzi6s+3bhgrppGbsGoZdaZZRKmPFz7cc+1vcdBd53SnTG2hzzmfVOOSe58VmbrmVhUyemmWuDeZFkEixzkpglyXMom5RnirY563/KPHBBuwI2ZA7GQgfg4tokP0BAUvXgxjhkeXu6ZGJudDxo6WHCox511f2o5OXWgLmK3LNmnq45DFm7L4qrCFSyfuz7ARWtSeWHN4hxPLSPKqcETss1re+036GCPdX/dZs3sVAb2sNLi9DaGlS77XF4i/qIQ5ZDrMTnK+PyAbOUJ2+RawBfiYnJ0lp/JaEJENL9+gyQqG3JbOyZAEnPB8rGfVmbjYP9vOyPmq8llIRrh/puEwDJs9/+9t5d27zUFmUnfm05R37kR/qxUx9WdOag+7Q3ibUcZGm7cZdNeihe29AYJ8kL8FCbgJv6LN4Z5hMLLPNT3e5zn96NfwmNrQHtNX72SHvcda/b130bL4NStrHfARSNeaxUyWq1LGxeen6yg4/Jn9q7iYzbDt1OfTJ/HAwL85BkUUOERwHOH/nIZqXYqFGjk4Muv7zfL+eST9nPyEn2uxNBjaXOgGqEIAIkgEKsDmDEmIC/VNkS7yMCbxlbKkTIJkiaGITUxOyZEoI2BRZ2dXo7BJJRIAjJFJMlbttDwp974vJkLPRH3LcI7EsEXuNCcKbA+Kz/KFP6mBCrjQR2ygBwRx/tK6bOqRAgfNcg9BJwdQis1lfmg3G1hmJJ5DNl1/8ve1k/3mXZTqkpbJQna2xtG8wLLmKS5FiXcceL9RGlT72sY/db2xTRKKksDtXV9ch3ypcXEIMFpf/8bn44eb/vfafjUp3qmZgbHQ9aephgz6n3IwA7UIBrpWutAet0k3m69DBk7b5o/wGsvPe9Pa/OnhVraL+xdK5j9gHY7Cn2kWSrzSGYtW8vdKhAofVM1nV1mzc5aCqf7Rnap29Li1B7d6xB1clzHHqom4yB4gNOAZaREdKH4W1eeK1neGYAMONcxhjEn8lPrgfY6bsAtfpdn7iWbJUMz2tCyNQ0BiAlPq2yYs30cz/X10UmcLFux8BBY6Wv5WcCknk2WUGdI5t4cXN2yDkmm4yNsUDr7jVuwEp7hvlCftI/OYDSh6770Ie67glP6Lrb3W6zNWCvYZkITNQGlo/GakoOyYHeEOgcN+fINtr+0Y/260Z7UDJzk930Qy0Lz8mfm8q47dDt1CdjxxpYJudSVxoisp+cafe851HVrlGjRo02J/ITeWYJMT45UbGAG6A4AaoRgLi3EKAIYIQrgt6YgL9U2UIReAlbZWwpQi9BkhLieVw0I0gSuqeEoDFggfAMlHM/MKW05tjF6e0YSEaRILgtddseE/4oKIR7CoU2nnNOby2wVAAMAESJY20RC5lkbwzICMxRv33G1DlOAcK123zQNwgQZpzrjJn7AqGXgquuq7OdU549J9ZDFJu4JVorgMK4Q1Na0oaUzeKYMgW4qy0U59pgPbJMTIwvCpI1mxiO6mc9+W5O1W50PlvzwJRkgqWIK4ulo2emncCNJYmCTvVMzI1OvsMEPHtoP6L4JdlQ5qr5b52vma9LXYOXAu45tEg8wHgGJBmIOgJE73//KydXC+CFlwJ7CHQsoAFPyRbsfvuPeHHWdF3XTQ6axp6tPbGyA6BpL0tsoOPHP97zHTyJZSKeM2eRpq6e+6Y39Tw18ZDxusgseK7yHYbYt/RvyO8AuoQwSXKWgI7+jyV2nYV1SQiZmoZkCOUDDO1teKn6sVIqvSfsGWPgIHrsY/v4z+63d2iLPo47tnlj3zC/hywTpxLD6dPE1TRXUCzY00/qbNzsGdrx1Kf2FqFLLBXrNWDP14/GCpg4d9ibuRa3+IT60E5rWX9bH5Ft7Ie1500SEvlvSBZeIn9ukwymHbqd2nS3u3Xd057Wg/BTZD294hVdd497NPmoUaNGx58++tHDxLRzZC8+UXytAYojoBphJrENCZCAv8RFGxPwlypbhLEIvL4TZAmjhC9lxDWSwApY9CKwLwnuPZT9kRD42tcOu1Dt4vR2DCSjbCRL5hK37Tnhj0vDJsJfxkW/6GvjTEFJEgyCrvcyePi+YuoclwDhhHnWKSwdKJjIvAPeGnPAnDEfcq/alQvREnDVnFS/MbBaP8UqsXSx86KcUnzL2GEpG3hKoSJ8ihG2tA367fWv798lV6FERbHkzoXMc8Agyw91iFKlXP95LsVbXfW5d/U0J73EmTL3KGssE5e65rRMzI32TWsPE5Ykhdok+cRa1+A5wL20HAPK2XMBSqxZ8BXADZff0vKstjZzsCAEg33ab+IsAvLionvuuePgz9qDprlnAwvDm5LExP94IbAzloxArliAj1nG+w40es1rev4Vtxr3EnL1PfkI0ASI8z/e53d9l9iKeF3mhWfbYwLCBVQUQ/CBD7xyH8+FkBkb7zI2pCzC9gjtBnTjt+9735W9J+KiXoODAAh9zapTX+LP6o6PuzbguD7R/+5bM8ax+DNe8VpBZM/swwmBQ57Sr7FkNybnn78+VAArYa6fwO2h/aWUQzLXjK8260f7qfHi8m39GQuWu5FtAqSXnjdxvXdNQFn9dYc7rJM/Nz08a4dupzaZU+Slxz++n3tT5GDF+j/zzKOqXaNGjRptRkI5zPE0ZF9+0IO6E0YNUBw50SZwsoIyiIROykqZ7XHIkmyNsuWeUuAlHHpF4CV8qQtQ4cEPPgRPlghBARbUz4n6nAvVtqe3YyBZ3K6UB/SZc9vel/BXjgvBP/Gv9Hfp0rY2QcAmdBwChJsXT35yH2DeuFD+KAeUZwCYcQQsmudD7lW7ciFaAq5SOFimUCZrsFr5camj0CazqP8SKsA1Qy4wlL86c+dcG6JYJbkKpdP/lCrWSABv8ynz50d/tFeGlU+ZNpfNOevBPLO2KZEBEvEcird23OQm22X2bNRoH7TJYUINdG8bQ3bT+8cA9yHLMbwZfyhdZAXyD/gydg8eEJdiAJ77AJFz++iag6Ylz3ai7dk3vWnPh/CXZz2r55U+4+txScbr5izj9QWeF7dt+0UZH9G4Jzs90AlvdADrf6ASQDNJ5lIH1ykryTjwSIc0SYpm/98mPIj+tm+wLFTfuCkrB5g15D2RhDwBB/X3u9516Mbrvrgg4/X2gtw/t3ePjXEsE92XRC9I3TJG+jYWoSif13ozlGuAlSfQckoOUVfuofHqUB+Aaurrd795N+fUyb11VncULxtzTzs9W0gSoUMk8fP7Uvlz08Ozduh2ahOrY3MK+D1F5iKZli7QAOVGjRodV/rt3+66d75z2bVCwcTD4URQAxSvoBpUIzgSeAAVrAwIxYRlAjWhMO49rg3QtVbZKkEzrpnJQMsia1t3jLUuVNsAeGMgWQLxEzaToXHObXsfwp92sEij4PkcN3CAmrZukyBgk7qsmSNrM37OkfIEoWexQdBPBmKAWKzoYi2h7/XNkHvVLlyIloCric00BlZbL+YUEC7xEBMjMxayUWjqssvMnXNtKNeTPlAu8JVSHAtcvMEaSgKV9BFL0He/+7BO+jaJDJTDwoUynbhk+A73nSG3uTna9Xxp1KikbQ8Tto0hu/R+QNJc6IY5yzGfE/cxmeGzH43dEys3vBJPfcADemvBuTW45qBpk2cTSnNIig/hn3iP3/CwWEaPWcZ7rnp51yfJ5uz6WIIrz4tAq77KND9uc5t+vMQ3I1fhzwGoctCIL5KzgEtlfL0lFuz2de0ZGmdj5pnf+71X7tch7wllRE4JgKd9qYPyAaPmvrLcHzdewLO+ndq7rZOhMU5dkhFcWQEllZFQAGXImNQvCer2JYcg7dc3wN7ShTlAtvYbO/MoVvn2vjI5ETLmZGdtsWfb39yXgwAH59xQ297VaFPCk25/+97SeY7Muz/8w143aNSoUaPjRpdf3ntsJN7+FDnwfe5zuxNKDVAsqATVZHS2KRHuAAU2H0KQAY5bCoHqec/rM/PFmmitshXQzMtGuCswYJNYfZsCeFPCaem2TYFY4ra9a+JeR+glPDgF17cEX25DrDm2TRCwBtRZo5BvkvFzrh5xd2JlEWuNMuEAomRROo3XlHvVGhB6qC5LlBrPoJQMgdVAYSfR1mfWJkXL91wbl/aS6sydXnNtKNeTuUS50jexgFSm3ynbpYVUMkJf85p9uTYG/CLKISULkCkOl+/aMeU2N0XbzpdGjZbQNocJ28aQXXK/BFyyFuMN1puDBvELxxJl1JZjCU1QxkStw1BMWRSqh/3ONQCYJXv4moMmcYDXPtu1gDV8xf8pP5Z2wDDPGbOQTP3snwnVgN+6L8AgUCwHUcpi8e43lp32WXyNFRseZ//BmxPDGAjJClLZmQOun7LatEdJLMLy0nOH+N1S7wn7G9AVD9ce/ZTD0NKN1z5JTtCXCbuhL9U3B0lje7e9wEGSvb8cY3UBVGovIFxbYr0Zl2d1TdiOxNm21yhvE2+GpXKI76l/7cJcujEbS2vNPuZd+8kNQGVzBMXVOW3WB97tz+rwS7/Uz5UGIjbahrgxS7Y0lxGVrGjO/fRPH1XNGjVq1Gg5waHIs3NElmCdeKIz1zdAsSLCDEGV0p84P4RnQhZBifBLCPcf4YogyiW0dLXaVNnapTvGNrH61lo5zQmnm7ht74pK9zgxreJ2ClwkuN/61j2QS5nZRb2WgDpL5sgu3AKH6sHaxjzO/EUUBcKXue63KDJxvZpyr1oyZ6f6ZE6pwSS5Zg0p2hRhSpw6UfIoe+pJ0QIiUM7y/Dlwv25DvQYADOqe7JiJBxoGrq/8pk4UU1Y5ylYGQFt7KU4OKGIZpK6x8Eh5m7q8bztfGjVaQ5tatG8bQ3bu/uzdQDfrLHECWWR/5CO98lgn9FJWEpa5Hn/gsht3U7wEvyjX5JRFIcAHIKQu1vWSZDNrDpq2CZuhbpuQ54qlKyO0+gCLchDlP6CcF/7o2fqRd4drWYCzlDRf7LtAJv0SgAqo5B5WlayFMgfQWDsBfYkJybLSs4b43RLvCTwTT0exFMeL9VXiRtoPAaTai7/i48pM2Au/5ZljvNgz0k/1GKcfYrHp2epiDgXo9e4/bfafeWlP3DQ0yxI5xJrwWwDg0oUZ6Su/J2mMBC/GMGUamyTt0U71Nlb6PpaLR52MrtGpTZG1klxrivCiRo0aNTpudPnlfTzEGPpMEVlA2JATTQ1QHHGpshnd+Ma9MEzIIUgRnAh4ETgJ1YQk/xFM46o1pGwRmAjXwIajANQ2VTo2tXI6jln0htzjCKsBh4wPIHFNxuhdgTpTCvm2boFT9aBYU4rMY89NQpoo3ikvik+UxoDra92rlvTJ3LxRpzFF+4wzeqsGYIH7tYHVhn5yP1o7J4fWgHlCmfOfelCgKJWx1tGP6mUMS8WoBkBiGRNXsFh4RIncJH6nNouVSuF1n+8ZT5YvfufmLpZYs/5otCva5ABs2xiyc0CeeMSUROvVHm1vBlTh+da/tXDPex5aKybOsDiosbbDD1nxWTv2evckVEdtsQe8JAfEBdU7vsEiT/2EOwDCDe2f9aEFfr5kDy2tGf1WZpj3zCEeEl7vOu1MTMNYdHs+8GfKMtph1Hnndd1TntIfyiUmXiy1Eysx+1Ws+ljz5dBHHF5884Mf7OsbMFG9crDifr8BpoasNo2zcVOePkuCmaH9cc57IvGD7XH6wB4H8NIX6m181Q0P11/mu3apt9/Ifdrtd89bsnerbywSM8ZiXZqvr3pV/1x9E6tE4+WlHnE5p0A4qN02NMvcwUA5z9U5cacTHsXcSWxNVsC5tyxTf5nPF154aKVZWxcfVTK6Rqc+WYsS7UlkMEfmNV7SDlsbNWp0nOipT52PBRsiU/zwD3cnnBqgOOFSFSGQgB7XUCALgYlQRQjyHfgoblEJJJTKlt+f/eyjdUXcJHj+UkBszILxuGXRG3KPS9B1xELR/7s4Fd8EBBxTyLdxCxyqh/EOWPjJT/ZjY1wpZIR7igtQjFKQ6yg0FPGAj4n9R9mRNGiXfQIQ5KI4Nm/MKxaur371lUHDUtGmqI7dr89ZWlDgEEV1bLzH1gDG7tl+p9glhhYFNHGvPIeCyh06ilEAkFg34xX6Gt+gjCa5jDKH4ndOWQvnP2bxb3pT/z3gR6yrvJIoQazGJCRq1OhE0LYZ4qfuByQCBq0pIB++FZAQAIOXWb9iFXuOE90k3HAwEZdg9cD7kHutaXsG97gccHi5h/X0b/zGodUWHposx8m0PHSgNHVwN8ULs+aBezKVOijAg0L4iniBJQ9JZnp1cL/nKVuf4G8AIf2F5iyj8VmyDl783vceugijZG02JqXlHXA3ByueiXcCw/CkWDOWGYCVYQ7g0UNWm+4D2AK4ymR5Y/vjlOUn4FAdcrgTUNhBsvmCH5tXiZutTGVol/rah4wFnu+/9Lc2mkMBTZPwxb3a95CH9ONTHjiTEY01T4oA1O5VjviTsYTU7hyY7UJ+TPxv9QfosvxUJ8/2e/ovrs3WiXmtT/SD3/RfOedq2cZ3ayJWwyciGV2j04PMNaF5eI5Zs1NEHpacxSFJAxUbNWp0HOjv/q7rLrhg+fVyAZxod2d0DKpwvKi2KPJOaLRJOUElSBnsuItGECbIe69PWE+UK+La4PlLwR/XUaLGwNHjlEVvW/e6NbRtbLBd1buuR7JQGvNkZDRXWTkAwZIwJxaIAaL85921nmee++9tb+uVzyVzdm2fTIF85hzriACelBPZS1OPqXnH5XiJ1e3YGgD2JRaU+1EUQc8t3QhrxYhChn/I0pWETgj/cF2sCCnltSXSFOiAkiHeKXuyqsatmiCNV+lj46jush8uHbtGjY5jUpep+60DPMyas3YDdgHwfU/SC+sE33vhC/t1ChDCA322Vqx35QFO/GfN4X8lr/IZGJmwB+6PmzPein8AhHxn8YZf50AJP9pEJij5AZDJu/KT7GPInbnOTO8QCcDnXZu4qKY9Sy2j9Qn3Z21SX3XAw/Ay/av/tNkzXevk3NiWlqX6VJ+5xvcceulfiToyB4Y8HzzPPQDbuM1O7Y9T3hPG6Q1v6Otrr1MPgDMwUdmJp+l5/rcPaLP9R39qh/FORmgHT3GfTuIaczouvqmbfigP5hx4JcFfbXlrvITQ0Df3v39f1i4PajOv7CXqr27qCfR1CGW9pf9yjT5xDXDZNT/4g4dhA4bqtu1BQqNGawhfE95CfFX62hjhwWRL15jfzYOjUaNGJ5r+7/+71xeXEPnguMSBbYDijEtVMvDZaAjghB+CZdDgxJChyNQnrNu6rm5La9yQlwa7F5uKwnAyxGkbco8rA+7HCmAXp+K7BC+3cQss60FZowC4nhJmjrEQofTFTYsgH0DRf7Fu0z/mNGWJIu6d0lC69u87XtoQIK/O2kNxedGLlsWSXKq8D62B9KE+ss6TjEC7gBXKM0ZelFCK5Y1udKgYAQ/8Bpxwnz7Wb66lnFI2ZWNl+VO6vL///T0AaKz0tftSb4kRkHHSrliPKjP1BHQYc8ABKxz1BCpyqXvGM47HaVaj05O2DY8xdr+YqcAOawH/SkzVof2M9RUA8mY367+73poAZlnX7vXO2g/vs9bCq8p9PW4meAkgCn9wDQs3ay6x56xf+ye+tYlMUPIxe7HnkUe0VfmAOyCXcpIlWX+UmekJnnhZLOvwCpZ+Ac+Wus/mUFH/SIDwvvf1hxiJn6h8FnsOL1jiqV8NKHkeIMr44bHhhTe4wVWT59SeD+rNlVzbh2hofxzznvCdy3v2WmXrr1gVmhf62ctv5oJrZaPOPuEez8Pj3/rWXhEAsBrzZNF2jfYqZ2jvntsrlaUf9ekuD2wzr6wb9TTPs3ew9lWn7JOxnNWW9KGxM69f+9rpw7ptDxIaNVpLrA7JueSdHOQOkTXqwPfpT+9DOjRq1KjRiaLf/u0+dvNSetjDjo8+d0yqcXyoFnwT84wyToCNmyhFJTFkCPKErMSQ2YfV2qa01A15TqClLBA6ncpzyTlqcHQXY0lRiNtqmclR2yl6Q7EMl7pvbxsbbFen+aWLrbZSFtXHvPU7Mo+VaR4bV26yQPLrXrf/nctTErV4HiXbXPU5GRmXzNlt+2RbQH7t/UPZXss+pPRi3AA6ipT6UxApefoKj7DeohgltqG+okD7HqAiBxXux0Myt/ADbowsQT3DGFFqY+GifP9rCzCE4o4/AS4o9UDyuNd5hrK94p6tXO06++zjBf43Or1o2/AYQ/fjWazDrFPr1XrD15A5H6tdYE+y2EcQs1bK5BLWJavfWLeUvGpoX896TrZbfEQdEsdRWSysua6ulQlqPkbWwM8TBxGf8NIfZRmAnvJZJYinrIRCAOLd977L+UEdFkbZgMokxorL8yMf2R+UjAFKwDlWeg5cPPucc8bjGZcW6OotLuXQ/ug/hzjAVJ/LuMBDVuz1XovXJllMGSPQeBo/fW6MA1RnP77Odfo+cL9EYa41V5JF2/gYE9+F3Kjrtkv5oaYxOSbzSt3MUe22t2lXwEK/5RBRaJKy/xJ/dKml7XGMs93o1CbziusznpND3SHy+3Of289xPLVRo0aNjpouv7zr7nCHw4Soc8Sz4rhYJ6IGKFY0JPgSTglVBOZYKxI0KSU2H78NnfAfpcvtnPC4FvwpLfkCTPjvRIKj24wl5YryREEsMzlS/n7yJ3vrDYCLeygYrMwkMFka93KXLj3bnOanHqxlzFmAOGUhyos5y9ohAdaNb8A01qcU8Iynd/3jnt/6rZ7J5Zm+z43ztn2yLSC/9v5kewWwAvLUMdYqcSf0bq2YQ/pP/xBU49pGKS4tHllB6XuKGl4RhdX1UVjF8XGtfmYt4vnmHKBSf5cWLgEG1R8/UpZyPVtdlBnl0Lvy4/qs3lwljZ3nHDeL4kanF20bHqO+3zq7yU267pd/uQfXrQXrIJZmvrs+fN9aiuBWJ0uK50EODktehU/W+7rr8E68wPq0JhNvObHw8AuHNXFTDpV7rXuSMGuMj5WgV5KRlJnilZ0EcOoT/hVQUTtdC/wjf/z4j6/jA7VcAyC75jX7Z+rXWEuzaC8pgBIQCl+Ma+2QVeIm+6Pvn/pUP3bmwpOeNB+rui5LX/otoHBpTW5OxSIcXyUTZD/Gm1npmR9kCf/HnTueLdqcfaWu275cgqfCZiSGtPnhYCpWmaicVw4Ux0BubUy8Ur8pY+qw77jF2W50apP5FYB+LluqNfu4x3Xdc55zJFVr1KhRoyvRk5/cewYsJWF7jot1IjpGVTk+VJ+kEsTEinFSnYzOZQwZbk9DJ6z7PHUeok0zNKNSoKV0OOUnTCbmHqE62S+H6Lhm6UtCj4c/vB8zYFqZyZEgTZmIRQFlhFLC5BiQTFFY4tq9a5eeTU/zU49Y6lAaEuePkqQMdaHk+K5PjC/llLKjvsaaYq1/YqVjTgAh3eM3rl0Uyal5tW2flIprDXBTXObm3BpAP5aBmHksA/WdukbRSj1jnUK5Mm9Yp7iOYszCpnx+sqZG+Y+VaCngukbbkiDCWgQqJmFLLFzMA3MypE+sybheW5uxgPQegEI9WQPpC20yZqwpj5tFcaOTi9ZYcB8FebbwAdaksADqBwSKJTDggxcBst6sJe85PCnj+llDfkd1sqShfR2PsLdYt9ZY1ibyWR8pT308K/dmXWevVee4zybGXs3HYk0ZS+cyUzwyJn/4h72CrGz8N/H+kqEX8OgdT1f3NTTU/iT2SN/m4GWIymzNm1K9P+LfPCj0BQ8KdUlcTeN35zv3cdWG5mhZlnKQPY7nSawu9RE+anz1uwNK7vCR/YxdxkiflJagXsrRXmMqmc+QPLFrl+C5cB9nnXUoJwagLinzKla3xjWeHD7rA/1EhsohWeJFTh32Hac4241ObbLeycyyyi+hiy7qumc+83gp6Y0aNTr16e/+rk8mtZRuetP+IPY4UWObIzR0kkpISsy5/JZMeFPWYkcRiHrb5C8Bfyhil17aAxFAFQSYMtldoywg6q7B0X0qp/qC1YB+SSZHQv9HP9q3zVhQ9LQX8OK0PRlDKSGJkVeevFNGjV9Z31279Gx6mu8+wdvLbMPJ9gtI1R/aaMxiwaNfzB3KU/pDH/jPXIjLv8+sUSivSwCpJX0yNvZRXP2nr6N0R3GxHqfm3FJAn/Ie1y3KHssedSndhfUDgBWViQTURTmsODD3si88PyBAlP+S4k7pGjyFpaLPftfPuae2Fgnpg9KqytxNbDTf/Q4w8HvpvgdMiHv1cbIobnTy0DaHV/skz77nPbvuBS/o+Rc+Zz3Zp8URxOfwcOtDYhEgfumC6xoHSgkZAAiq+ffQvu5lf2HVjndYr3iDvrHuWDQDkwAweLB9VB2STVj9XA8Mte7L5Fc1H5uypmSBzDodH3Gv//BOQJiyAarZvzeVP9bINSVvx2e1Sx/EIlybHH65Z0hGmZILsj8CuYy338U2zP/2KOMnTiSrbAc/Ae7q55R7rWtf/vJ+bMyfWCQqlxyhbfrZ9Y96VN/36lCOUQ7gjDO+njjE+h5vHwq7sYn8MOfOPBXug/yjbYnzWe9RmVeJqSxTuDE0p7WfrGgv0Sf2yDJepHFINvFGjU4UWQt3vGNvPWw/mCPA+SMe0etSjRo1anRUdNe7TieQKokcS0Y5btQAxQkaOkldo3wfVSDqXSV/8b9TecJv3H4IlBQl1mgf+UivbAE1ynK2BUeXKKfbAI6x3jB2iamVDMdxj4qLGqE4Cqhxolzc4hb9PQm+Lg4WpYhQPVTfXbr0bHqaz1KOIMXFzvMpreZBLNjMSe0rXWT1gflp/LUrMcgSU4ZyRuEArJknSwGpqT6ZGnv3AMi4MMYqsVRcKHEyPY/NuSWKb2JflWuHpVEyqRJCPUt8Sf+jJYkE8nxrQowwc8e15lasfimp3l3H4tPa0v8BKb1iPRVrEe2PW7r+KK2qkqXW+Pkt1o3mfkAN1yfGmfZry3GxMGt0ctC2h1f7rhuQ0NqQGde8j9UxYKe0KlNH8e5qAOfud+8tzAAlQ+tiaF8HPLEKjJWh/rDugUj+T6Zo5f/AD/RJTewjrsVLE2dRvevkV0N8rLamBD76bo9WhxvesAd7HCAkA7FneYbsvdrlfa38kX0Y8Mr126ucA6Vcw8shfZv+Udcb3/jwgKeUUVyLzytH/bzrpym5QN298GL/pS1JpmW/A+xlf5vzMrCXqWsJqNXXGCN8FUCrve4Zi9fsIM68QtpWKgxDYTfWyA9L3Jmnwn3Y18w96yMhUGLBWh5A5RDd3qMuiaftmWRE92pbGS/SoVzmWaNGJ5Ksqcc+to8bvYQo6mR+smWjRo0a7Zt+67d6PXcpkU/tr8eNGqC4Z9rlqfMY7Sr5i/+BRre8ZS9Qlu6lymHd8PGP94oZoXdIiUBDCU62UU7RNtYwQ5Zq2kZxSHZPCgdhPwAjgTzu7QRu46aO2uU3bQQk6YchZfpEW33lZDb1NgdYDVCyovhqt/4AribGmH7yuYylpM3GheKgXEAbZrbGxX0IGJ0be67qSL3yGvq+DaCf2Ffl2injjFGcKEdJ1ECZAqgn0/lDH9oLn2OJBIwBqyXWIKw7Un9zi4IG4KDIUd7UzVx1nzr6TT3Vxz3mpba4J/2XcVVH1xpTCq3xNW8T06x0eSzdImWSds9xsTBrdLxp09hpR1m3ZDXOelYvPM56Ka3KtrUCz76Op1rj1pz1BfDXH/iH/VP5+AkXUfSrv9rzUH3oWms7IQuyRt1X7tlDCU1iTYmX4MV4FZ7hECaHGN6t7cQC9GKtqIzb3nbdWq8BrOyhnqu+pVyDSt6ujsBH7yz/8N3wIuOER11ySS9bGBtlA7zSzinQeiqZVngnIBX/npujmUPkAONhPvhNnWLFr2ygdLn/DcVr9nzWf+63b6C67UNhO5YcIi51Z54L9wF4tkfEtdkeZSzcm8OrxObMmkryL/KA/+xfwPdYyeozexH5aBfeN40abUs/8ROHYY/myNyX0dyBVHN9btSo0T7p8su77iEP6WWFJUQ+EDvxOBp/NHa5BS0F/nZ16jwm/O8q+UvKYaEVS76SCK4ETu6+BPQaHEViACy1NFQvceumLCsBHpQWz9vUGmbIwiOupBQXSk6SX1A+1N27PvA/pS0xoZIpLgqSvqIcnGhlegmYrR+1g6JkDCmCxohyoD3ammQG+sdv2qefgAfGxTXGixKxrYv7nFWtOJbGXYKcuDxH8eE2qE7+nwLK5wD9MvZVSYkzxgVa/7DQ1V9eSSZAoaIAm5djczAumOZKrIQSS1H5iXNJyYwSbT4lvALyPONSWkOikk8AeP0nfpj7lfnSl/agov5MzDRUukUCR717rjhD+t1pvnofp/h4jY4HmROx6F0bO+0o6jZ0sOZzgKnSqmxbK3BrBB+1XvBW3wOYBcwC8Dl9zh6sf/wOYLLm8AO8VmgN7rCpd71nj/ExhxlcevEOvFrf46HKdp1rEgsy+ygwzPUOISjNS9b1GIClzz2jjFEYOaDk7fZN7yzi1EHdzBm/AVYBst65hSvjAx/orfsI2eo6FHYk+2x9YAg0SDKt7PFlZuapOVrOIXUmA+ClyjCmylBP/Vvvf4nXLDGXcnIIlGRmiVFctn2TUDFr3Jnnwn0YM3tbgHH7WxkfXB+zNLW/JIaxOalN6mz/sqb8lnAyyXZuP2p7RqPjQOaj5IvPe96y6/GH+92vl0EbNWrUaF/0vvf1hlpLSRI9+/ZxpI0AxRe/+MXdc57znO7zn/98d+1rX7t74Qtf2P1gndLvCnr1q1/d3fe+973Sb1/1VV/V/Q0t+Ar6h3/4h+6JT3xi9/KXv7z7whe+0N3gBjfoXvKSl3TXKjMQHDNaC/wNKS01IEnIe9GL1ruSbZP8paxDLCqmyuHuyiormYEDNhA611oaxooKaDNkWQkwAnIAwLiJberKPWapRvBVR/9TOBOcnOJAEfQbAZqgTDmhxFGGCCeUM/3m861udXwzXZdgtn4H0AKR9KEx0P9x800WYv2RRAZJRhI3W7/pG315s5ttboGw1KrW/AT+6c86KQtlM+58S/ugBsjq2Fdjc541D+HSXFTnJECZW5vqL9aU5+sv8yfJECicXPqi+JZujOriGn3t3XynqHJlz1yv2xQXQWssFkRJzOB+c541yoc/3D8PUAssBXhQkF0P+KRUWm+UxeMUH6/RiSdzBfiDDwCpt42dtsvYubs6WFtDwEnAE6vh8I8yIQcepW/wMy9gnrUXK3gva1S9ytjEQ3t2zce0501v6u/FI/U/cDEgm99zMBg+ngMw35fuVUMAVsAywJgy8I3b3/6Qp9a8PYlk7K9lVmq8Tz14RgBZXaNt+JT+Cv8KADe0z9YHhmUW7NJ1N8lnpuZB5pAyPVNbtBOvz2EQUiftrfc/Y41/kx2S4Rngpq3mir2kbPsmoWKW7J1xZ1b/uTiXxizzqo4P7vvP/Ewf59IYxaVfG73rY+/KMNf1tTntmcdV6Tkd6JnPfGb39re/vfuDP/iD7hrXuEZ3/etfv3vWs57V/TsDPUKnqq4WesYzendmc3QJ8Vyxlp7+9H3XrFGjRqcjXX55fwhpX11CZJeLL+6OLa0GFN/ylrd0j3jEI7qLLrqo+6Ef+qHuwgsv7G51q1t1n/nMZ7p/kawFFX3d133dwf+hr6ikoGc/+9ndz/7sz3avec1ruu/6ru/qzjvvvIMyf+/3fq/76jIt6hHQEgVnFzGkakCSwJ1T/CgdS8GzTZO/jNWBBVNZh7ocQnxZhyUn5kOWhlyvEm8nik5JFhkhlrK2jSv3kIWHthCACcTaEteGWC/6L0qbKWhcKTmupUgn8zUrHSf8TvCPa6brgNmx7ovVoTmj77QryhpwwLvrALrGx9yI61YyF1vq28T/XKL8R1EJ2KffSyqV7rl1O2aFNLV2lIltSULznvf0iioLwDVrM8qf57g+iY6QtZaA/0mkUoIRxsKaoZg98IHjMb+QdTB0GKGPAYNxS4yiLXyBdgDsjXFcyD2T1SWg+cwzx136G51+ZD2wbI1rbxI4TMVOm1qXyazOAhwPwpfMy6F4pEtom4O1TWmIj5UhE+wRQgsAy+wT4R1JrMIKT/9ZW17WLhrbs8s1DyzCnwIslclagDpxHc4hTAms4edze1XGDj/CExxExaKwzkztmc6UWUwO9UlZNwckiWuMzwAj8Tl19hzvxso9xlEfAUrd77d6n60PDN2TGNDqUcaOnZsHmUPGjRuvwyD1VIZ6JZlZrClrOUgcJM8s4zUD9vS3+pB/zPN4eGwSR3spcB53Zn1iLzdW5qRnm1flc8f2R9YT9g5k3Owd+sO8sFfYk4GmPAa0VznGy3WxjG109PShD32oe9CDHtT9wA/8QPelL32pO/fcc7szzzzzQKf6J2MT5yTT1daSeQpUZBCx1L3wOc/p+dod7rDv2jVq1Oh0o6c8pccQltJzn3u8wzCsrtoFF1zQnXPOOV8+yQIsvutd7+ouvvji7jECTwyQTelbSFUD5MQLKPn4xz++u8MVXPu1r31t983f/M3dL/7iL3Z3u9vduqOipclBtk2AMgRIEsLs4wRmv5fg2hx4tknylzFQFJjoHnGAYtU0l0Rm7sR8zNIQuOJFQHYCTkDX57HYSryTGkgKrQXwhqz1fKfEJAENoZjAT3mgVKgHCwOWXMkA7ZoAc1xRjRvrkn0orLukIYW7TEaTAPf57lpt9CKAUUT0kzURt9hd1qUkv5sbS6wsXDvnaj9GY2vHHPn0p/txV77/zV9K5pq1Oab8JUap91xTgxH627MJwFMBeKd4koMBCrv7mcpbL4BH484tDt+JO6C+MJ+TVMK81p61FsEnG334wx8+sLj/1Kc+1X3uc5/rfuEXfqH7T4nhMEAf/OAHu5sxN63IveU+t8aS/2Qg8xsvNN+B1HEhRd7r2GlT+yl68pN7a0e8JVZvLI6Bkk984nr+sunB2jYUPoYv1nGHE2YghyMlD0jWeH3jXn0goYrf8NslCVNq3lJaOWfvxMdjcV8Ca3N7VTl2xhwvMOamNwE4makDMOEr9lN7vTL1Ad4SN9gygZTy8Bx1+o3f6N/xGPKD8pLwKlmyfcaH9Qve6BlD1ps5MFR3hH86DCpjx87Ng8whvN9hpnrFQjEJzfSB/b52Gbc+7BPqmcRbyPioc2LlqoP+JwuNxdHeBXAed2ahLz70ob49yL7q9znSbm7QxtD8jMdCDl0DUGbO6pvE8PT8OrRAo6OjSy+99CrWhww+7HE3lhVphE4WXW1TetCD+kMNwOJcDG5kTotvxkPlOCvyjRo1Ovm8fc4/f/n1PDnvf//uWNMqtfDv/u7vDjakWyTt7YFCfrWD7x+fcAL/4he/2P2rf/Wvuu/4ju842Ih+l4Z7BX32s589ULjKMr/+67/+wPpxrMy//du/7f7qr/7qSq9tKQAbZYTQmkDqvvs9QuqaBChLlH8CYTLpEjxtYMqvNzv/TbmSRaCWjZYgTTHzTnCurYrG6hAAIifL/p8qp1ZsKCwACZZXicVXWhrGbSlEyXCP/0wJWS/FTmIFA9j0XMLp2Ea+CYCXk3gCvnItUrKR+FpO4NUJcGj8/ceTIwqeV+IIxuUrLsDaS4DWP8c1EHmUJUqPumeeqTPlV3/o7yidFEfzztLkyqjPWD1ccEHfX7uqSz3Xo/SZm/e5Tz9vgFmUlygxvvsdCA0gm1u3U1SvHQAzQF0fsEhUT31jnlKwKLxL12ap/IXcb457jjLNdZYwKTfWRsqkdM4pZeFJ1q2+KdefsvAqyqzyrS/Xvve9/Xvii3kl3lesdgG5ylnK205W+uu//usDwA8AuIZYcgAR8yot9GPJzz3s05/+9EH5LDn+1GCfpBSrMnwR3471snnjHR9M7LSEwBhaly94AZe8PtYgoALv8Z933/0OnFLuGsrhwBS/2MaqeoyP4ZnW0/vf34cTKPew7AmJnxfSd/gr3hBXX3V1vTW3JGHKEG+JlbM1r53GhUzhMCTJQMJfx/aqIVlIHd2jfQC+WKh6Bt6gfYBRBw7mCR7Eug2Qlf5A8PQkcMHz1N3+mv0n1m7qyIPB2PnN3qwOQEpl+V7XXXucaT/1qV33tKf1e5W93P1L50HmkPqxisSH8T11svez0pTwxP5X80LtJkfBYzyr3NcSr9ZB5U1v2lsacCXe5FBuyd5Zjq05YPzhSDLXej4AeG5/zL6SAyT3OFCNF0PG335hH/Of51z/+v1/x81T43Smv7zihOEbSxeJI9DV9qWvbUN4QxL+LSHrTCKvRo0aNdoF/e7v9uGryNNLiOzzxjcef0OOVWcuf/7nf979/d///cGJVEm+i9UxRGJ2sF4844wzDja15z73uQfxPGxU3/7t336wQaWMusz8NxQf5MnMG3ZEUxY+BDOK/0UX9ZZC28ZpGgMkE8zahEmMndIybwl4NhYrrs68HDBpDBTVB+rwgAf0AvVcbCv/WxgUB0pFHag/8kNiGIWSZCNAhvZ5qT9XKGCKk3QCsrHYpcVJqYzBAWS2LmP0IeASBUF9KD3ar00J0E75VY66E8z/zb/ZvcK6Syqt8cxpyln6VTvMP+3UPgobBUHfUCD1FaOsTSwq5uoyZVU75qpu7lK6gQ/bWAvXa8c6ufDC/nogaqz2ynhnZUyvubVZW02pK1DS/FHPWPnE9Zwy5jm1RbA1om4AfmRdJPSANQS80JeJc1WuP0q1+RmQhtLneYkJFpd3a0rfer4NTLvU1/3ouLr0b0u3vvWtD15rCYD4z0bMpzex5D/uFJ6ZJEJxe00oBbpqQP43v3l8XVqzSVSCv5Rx9nzHl1i0m+9TlrmbJGHatbs+4JSYEsv1rJXsYQC0e9+7j20aHoCShdghjX7STv2mD9R5ScKUMYtMYB/+jQ/g3Xgr3oa3J5bfGKg2Fi8RoAbgwyvKhG1ljEI8yUEMq9McigCfXK9NQFTXAfq8XvnKHuxTH1ZD+Cy+o25+96wkBkuSsFjIzR0YeiXZyNp54D9JZszRHIaa36wSY+3o95oXWh/WhnHxe2LhagsLS/KE71jC2nm9yd6JtN9zS88QpB5z+6P28xxJYhvj4WUszBNl+OwQOp+NuflwnD01Tje6/PLLu4c97GEH8Q6/V/ygEdqHrrYPfW0X5FD8V36lD0exhGRVJf8C5Bs1atRoU/r93+8PJeMxsNSyelsjnqOgvRtxX+961zt4hWxQ3/3d39299KUv7Z7qKHkDeuxjH3tg/RFy4uVEbVMaA/kSK4iCA1EmwAGNCFebxmkaAyQJYpSAKPpllsI14FkdC2fI7Uy5lAPCr2flOaEAB36n5MyRNpMnksWSAJ1A/ZQE5dWWhtoUCzn9DhAhpBNY1StKjMxsLNCWunIvpSFlLNiAZ3ue/hbT62Mf6y0utEHdKBTaFuUGCHOd6/SKwnGNL5d4WPr4jnfsFVxzWv0BWuYMxSKJWSiBxlT/UwIDRmfO7AI0Xar8B+xjASRGlXVoTQL5p5L6rE2SE5dvc9bcSBvL+F/6oAT859Zmqfzpb2WEd8Q9jEKmr1nEcEM2l8o+0IYht7Wb3KQH/c1Nca7URT3rRBnmt2vUhWJJH0jcxATTj8u/78Ygc7vs1+Pu0n/UdJ3rXOfA+oKS9qQnPelAYSst+e1Tayz5jzvVPBMolEMYfMP6xS/R1IGVOZSYoUP/A+XMV+D5JsDLVBKmXVLAN+tHYi7gYuIKZg/DO9XHswMAqY/9DgBjjeo7coV1meQpS/jWHLBEAHXowhIwcswcqDYkC8WVGo/SVkAoANXzS1dqz8aHtJnIpy+0QxvxI2PBeo8LIUXes7Tdb/rDPDIv1B8Ahx8pO14MvitbO4Fkc/2zzTzgLowPq1/ptj11iFSuD0By5kMsF5Xh4JJlwlHsnUPJccb2R3WvE3xdcslhUjCyWEBR+4s16prIQ6XstI/QAo02J7EUf+d3fqf7tZgJH6Gutg99bReEl7ASvtOdliVEwPe4Gzrkaa7PjRo12lRmvPOd+z1yKdH1WFWfDLSKNX7TN31T95Vf+ZXd/yLtF+T7WNyNmv7xP/7H3XWve93uD684Gsp9yviXpMWiTArbEMk85rUrGgL5KNylJVEy4QIwCMiun0pcMiZMjcW/IXh6FoGNYO2kn5Bo3yW8bwKeDcVJJDRKMKENQMWAJTl51waKh2cS7ufAI/8Dp+KulnhIhPBkmiSMcrcpLQ2VrV4BViiowEtCa2khqM77sDhZespPISFEcN8yPrHGcdCrXRQh01RMluMqaAyByiyBuHNbcnH1LudyYumZL1zRKZPm5a4z/i5V+ihnP//z/ZyhRBorCpPvLGKGkvpsYlE3BvgnBlayNCe+5hJgO8ofixzWWeln8yfrzliwgDGfgIQsFQMsONwXayzudIiC/Uu/dJjN03qLC37c0ZSrPHyMUq6f/ed3Cm8yOyvXuksIAu333VibGyVvM9c9hwXVvoCa4072KRaH3//9338AKL7iFa/obnrTm3a//uu/3v3H//gfN7LkR8ryCp1o17AlPDMJnswN88o6SDKgMSt+8yohI4ZoygKtpKmEL2NJJnZJJfhmH9P+ISt315UAEEw5gH7kCtZgeFUsipfyrSXAkv1rKahW8z91jByAf+C3Sa6m3vaP8DDzwtgPAVgI+IQfqWOZ3Ed98S1luz+xCskUEkPhQWVsSnIGsHlJ/2w6D/SRvlsTj7NcH0naUidCAUrsil/O7Z1LvWnMPe5UZXI+e6t+tkepf4DTyGu+l27d2rmLg95Gu6UHP/jB3Tvf+c6DOMGsDNfQLnS1fehruyKhju5+96573euWXU/thYvSqRo1atRoLf3cz/WGJWvoSU/q5aOTgVZBIFe/+tW77/u+7+suu+yyLwetZ07vu41rCVG0fvu3f7u7DSm3o0R/18FGpYxsShQpytlP/dRPdUdBNcgX6zmCLYGXMOtUFlJM6SeoAVxMjDKhyRJhasgyLuBlMhsmLo0YSwQ+VgYE0TUAzpDrkueoMwBB+Z5HRoglE1DDpslSSj+wihIzaQo8ilLFGkI/1W5w4gbpk9vfvgeEoojGygFwof+UH3exCKiATeUQzPdhcbLUQg7AQ9D2/IBv2uZ6liUsE48zmDiUfIfCQDHQh+Z1LGa0zTwx7hQKLk/ejZlxADityfi7JGv6nNI3FpLAWJgzyq7dkDe1qKuTLAAR444cCxr9AeA0t9cA28mWHdm6jH+l3rEEDQ/QbmsGYBqAsAQjjZnxMSYsw6zt2s3OOkoiAQBAyLxNHLA8X/nq56DBfcakdJPEN5QvYQZAUx3xMnEuTwZz/F0R1zCv0pLjj/7oj7rnP//53euWaicniWvYppZRU0kjAEuJsYb31GCNuTWXOGJJArVdU83LrIs6KUrpAV/uYSUABLxhNWj9wJxLi/5YFK/hW8q1dzuEtH8r02Fn9qQ1oFopC5X7eZKMGDdjpHz8ovSisCfoC3ysPJDVJ0neoj/E0FRWmdzHffiYa/ymLP+zUK3ByaOwlN4k0d3Q+sjcvNGN9uNyPzW2S5K36O+3vrXfK8gHxsvhlbobM2NHTrMPpq32CONLXPeyXpdYvzY6OpJA5SEPechBgjFJxOhZa+k46mq7posv7g0ilp7dveQlvYXxRM62Ro0aNboKMcI499xuFQlXy6PjZKHVMAjT9Xvf+94H1hkyVsr6Jah9YkXd61736r7t277tQDlCT3nKU7of/uEf7q55zWt2X/jCFw6yXv73//7fu5/kS3lFVjHxPZ72tKd117rWtQ42rfPOO6/71m/91slMm7ukGuSL9Vxi/iVGUIRn13DtsUcT4NdYzdWCKsunBJAnwBFUWQ/5rA4UGIoBhWEN1a5LNUiqfIJxEp8kYQNBH1DDQmoJeFSeghNak6E2FgV+B4xSckpB23NjoUA2qa3LaqVhXxYnSyzkXCN+ZuoOyDkZhOep2KAAIAqsuadN2mO8zDXXmx+Z/94peeIuip22Jpv5LpT+sZAE6mXe+N/8LeOObup6VSZZoOQb64QFCKCnvSw873WvXricA7YD6sYi2BxzT7J+JllCPeeTaXooLEFilOE/wE5jOhTXjiKceFd1Jlp94zfzwFpUF+OuLkAf/Z3EEcpxnba4J+seMAJ8Pu+8rrvd7brTluyFcSnb1JL/OLqGbcIz57ItxyLdfKoBcP+ZrxJHjPH7sUOSeq9acpixlIZ4mT1tk/AnANfEMk6m7NKi2Jq/xz2W862hus0dBI5Rxk54hVgjJs6r8TGlcziJBwKXArL5jm/4Xsoapeu0A6BkoSZjfOpTV54DuS77UU1H6VK7aTzOo3K5n6O5dWitmC/GljxgvO3xDsszL/1vHBPj2p5CRrQ3+n7OOf36O5HtbDTs5vzGN76xe8c73tF97dd+7ZdjHEqicg2L9CTV1XZN5jODgec8Z9n11oF4ZvSx0+kQtVGjRpvT7/9+H2psjbccuetd7+pOKloNKN71rnft/uzP/qx7whOecLBJOam69NJLv+ze9cd//McH8aJCf/EXf3EQnN613/AN33Bg4fixj32s+/eJTt513aMf/egDUPL+97//wUZ2wxve8KDMryaxHAHVIJ/HxuWPsJsYQRHIfLexUOAJ0RRsZSRRwhpBlQAHnMzJvucgVkkR6FkpobPPXq4g1O4uJUgaMILgDzyJe7PrxaMjMAcYBC4CQtR1CDyqT8FrKw1lRKlKnD6Ctt9f//rehdyzSjrqODxLwMrjoiSsoamM5GVCHEuXgmD8rQHXio/mfmNJufBKTFH/zcUnXKr0L6Ex163E9gJ2Jis4i7ptXK+SZIESdUVixIPnBkRjGSh2ob5gyTEXD6sEdSV5AUAAUijaXulT66ye856XDK6Uvpoo4JS7uCWy5qkBfeTZvos/qZzEzUwCDaQMhxv6Tz25A0VR9P6mN/W8UR/rG/zD3MAn1VuIJQcsp6uQ/Zu/+ZtfdgPb1JL/uLqGreWZc9Zd5j2rVvw/+1xCa9grxPkccw2dOiQpDzoSimMXFoxjvMzehVesCX+CX3LXnbIoBtI5VFzCt3bJZ5FnWvv6EHiIJwRMBPZ6RsAmzyxBNgkL9DlcXbvKQ5AyeQvLbkl3IkPVhyCJ2efaXcdOXkub7vtZHwG1WSfkfv1yFLLD3Do0bvb9zM+AwPo3ibq8G39jDociK5ifXsoXdkO26uMsB52O9BKmdJ2DmZte6fdXvepV3X0w35NUV9sHiU+mu8z1JcQa98d/vD/4afO+UaNGU3T55b28yzhjDdGpThZX59BGjpqUojHFiHl9SdzAvKbIyZfTMa8TRTXIlxhpZYwgRFDmZggUkPkrpvIELeDiUqUlgqp4hroHGAncK7PAxpoJWCLODcVhqYJQA30ABQJ8gIm4GlOECLrJWiwYOaIUxNXJgtBeSg4T3DWn4LVSVSqiFos2nWilYSkdRVyuXdIYEBdrVXOAxQgF3lyJhYIxN+coG5kvxtU8SkISwNNYnK+lSv+S7MtjIQlK0Ew8Swqb/ynrm1qPlkkW5Ndgpeizfoj7oLrgBZ67JHFCCerGRVjdAyToRwKqfqdol3PeszJ26lBjTUlcYAz1NUCvTi7EDZKgbKxck8MEvEbdWEsBEFma4GFDCnOC+yuntjrS14kv+ZrXdN355x+vNbuEvvjFL345ThT67Gc/ewAQfuM3fmP3nd/5nQeWg3/yJ3/Svfa1rz34n1U+64zv+Z7v6f7mb/7mIIbi+9///u49mPlCS/5TnZZYd1lvz352n6AjFlBA8Xvecz7ExlSiiWQajhvnNiDbnJX32vAn4cnJujxkUWydV+E3V9dtEz4byuEm3q9eXFqVrT28CdTPM1n24CXhUdpNRtDP7jGe6hgwMgez+JN7jIUcEGPJfQJQHkW27n3s+7EcJc85NNY/2o1PGxPtJm/tE1ycWofmyBve0NepPHA2BsbKvLbv+D+gsgMse0Cyeq9JetboaF2e5+hk1dV2Teb705/eeyEtJfqY2GanUDc0atRoD/Tud/ex89cQfexkcnUOHdPIbyeGAvJRoC+8sFd0KNsR9hIXiPJMqY4FUYKrUwLWKC0BGNwX4KZ2FaJ8OBlWFuBhSkEoXbwIgQQ+Gx/BMe6sBEQbaKwFYmWkPM9Jdk3CPQUiWX8Joi97WQ8elO2aOgX3m+d6fjIJ1q7E+0i40mg6hlKUB0oDwMw15kFi/AVcTGyvAFm+m1vmQ9zShuJYLVH61ygiJWhtXSgbwG3eWjeUHNkzzSVtXWs9mnWj3AB7+gLoRun3v7VjnceadwpQnQJ11b+0ytG/1jsXmgc+8MpzXhusBeuxzoobUFW9gPyeUa8/363BrHl8A1Bs7fs/rs2sgaZctwMqJL5jPaaxYD1ZlctPfvKT3c1udrMvf4/bMUDw1a9+dfe5z33uwJojJIvzIx/5yAOQ8Wu+5mu6M844o3vf+953pTLmLPlPB5qy7nrnO3slzl5qDprHCbHAzUOMz7kQG0OEp5WZhrcF2eZ42drwJyVPtv6GLIqttSXxAZfyWfKMti61sHOdurBeFtJAf+M3DhRYcONV6ptYwm9+85UtQT3DK/JRsjPnYDbW1HjoVHIffed1MnkF1Jaj5kZCSthjgXSUC/vM29/eH4bZD/YZ+3NsHfrO+yWxFHPgHPA4yXiQPrePkIHti8Yyh2HxdDgZx6lRI0R2/OhH+3iiS8n+5UCAK2OjRo0a1WRfXHNQgfATWMvJSA1QrIgQRNgVY5hASDAk8FJUWCZSgFgilqAcImgRhhMX6KKL+olEuZ4SrEqwhGJfuiWXbkKE0WR9HVLah+IoEfyALYnV6Ls6EvApZHHj1pYknZCBEsBByQMuESyV4V7XDCljQ8CgstSDEOoUnOA6ZL0551LUBNXNacx61NgYF4CcOZdELJTHWLFRLijhlA3zPYCad/NlzCXdeJkDlGvlBmzfJvtyQGv147ZrfiJlq6c6BQSPC+9SKteNOnvnQk1JD1hp7adtWSdTgOocqFsCCVyI/YdX4Dt1u20urK24V1PerEPtVse4RrIUQuX6CzjBfTAxMb08w7r0m3o4MEkm2qng/urivjKcQSiZ2fXPmhghx4W4hU1ZdAAVS+L25bWNJf/pQkPWXaz5WHaYz4nxaW4la6y1NQb6zSWasD+PZRre5DBjSaZcc59VJX43t08N8eTSothevTTUx5K6aaskKPjFUtdv9cfjPvaxnr/iIXhHEsfYKwKg2tdrd2t9m3FKgplSprF38IxYYoE4Zh14nOWCWI7qJ32mD+2hSUQX75PEyeY6uYl7+hoa6sda9syBs/lsz9OveHviZBo7smhiXiecjXlgXz7KBEmNGu2a3vKWfk95xSuWr3OxbsVftHYbNWrUqHZbdqi4lO5yl54PnazUAMURqkEygAVhmvUSpRy4UVrr2IgIypdd1gvvlCZCIoW9FKyGBOFY+BH+CZx+J5iVbkKeMwbEjMVRUiZABJjI6iGxj/xG0Ocq6cScQOt5nk3w9PzEz6FYABcJo1MuLiUwyCrykkt6gVn75lzOxpSGfWTyPM6KyK5pzHqUkmA8KLL6s3SzZ3WQmKDezQmAkzkQhdwcjBVJ2XcZL9YXxsxz65ABm2bpNLcCfMdi0Et9vXueU53nPW/5eNbrxnpWZ+vY/NDm0jIwLsZTgOpSUDeux/qSy/kYuGGey6os47pECVfEVj8AFoVHKrO/l8C8enMnpewBbkpwFJipTfqSsmhtTQGBaQOel9iyoRx64CXqtM/Mq41OfrJ24bPmpfniHd/xuzURqyj8amifWZJoIi67Q7T2MGNJptwAZkuBr02yB29SN88gzMYTYqnrtzrh+2QGso779a0Xnqj/5BYCOM65goe3lslb0sZNLRBPRIbvOSrH2RxWR3NC3KRY3iaETIC6xCokn815n+xbPjCm9lJ7fYBxe4RxVm9j7/PNb344H4ylufK2t/X37SKGZ6NGJ5Je/vKexwlntYSs44c/vN/HWCw2atSoERJfmD66lERDknX+ZKYGKE5QCZKxOjTY173uYYbiMlFC4s55JygSsAlopWCFxgRh/yufm7VybGo1GDMExCyJo+R0PO6gNj7gEdclwA+AIpkb1Z1yBzTxnLi4+i8xnwie6k9oHgoy7v2Nb+yBSIrFpi5nuw42f1wVkX3TkPUoYDnJf1ifcPWIm71+NjdYKpiD+iiZgWMZZzxKIKseL6C76ygcQHhzJZmMN024w21PnET19aKgmqexxKOQCQnkutrSb4iG1k0sMNTZXDOvAXAsTcxzwBkQZAxQ3SQw/hiAUAMRz33uYUIHlARQ5X0lMM/yx6EGso69ykMCFinWe5k0aaoNggrLHKvOFGD9ntho5gneoB+PIolSo5OX4qabTMHmoLkE7Lam8SFJwOwXQ6Df3HpKpmHlrMm8PEZrYwQv3W+WhPqYO/yaqpt7ySzWfRm2Zck+rE36MDGdyTn4BN6R8CiASu1nEb6NK/ja+IT7kAu2pXqcgbH2IWMTORHPNScz19OP3r3WWs7uQz5IOB8v9TG26mydGlOu7rFCN0fsw+YAeXiXMTwbNTqRdMEFPRhgH1pC1gQrRTKVDNCNGjU6velLX+p5AnlgCZELfu7nupOeGqA4Q7WSHqGwdA8hVBGabSwBEwmRBHKgBMGK9VSsvcYE4Wc+s38OCz+CHguyMmbaWNbIuThK/tcOAqKXeGnvf39fJxOesEsIBA7IXEl5SEKOgCoUE/UEeELd41qmHQCcxAGiiKQ+iJVC4kMpa4ngvI9g88dRETkqa8kht3Jtf9GLelAZGJfEPZTGxDTz0vcUfTHNrnnNQ8sF5U2Nl/fE0DKfjJl4MxTLTRLuANJYzLCSUL+aWMgl/ucSQHFo3SRrtPrmZb1RDhMqQN0lDFgT43NtrNApIOKss+afZzwkVbKp6a+4alvHXniYvsJf8KMb3WgYEKnn5+Me12dEtPYTN1G/AxP1+XFLotTo+JG5hJ/YC+0xsYZHsTi2zs3PMVfeqfUUN9pNAMBNDwQ8s+bjDmXm9pvHPGac/y85/Jqqm+cDqsSRrNfknOt3YigK3yLMCyu7yDpAJGPk0FPd7AtDwG1cwbkEqg+eof/tIfh3snqvoX0lodmEwhvJauKu2TvjjWE/Zc0tVIXr4vbsc4Bz9YulvX5aazm7S6q9S+wdxiuJdWT9Nna+l0nPWNbLU7Wr8AKNGh0Hsiblprnznfu1uoSs8Sc/uU+mcLJlZm3UqNHu6G/+puse+9he1ltKd73rlT2/TlZqgOJCijUA92AnUUlcwaKJMAmMA5glA6Lf4xLNoof1lN8IYWOC8M/8TNedfXaviBBKCZ1Ls0ZOxVEaElQFBickapMTaPVm3UHRU39CP4HQ5kiQZLUFfPJsm2yCjLseCKkOFBuAR07pCadx8wkY45R7zsVy10k9jlIRWQoSHrW15JAlCKX2JS/pLdkCggOItMF7BCVz27wFTgHZ1Lns+6HxKpOPmMusVZJReh8Jd+p5Mkdj6yb1NifU2ZwBlsn67LVpVk5z6253m7Yw3BXwbTxiZcJS1LorLWSMM6AfuKgtQ0Dg2Px8/OO77iMf6X83TxyaWEMtiVKjJYQnJt7m0Jq1t/h9bn1Nxd712oVL8RIA0wFd4gBmnVjb1u/cfmO/Hwv1sZQHjNUt1mRjwOkUgBVXajIAHpGD0YBfeInf7AusxuUZqscyiT54K+B5ZZbj8gByDc8o95lNDyt3QeGN3gGu+gGwqh+MsXr4DtRNMhO/xwsE0AuUNV8Sw1gZa8OA7EM+8Lr97a+6rlD9G7lhE9mzUaPjTngTJR//Wkr0KPKRUDONGjU6/ei88/pwCfbzibDsVyJ69Stf2Z0S1ADFFQLXGWf0ioAECYRDkwbYFndCAFuy5ybuISJEuk5GvzmAbK0109IYT6WgWgrmOSWPBQJABRgY9ybkGsqMBUKRICACH9VduXFd8859lpDp3W8JPl4HdJ8SnDcFSY8KoByjpSDhcbGW9IyHPaxXtNWB9Yl6A4zM6Sjd5nNOT4b6fgqco8CzgmPlwk36zDM3A20p6eYegExdassj68v/rltCU+tGvQGHAFB1NobbWI8unRe7Ar6TiRu/wquSUTZui/5DErpIBjNkISmRg/VgTlCU8YjMT3lGjPXpEIe00W7JXMl8Ya1VuoHaL8wp8x1fNG+naMxddu0euq2Vd83HxRZkyV9mmV6632zCA4bqppwnPWmdXFAfnrJUUw88PKElEjMVEIY/2jsAezmAyjXq6XeyhMONsQPINXtd9pltDiu3pXLvTr/ikdqoXxLaA8/UB/Yl9UscQv0OTMxhcUKPbBIGZF8Hn2Prqv5tE9mzUaOThV73up6Hvfvdy+9xQO/g2Fpu1KjR6UMPeECf0MneupTIAOLjkxFOBTpFmrF/Iki+61294Awgi9BqwyHEAmAIt2XcQwIkJZ7LZMC1IapBmrnMx9vGeCoBIGUSxoF9iaFHOfJs4IPrCIsUCqfuFKUyGY13/yd2Hms0QjSXKJaZQenLgO76iFI1RrsWVHcNUA7RUpDwOLltRUkQY0s9Mz8DMJeZzPPfUN+PjVfmv5f+APZt2ib1vMlN+mySQGnPUb/E8dOvkpQsBYTn1k2SpWwKgG4CHu8K+C4tjGIlmoMOv+XggItO7R6uH21wwATtFkcoCrs5qe/FF2Jd1UDERmvJnGEB9Su/0gPb5pt3+yPrRHMXP8JvtgEi1uyha+qedafe558/zMc9h8tr1umaLPeb8oAaBFK/TWM/xpWa9Z0DnLgoh9fmwNR4cU1XH/GSy2Rw5CJjaFyT5RiRnfAQbScjrNnrkn16m8PKbajeu9XfbwDCHKwaO/3rAE0/qVsSnQFC9Zl7WCWwbrWH2fM3sZzdlHblHbFNfNFGjY47WYtiV+N55KElZJ3f8IZd98hH9hleGzVqdOoTA4yXv3y5VSKihwlzJ2TOqUINUFwpSP7wD/e/AUkItwRaLj1xeQZC2IgiXHoneBLGuUtL6lJmvB0DaZYGK98k6UMNACVuXIAa17L2IvQ6aZfZ773v7cFUbSqT0aAkbwE8/NEf9aCiviFUszzJIkvcJMoQF/Bb3GKZoFr2t2dRxsSxGxNU69N3/bHPk/Q1IOFRWUsuJeMhRpI6fvzj/fONsz42nrGiSNKSISVhSLEo5z+A2Zx/05u67sd+bDMLIfV0AsQSRGwq8yF1Uk/rjjXhUoVs02Qpa2gteLwr4LseDwKu/kq8VO3Dh4bWj9iqTuT1qz4oFXZlKK/FxWq0DYnhe5vbdN373tfPe0CLtYFHsKq1XvCIbYGItQk/1tAUH89egldZMyzzlu432/KAcu9jgezzJvxN/+On9nBlUZTx2fLAVNt4XTgoKhOvOKTAMzxDmBRyEUtU4+rdf4DKAMlLeclQ9ukI5p7FrXrusHKXY17H0sbX7XfqmCRnwEQAOblFe7lBu8fcTozCbSxn19IuvSOOYg9t1OhEkrVw0UW93JpwNXNk/T/jGb0MJeZ0o0aNTl1iYCHUwT8sABODndgnn/KUrnvIQ7pTihqguKHyUCoJNh3CLAWBwOZkWmyhCP2E3JRDqARKBlTcxUmu53NDfPWrrxzbbExQrQGHMt5dCQCxzkqiFSd0yawbAToELI1bD2tM3/UVV9cyI7Y6xW1VQhgWjEPCaymofuITvTIDsNV3XoBOWWeXxiaMu6zydnWSXipuFCvPXQISHoW15BpSLzHAPA9oxAIVCJwx1l8ARm0cUxJqxaKe/6xTWGOweFHGpi7d7nniE7vu53++B+cTkwu4vAlQuQ/XyJLWgse7sswdUvTMOWOS5DLGSKyf0irFnLY5UoZZ+uQwwMv15oAyzYEWF6vRppTDAXMybvWJ0bdp0qajpik+ri32KLy0zvI3t99swwOG9j77nn3WPryWvwF+73jH3oVbXd0b74S0gyzzqEf1n3OAh088/emHbuz2EoeM2VO8tIOcwZKR+/ISQLHOPl1bqftdHV23DyC5HnN9UXp3qIt+dk1iTJL9arlR3c3/WOEeVciIfXhH7HsPbdToRBPr67e/vetue9t1mZ/JVw5u8dBGjRqdekT2YI0Mo1hCZAR740//9KllmRhqgOICWgICEZJlBaO0AzwIbYAYgmbi5Pz6r/dWC4AV7pkU912c5AYUItia2DYzSsTtbjcP2AVwUFegj1M49WWdQKFINsIkpEm8IO2KYkFwpkAlAyABFQCh37wnkLvF5Lv71HNKeFVvGzgUn/VDFJGc+nM/54K9JDYhhYVy47WLk/RacXMiCUhlCTaW8TIg4bag0S4zQ5f9pS+NvzlkXhgrvwF/y8yOY0pCFAtzf2j+JwTAti7dnnPuubvrgznXyG36ey14POdCZlxY5iSMwlRdSkUP32HVSbk3942zdVhbpWin9WBeulbdY1WkH9QBAHCd67S4WI22I/NN/M7wUVb8xwWIWLLmp/i4desea1s5QLCl+82mbqRje5/1bc++1716b4M1PMw1lGHtiPcCXoA32PPxdO0ABJcAHt6kbxxA2nPt38DE7P2JewhQs79wYeYGP1enMvs0y0ltjWcE4E4MRSDlvg476jHXltK7I4es2powH2Us7ZLnazs+fJS0L++IfYQXaNTouIGKwu3c7Gb9ocESwgfoUYwpTkXwoFGj05lgPfe7X39wvIS+4iv6LPDPec6pEzOxplO0WfsRJIFghPoys6BJEhBIIgdCIuCNK1AsLyK8sQIEJgJtvPt/WwUqigQLSfULiEGoB6TJOgRYXHqyfKMbXbU+JQAZAZ6SQFHyLBtmsheyWIgiRfmgRLg+AfhtxmItshqcEl4pdeJQEUwFt1d2+hzVwNSS03cCM2WO29GmJ+lDihvrC3WlGOm/KZf2beIOrYl9NKcUj/WXNukn/cWykNKv/mW2R3NrqFx1uMc9xuf/rly6d+3KOFbetrGm1oLHUy5kSXJASGX9s6QufqdkP/axPejtOwuZjEdtlWJMrVPAQ9avdZ2kGXFVdKAwlzCjUaOTEYhYuubn+Li140Bs7X6ziRvpkr1PcqZN4p7mYM+eh6/jAfZ7fIWXQOICG0MgmnFUXzyETOIzqx5jmwNI8pNDQe/aRx5ash+En5IpEsahlMXqTMm7PHwbG/N4d5g3wr0kYRgLRQcvS8LbHBXt0ztin+EFGjU6DkS3u/jirnvQg/p1ssTF0Vp6whP6w3mgZKNGjU5+evGL+xipcJCl9HVf18dMPFXBRHQKN213RJAkIIojSHCK62+ZqCAg0O/+7uGJPSW8JMIly0Rg4tlnXzkO4BhIM0VRJAjugDpKDMEaaACAo4CY9NwXhzazNQpdbfHkmTmFV772UpyAhYkfBcTQF3Gb9F2fEcopFIC4MeE1p+nqMwTG1MDUktN3fSRmQeLVrVUyxhQ3ZRMYWPKpgzbmvxok3DTu0JrYR0uU4iX9ZTzVI5YUyq3djbWLFUvK9bt5bw5S9syRElQ8apfuExlrahPw2HrUn07DKeL60loGJupT82xNXTzDpgfgHbKkKteR9eCQQH3M5QDJ6oDnmUuUeZanXKM9s1mhNNqGtgUiajDLfMVv5vj6ENiE3y1d8zUf5xEAfFcP+4zyWKdsApiudSPdZ1zeJKPDO1jnhBdop9+Rw7TIBNkXyDoOOAGQyN6fg0dlJMuxvWWpVWHNT8uwMzU/3VXikZLG9m7W/ORDma/jIi6Ttb28pBOdqKRlZW7UaDuKpSHevgRMsObtK0IcXHppr/c0atTo5CUyojAv9LI1ssNDHtLvr6cyNUBxAdkQAGQAOxsEIZKgTkAHBP7/27sX6Pmqsn78B0zUfpHm3zRRU0u0UgGVywJUUERUJF1qIpmghIqBCyRFpZ+igSJCICniFcELclHUBAMRueS1xPgZWq4kshtWttTUXJr6+a/XHB7YHM/MnDNzZj63573WfOfznTlzztn77P3s53nv57LTTrWiDxRtyjOyjMLZVPCdg+cWMpFyP4/i6/p+T3GPJOBxPedh5Ljvs8+uK1K2GTJ9DLqSgGwacAy0V72qVkrdh/YxrEw6r8jDRpmOhO6TlNe+u+mTjndthg0FAFEya+XecYabv/UNQ5T7M1KVcTGOJOxrMPbJfdTVKO7bv8aZqsBCZ/0uCuzoT5/Jbei8+lgf+Mz3QbxH2PN6MFqGyjXVlzwuZQEZAlIJOJ4xblOg7730ec7O7znJl+pzhj9S2PyNZynk2jjNwiyJ1UbMlyaZZYzyGhu3hratubEx2GfOhxxXFf2qq2piDJBLPPDnIUz7bPbN43k2yYuvlIOl7AGyTH5jG5bWf3oGshDJR3b5jfORHTYpfBdpTxzj92SN/3ddD7rK0z7EcF+MW7vpO7F2a5frr2ahkrbnmlWZE4lhSEXzmpd06GnjEFXuRS+Z+895TlWdccay7jSRSAyJN76xqo48sl81ZzjkkM1R9T0JxSkIpVqoH0KE11AYDpEvUP4exyHtGCtIRrv2keNvXAGW8IJiyFDKQ/HmAdZF8aUsxu5+6QUWiLyDQxr/4wykyLMYyiqvRe/aoY+EI2kzY6+L8tp3N33c8VFtGMGLdFUMRv/O4qkwyXDzjOV2oji4JpJ3EknYx2Ds6oFi3HUlwvr0r2fLaNY27S+FqWsgh/UrofmBD9TkLS8WCpTxHBWCVR0tvXnXKmbx+BlnmHclj8d5RPoNglbY/yzeR32ecxjsPKgpylFMyjMP72eG8zTv4kRi0ShTfZAvJZnFO8yYbVtDx80zsq1tnpF1sfklbJiMtYaVcC1zhbddFJexvrnOPORVVzKyrywPOWXzByloU6htM3OSHARrnL6P4itSZDjOdSKnoNDnKJ7iPD6L4i5gTeqzHkyTp9Y2etiQhUfa7mHS2r3ahUombVJnVeZEYn6Yy4oxqOZMpnaBDRUVo801Oe9zniUS6wf0BsVU+pKJhx9eE5GbAUkodqjgS+kOo4WC7/soxoEElKvQwhLVje1cMVAo6hRbRJPjSqUNIlwZASPJeCQr58Ho2tMU3yAB3EsZ/hOIvIPut693Ql+0hYAxsrSZQs3YkHcJsdhFee27m952PKOG90rkgmMI8h6c1VNhmuHmGcub1LWCY1eDsasHSoRcdyHC+vQvI/rSS+tnx1NOH5RhsD4XzuEzXqmPfGRV/eVf1n/rpyjkc/XV9dxYbaNl2rifxXuzzeOJl1QUQjj66FtXQh3nCdQ0gh0n+a/xaqw0n+u0EPK+88h8EM5DHiEMHE8mmTfhZTrNuziRWCRivpDv1s42Msvn3rvm2W2bZ7EZ5XhrqXXktNOq6tBDb8kd6HzknCiFcm455xDkVRd0nePWLWRbFMGheyD6bBK4x6YXXxRmapODZAC5T+brHzK+zJWr/frFxqJ1wiYEeUJPcb6uekBfQs9atajw7z5r92rlB+2ySZ1VmROJ+cHjiHxVzTlSO3TBRRdV1UEHVdXLXpZ5FROJ9QB6Ebu+T5jzbW9b62OnnlptGiSh2ECTHGBE8EygBJdKqvBdi4ldfoYDxRpxGMq04hyRqBu5iGgqlTaKL7IriErKnwFoYUK+MOIRmZMU3zAkeEMa6GV8flRflu9MCFbT+F9EjqG2EDDt0SfetZnh10V5HRfexChBnGkPI24Soemd4RMVJU1u77Mae10NN+NgSMOhqwcKdCXC+oTjGiPGaeS9inbr1zAOnVe/KEzkHpFpYYxHIR/j+2lPW57RMi5P2rRx38fjp83jyTXf//461QAS25iPa7RV9pzkCeQ6jHEywVhubhxMCyGfJWen6u6RC0yfRfVSMoantmdd5n9NJJaJmC9kOeK7WfipJLMm5dkN78MI6zcvYp5Zr2IzyvljDrheeB4ia5ZBXk1DlzlO7rzpTbWc8r1jtZ+MlPeZjLFZUHrx7b//eDmoz7zIdOfxXgJRGUWe9N3Tn15fZygSaxyht8jCI2u9UEmZU3vSJrXiPDa46Jf0V5teiult5GTxicQicPzxVfWQh9SbsOYXWWjOTcM559Sb7iq+ZgXoRGJtwppq4+Dkk2vuoStue9va9iMfNtO6uomaOh1t5AACwkCyy864CEU1qhVS3BAqZfVUoJxT5CmUdoux2yXRxGih+JXeFUD59tvwIHDcODiXSos8vxgOSDS/Zxy5JwYPQ4GRUBr/QxScmIRmCBijAgnoXg48sCYsuhBuzdAh9x2JkE30d7+7XpSDDCqP/8IX6v5D/MpnGN5V8xh7sxZUmRfTiEz3Q3jpE+PJeGUAllUw/R8pyKvW544zPh73uDpnHkN6nKGnz51HX5oHnmdpwDMejTevmB8x/uMe/CaMl2WgjTA3R42J8CTWr+Z0c9w3+xu0w3m8hEbytnWeCy+8tceTuc5w1k/gGMbcpLk1yQg2f+RRZBw6pkTXvFd9Q/CMX4Si46J6vGcbJIL7IXcyZCexGoj5Et5Xk8gs7215dkvvwygUYq6S5WSkOR55icHx1pEdd6xlC2LmCU9YO+TVpDnOYBViF3KKLLPZRz7rO+kLrJdIpchvqI0wbt3Rx2SB/tFv9KAgXcFnFGly0H3YaNpvv8V77C268MjQlaOHvJ7jpm1Sf/azNZlhk9x6ZNybR3TIeTaTZ73nRGK9g65knqnmzF7sQiiaI9YYRCQkqZhIrC2w4xTPxTH0xYMfXNcceOITq02FJBRvQjMcCijejHYKKAWZUYFUYWg4jnLqRWGTtwkxGAYIUMAZIQxyyl0Z4ohg4+0TuYRK+J1rRuGTSeAy/4pXVNUf/3GtNEbeRJ6JDBpGg/ZEmCt0ybOHMBkXojmtD9tCwPzfuSmyCMWuiNChT36yztPnHvwfOdlGgsbxH/94VZ1ySv03D82+oaKT7mfZIUOTiEz/VwE4xqCX0D1tZuxGUmjf+z9yS4hGGOQxXpBEwpEZfuWzZlheeWVtGCKV/I7yZB4wKs0Pc8NnxlBpyOnz8Kgzll1vGWGybYS53KfnnVffH1ITuRnFYtpya0V/8+IwfxH85r+5r10UR8ab9ssNGR5PxoRjyAIGt7ng80n5uyYZwc6rDcaZOawP9T2j0fwkbyijXSrH9gnBc/y++9ZyRV/FOHE9c0+F18gRm0gsEzFfwvtqGpnVzLNrDlAWw/swSJfY/BAeGpsy/k/umXNkhfkShJsohLVUNXfcHG96ZmpTrAl0BseSbdppI9BaQG7RUZ70pPZ1hzxynP5zHseQ9fo9Nph8r0/Dm3koj71JhNUiC48sIqpjyOtN26T2jETLyJGrL8hxz0hfDLWZvOw+SiTWAuhg9CEEociOrnKMbvWiF9Xe9G3RK4lEYvn4sz+rqt///dqG7Iv737/euKMHbTYkoXgTSqXbIArvBUZH5GmiZDPoETiU8iD+vDsWwSDUsyQVm0ZFKFwWHQoxxds1kBul9yMvCf/vYoxgwS1IZ51V37eFKiq0Moze976q+uAHa8UO+TEtTAuJ8vKX14tdH6VwlmIWXWGXQL+UROW4ROte7peyzFhsSyg/j7E3ZH6krrv5QWR6jgxe9++3jAjkMWXGeGFMX3FF7XXiXMar5+h4RrFnIPSchwrScffd62N8ZqwQhiWZiJhDpjm3ccpID09In8X/eccK/UDcrWYFybY8aYxlBpOxHESDNkexGHO2OTaDUOPuztDyfMwnfcNAc14bAuavvxlnxprrRghmeEqFrBg3/qcZwWSBe0EGI+TLirbaEQm+pxlsfQx6/SiVgntTqCLysZbFFJaRHy6RaCLmCzkY+VmtuUHqt5FZ8Tvy7dxz6/EdvwFzNTZJrJ3ml+/MaSRb6eEem1Hk9Vqrmts2x5se0OYx+U2u6YcgY/193XV1e8gVG3g8MskesqBZ1ZiX8nvfW1XXXFPrRtYZ/aX/rEn+1mdDeu1PI6wWFUWw6KiOIa7nOTumGS0D1m7zwjGeLX3RGPDMfBYF0+aR6bwmk3cAAF+XSURBVMvuo0RiLYFzh1zjZAydryvoc2w4JIYN/UQisXqwBqrGjufpi622qqrzz9+cZCIkodhQuilewn/CeyG8FCjMsaMfhAQDJBQvA8hvKLqMnPDmQh4gbcqqzhQuXlJeiB3n9ltKGMLDb52P0tfmwThuMTvxxPp6isRccEFNRFAuo4AGA8zutPMrstAGv2FUeH/Qg/ophUPmL2oWxtF3fYjKIT0VxpF+83pbzLqbH8aBccNoY/QZp9qFFGTE+R7hFePWWAuDkQEpRNo45IXCM7FJzEIQc0hc5/J9EIgIJu+eqWsLnSaE5elazQqSbXnS/N99mFNexjbopwh9FO5Xjs0g1LTDefSTvkYc+r9nYF5FKLdz8OotQzDDUyoM9nHjv4sRbOfbPbkOgkP7vLeFbA9BZEc/+jy8r8qcc37jXhedHy6RaKKcL5Gf1aYH+Wlum+NtZJZ381yqjEhZ4thIEWLOkYPOad3l5WUtL3M0lptRPl8PVXObHtBe5FToB2SB/iDjyXfrBUKw9FxTqfB3f/dn89FCRETE+h+bD2SRVC9DkUhthJX1TsoOeg0ZKfph6CiCScV8hqocPcT1PBd94rn6O37n2TqXzx1vIzHWrlgDPUseUrNu+C67jxKJtQj6IT1YHvk+1WDDTlRFVuh0zpFEYvlA6tNZZiETb3ObOj/xZt4USELxJlDAKMHCRSN3UihFyJgy9xxDHpnIIKHA8XpAOPheyCnFPcKVHed7ilqZxwgoxRR4L8q8RYVnhVdZUdqrywLjGIq+HDlR6VKejjIxt7/dV4Rhl7AAar9jKN1BJHRVCofKX9Qk2vQ9DzoLbtt524iaoTwVFhXC03c33/FyMiAEw+jzjD1X+Y/22OMWDzmGsPb529jx3PVhPHf97xz60jFR7KMkZiGIOX3EIyVC44yPIBYZkgw1xtwQhty8+ZeapLa2hdeg/o1raIN7iz6wUVCOzSDU9EsUXSIf4l4iV2kZAoikjxDMCPsjK2KeTRr/0/rOnFOhlczhMTiPwdZlTDf7sZlzLq5h8yIJxcSyUc4XkQGRb9h4tRGHOGyTOdZymynmkc28ICTDC5E8Q66YRzyYm2RiczPKPFhtmTcNzc01ckmbbYrSdYJQ9CLn9GFsioRsoWhTlpuV6a0DT3lKvT7rN/IhyFph5Y5bpOe5PvfuWcozq+iX+xkyimCRkRdDXs9YNbbpoPrE2hBe8vrHM9X+snhfFDEKuU7mz5Lzc9l9lEisVZxxRm3P8VTqQyrSD+n49Lj3vCdDoBOJZQL3ofK6tbIv8EXHHltVhx1WbWokoXgTKJuIPOQM46KpFEUxCgo4Q4PSTTFCtBhMDBHhiJQmC4NdYB5LzsvIOOGEWlETmhrnpuQzgqLYCyVczkWEElKCgv6qV/UjsLok5o5zN/McYuUZS5S/ZjXZLkrhEF6BbUSb8F3eYsLE5a0qQ8onETXzElyLCuHpu5vveDuewr4RWZ5NVNwF7RJ2ppJ4s0iB/3uu8bnzGQOIxSCMIjyjScyWhJI+33PPuk+MrfBE4Zn4ghfc0g/zGHJDkLdNUjvyhZmPyP2o+h2Vt4L48zwf9ahbxmYQapE/Fcz/gL+NafPecZ6F41zHOI88k+4/PCWnjf+2vjPn/E5OUJ7TSMt5DLauY7rsR+3jBRSbENrobwsvT2gbJhnKllg2yvkSG3jGrTE6Tub4niwzP6VpABsuESYauV7lxJJeorkZZY6YF2Ve4tWWedPQ3FxzDZ/ZeOJdTbeJDRYeNpF/d1KqhpJA4gXvvJE7Vt/6zObXH/1RVb3mNXUExTxoElYIs7IKt3vX93IEkpchx4Ygr5ZdOXrW6xlz0nf4LR3PM3BMbHAZ19ao5rgM0tHYnzUNzFqqrp1IrDak1fjDP6w3N4z7PsSiTVrzWMTZC1+4yLtMJBJg8/MP/qDejOuzCcoetwkgD+pWmzTMuUQSijeBkiX0U9XWqKxsgPg7PLYY8+HdhpAoq3nFZ0gMxAujJbwbLCaSdCJiyl0nx1g4KMpCthjpFHfn4IVEQexLYE1LzM2AiFDVprHk2trgHtvyDk5TCuf1CnTPZ55ZVddffwupEQYNIpYXqHt0njKcZxJRM6uxt8gQnr67+bw/rrqqJrHimWq3Z8V4Y1Q5RluDMPa975BlDEbtDgMx8gDqjzgO6cgAidyI4clQepuWlZsd67sjj6y9IkrMEg4+FHnbJLW1M+aqew9Xdu32jCPvlH4tx2YQavouFgp/BxHp7+hHpGJ4+0R+Rc+KEe07/dXVK7bsO32igI6xYjPAJgDiUruapHoXg63PmI5+VJCHl3OE10cuTvdpTjIiM5QtsVroK2uMX2uguRSeeFGcyXusJUJnEY7lZhT5GWRNmZc4yL/VknldUG6uRUoX89ha793cR6ySY9pIVlg7yLM22RIEkt8ygCOqwztZFRsRSL+jjqoLpHUlFds8NkvCqix+FZEkfuOajtWfQ8qkRVeOHup6pf6FcOWpax2y5smLjTT3vOK5hvxHMjqOjLdhO0vOz2X3USKx1sFh45JL6kqxnE36kIoiiujWZKkNmUQiMSxCz6C/vOtddYQDfTBSek0DW/Dkk+t0MIkaM6lbp59+enWf+9ynuv3tb1/tsssu1V9OqKv99re/vXrEIx5R/dIv/dLo9ZjHPOZnjn/2s59dbbHFFrd6PY7r05Ih9l3eQDv0BDrFNBKNM54pZHbwI0QqciZaKChtlG5Gxf3ud+vE2FGplVKFVCxBIUZkWnz8hhJIKQxlMIz9UJKnsedBkDAM2sgqnyNXVG9URCOqOXrn4ab9lM42dFEKw3BpnpuRNslAYlwpBMNIQ44hMnhFUYzdt995LshGRp82IGoYQtOImjA6GU/euxgZfUi/Rezml6FH+jCKqJQEcYTdeybhMRiEn1fkSgoCMnJ/6rtQbvzNwFRFWzEXOzTvf3/9rBnLjJNSEXIuRLnrGbNDVe0siS5jftLY926McFH3Xs6JMKr0g7EB+sE5EPY8gBGg7t+41K/aaezF2Iw0A+Yj71hhklEdNUID/a3/yQnvBxxQLy4nnVRVb35zVe2/f31c1/E/jmxALmgL49h1yBhGunnRd272GdP6cbvt6vFAqY2iFY7Tnih84VyzzoNEYpkwTuV4DRkWIb7m1F/8RU26lGuJuSoERqXzZz6zXvvNL7qA+ehY89M8de5FyrwhEO0hp7SRjiGNiPZoWxSjMedtXGibNcFaHHlTmwQSfSZSStCH9CU5GxtSZC+Z89rXdusjx0jtII+Yglje/Z8eFoRVmcaiJMXoZY6ZZ21uQ2yuNNfCckNT3w5VfGee64X+Zb1BfNNLI58lndXn5Lj1wxpIJyDPjTPnmzXn57L7KDEZJ5xwQrXTTjtVW2+9dXXXu961evKTn1x9NZKebgBbbb3AJgonichL3gfmJLn5rGfd2nklkUjM75F49NF1JecjjqijH2Njraun4UtekmTi3B6K5513XnXUUUdVb3nLW0Zk4hve8IZqn332GS1WFq4mrrzyyuqAAw6odttttxEBeeKJJ1aPfexjqy9/+cvVPSLmqBI6+bjqXWjim3C7qGSwRETIiOIlbo3S6m+Kq9uhhCFQCHff+YxnISWKwjTJu4/xjShybBR6KMFoR/Yg4poKXRj7CBID3/2M87Qbl5g7FLsgstynJOvN8EoeUfMWMunrFRjkCbJQHxpGFN2yCi/idbfd6pAmfe688yRan7ZrEZUrx7V1nhCeIXbzPZuoJudZBwkWVZw9Lx4nnhlBiThjSDAqtIuhQXgaDwxI19PvxoUE936nuucyCg70Ibq0dVqIYDPUvfQaNF5cx9jSDuPqmGNu8Z4pQxCNM96++lLf6TPjMcLGYycLEf/Up97iqakPeTjNmr+rzZPQPSBDEZyxkRGeul3nZulVFJXqo3Kz85RjOorS6J/w2I6k/saVd0Y+UiJD2RJrHeWckl/Re+QEJReMcbKRgliuJWVeYnOdnBjCW32enHPz5Fx0HDl16KG3EKF0HcQfWWejIKIxtE+bv/71WueJHLRQejAjrmy60mH8TY8hKyJ8GrpUEJ7ksam9zmU9ilzQkdojKntHvlq6w5AyaVGVo2e5ns/I7DLkvnndNv3Lb5HpnoMx7DvPK/J87733LXmQh77ntVSgaLPgqquuqg477LARqfjjH/+4OuaYY0Z211e+8pXq/4zZyV5Pttp6gvkmnyIdkY3Td5Pove+tN3ZOP712BEkkErNDLQshylFgN3QJ8zLSYYWTThsci4w8/vhl3/kGJBRPOeWU6rnPfW71HKWsqmpELF588cXVmWeeWb3M9ncD7xMbVOAd73hH9cEPfrC6/PLLqwMPPPBWi9KvYN1WEaVSxHCP5NUGGkWM4iVnIgThwDD3HVIhKj+3AQlAkadktylclD7X8X0bKOiIHnk1XGdcrqVxibmjkqXJENWj28LFhlIKu4ailYaedkROpwjRjsTrrq3d+lkVpkmk6qwoySSkm/97vq7ZNW9jF/TNNSlHHWMqvBQJQP3GEGZcMZ7CKNZP8n+5/yBFIXIxGgc876KAS+x8ui5PPOPPc/P8eQAysAngIaplzpt/iWu6EJIuIYJNo8q44tlnk55ru3bImVi2o2nQMqr1iX5kKBtzQbZZdDwLxXCe+MS6HxG5MR7nqQLeRjZ4j5yrXuRThCF3nZsR9k455UUUxZoi5JOciDEd96BvHBtVQaNqtfO0FbNJJNYimnOqTN9gLHuZ420yaBEFJ2bNOTdUzsW2TReylGwryUQ6AxlozVCYxe9CvrmmdYJM1Q9+T0bQVSKUXJ+SGdP6qEs6Buew3jmH4yOFh3ss89UuIrx26MrRs1xvWsh9ibb1pzyfZyMdhzG93371Bti8etSy+ygxHpdQlAqcddZZI4ePa665pnrkIx/Z+pv1ZKutN9hklvaBiUyW9Ql/BnNJwSm2Dx01iflEoh/oDPIdqmdhDS0RIc6OoUPEHklEpQVEc/zJnySxPwih+KMf/Wi0IL1cfOBN2HLLLUeu8Z+VJLAD/ud//qf63//93+rOsXVd7I5Z8LjaP/rRj66OP/746v+jPbbghz/84egV+O/YVl9QriHgHUR5C2Ip8i0hFVU/5PUwzbvPMcieNoJG+Oi7393utYZU45mombzI3Ms4ImVcYu4I0/buPiYVhlimUlgaawwA/cp7LHIjRQVCxB4SxX3wVBx6QW2SSfrHNXln6Et9Fs++j7fmELv5Ea590UV13yBc3YP+iR0VBoHwsKhm/MY31vcWCddNJYSk/wvJt1OqrYwKBLNrGV9IN+MnDEChvJSgRVYh7eKxScALge+T07I0qqZ5DY4zaPUNA5ss0G+SbJMJYVTLjWPeDllQYRzZEDlXtZU3EYKVoe9aBx00/Zr6EQFoTnu+MTYQoQhXciUK0wgJcA/+dt1yTk4qZrMecfXVV1cnnXTSaG278cYbqw996EOjELFxuPDCC6szzjijuvbaa0fr0AMf+MDqVa961chTP+D/r6a9FHjAAx5Q/R1hl1g62uaUsRzFx5Dr0hO0ebUtouDELF7qQ+dcLDddDEuKsvN50RvK6tfme5MQ9HuqIB3I5lPIQJtS1rAIrXUOLxs54/qoC2nrnvAaQtPJI/qA9SvukXyad23u2l+LWgvHXY+sVwALUeuaszz7Zdz/svso0Q3fuSnMoGl3LdpWW7S9tp5g45k+aa5KMdQX1iheinTRd75z/kJXicRmAXtGLtNx2fnCnmYH4k3oZNZaOhDRhXdRwVmYc+TRT/wsenXNN7/5zeonP/lJdTdb1gX8v6uh9NKXvrTaZpttRiRk6UL/lKc8pbrvfe9bXX/99SP3/Mc//vEjkvI2ZWnVIj9I01gbEqEUMbRPO61WhHfc8WeVIusicisIri4kkXN7NRUuMNibhKSBTpFHBvFUi3DpcURKMzE35T+KUrhfSvc0T6ZlKoWlsVZ6YYV3pXvn8aAP7A40732e8K/yHG1kEs9EwgQJwztUsR1k0hAhPH2IWx4gdlCiAIv7dd3wVAzDNMKZENuMr513rtuEJNQ/9EJ9qy36lMen/gqv2gjrdz8I1DCS5/G2G8pjkyLGiJzHS2hSOyYZtH5nPuhTv/daZEGFSWSD+et6jHhGvuevX2xSRN63NjjOMQgUhLTnbExFFexIL8Aj1XniHoy35pwMIrKtmM16xPe///1q++23rw4++ODROtSFgNx7772r1772tdWd7nSnUfjXfvvtV33+85+vHiJnxU1ANH7iE5+4+f8/l5rIqmGeNBOLKDjR10t9UUXCQiaaz8g5GxY8kpvpEMiINtLUenPqqXU1Z+uMNcaLUh5RHdpJjkzqo66kLdVTigrr09veVt8rvQiJ2af41axY9FrYdr0IufdM5g25X8b9L7uPEpPx05/+tDryyCOr3XffvXqQJOkdMYSttgx7bT3B/L3sslo/lGu7r6cikLOPf3xVHXtsVQkUXM+6VyKxaHDEUcGZXTYJ5qK5ZH2lq0REFpUekV8W1E20Y6kWzute97rq3HPPHe1wydEReMYznnHz3w9+8IOr7bbbrvr1X//10XF77bXXz5yHh6Q8juWO171Y2QOiLdfQNE+yriTROIWrjZC0C8+bjJLu96XhMY5Iad4Hpdt9CNee5GU4BDnXF01jrax8zXhCfDFmkHsWz/Lehwr/Gkcmxb0g4DwHXqIMl64eYdPAADD0ecYAw6hZNCYMSX2AVIscLF4EIMPN39ddV++emC4IcORrhPaV/RnFSFzHb8sEtKVH6DJDWbuQ8YoHiMhpMzijH3jZaecs47aPF9IiK4A3yQZjzEZAGPjeeWq6H0VTjMcuRGaMcQot8vDqq2u5EB6ukXtMrp9tt63vvSQ8yjGkD/y2WcxmvYJB5NUV8gaXQCx+5CMfqT760Y/eilBEIGZo2NpAXwJv2m/9BoFFZphbCqv18Yjr66W+iLDrEuUGQnhtdiVNyRSVSOUliroPlHHn0Sfki3bSP8b1UR/SVp/gOMoq3JGiZpHhtauhHy3j2Sc2NuRSvO6666pPURyWbKsty15bTyAz5DOlZ734xbMVXCFPVYEW2S4yKcmOROJn12v7+fSSaWRi+Ru6i7kJHCbYOOkNvABC8S53uctoF+rfWe4F/H+a4XTyySePFikeGxahSfi1X/u10bW+9rWvtS5ScngsKxFwH08yg5HXl2IW0pRQOhnqXRXPtmsh1CjYvCCbefwmhVvNUhhlCHKuL9qMtchvJeTYfSETVTsrHXxm9RBrMwomkUnuxaau6wSR18UjbBq69ncYE8ZREIWA0OEBEl6pIk6QTXYvGVfCwMIwK/OF6RvE6K671mGzfUJZF2lQTZtn5pWcUU2DMzwqo1gJrxWFlPqO2z4G7aINvCAbFEW58MKa6AMkhuqrntEjHlGPia5EZlmQhXej37hP5zaveL8imn3nHNI4NAkPXkHjitlsdg+Q7373uz8TGvb3f//3Iw8PBtmuu+468tT41QmsU4aGLQ7zFI1o/pYs8rdNF3LY/20GIdPmyWM4SbdYRNj1UIRrtIVxLKJDv8Q9k8WGNPXw2c8ev17Mcv1lRlJMW69nXRu7/G7Rzz6xcXH44YdXF1100cir/p6EXgcMaast215bT1BdVjodlWZFoPWFtYd+KCc2b8UXvnARd5lIrC9YUxHtdBHpAfrOrShQKcIvc/8ukFDcaqutqoc97GGjJL2RY4ox5f8WrnF4/etfX73mNa+pLr300mpHscNT8C//8i/Vf/3Xf1V3x4osEeOUuy6K6ySFs4+C27wWEuitbx1f7GWS50CX0BNtls8jwodce5zX0yIIpUmGHpIIgcYzsSQTZ/UQG/eMCI5xZBLCSnpQx8uhNyl/ZVf0IUPDmAjvkfAo86yiiA/S2a6KnU7PxDOS00p4WFnUg8eI8zGA/bZPKOsyCOdJ8yzutzQ43TcCVb9oO49iCtosz6aPQRv5BZdl4MW98MJknEcYYh8iMwhThKBxZyyUOr72IBWNxzjHOMKjWcxms4MB9r3vfa96+tOffvNnu+yyyygRvryJ8jIK+XrEIx4x8hTZeozbb4aGLRbz5AeO31qLP/axWuaQmXayzRnnItPnyWM4aV1dRNj1rIRrUw9wTOSFtp5EVWgyxvc2H6xTF19cr+dt/TMr4buM8Npp67UNZJs/XdfG6D95ETmNIWDJ9XG/6/vsy+cTa5RjMp/h5sHKykr1whe+cJQPmPegEOUuWC+22kYBmWYNmZTfbRLMdRvBf/iH9Wbwccct4i4TifUBa7Xw5r/4i1scMfqAHb333nU+6Wa0YGIBIc9c1w866KDRYrPzzjuPwr/koIqqz6qB3eMe9xgZR3DiiSdWr3zlK6tzzjmnus997lN946bt61/4hV8YvRhijKinPvWpIy9HeTmOPvro6n73u9+tktwvGtMIk0mK69D51MprWTCEJ87qOTCtzXa4PvCBmpzhYEOxjQTnJTkXOdiif5ARvA6Eem2/fTdFdRJh28fQm8VDbNIzcpy2e1bz5K/sgr5kaFTm5enhN+7Fb4LQinyK7jUq9rpP44KHp7xYgQjTo8B4d1yXUNZF5gtsYtw8axqcwt28a0eE7Oo/7/qy77PpY9Au2riPMWJBlNIvQp69GwcQlTrL8T+OyAzPWga+ZyZ3Yng3xrhwbjaBOV0WT8gk+5NhXbN+CXmWqD5QhlDz8kAw3vve967OP//86ve5JLQgQ8MWj3nGs9+ZczaW/MYcD3LfHJo3j+EiPQi7oMs63NSTyCWbFNYZ90V++ts90RFkAAguY1r/rMUqwdPWawViGPFRyG3a2hj9ZyNMmhLEq7VGyKJN43GF9ro++/L5IBgimMjmIvG0jKiTxNoIc7Y2WZdsYIXddcc73rG6gx3ldWyrbTSI8uC0MK4CbRf4jSgumxRCoUXIZcrmxGaCsU9PUPtiVtBVpG/hnJLoj94iZ//996/+8z//c7TwWHB22GGH6pJLLrm5UMs//dM/jSo/B1TDVB36aWreFzj22GNHlTCFUH/pS1+qzj777Orb3/72KETssY99bHXcccctzU1+HsJkiHxqkzz/5gnV6tLmqGKMoHGOKM6AaEIquh6lmVcW40H/8M7gAYfoREgKCXb8JEW1aYg0CUn907WacN8QoC7PSDuFDc+bv3Ia+pKhnrNnQrcLb0R9QoHwHa8yRq1ngxBCGjFOHO88lJVyvHimQs94i3QJZV10vsB5KrAL2WaENSuwz/psuhq0sxRU6ENglGPEcZHTzJzhReozz8M8LfOdjasMWxqY7k3YNOgv5CIycVLxhEyy3w45pg455JDqggsuuFXi+jYo3nL/+99/FBo2DhkathzMOp7NS/luzZPmRsKic9ktSg/oQ7g29SQyQ7idddLmR2x4uRdyyiYlGUpJ79o/a20DY9J6DTbgrLXW0BgT49bG6D/9oq/0ERlMHlvP6FDTCu2Vz961jUd9tNNO9fnlZnPuSG3hmPDmp6IvYhMwsfbA7oI9VRIsoIDYsymA69RW26jwGBCK9Eb7jbwO+4Ke+dGP1h70nAZOOqmuLJ1IbGTYlOOhS+TNQsYH6BkKzGUap9kx0x6G8OZxIc7c60v84xS62G4Z9/rVwryEybz51LqEknrX3WedVR/nnpFcs+7cl202iZCK9AHto+BGXjqGAcUUcYOsknfPbyi/iAefITUsfjynximqTUNkFkKyxCQPMYQOcgzx5t6CzGl7RuGx51z6QAEebZs3f+WQxT94hfL4CIPNPUeaNWQQeG5BCGmfDWh9yquSh0IbMSb0rEso61pLCB8G58c/XlWnnFL/bS40763vs4lxYnGKvOPjwsT6GPezhIqPGyOIY+dmwGtvkW6vlchszjvh4LxUiFvHGj9IavPYPTm39szr6bQZ8P73v39UFRqpuK+Yxyng3cGj41nPetZS7i8xPFY7l92yPPjaCNc2PYkHPMKK/LMpgdyi0NvkKgt8xcZH9I//UwvHEYZraQNj0jPXDu2mO8VaPG5t1MboP5u3vMAj7YRX6Fw2WLsU2vN9eB96NnRDOgw9QaQq70f3bbMNnJ/MV9zMb5e1CZhYvZDnaVhvttpmwJOeVHvAIxV5Mc8CMkA+3wMPrL0Vf+/3MnwzsTHBPrY/QheZBzYE3/GOJBPnxaZ3ip6XMJnHyOjqGek4E8dOeIS48u777d+ezYgo2+x8XOMZAhTbpiHgZbJa5KJICkKwLOShbSo4IjqaimrTEJmFkGxinIcYpdn98SrUBvmukJaERPMZhQLvfhgD7ofX3vOeV1W/+7vz568csviHZ+1eEEju1Qvxpd0xFoSWeSZBLBGQqj77u81w6+oJMqQRPVQOTr/x/LU7jNdJ/TgNk0i/SZ40XcIDZ/F8HjdGtNN9GbvGQ4yDcXnO2jZKuPILozbWHWfemofGPzJxKE+n9QRkX+k5eMMNN1TXXnvtqMiKIipCkf/1X/+1eve73z36XkiYtB+nnXbaKJQ5QsMYXELK4MUvfnG13377jcKc/+3f/m3k5cHD44ADDlilVibmxaJTHXTBannwtelJ1iPyh6ed/iCTIHSJyMkbGx/6x9/vfW9Nhi2z+Nsinrm2RO7DNgetcm0s+89GpX6zdkFT57LJM6nQXuS89sz9Xz/+1V/V6w1djjgiz62P5Qa58yNAsyp0IrF2wV5ROBHBcfzxt3iA90EU8OP1aLNhjz3qollJmCQ2Atg3yPLTT6//nhXWaPNCpfTNZPMsCpueUJyXMJnVyOjqGek4YSxIBLaq3W2Lyw031J/PErpSttkkQiJEtd8grSikFjJEn+Mpw14WqVJRDaPBb9oU1VKRBn/3ISTb0OYhRkm3CAu5ErrMq5CnHvLGMdoVz6gs5qFPwxjgNRB9Kmx4Efkr+xb/ELbk5XkJWUK+8goJY85Le3kxInx5iTBIhEBN8/To4gkybnyHd6f7cQ/j5k9g6KIus+QUayM07eTOmu5gWhGZWT2fJ7XNXEUAeplznnebl9KkjRLjSCQUL+HwMlrtXGWriS984QvVo7jn3oTIY4g0VFhFURXhYYG3ve1t1Y9//ONRniqvQBwfyeqRhxLW//Iv/3L18Ic/vPrc5z43+juxPrGMPIZdsBoefG16knUzNiPpAfqDDLQuRDoF3zsuckySN4i0LvkG1/oz12brMK/vMidtm+5X9l9zEzfOFeSra0wiphVv0J/WeOsLMpHeExvCrhubTK5FNyjPT1/IqtCJxNoFGc+5QbGWc84Rqj5boQnzn63odd55tQfkO9853kkikVjLYGu+73110RT2yyygf7CBON0gEtn6iWGw6QnFeb0OZjUyunhGUsApikKOKZ8ILxOKMkoppBDOErrSbLP75zGA9LEAWbRcD/GGlBNS6jikHRLOsSYl5bg0GtrI11KRZmhQgMsqtdMIyXEoPcT85tpr6913fVHm0/NMoiqv8/p/SWqCdgoNEirUDAeaFtrKS7SPt0ifcFmf62uEj/Aofeu5IAw9D+Su/xOs/nYOICw5UzE8JhF2XTwG28Z3eHd6Nz714/vfX3u+tVUDd1+R22mooi59c4q1EZqeceSzmjU/5Djjfh7P52lt42UoBYLPxj27aRsljjefhdbYpFjtXGWrCXmmJoWIBUk4LlSsDUKhExsLy8pjuF70pEjBYDPS93QCslLfkKvWJn0E1mBkonWMl8xq5uId6plbj22utsnYpu5Hzkf/lf0WG6uhR9GHJhHTkzZonZvuRvZ7d05rgO/0c+hpy/CkTSQS88OcFbosbPmP/7guGMEGnAX0PWrJBRdU1XOfW+ecSyTWA9iUZ55ZzwHrY4eMDq2w/iEj1UzMNADDY9MTivN6HcxqZHTxjOR95BzhBUYRpbRT1IW1WGwUTOkbutJscxOupe2xu00ZRdaFUUFRRcIgG6M6rHvzd1NRLQ2R8KqLUB+YRkhOQniI8Uw88cTaUyAqMQf8TflGyrqGcGuekNoUlXMj/6Bn1CR6nP+pT62qP/uzOkeRsvLabUzY2SgrX3f1upslF1YYaO41qooGqctgiKrNro9wnEbYdfUYbI5v10dgxjPS5/oBoWusSif3pS/duvgOUtQ92xEa0pDs2o/jQo8//emqEukqN+jQ+SHn9XyeN19al40S49gzz7C3RGJt5DEcKi3EkCirxGuzjTf3FCkYrD36QY7W2EC55pr6nfy36WQTxPold+9ayMU7xDMXVdEscDZO92vqXNFv1vXw6gzPQev5OGJ63AYtIpIeFXmj6QZIRa9IW2ONtRbo58yTm0isH5AFr3pVPZ8RIsjBWeEcb3lLLaPYL6u9viQS42Atu+SSOizZujUP2O7SgBVBRYmBsekJxSG8DmYxMroY/BRt5JdrI25CEaekUzoRNYiyyF00S5t5DtgpR/Spxkj5j0XHNRFugEiizLo2jzl/uzdGBuUY2sjXUpHmBViG+iDFphGSXdrit8gR52/Lp+d5ut7Tn15Vl19et9lxlO4oSBHeiiXR47gohKM/nMM19tuv/t08XnddcmE5H29D/SXsWRvBs0KGBgnre32nCEuEXk0i7Prm9ovx/cEP1i+/QzTrs+g7zxK5fdxx9TkjpM0YEVbsvvyujPhsMyT7GtTT+nFS6LHjkKPa7NrzFnYZOt/aPPnS1kp4ZiKx0TAt1cG0+TrumKHTQgyBZpV4+oZ7R6aR84gsRBhlna4kisJ9SxWq0Jr1Kwgz3jWrVdBmkc+8rcBZU/dr0zMRs9YfsphepP/06yRietoGbYCuYAxFnl3Px9+uPYmwTCQSaxf0a3KDpxbdblZPLbjoojrCyusxj0mPrcTaQOhHNiVf8Yp6XZ1nnMd6qBK0+ZNYHDY9oTiU10Ff47+LwS8UkQKItGvb1TdJKOqzKOHRZm7E8iRSaCmg7ovCSdGNZOt2w7bfvu6XCKkRZhNKsePGFXTwt7wdvvdyHeG5CCbnCe9AmJXkCCUb0RlVkJFtEVod5I028KZzHQYMQ6gMv4Y4Vriwgiw8QSnj7ltfhCLvmHlCZaNvJnljaBdSV/8y5gha/e53EfbMSPB8ulSaDMJultx+xotiNcaKCtJtfaf/9RdPxCDR3HuQnlE5vPxNaUjOalBP6sdJocfOrx/dc1QiLTFPaNhQhN6s+dI2c3hmIrFotM3LLvJr3DHbbVd7ug2ZFmJelBtP5Ed4wrl3UQGINOuTfKyM0kkpGBSQXe2CNvNinCzuqvs19UzPn+emfM82Az1375Pk/bgNWmsK4pAe4Lqhs8RGqGfDS9H1nvOctZerMpFIdAN7SiTQS19aF6WIolezwJqjyBMHiSc+saoOPTRlQ2L1wIkHJ4HsFj02T8GVwA471I5B7P/EYpGE4oDVE/sY/9MMfoSNyr2EfVT+K++FAhmhL7Mq4dosN0dcH0HJaHA9xkQkW9cfrvPwh9ff8VJQSTk8GieRr1Gh2jkQN5RabeRR5/cIvkmEZBd4TvI8XnZZ/VtKdOz4R568krxBglLIm4RYSeQiE4U42/0PTwCkHm9ObXYNhtQiw7fCePjUp2pPD20KQ0GfMfQYZ/EMplWaLAk29xiVo0vyddK9e26u7XP3UcK5PNMmsen/+tBziSqWQdzpbx6MCNH/9//qdgrvH9KgnhR6rM1yYPGqcUyJeb341gKhN3R45loMx0wk1gK6eH1D2zE2aayR5OLQaSFmRbnxZINRGgt/WwfJEOuGz4XhdfFs2ege0111v6aeKcqEZ7+CC9M20UL+ykFpTOgzeqH137psHTWmrDWx3tIb6DvOTf4/85lJGCQS6x3mu9Dn+92v9lYMh4NZwM4jSxA5ilDy5HrGM+prJBKLhnFrw/G9762LD+EJmvbYrECSZ1j/8pAiYxWrJ44z+CmElOxLL60NDooi5TNCgxE2yBtEDVKurcJgV0LAb5GXFNFxydYjxyEjIKoiU0wtOu5vHLlQGlm8GZCHzunzyOGm+phrC/WJoh59IaSWENJPiC7huKCtzr/zzrcmb6YRufrW3xCEm+eCRPSdc/psXHLkocK3gpTSDq8ozsJLEfHmWfBooAR0qTQJ7onyof0MkSjy43kzZPTduHtvhvFGpWd9FMSdZ1oSmzGWEIfGT+ymInmNA8S0c518cn0vj3zkLeNwCIN6Uuhx5NfUXv3r3ock/Radb23RGyWlvAjDV17XtRKOmUgsA9OI9C5e3753XNsxNrBU6m0z4ObdoIp7j0gG908mT5MBsfEkgoC3vjWnzOFsrf385+vNRV5v62GDZa3pmZ5ppBCZtonW9Gy1jpaRCbGZh+SlA/m/tdymtM3WyNHYVVdMJBJrHy94QV1Y78IL6zzvH/94bRv0lUdkiJeNfeeUY5F9h5DJjePEIsDeU8Gc96D1LTYshwC95YQTbtnITSwHSSiusvdN2471Bz5QLwqSnAsPprRT6CneFE6KJ3KRAcKjocuu/rhQK+7zTc+BtmTrkQQ8lH/GwSRDYpyRRXGm+CLBkIuMqXkQ10H27bNPTS6GYEIQIb30lT7uQvTstFNVveENtcLunrU77l1/Rz4oRhVvS0r6IsO33OsRR9TP/2Mfq+/VfRCYvBOMF152/m6izfMj8m6Cew8D0bPQLt4P4+699DJhuJR9rf+RhMZEabTEWPKd81NakL9C5hCajB1EMy8d52C8yr0VuRbnNainecbo10c8on7OzaI7Q5B+Q3g+r8ZGSVvuNF6xiH/tWe1wzERiGegSxtylortiYNCWq5VMtCYigdpSL8y6QRX3HsRf6A5kNBk7aTPAtRBW5HtUES5zOFtzeBV89KNV9ehHd5Nns2ywbFSv6D6pRzzH1762XkMjP7Fnol88CxuxnsUnPnELmVDmht4IHqCJRKId9DLkn5dQ0Re9qA4X7QJyh/4P5CpZQe7b4OKVjvBhE8kb31XOJxLTvBHf/e7aI3aeis1t4FjzrGfV66V5kVguklDsUfF20Qa/yUZBpxSGkumdMh2eiggYpI/PuibXnhaOJR9H03NgXLL1rkTLOCOLUow0QtghxijMSK2oEtyXnCivQxmPisfhWQj6s0lGjSN65HDQN56F9jaNP/fs5Xt9xjhrklTxufsgPIcwghCIxgKj0zhwfYSc56TSpMV/mueH3zAu/QZ55z0qceo3zwaxRzFpMzzCy8S1VN4yNoxHcC++Rz45D8EecA8MHC/PxfOPIjKeg/vyW8d5VmWuRf1J4UGE+nyWNATjPGP8HykcRW3APcoHNqTytGzP56Fzp+m7qPpufiCvjZfVCsdMJJaBrsWrulR097v4uwny14tsbMuHNcsGVdw7IjGKriEqrR087N3vpM0A17JGkLvN1CBAZpIDztFno6fPBstq62VtGIrg7EJCaz+SkPe+zTtjx/OIaIIIfXYvr3tdVV15ZVW97W11JIO11fMpN4E3iwdoIrFZwaNQ1BonBOmyJpE1IXcc42+ywTpBxpE11gp2GRvm/PPr8GqbF6rkJlmT6Au2w0kn1SHI7K4hwT6W//PEEzNUfzWx6bu+b8XbRaJNyWS48ybwubBRCiVl065RF2Kvy064AiyHH15P9NJzoEuy9XFoM7IsXPqbkutcjmGYIC5LcmLbbWsluMs1w5MiSKcyHyBYIPVbm3dHG9Hjeu4ZWRY5JEuF3/m0wz17NpNIKlUt5zWC4vkh2jwPfefvuAdtc72259ckf40vhgkvM8Id8WccaCMvGfesfcbbuP5mDPJOIcAdw3ghwD0juZqQhbxPVY1j0ASxiWB1jzxuCX2Eo37Tt+7fOVzb/USuxSjkoo08MhhLCM++fdnmGcNwd11GtnD8eH7mvDA0nrOb0euuKS88B2Qxg9Q4MWZKwneofKGJxHr1IOtS0T3WwbZjrFc+Iyebhtos3mVx7+ZqyHTyVhvcq8995n3cZoBrmdvkedML3z3ZgLEOWCf7ek522WBZtl7WhSgckuDsQkK73mmn1Wu2Z2A9LaMJrNMhf40Ra651K+7RurnsFBuJRGJ1YaNB6PM731lVRx89nrwhu60DEZVW5mBkD0QoNBlM7ogs+uxnq+r1r6+qP/iDqvqjP8oNisR0GFe8EY85ph5LQ3okAvvtlFNqriKxutjUhOKsFW8XtXs9TslEXFEo7RRxZRemLIdhFya+6074AQdU1cteNlx4UZuRxVtCn1rEkBT6i2s9ApFxQhmWp+3lL6/JwS5Ku+P0CYJMe8p8gPqtr3eHNrtOhOAispCUsfhGZWphus99bl0IRv9qi2PaSKp5jKAyl9WnP31LiHG0s8/zi/FlPDNOnNf5fO58zqWtErlPuh/Pbu+92ytqM4h5MDrOOZsGDfJaSLEKlTEey5ydxnkU8PFc9b/2IiSF3s/al6VnDGNMAmCesZSvcfO+D7G9UdCUF1GQSF/5f0n4GudD5QtNJNYSuq6bjutScMRmizVCjqrmMUAeWwPNJTLGvLJZI2cp2WMDsav+4b6FWJufIgvKDbZyDpOn4zYD3AMFnSc6WUwux8YTMtF6pG9g6MrMQ+tl09C1OveQBOc0Etqzp9sYF64VRfnKaAL3K+VNKX/XQoqNRCKxujDf2Scquit0gQS0DtHlvHwfMqH0Toz/B+nDBooIIu/+bz1QCMba8PSn1w4K5FB6hiUCxhJb/ppr6kriV1wxXH7EAJ3l2GPrwrI59tYGNvVj6GM0dNlRn3f3epySGcpjeGrxRKNEdjl3l53wUEiHDM1sGlkUcSSd+9dO7xYopBGiMYqKIJV4HD7oQdOVdn0u36TdMy8GGaEVO/iKsTQrPE+DPhBCzMsOgRsVLS2kzu3e9RHCEBlqcY0Fl/cdo0vIQXw2rxEURVS0Q7+UifG10zX1XZfnV44vRgkSrxkejix03DhyPMYTA6dZ6RnMJc9WomgEcfwW9Kexph8ZTJFrsczZqT8tDo71f387Th+GJ8+sfRn949yMNfc1bt73JbY3CuL5IgyQ4/5vLCAS9EFUfY/QzCHzhSYSawV9181pBUd8D37TdowNE6lHbMZY661tZA+Yf3IO8RYcJ39K/SPSQ1gXnL9ZiCPmMNlKDo/bDJD24QlPqMNuyfT4TeQk7ru2roZeNg1diEJtHZrgnEZCI5LBphYC13ofa3RJCtMBmvJ3vaXYSCQSiwF5jVikjwuBVgBDWi0yriQQwzsxvBXp9mR+k2B0vrCF5EEXEi3tUUQBCblObF4YF6qPy72Jr7B2sR2GhLXvxS9OD9m1iE1NKPYxGvrkHDOpGOOf+lSt9Mpn0YWEaFMyKe3y3s3qqdUlHGsRhEBpZPEepPjqa8YMIyYUZH3sc+3Tf4gKhtC0Sr9lKLDKwIwtfzueNwVi6i/+oqp237177qAg0bw/73lV9da31udxjxbSOLcFVHsYgowQynuEjntmvvOb0lOy6dHS1YMg8iZ5Tgy5MjG+8xLaFvtxY3ja+IoCAM6hDQxE15KTqY0c7zKeeCA6Poya0tiNHF4MJs8tci1qCwIYketetEubeDJGHw5lUE6b9+7xuuu6E9urjSELF/i9OWhHMeYp0jqKRMXccy1zmXy0Q53J/hMbCX3Xza4FR6Ydg8Bj+EnvYK6FN/m0jbWSFEMgOs7/KfTkl4q/AQp+pJiYtPa7/vOfX8tK8iWqBPute19UXr5x8tm6YJOJrkAe+XseGQldiML99x+e4JxGQsemnvVPsTA6RVkYJ0hhxz7qUSl/E4nEZHkjJYJNIh6L0g6xbcgbBGF4LHJWAJ8FglCM9zJk1WfWETJMeLVzkmUgjyt5mKTPxkY4BrEZFQ7FWcR4KcPo5wGdQ+Tc7/5uVR1/fObwXKvY1ITiEGRbGZ5D4eNhEGGpdnkomQgWrP00wdpUMnl4eZ/HU6tLONaiqv+FkSV/Au9E/aEdQSxqg/vRx4yEIBmRSTwAyzCtptLeLMYSeSbLEF6vpz2tG/nT5mG66671uQhIzxmRGBWLGVQl6et3FmELclSYLnMdMej8Rsib3Zu2atuTclUOkXeiSfLqtzAsGZ7Gr1DuN71pvMeGPIh9xlObBwjvN2TvpZdW1cMfXn/uGvrR//2e56lxrc+bRty8YbaT5r02IIb1iXEzjdhebQxduECfUAr1rzkXHrEx38xh17DJgZjgFcyjdy30RSIxFGZZN7uEm3Y5xuaYawhznuYN1xYe7Lc2n6w/NgW82ziK78h633ufthngfm2IlhXfrdG88G3WWefCG38otMnnWGO100YP+SxtBT1impwbJyNtYHUhCm1+dd147rO5M4mE9ux5pdKLwnu/zHns/J5t18J8iUQiQU7wVhSijFiUsklaDHIr0tpEmps4viSFSqIR6IO+t7nEUUCF6VhrrA3kFXuN8wBPSfItsX5hXHCUuuqq2h70PNn2Xs2CcvParNY569v229cpvRQLzdDmtY1N/XiGINvKHHcMAQpgGZZKAZZDQDiTHaJpKJVMeZCEAzt3F0+tccrstHCsRSqk2iPHQRCk+oMwisXJghS5+NyDdob3QXjPtZFITS+GZgiv8/Lsm5QPcFrYkz7jlcGgch59SqDaiXOMa1kwPX/kiufkuTB44p7CEELUua8LLqjfy+uozqiKWuSkixACz831XDuIy7KICoPQPUVoW9fnYSxqr0XAGDVWhVYdeOAthPg4j40/+7Oa/OwynsblwmKM+g1vRNczZygf4anjb4tWKDjTiP6+HnqT5j3PYu0wVqFZ6GctFSEZOq+XfpROwTg0N40vz17bjTEKI/i//vcZ7ynyzQbAWvLaTCTmwazrZpdw00nH9A33bTu+TCFhTfJu7SQbrZnkKsW8KxlVkqA2xMhmJOX73lcXsBo6FURbupSI0iCPrH0hj8i/SXJukowUrkfG8bxuQ+gc0GXj2VohnLDP5s44ghnok9EH5Yape3ZN55boPuVuIpHoA7nD5VUkdy66qKrOO6+2Nem/7DHrQ4Sq+r81wroShGJsToWdS046ng5JNtt4snYCO5aDgDBVxOLpp9cVo3MTZH3AMzU2PDf2K4eDJrE8JIw940RkAM4kvVzXDzY1oTgE2RZVhil6FN4yLAURwYOH4kvR5G7eZWKEkqlSl+pFXMcRZAQ2gR/kRkmyTfNU6hKOtajQSvcbVQq1g7ceoky/IdcsTEgk52QA2Xlv7nY0SaQ2L4YyhJcRFeec1qZpYU9yJb70pXW1xTPOqBPN6nuLqXcEqPZF0ZYIA3B/zoMI9NvYBSwLgRDOwms9V23nOeLvWJCf+tR6gUYqGpOlB6Zjg/jqGrJunCCA3JdQKc/D4qC/kJrOXXqHjivg02U8TTKOtcli4Rg7psZqjCf91JXon8VDb9K8dz7X9/wQvWUBHOcNT9PVLkKyiMIF8byMT/OvNGCjMrvz80zSH5Gbba15bSYSQ2CodXORaVjajg9Dj9FGdjH4yAdz2HE2dHio9GmDeW29loh/0ZWX29Kl0An0vXWRHrHddrWuNUn2TJORCDvXIMtCnpVrTegc9K9p65E1hNFMF+jbN+MI5uYa5ZnRF3xm/ZTjl6xOJBKJvgi5I+ro0ENvKaKh+CNnA3ZreCc2PRXJPbYDG9e6EmHTYH1q2m/AfpWPl8wiT0WAcSCxofOIR9TpvFJ/XFueiDYM//zP6zVn6FyIbbCuveY1VXXwwTkW1iM2NaE4hNHAyI7KV+HqXYIy7xgTsm+OHUIXKUYppVA3yQ2earEzbuJPU/Tnqf43T2hl6XFgAXF/2gWRbzJIJ/fru0hAPs5bdKhQ7q4eIfJa6WP5jNy//tN3+j4KmXguSGX9E9XRvHzv/J5XWQiEccRb07Nl5DjW85WzLhZknhmeG28KRA5yJ4qo+I17m9TOkgTWr+98Z1Vdf339zMrxqp2f/WxtvMkb6Jk0KziXxiyPy2njaZpxzDDUXqRoOS+6Ev1I2lk99MbNe9cS4uYZuE5ZAIfiZKz1zTk6ZI7DSeM2cox5bpESoY/MKZ+X34fHL0Kcgune9a/30nt4LXltJhJDYtlVc/umYWkeX4YGW1utQ+YqL3uGnOPJ875tWHbl5TJdijUQmakt1lAymeyf5jE+aW2PSvXkuvUZOekVUSClDuG8k9Yjm4mORyYO2Tfj1igbgYsitBOJxOYDPVy6Ia8XvrC2d+SqQy7GOlLKrigMRS5bG6KYSxTInATn40ThBc5LnnJk4DhhvdpttzqPfYZILw8IQxFKNg0vv7xe2xbpiVjCM7em8WLNTbL1i01PKAJFT3x+VNbrk0yWYk5h5cXGAC8R+Yp4KdrNaXo1TSMamvnMKNNBbiB8XG+PPeqdpaai73zIO8q2XBmvfW29aEwz+NvuaR7ipkkQaQsiifLNsEHAESbuXX8h7GInzMIzzlvUu9BbHgyIMP3DY8/5JnmXNtvHqJjmEeJ8Qn21f8cda8ImkqS7js+Rg/pW27wIYm10vQgtk68krqOtSMIgE6OqmvcIlUbmMSQOOqi+B89SOxkw4U0X7QTVi5vPrcx9pd3Gk+shQsuiMcaNZ+ucFhR9P47ADmO2T1XpvjlKpxH95qwkwPMYuE2ywLMRxuf5eW7a67xRAEcfItYkBp5EVJdjTD+bn5GHq2vOzGlokrVNIiHOJUSxK8nXfF7h8RvpCMB4KMn+IXJaJhJrGcusmtt3o6w8nowq066Yq+S9d98LI5qVhFpm5eWAe2VYCseLTQyymXyLDR7rMTnYJnvGbWhFobtYe0UGROEZG0k21BjKpQ7RJd/hIvpm2YR2IpHY3CgLuPAWe/Oba5lZhjuTQ2wVCC/4WcmnKPLHHgqQ+cglVaPp22xoHtqZQ28YWEPZJZEWjH5w2mm1ftHmXbqoccaZ5DnPqW3cDG1e/9j003PeogYmwH771W7BJqf8d2WOO8oqBZAxUBIn0647Lp+ZczsPhZZwpVBLTl4qs80E5iowuT434kltarsnyqzzzeuZUCrklHmGTlQE4+2mXYQZ5dziwWtAcZZx3qLuVf9E0nltZDhwmx8XztXWPsKUAJ1Eeul/9xYCr0yS7ll4MUS0QUisZO/+DiPFrt9ee9WFSOI6fq9PPcMIO3Zu/4/dP89cP7jHSeQaNKsyG4eR68IYRIbpK+PSMQzOsmgMY9S1g8AVFlcS2I5DZO65Z/cCPvN6kU4yppCnQxi4JVngnBJUK1SAqG7mrIydWs933Fgvx5g+l3vE751TW/Qvr1Rj1zhHzs1SSKUk/4zfyDEW5/OMPW9h7DZIZq0yD85pjBrjjolQ50VXik8kNhv6pmGJ48k5OWnJAnKF3I5NO/KKLJvHg3BcaHWZs5iuMeSmAh3oM5+p5ZA1MLxVyk03BbSs+W2yp21Dyz2TzUG6km3Cp+kazkdmO+fv/M7PymN/yzVcGmJ0DTK/T5j6Wia0E4lEIuTOK15Rp3uSP0+4sjBoa5P1hV3BziDb/D/IvqEq+zonXZquHHm82Qt00/CmTIJxOjwPtg2nBusf/V4uRHYdsGus40NWZR43niJtknQsijkii/MZbhxs6kc5VFEDOzlPeEItcCmqZY67IOSmVb5tXld4als+szi3vBOMCwKg6akU5AIhbAJTknkqTUpgPu6euLwj6+S7mHf3vS25O9ILadb0Ppu0I1/eKzd5hCThqO8c/9u/3U4mtrXPAuke9CHjoI30cjyDoywAUyZJD48tv/W8LLLOzaDznBgm+qYkayJ3JOOIQEdY8b6IcyGh9EsIYb9v65c271FEEm9IY2CffW7xjjMeXTfIbr8P8hlZKAQhyMg2Atu96tuuBukQOUrHGVN9c411QZxTP3sWzTnn/j2ftkI/5qEwkbe9re5/JJ52e8a+Q1A6JxgX4TkkfM1z6itzgvzjMWmcIPtcx7mRnpQxz7QPkTDueUX7nNd5llkpPpHYbOibhsX/n/a0et03R8mD0D/CA53cmseDcFpoNfkQ6Vesx0OkegiPenKIfNOGsvCMc5I9UoG0yZ62DZLYyIsNO32EkPTyHfmpjSJWfDZtQxKJi7Cd1RM/kUgk1jLYAKo3S5tRFnGxLpGZZDr5Rr+l+04Lee4L6wj578XeiXtiP5D9PO9tCvFm3+zkVJCH1iovfcaGF/lnHS7rE7DnpA8JWzQK7QwN12EPKbLCbu4TAZpYX9i002/InEC+f/7zb/FIY8hHyBGh26XybfO6CMq2fGY+QwiZpEiuUOQjt1nsvkcYq+ORk4wOx7e1adI9Ucrt2CMZCIEmqdiXuAmCyItnZ+ycQCloxhk94+4VmcbwiErE2httnNQ+BKB7F0KO9CnJxiC93KeQptJgKKtKB0GkvD3yVnvaDMCSrHGe8PxyfYux88W9EfJefhvGUrNfxrUrqrI5tyrKzm88WoSj6md4trkPv3df2suIsjgbR0haYy1yP2pzk8CbZjQuqrDBPOHUXc7pWQh90zf61Zz2HvkyS1i45deMPKa8VI0n48J59F8Y4J6N+cnV3+LuFSH/fWWO8eQ3UWUcQqHSDvdrXPKo6UokjHtee+9dj4cIxV9mpfhEYrOhb6irTQ67/rwTEXxl7tshvOSmhVYjEl1XYZIoFDZP5Ae4V2uU9UhKmabHOELQtRmVbf3StkHinnlS+r0+cU/RRxFSbf0m20pM2gT2jGzCuc48+ZwTiURiPRVxIffJUzYXGU3WLwPkN3uWp501h43r3thg1j5rh/WIXEY0iqzaSEVftI33fhT0tPZE6i3kIb1/WuhyFA9dBIkYkHaNPfGHf5hk72bApn3EQ+cEoiTbwSnDHftWvi2vq+pVM5+ZnR8hmRHKTBjwigpl1uT1XRgSkcPRLjxlmTBta1N5T1AW5PCiZBNQPnfesljHPLvvZY6/rkbHLM9t2m8YAUJThflaINvy9TGgmqGg3vWB43mpvuQltfHQhVxzj5HIOIgsBCCCTv86J8NMbolxi+C4dvk9TxXEFiPMOIgCLMgffe25Ma4isbLzEPi8S5p9BIw45y0N0q7pAhaRB2qoojxt5xSSHCGDkUcSoWg3rxnyHYamRVz/mIPNYj1RQIcCBJ6Fc0ZYPxhHs8gcVcB5RrtfzyhSK3jOEepubCORu2Lc8yrn6zIq3iYSmxl9Ql3NUUYVGUVWDe0lNy20mnyL0Gpe2taUWSoeN9vknrWrjAgIj3F6DznHiOy6QRIyXfic3yFHp/VTl03gyG08qyd+IpFIrLciLgEpfd761qq69NLarhjaS3ESYpOe7PVqQg0BurD0YHKXR5SNz8hocj0Kcq0Fz7nIb8g2YEeEjShK0L3J885D1Frc3Pjqg2ahnSHgXtmx7Bm264knJpG4mbBpH/WQIZPhpUUQCJWB8BjsW/k2ruu3JWFC6EUoM0XWDg0hyMMv8vAhIyjyfusakcMxduHHtSnuyW+FIkcYUxApzqd9ip8wJKaRLF0wLezbLlhb0YpZnluX3yB9fu/3akHYRnp1Cd3tUvSmGfYtxx0jzLkiZ6I+RibKXzKp4tW4dmlL5GIMV3YLfHiWMaYsVD5DOHmevECQxsYXT80olhNVjvWp80RIW990AeOM41nD4oYIp247p36wYCPgzC+krHPyWjE2tL3N89V9IxX1se/LYj3uK7xqwLt75J2ovxB1jpefa1yBgXFwjwxuc9F7FE0Jo5dxrC19PZPanlcWCEgk1iYWscHSRBlaTfa1hVaTc1deWX8mH/I8kR/NNjFgI2ej61iTGLLRpnFrSSm3/F7OaalO2orotfVTl01MROWBB9Ybj7nhkkgkNhPIt1NOqe1RG9xyLvKeW2ROvj5gz9gIk8c+7OVIR+RvOrMNMt6M++5b2zwRORdFM+ntougilRi7IGxUL/q+TS5hxldcUa8b1hGRThFa7HtOB9ajIC/LHIfWVv3nb+dhm4F7dg7rTVTWnhfaX3onzuqp6L6kHkN4ahsbiW1mjU5sLsxEKJ5++unVSSedVH3jG9+ott9+++qNb3xjtbPt6TG44IILqle84hXVP/7jP1bbbrttdeKJJ1ZPENN7E1ZWVqpjjz22evvb3159+9vfrnbffffqjDPOGB27KAwVMjnJS6uNQOl6XUIrCBMEj3DD+A3iiSDbYYdaKQ5CxUu+QyQGcqFU9Ce1yf8JO7kWCDDXDiIpSCbkBwFJYDjeZ20kSxdM2/G3O3PUUTXx5b7KPp3lufXp83GE4JChu2XYtwUqPBYjZ6Jz2d2ZRCZOapd2GBeeV/QF79IYB56rfrbQaYtxdPzxVXXSSVX1/vfXO1f6Pp6LhcF4sKha8BDIQ6QLmLcg0tDh1MalEHHzSAghI9GibjH3nPSB8H+iS7tKQ9Nvo9pdFEaJ4jvapo/Cy5PRSinwnMzRKHyDWOYl2zdMOyqfkglNIsF1fD5U/q4sEJBIrD0sYoNlltBqn1nH2jzd+0Z+tLWJrHMebbKeRZumrSWl3CKHbYZ17aeum5j65mUvyw2XxOrjhBNOqC688MLq7/7u76o73OEO1W677Tayux5AKZuAtWirJdYHyDlhxc97XlUdckhtH4raY1fO40k3JOjE9O3woIwoMesWUs9G03veU+vzbaQdG8j6EdEAzhNONo6f5pkZ+SatC/Lbq6aNQBQVZQ2JXOhxr233vEiUabMmIQpNasMee2SBnESN3kPgvPPOq4466qjqLW95S7XLLrtUb3jDG6p99tmn+upXv1rdFQvRwGc+85nqgAMOGC1wT3ziE6tzzjmnevKTn1x98YtfrB6E0aiq6vWvf331p3/6p9XZZ59d3fe+9x0taM75la98pbp9lPZbgzv6sxR16XNdwsc5zjyzLr5gwkZxjZIojB3yV76yPh/PN9eNMNdpbfJ7xANDoMwzwVigYF97bf23a0ZyXPdCN/FekixdMGnHX19GVWH3xQhoei72fW5DeW8swkNrnnOOa5d357RAah8D0G5hhNciuvS9fraz9Jzn1AuEsLKzz66PCS+Qslo5gpM3HcJ33nQBQxVEGvKZxLjUTucJb5gwmvVD2a7S0AyvRH0a+UsZmIh4RCFFhNep8GPncT5Gud/FPPOdua3/usJ5zFmKUFuOMX8jKZuVmROJxMbCovLV9gmtjtQK4+RN31yOXdrUdy3p2099NjFzwyWxFnDVVVdVhx12WLXTTjtVP/7xj6tjjjmmeuxjHzuyqf7PGGZ8rdpqifUHcpBtIgSaLkrWXnhhHeXG4WVafr9lgV7OgSK8Ff09Cb5nK9P7w8uxfE1DFFEVzXTuuXWf+J2pE8VRSiKTfT2O3BwCkWs/yEr/t3ZzQGm7prVfOraTT76l+FoiMTOheMopp1TPfe5zq+dgIapqRCxefPHF1Zlnnlm9zPZsA6eddlr1uMc9rnqJBHNVVR133HHVZZddVr3pTW8a/daOF1Ly//7f/1s9SYKDSgGMd1d3u9vdqg9/+MPVMyKGeI3t6M9a1KXvdSm3QnEdi5BA7JQeAaWSTtAdfHCtXCOPnKNLm3xHUHDHjgqIQUogKh2PnJRzqJlDsUmydMG4HX/ClIJPuEWYKGFX9qnkv4ZJn+c2pPfGIgyGWc85qV3IJSFnSCtEMa4/FjyEl7+bBhQCDDnl+fpNWa2cciD8166jsOd50gUMWRBpnv6bNC7dkzE/qV1NQ1MfMaiD2HNf+ix27kJZMG+cK3JmBvln/jmfMdm1PchTRLD7jnxm8dw8e4a/6uVZECCR2PhYdFqCaZtz5A85Ns5bYZZcjpPaNOta0qeflhFOnkgMiUsuueRW/z/rrLNGDh/XXHNN9UhlcVuwVm21xPoGO06FX68oJsIJhaOKiKDrr6/XjdVA6ORNIq/L7yIc2ZrRJ1w4PBmRdn5nrbJmsrusmyWpGfe2KMS9h6em64s+xAewUx7ykNqOsD7aU+CNuJGK2yRWkVD80Y9+NFqQXv7yl9/82ZZbblk95jGPqT5r66EFPufRWMKOlgUIbrjhhlHotHME7njHO468H/22bZH64Q9/OHoF/ps1vuQd/XmKuvS9ronNG0C4z7Qdctfq2yYKNYJQ/ogo+lImPifUfI/4QDqVmKV65Lgdf2SMa/surtnWpwcc0L+Ny/DeWA1Ma1dpNAUBOC6/p88Qj8aaRaYkjvW/5+PcxsA86QKGLog0FPqG0zcNTURtFA9AKiJlfSbvmM/1H29j7W7OM6StqKEgcmchlSNkOnZdIw9kFgRIJDYPFuklN21zjkyUHsLfUUxuCPJtXJvmWUu69tOywskTiUXhOze5Dt+ZQj8Gi7DVhrTXEusfdF18dnDakT+QjJZP/qMfrfXf8BpcNLp6Fg6JcCRwXWsGYhKJ5/++K7HoHJSubZ1k9x1zTG2HWOesp/YMMg9iYmGE4je/+c3qJz/5yWhHqoT/y9XRBgtQ2/E+j+/js3HHNMEl/9WvfnW1mjv68xZ1WeQOed82BZHC+7FMfI5Mcv6Pf7w+riT45vE4GNce17Rz45pyNTbDpso+5W7d97lt1KIS09rVx9utyzjj8SbB8aweG0MWRBoSfedZm6HJI9HY5MnpXPLJqADuWIrTRz7SPs/C23eWSqxNUlm/OY8cJ+uZLF8Wrr766lFOYJtlN954Y/WhD31oFOo1CVdeeeXI+Pryl79c3ete9xp5bTz72c+eK9dwIrERNrGgT47CebCstWSjbkgmNj5++tOfVkceeeQo32GELi/LVhvaXktszLyLXoqhhAejugHk7Cc/Wds1UgctglxrbkItC2V+xCAS3cuyithEgU6bfiLZFADNEObEvFiXaTR5SJY7aXa8GHXL3NEfoqjLInfI+7SpSaSUoZ5RBYuwa7ZzVo+Dce1BrmgTciUqU0/q01me20bNcTREu7qOM7uM83hsDFUQaWjMMs/GGZryjDQNzUnzbN7QuY1Kli8D3//+90eE38EHH1w95SlPmXo8T4199923OvTQQ6v3ve991eWXX14dcsgh1d3vfveRR8csuYYTifWEafJmWeTbMteSlLGJ9Qi5FK+77rrqU5/61Iaw1xKbx4MRwShnuxReOGtFIRUwEd0jYq6vdyGbsu03ZPi0/IlDIkKM48XmFWZsvYpUHuW9zUs06lcRjiKYfud36vRlziuaIKpNJxJLJRTvcpe7VLe5zW2qf5dErYD//4pA+xb4fNLx8e4zBll5zA7Kz7bgdre73ei1mlh2Xp1F7pBPI1JiU5Nb+lAeB23ticIv4LwlMlfRctB1nM0zHtdyTqpZ2tXV0Fx06NxGJcsXjcc//vGjV1cgCSWk/5M/+ZPR/3/zN39zZKydeuqpNxOKfXMNJxLrDZPkzbLIt2WvJSljE+sJhx9+eHXRRReNvPDvOaXa2yJstbViryXWJxBhonlKhBej/IuIRmmCVEq21kyqhGxtaBKH/l42meaa2hVFXfxtekTRxmY+xyaZiHgEnvlt5Ki1lrenCCU51LWPU7GoP9FlWY05sSj0GlpbbbVV9bCHPWzkkREhYdzp/d/C1YZdd9119D2X+4BEvz4HhpmFyjGxKNnB+vznP1+94AUvqNYqViOvziKV9C5hTEOTmW3t0X9velPmKlpNdB1ns47HtZ6TapZ2dTU0M3Ru/UO+qDKPFCASY42bJdcwZK6pxEbCMsi3tb6WJBKrAQVUXvjCF47Sd0jPwc6aho1qqyU2thdjkIwccHkvSi1Eb/eZUGk6tqIv1gSEIyIvipEg62ITCvnmN1FsZRL8pqzyPM7zsQ2u7VpR/NTvbryxrleAVLRuRY7FOLc2+w3ikb3gb7/l6LvddnV0n/v293OfWx+TSCwbvblqrusHHXRQteOOO47yQQnlEjIWnhgHHnhgdY973GOUNwOOOOKIao899hh5cwgTO/fcc6svfOEL1dve9rbR91tsscVoATv++OOrbbfddrRoveIVr6i22WabqXmsVhurQQ4sUkmfRqQsgsxsa08SLquPPuH4s4zHtU6sreY8S6xtjMs1xbj6wQ9+UH3rW9/qnWsYMtdUIrHx1pJEYjXCnM8555zqIx/5SLX11lvfnONQEZU73OTitJlstcTGBsJtzz3rVxMRNo20Q9QJ/UXSyWWOZBQ+/YMfVNXXvlZV11xTe7vTy9vCjJGIiDy/dU0EZZB5Ub15Euj41ib6/uMeV1V77VV7VyJCIw0p20AoMm9CxKF7ZSPg9f3efUKGKyfWPaG4//77V//5n/9ZvfKVrxwtUnaqLrnkkpuNp3/6p38aeWMEdtttt9HCJmn9McccM1qIVA0rkwMfffTRI1Lyec97XvXtb3+7evjDHz465+3XAc2+0ciBSUTKssJ9NlqfJtqxmZ9zhs4lmshcU4nEbNjMa0ki0cQZZ5wxet+zwbC8613vurl42Gaz1RKbE21h021ACFo/vvWtqvrqV+vCisCTEJEoZyMST77DiKbjDW+98UJM8jL0+yuuqM9lDTJ9EIOIR98LPbZWBRn4hCfUXpVxvWlE4f3uN2DnJBIDYosVvvHrHAwvO2/f+c53ql9sy8ydSCQSiTWDtSqzeWFMq/L8yEc+snroQx868s4vDTXeG9oj5Pnnf/7nqw984AO3Og/PfkYYr5H13EeJRCKR+FmkzJ6O7KNEIpHYePI6928TiUQikeiIyDVVosw1VeYaDkSu4TgmkUgkEolEIpFIJNY7klBMJBKJxKbF9773veraa68dveCGG24Y/S0kLEKR5ZsKHHroodU//MM/jMK/5ER885vfXJ1//vnVi170opuPEbr89re/vTr77LOrv/3bvx0lrS9zDScSiUQikUgkEonEekcWEE8kEonEpoXE84961KNu/n/kMRSifNZZZ1U33njjzeQiSEZ/8cUXjwjE0047rbrnPe9ZveMd7xhVeu6aaziRSCQSiUQikUgk1jsyh2IikUgkloqU2dORfZRIJBLrBymzpyP7KJFIJNYHModiIpFIJBKJRCKRSCQSiUQikVgIklBMJBKJRCKRSCQSiUQikUgkEpsrh2JEbXPNTCQSicTaRsjqDZBxY2HIdS2RSCTWD3Jdm45c1xKJRGLjrWkbglD87ne/O3q/173utdq3kkgkEokeslt+jsTPIte1RCKRWH/IdW08cl1LJBKJjbembYiiLD/96U+rf/u3f6u23nrraosttujNvlrY/vmf/zkTBA+A7M/hkH05LLI/105fWnYsUNtss0215ZaZeWPIdS3H+bDI/hwW2Z/DIvtz7fRnrmuLtdcgx/twyL4cDtmXwyH7cn3aahvCQ1Ej73nPe851Dh2dA3c4ZH8Oh+zLYZH9uTb6Mj04Fruu5TgfFtmfwyL7c1hkf66N/sx1bfH2GuR4Hw7Zl8Mh+3I4ZF+uL1stt9ASiUQikUgkEolEIpFIJBKJRGckoZhIJBKJRCKRSCQSiUQikUgkOmPTE4q3u93tqmOPPXb0npgf2Z/DIftyWGR/Dofsy7WLfDbDIvtzWGR/Dovsz2GR/bm2kc9nOGRfDofsy+GQfbk++3JDFGVJJBKJRCKRSCQSiUQikUgkEsvBpvdQTCQSiUQikUgkEolEIpFIJBLdkYRiIpFIJBKJRCKRSCQSiUQikeiMJBQTiUQikUgkEolEIpFIJBKJRGckoZhIJBKJRCKRSCQSiUQikUgkOmNTEIqnn356dZ/73Ke6/e1vX+2yyy7VX/7lX048/oILLqh+4zd+Y3T8gx/84OpjH/vY0u51o/XnWWedVW2xxRa3evldoqquvvrqar/99qu22WabUb98+MMfnvqbK6+8snroQx86qth0v/vdb9S/if59qR+b49LrG9/4RrXZccIJJ1Q77bRTtfXWW1d3vetdqyc/+cnVV7/61am/S7m5HKTcGBYpO4ZDyo7V78/UucbjjDPOqLbbbrvqF3/xF0evXXfdtfrzP//zib/Jsbk8pPwYDik7hkPKjdXryxyT3fG6171u1D9HHnnkqozNDU8onnfeedVRRx01Kpv9xS9+sdp+++2rffbZp/qP//iP1uM/85nPVAcccED1+7//+9Vf//Vfj4Sw13XXXbf0e98I/QmExo033njz6+tf//pS73mt4vvf//6o/xC0XXDDDTdU++67b/WoRz2quvbaa0dC45BDDqkuvfTSarOjb18GKFjl2KR4bXZcddVV1WGHHVZ97nOfqy677LLqf//3f6vHPvaxoz4eh5Sby0PKjWGRsmM4pOxY/f6E1Lnacc973nNkdF1zzTXVF77wherRj3509aQnPan68pe/3Hp8js3lIuXHcEjZMRxSbqxeX0KOyen4q7/6q+qtb33riKydhIWOzZUNjp133nnlsMMOu/n/P/nJT1a22WablRNOOKH1+Kc//ekr++67760+22WXXVae//znL/xeN2J/vutd71q54x3vuMQ7XJ8wFT/0oQ9NPOboo49eeeADH3irz/bff/+VffbZZ8F3t/H68oorrhgd961vfWtp97Ve8R//8R+jvrrqqqvGHpNyc3WQcmNYpOwYFik7lt+fqXP1wy/90i+tvOMd72j9Lsfm6iLlx3BI2TEsUm4spy9zTE7Hd7/73ZVtt9125bLLLlvZY489Vo444oixxy5ybG5oD8Uf/ehHIxb8MY95zM2fbbnllqP/f/azn239jc/L44EH3rjjNxNm6U/43ve+V9373veu7nWve03diUiMR47N4bHDDjtUd7/73au99967+vSnP73at7Mm8Z3vfGf0fuc733nsMTk21y7y2SwGKTumI2XH8vsTUueajp/85CfVueeeO/LYEnbXhhybq4uUH8MhZccwSLmx3L6EHJOTwRNZFFJzzC17bG5oQvGb3/zmaMDe7W53u9Xn/j8u35HP+xy/mTBLfz7gAQ+ozjzzzOojH/lI9d73vrf66U9/Wu22227Vv/zLvyzprjcOxo3N//7v/65+8IMfrNp9rUcgAt7ylrdUH/zgB0cvC9Wee+45CuNP3ALzVYjs7rvvXj3oQQ8ae1zKzbWLlBvDImVHN6TsWJ3+TJ1rMv7mb/6m+oVf+IVRPtlDDz20+tCHPlT91m/9VuuxOTZXDyk/hkPKjvmRcmN1+jLH5GQgZOmecqZ2wSLH5s/NfYZEYgLsOpQ7DwTBb/7mb45i/Y877rhVvbfE5oVFyqscl9dff3116qmnVu95z3tW9d7W2s6X3Bqf+tSnVvtWEok1gZQd3ZCyY3X6M3WuyTB35ZLlsfWBD3ygOuigg0b55sYZtInVQcqP4ZCyY36k3FidvswxOR7//M//XB1xxBGjHKlroVDNhiYU73KXu1S3uc1tqn//93+/1ef+/yu/8iutv/F5n+M3E2bpzyZue9vbVg95yEOqr33tawu6y42LcWNTwto73OEOq3ZfGwU777xzKq8FDj/88Oqiiy4aVcGVSHkSUm6uXaTcWDxSdtwaKTtWrz+bSJ3r1thqq61Gle7hYQ972CiZ/WmnnTYyUJvIsbk6SPkxHFJ2DIOUG6vTl03kmLwFUtApiPvQhz705s9EkZrrb3rTm6of/vCHI85mWWNzy40+aA3Wyy+//ObPuMv6/7h4fZ+XxwP2d1J8/2bBLP3ZhMHO3VnYWKIfcmwuFnbMclyOCnWNlFBhCJ/85Cer+973vlN/k2Nz7SKfzeKRsqNGyo7V788mUueaDDosw6sNOTaXi5QfwyFlx2KRcmM5fdlEjslbsNdee436gv4Zrx133LF65jOfOfq7SSYufGyubHCce+65K7e73e1WzjrrrJWvfOUrK8973vNW7nSnO6184xvfGH3/rGc9a+VlL3vZzcd/+tOfXvm5n/u5lZNPPnnlb//2b1eOPfbYldve9rYrf/M3f7OKrVi//fnqV7965dJLL125/vrrV6655pqVZzzjGSu3v/3tV7785S+vbHaozPTXf/3Xo5epeMopp4z+/vrXvz76Xj/qz8A//MM/rPz8z//8ykte8pLR2Dz99NNXbnOb26xccsklK5sdffvy1FNPXfnwhz+88vd///ejua0q1pZbbrnyiU98YmWz4wUveMGoqtqVV165cuONN978+p//+Z+bj0m5uXpIuTEsUnYMh5Qdq9+fqXONh35S5faGG25Y+dKXvjT6/xZbbLHy8Y9/fPR9js3VRcqP4ZCyYzik3Fi9vswx2Q/NKs/LHJsbnlCEN77xjSu/+qu/urLVVlut7Lzzziuf+9znbtX5Bx100K2OP//881fuf//7j45/4AMfuHLxxRevwl1vjP488sgjbz72bne728oTnvCElS9+8YurdOdrC1dcccXIgG2+ov+868/mb3bYYYdRf/7ar/3ayrve9a5Vuvv13Zcnnnjiyq//+q+PFqY73/nOK3vuuefKJz/5yVVswdpBWz96lWMt5ebqIeXGsEjZMRxSdqx+f6bONR4HH3zwyr3vfe9R3/zyL//yyl577XWzIQs5NlcXKT+GQ8qO4ZByY/X6MsfkfITiMsfmFv6Z388xkUgkEolEIpFIJBKJRCKRSGwGbOgciolEIpFIJBKJRCKRSCQSiURiWCShmEgkEolEIpFIJBKJRCKRSCQ6IwnFRCKRSCQSiUQikUgkEolEItEZSSgmEolEIpFIJBKJRCKRSCQSic5IQjGRSCQSiUQikUgkEolEIpFIdEYSiolEIpFIJBKJRCKRSCQSiUSiM5JQTCQSiUQikUgkEolEIpFIJBKdkYRiIpFIJBKJRCKRSCQSiUQikeiMJBQTiUQikUgkEolEIpFIJBKJRGckoZhIJBKJRCKRSCQSiUQikUgkOiMJxUQikUgkEolEIpFIJBKJRCLRGUkoJhKJRCKRSCQSiUQikUgkEomqK/5/JLF5rzZlx/8AAAAASUVORK5CYII=", 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", 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" ] @@ -212,12 +211,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -291,7 +290,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -310,12 +309,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -346,12 +345,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -383,37 +382,11 @@ "We will take a look on how to create our own geometry. The one we will try to make is a heart defined by the function $$(x^2+y^2-1)^3-x^2y^3 \\le 0$$" ] }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let's start by importing what we will need to create our own geometry based on this equation." - ] - }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], - "source": [ - "import torch\n", - "from pina import LabelTensor" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Next, we will create the `Heart(DomainInterface)` class and initialize it." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "class Heart(DomainInterface):\n", " \"\"\"Implementation of the Heart Domain.\"\"\"\n", @@ -432,7 +405,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -467,7 +440,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -510,7 +483,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -527,12 +500,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -552,9 +525,17 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## What's next?\n", + "## What's Next?\n", "\n", - "We have made a very simple tutorial on how to build custom geometries and use domain operation to compose base geometries. Now you can play around with different geometries and build your own! " + "We have walked through a simple tutorial on how to build custom geometries and use domain operations to compose base geometries. Now you can experiment with different geometries and create your own!\n", + "\n", + "1. **Experiment with Complex Geometries**: Combine multiple basic shapes to create more intricate structures using domain operations.\n", + "\n", + "2. **Optimize Geometry for Specific Tasks**: Customize your geometry models for specialized applications such as fluid dynamics, heat transfer, or structural analysis.\n", + "\n", + "3. **...and many more!**: Explore new geometries and build them with `DomainInterface`!\n", + "\n", + "For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/)." ] } ], diff --git a/tutorials/tutorial6/tutorial.py b/tutorials/tutorial6/tutorial.py deleted file mode 100644 index 295b760..0000000 --- a/tutorials/tutorial6/tutorial.py +++ /dev/null @@ -1,293 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# # Tutorial: Building custom geometries with PINA `DomainInterface` class -# -# [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial6/tutorial.ipynb) -# -# In this tutorial we will show how to use geometries in PINA. Specifically, the tutorial will include how to create geometries and how to visualize them. The topics covered are: -# -# * Creating CartesianDomains and EllipsoidDomains -# * Getting the Union and Difference of Geometries -# * Sampling points in the domain (and visualize them) -# -# We import the relevant modules first. - -# In[ ]: - - -## routine needed to run the notebook on Google Colab -try: - import google.colab - - IN_COLAB = True -except: - IN_COLAB = False -if IN_COLAB: - get_ipython().system('pip install "pina-mathlab"') - -import matplotlib.pyplot as plt - -from pina.domain import ( - EllipsoidDomain, - Difference, - CartesianDomain, - Union, - SimplexDomain, - DomainInterface, -) -from pina.label_tensor import LabelTensor - - -def plot_scatter(ax, pts, title): - ax.title.set_text(title) - ax.scatter(pts.extract("x"), pts.extract("y"), color="blue", alpha=0.5) - - -# ## Built-in Geometries - -# We will create one cartesian and two ellipsoids. For the sake of simplicity, we show here the 2-dimensional case, but the extension to 3D (and higher) cases is trivial. The geometries allow also the generation of samples belonging to the boundary. So, we will create one ellipsoid with the border and one without. - -# In[ ]: - - -cartesian = CartesianDomain({"x": [0, 2], "y": [0, 2]}) -ellipsoid_no_border = EllipsoidDomain({"x": [1, 3], "y": [1, 3]}) -ellipsoid_border = EllipsoidDomain( - {"x": [2, 4], "y": [2, 4]}, sample_surface=True -) - - -# The `{'x': [0, 2], 'y': [0, 2]}` are the bounds of the `CartesianDomain` being created. -# -# To visualize these shapes, we need to sample points on them. We will use the `sample` method of the `CartesianDomain` and `EllipsoidDomain` classes. This method takes a `n` argument which is the number of points to sample. It also takes different modes to sample, such as `'random'`. - -# In[ ]: - - -cartesian_samples = cartesian.sample(n=1000, mode="random") -ellipsoid_no_border_samples = ellipsoid_no_border.sample(n=1000, mode="random") -ellipsoid_border_samples = ellipsoid_border.sample(n=1000, mode="random") - - -# We can see the samples of each geometry to see what we are working with. - -# In[4]: - - -print(f"Cartesian Samples: {cartesian_samples}") -print(f"Ellipsoid No Border Samples: {ellipsoid_no_border_samples}") -print(f"Ellipsoid Border Samples: {ellipsoid_border_samples}") - - -# Notice how these are all `LabelTensor` objects. You can read more about these in the [documentation](https://mathlab.github.io/PINA/_rst/label_tensor.html). At a very high level, they are tensors where each element in a tensor has a label that we can access by doing `.labels`. We can also access the values of the tensor by doing `.extract(['x'])`. -# -# We are now ready to visualize the samples using matplotlib. - -# In[ ]: - - -fig, axs = plt.subplots(1, 3, figsize=(16, 4)) -pts_list = [ - cartesian_samples, - ellipsoid_no_border_samples, - ellipsoid_border_samples, -] -title_list = ["Cartesian Domain", "Ellipsoid Domain", "Ellipsoid Border Domain"] -for ax, pts, title in zip(axs, pts_list, title_list): - plot_scatter(ax, pts, title) - - -# We have now created, sampled, and visualized our first geometries! We can see that the `EllipsoidDomain` with the border has a border around it. We can also see that the `EllipsoidDomain` without the border is just the ellipse. We can also see that the `CartesianDomain` is just a square. - -# ### Simplex Domain -# -# Among the built-in shapes, we quickly show here the usage of `SimplexDomain`, which can be used for polygonal domains! - -# In[ ]: - - -import torch - -spatial_domain = SimplexDomain( - [ - LabelTensor(torch.tensor([[0, 0]]), labels=["x", "y"]), - LabelTensor(torch.tensor([[1, 1]]), labels=["x", "y"]), - LabelTensor(torch.tensor([[0, 2]]), labels=["x", "y"]), - ] -) - -spatial_domain2 = SimplexDomain( - [ - LabelTensor(torch.tensor([[0.0, -2.0]]), labels=["x", "y"]), - LabelTensor(torch.tensor([[-0.5, -0.5]]), labels=["x", "y"]), - LabelTensor(torch.tensor([[-2.0, 0.0]]), labels=["x", "y"]), - ] -) - -pts = spatial_domain2.sample(100) -fig, axs = plt.subplots(1, 2, figsize=(16, 6)) -for domain, ax in zip([spatial_domain, spatial_domain2], axs): - pts = domain.sample(1000) - plot_scatter(ax, pts, "Simplex Domain") - - -# ## Boolean Operations - -# To create complex shapes we can use the boolean operations, for example to merge two default geometries. We need to simply use the `Union` class: it takes a list of geometries and returns the union of them. -# -# Let's create three unions. Firstly, it will be a union of `cartesian` and `ellipsoid_no_border`. Next, it will be a union of `ellipse_no_border` and `ellipse_border`. Lastly, it will be a union of all three geometries. - -# In[7]: - - -cart_ellipse_nb_union = Union([cartesian, ellipsoid_no_border]) -cart_ellipse_b_union = Union([cartesian, ellipsoid_border]) -three_domain_union = Union([cartesian, ellipsoid_no_border, ellipsoid_border]) - - -# We can of course sample points over the new geometries, by using the `sample` method as before. We highlight that the available sample strategy here is only *random*. - -# In[ ]: - - -c_e_nb_u_points = cart_ellipse_nb_union.sample(n=2000, mode="random") -c_e_b_u_points = cart_ellipse_b_union.sample(n=2000, mode="random") -three_domain_union_points = three_domain_union.sample(n=3000, mode="random") - - -# We can plot the samples of each of the unions to see what we are working with. - -# In[ ]: - - -fig, axs = plt.subplots(1, 3, figsize=(16, 4)) -pts_list = [c_e_nb_u_points, c_e_b_u_points, three_domain_union_points] -title_list = [ - "Cartesian with Ellipsoid No Border Union", - "Cartesian with Ellipsoid Border Union", - "Three Domain Union", -] -for ax, pts, title in zip(axs, pts_list, title_list): - plot_scatter(ax, pts, title) - - -# Now, we will find the differences of the geometries. We will find the difference of `cartesian` and `ellipsoid_no_border`. - -# In[ ]: - - -cart_ellipse_nb_difference = Difference([cartesian, ellipsoid_no_border]) -c_e_nb_d_points = cart_ellipse_nb_difference.sample(n=2000, mode="random") - -fig, ax = plt.subplots(1, 1, figsize=(8, 6)) -plot_scatter(ax, c_e_nb_d_points, "Difference") - - -# ## Create Custom DomainInterface - -# We will take a look on how to create our own geometry. The one we will try to make is a heart defined by the function $$(x^2+y^2-1)^3-x^2y^3 \le 0$$ - -# Let's start by importing what we will need to create our own geometry based on this equation. - -# In[11]: - - -import torch -from pina import LabelTensor - - -# Next, we will create the `Heart(DomainInterface)` class and initialize it. - -# In[ ]: - - -class Heart(DomainInterface): - """Implementation of the Heart Domain.""" - - def __init__(self, sample_border=False): - super().__init__() - - -# Because the `DomainInterface` class we are inheriting from requires both a `sample` method and `is_inside` method, we will create them and just add in "pass" for the moment. We also observe that the methods `sample_modes` and `variables` of the `DomainInterface` class are initialized as `abstractmethod`, so we need to redefine them both in the subclass `Heart` . - -# In[ ]: - - -class Heart(DomainInterface): - """Implementation of the Heart Domain.""" - - def __init__(self, sample_border=False): - super().__init__() - - def is_inside(self): - pass - - def sample(self): - pass - - @property - def sample_modes(self): - pass - - @property - def variables(self): - pass - - -# Now we have the skeleton for our `Heart` class. Also the `sample` method is where most of the work is done so let's fill it out. - -# In[ ]: - - -class Heart(DomainInterface): - """Implementation of the Heart Domain.""" - - def __init__(self, sample_border=False): - super().__init__() - - def is_inside(self): - pass - - def sample(self, n): - sampled_points = [] - - while len(sampled_points) < n: - x = torch.rand(1) * 3.0 - 1.5 - y = torch.rand(1) * 3.0 - 1.5 - if ((x**2 + y**2 - 1) ** 3 - (x**2) * (y**3)) <= 0: - sampled_points.append([x.item(), y.item()]) - - return LabelTensor(torch.tensor(sampled_points), labels=["x", "y"]) - - @property - def sample_modes(self): - pass - - @property - def variables(self): - pass - - -# To create the Heart geometry we simply run: - -# In[15]: - - -heart = Heart() - - -# To sample from the Heart geometry we simply run: - -# In[ ]: - - -pts_heart = heart.sample(1500) - -fig, ax = plt.subplots() -plot_scatter(ax, pts_heart, "Heart Domain") - - -# ## What's next? -# -# We have made a very simple tutorial on how to build custom geometries and use domain operation to compose base geometries. Now you can play around with different geometries and build your own! diff --git a/tutorials/tutorial7/tutorial.ipynb b/tutorials/tutorial7/tutorial.ipynb index ad74cfe..b53d1fc 100644 --- a/tutorials/tutorial7/tutorial.ipynb +++ b/tutorials/tutorial7/tutorial.ipynb @@ -5,47 +5,34 @@ "id": "dbbb73cb-a632-4056-bbca-b483b2ad5f9c", "metadata": {}, "source": [ - "# Tutorial: Resolution of an inverse problem\n", + "# Tutorial: Inverse Problem Solving with Physics-Informed Neural Network\n", + "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial7/tutorial.ipynb)\n", + "\n", + "## Introduction to the Inverse Problem\n", + "\n", + "This tutorial demonstrates how to solve an inverse Poisson problem using Physics-Informed Neural Networks (PINNs).\n", + "\n", + "The problem is defined as a Poisson equation with homogeneous boundary conditions:\n", "\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial7/tutorial.ipynb)" - ] - }, - { - "cell_type": "markdown", - "id": "84508f26-1ba6-4b59-926b-3e340d632a15", - "metadata": {}, - "source": [ - "### Introduction to the inverse problem" - ] - }, - { - "cell_type": "markdown", - "id": "cae54664-4572-49df-8b2d-9e7dd1e45ec0", - "metadata": {}, - "source": [ - "This tutorial shows how to solve an inverse Poisson problem with Physics-Informed Neural Networks. The problem definition is that of a Poisson problem with homogeneous boundary conditions and it reads:\n", "\\begin{equation}\n", "\\begin{cases}\n", - "\\Delta u = e^{-2(x-\\mu_1)^2-2(y-\\mu_2)^2} \\text{ in } \\Omega\\, ,\\\\\n", - "u = 0 \\text{ on }\\partial \\Omega,\\\\\n", - "u(\\mu_1, \\mu_2) = \\text{ data}\n", + "\\Delta u = e^{-2(x - \\mu_1)^2 - 2(y - \\mu_2)^2} \\quad \\text{in } \\Omega, \\\\\n", + "u = 0 \\quad \\text{on } \\partial \\Omega, \\\\\n", + "u(\\mu_1, \\mu_2) = \\text{data}\n", "\\end{cases}\n", "\\end{equation}\n", - "where $\\Omega$ is a square domain $[-2, 2] \\times [-2, 2]$, and $\\partial \\Omega=\\Gamma_1 \\cup \\Gamma_2 \\cup \\Gamma_3 \\cup \\Gamma_4$ is the union of the boundaries of the domain.\n", "\n", - "This kind of problem, namely the \"inverse problem\", has two main goals:\n", - "- find the solution $u$ that satisfies the Poisson equation;\n", - "- find the unknown parameters ($\\mu_1$, $\\mu_2$) that better fit some given data (third equation in the system above).\n", + "Here, $\\Omega$ is the square domain $[-2, 2] \\times [-2, 2]$, and $\\partial \\Omega = \\Gamma_1 \\cup \\Gamma_2 \\cup \\Gamma_3 \\cup \\Gamma_4$ represents the union of its boundaries.\n", "\n", - "In order to achieve both goals we will need to define an `InverseProblem` in PINA." - ] - }, - { - "cell_type": "markdown", - "id": "c1f8cb1b-c1bc-4495-96e2-ce8e9102fe56", - "metadata": {}, - "source": [ - "Let's start with useful imports." + "This type of setup defines an *inverse problem*, which has two primary objectives:\n", + "\n", + "- **Find the solution** $u$ that satisfies the Poisson equation,\n", + "- **Identify the unknown parameters** $(\\mu_1, \\mu_2)$ that best fit the given data (as described by the third equation in the system).\n", + "\n", + "To tackle both objectives, we will define an `InverseProblem` using **PINA**.\n", + "\n", + "Let's begin with the necessary imports:\n" ] }, { @@ -67,7 +54,7 @@ "883" ] }, - "execution_count": 20, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -81,7 +68,7 @@ "except:\n", " IN_COLAB = False\n", "if IN_COLAB:\n", - " !pip install \"pina-mathlab\"\n", + " !pip install \"pina-mathlab[tutorial]\"\n", " # get the data\n", " !mkdir \"data\"\n", " !wget \"https://github.com/mathLab/PINA/raw/refs/heads/master/tutorials/tutorial7/data/pinn_solution_0.5_0.5\" -O \"data/pinn_solution_0.5_0.5\"\n", @@ -91,6 +78,9 @@ "import torch\n", "import warnings\n", "\n", + "from lightning.pytorch import seed_everything\n", + "from lightning.pytorch.callbacks import Callback\n", + "\n", "from pina import Condition, Trainer\n", "from pina.problem import SpatialProblem, InverseProblem\n", "from pina.operator import laplacian\n", @@ -99,8 +89,6 @@ "from pina.solver import PINN\n", "from pina.domain import CartesianDomain\n", "from pina.optim import TorchOptimizer\n", - "from lightning.pytorch import seed_everything\n", - "from lightning.pytorch.callbacks import Callback\n", "\n", "warnings.filterwarnings(\"ignore\")\n", "seed_everything(883)" @@ -111,12 +99,20 @@ "id": "5138afdf-bff6-46bf-b423-a22673190687", "metadata": {}, "source": [ - "Then, we import the pre-saved data, for ($\\mu_1$, $\\mu_2$)=($0.5$, $0.5$). These two values are the optimal parameters that we want to find through the neural network training. In particular, we import the `input` points (the spatial coordinates), and the `target` points (the corresponding $u$ values evaluated at the `input`)." + "Next, we import the pre-saved data corresponding to the true parameter values $(\\mu_1, \\mu_2) = (0.5, 0.5)$. \n", + "These values represent the *optimal parameters* that we aim to recover through neural network training.\n", + "\n", + "In particular, we load:\n", + "\n", + "- `input` points — the spatial coordinates where observations are available,\n", + "- `target` points — the corresponding $u$ values (i.e., the solution evaluated at the `input` points).\n", + "\n", + "This data will be used to guide the inverse problem and supervise the network’s prediction of the unknown parameters." ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 11, "id": "2c55d972-09a9-41de-9400-ba051c28cdcb", "metadata": {}, "outputs": [], @@ -132,12 +128,17 @@ "id": "6541ffbe-7940-421a-9048-a796ec56f1d6", "metadata": {}, "source": [ - "Moreover, let's plot also the data points and the reference solution: this is the expected output of the neural network." + "Next, let's visualize the data:\n", + "\n", + "- We'll plot the data points, i.e., the spatial coordinates where measurements are available.\n", + "- We'll also display the reference solution corresponding to $(\\mu_1, \\mu_2) = (0.5, 0.5)$.\n", + "\n", + "This serves as the ground truth or expected output that our neural network should learn to approximate through training." ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 12, "id": "55cef553-7495-401d-9d17-1acff8ec5953", "metadata": {}, "outputs": [ @@ -167,20 +168,17 @@ "id": "de7c4c83", "metadata": {}, "source": [ - "### Inverse problem definition in PINA" - ] - }, - { - "cell_type": "markdown", - "id": "c46410fa-2718-4fc9-977a-583fe2390028", - "metadata": {}, - "source": [ - "Then, we initialize the Poisson problem, that is inherited from the `SpatialProblem` and from the `InverseProblem` classes. We here have to define all the variables, and the domain where our unknown parameters ($\\mu_1$, $\\mu_2$) belong. Notice that the Laplace equation takes as inputs also the unknown variables, that will be treated as parameters that the neural network optimizes during the training process." + "## Inverse Problem Definition in PINA\n", + "\n", + "Next, we initialize the Poisson problem, which inherits from the `SpatialProblem` and `InverseProblem` classes. \n", + "In this step, we need to define all the variables and specify the domain in which our unknown parameters $(\\mu_1, \\mu_2)$ reside.\n", + "\n", + "Note that the Laplace equation also takes these unknown parameters as inputs. These parameters will be treated as variables that the neural network will optimize during the training process, enabling it to learn the optimal values for $(\\mu_1, \\mu_2)$." ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 13, "id": "8ec0d95d-72c2-40a4-a310-21c3d6fe17d2", "metadata": {}, "outputs": [], @@ -204,11 +202,6 @@ "\n", "\n", "class Poisson(SpatialProblem, InverseProblem):\n", - " r\"\"\"\n", - " Implementation of the inverse 2-dimensional Poisson problem in the square\n", - " domain :math:`[0, 1] \\times [0, 1]`,\n", - " with unknown parameter domain :math:`[-1, 1] \\times [-1, 1]`.\n", - " \"\"\"\n", "\n", " output_variables = [\"u\"]\n", " x_min, x_max = -2, 2\n", @@ -242,12 +235,12 @@ "id": "6b264569-57b3-458d-bb69-8e94fe89017d", "metadata": {}, "source": [ - "Then, we define the neural network model we want to use. Here we used a model which imposes hard constrains on the boundary conditions, as also done in the Wave tutorial!" + "Next, we define the neural network model that will be used for solving the inverse problem. In this case, we use a simple FeedForeard model, but you could build one that imposes *hard constraints* on the boundary conditions, similar to the approach used in the [Wave tutorial](https://mathlab.github.io/PINA/tutorial3/tutorial.html) to have better performances!" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 14, "id": "c4170514-eb73-488e-8942-0129070e4e13", "metadata": {}, "outputs": [], @@ -270,7 +263,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 15, "id": "e3e0ae40-d8c6-4c08-81e8-85adc60a94e6", "metadata": {}, "outputs": [], @@ -288,19 +281,21 @@ "id": "b272796a-888c-4795-9d88-3e13121e8f38", "metadata": {}, "source": [ - "Here, we define a simple callback for the trainer. We use this callback to save the parameters predicted by the neural network during the training. The parameters are saved every 100 epochs as `torch` tensors in a specified directory (`tmp_dir` in our case).\n", - "The goal is to read the saved parameters after training and plot their trend across the epochs." + "Here, we define a simple callback for the trainer. This callback is used to save the parameters predicted by the neural network during training. \n", + "The parameters are saved every 100 epochs as `torch` tensors in a specified directory (in our case, `tutorial_logs`).\n", + "\n", + "The goal of this setup is to read the saved parameters after training and visualize their trend across the epochs. This allows us to monitor how the predicted parameters evolve throughout the training process.\n" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 16, "id": "e1409953-eb1b-443b-923d-c7ec3af0dfb0", "metadata": {}, "outputs": [], "source": [ "# temporary directory for saving logs of training\n", - "tmp_dir = \"tmp_poisson_inverse\"\n", + "tmp_dir = \"tutorial_logs\"\n", "\n", "\n", "class SaveParameters(Callback):\n", @@ -321,12 +316,12 @@ "id": "fc6e0030-f6ae-40cf-a3b3-d21d6538e7f2", "metadata": {}, "source": [ - "Then, we define the `PINN` object and train the solver using the `Trainer`." + "Then, we define the `PINN` object and train the solver using the `Trainer`" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 17, "id": "05a0f311-3cca-429b-be2c-1fa899b14e62", "metadata": {}, "outputs": [ @@ -340,11 +335,18 @@ ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1499: 100%|██████████| 1/1 [00:00<00:00, 68.34it/s, v_num=2, g1_loss=0.000142, g2_loss=3.78e-5, g3_loss=0.000105, g4_loss=3.2e-5, D_loss=0.000561, data_loss=2.71e-5, train_loss=0.000906] " - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "ca3282f5c0654d9d8d4335107e7254e1", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" ] @@ -542,10 +959,26 @@ }, { "cell_type": "markdown", - "id": "b062369e", + "id": "49e51233", "metadata": {}, "source": [ - "#### References\n", + "## What's Next?\n", + "\n", + "Congratulations on completing this tutorial using **PINA** to apply reduced order modeling techniques with **POD-RBF** and **POD-NN**! There are several directions you can explore next:\n", + "\n", + "1. **Extend to More Complex Problems**: Try using more complex parametric domains or PDEs. For example, you can explore Navier-Stokes equations in 3D or more complex boundary conditions.\n", + "\n", + "2. **Combine POD with Deep Learning Techniques**: Investigate hybrid methods, such as combining **POD-NN** with convolutional layers or recurrent layers, to handle time-dependent problems or more complex spatial dependencies.\n", + "\n", + "3. **Evaluate Performance on Larger Datasets**: Work with larger datasets to assess how well these methods scale. You may want to test on datasets from simulations or real-world problems.\n", + "\n", + "4. **Hybrid Models with Physics Informed Networks (PINN)**: Integrate **POD** models with PINN frameworks to include physics-based regularization in your model and improve predictions for more complex scenarios, such as turbulent fluid flow.\n", + "\n", + "5. **...and many more!**: The potential applications of reduced order models are vast, ranging from material science simulations to real-time predictions in engineering applications.\n", + "\n", + "For more information and advanced tutorials, refer to the [PINA Documentation](https://mathlab.github.io/PINA/).\n", + "\n", + "### References\n", "1. Rozza G., Stabile G., Ballarin F. (2022). Advanced Reduced Order Methods and Applications in Computational Fluid Dynamics, Society for Industrial and Applied Mathematics. \n", "2. Hesthaven, J. S., & Ubbiali, S. (2018). Non-intrusive reduced order modeling of nonlinear problems using neural networks. Journal of Computational Physics, 363, 55-78." ] diff --git a/tutorials/tutorial8/tutorial.py b/tutorials/tutorial8/tutorial.py deleted file mode 100644 index 374019f..0000000 --- a/tutorials/tutorial8/tutorial.py +++ /dev/null @@ -1,315 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# # Tutorial: Reduced order models (POD-NN and POD-RBF) for parametric problems -# -# [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial9/tutorial.ipynb) - -# The tutorial aims to show how to employ the **PINA** library in order to apply a reduced order modeling technique [1]. Such methodologies have several similarities with machine learning approaches, since the main goal consists in predicting the solution of differential equations (typically parametric PDEs) in a real-time fashion. -# -# In particular we are going to use the Proper Orthogonal Decomposition with either Radial Basis Function Interpolation (POD-RBF) or Neural Network (POD-NN) [2]. Here we basically perform a dimensional reduction using the POD approach, approximating the parametric solution manifold (at the reduced space) using a regression technique (NN) and comparing it to an RBF interpolation. In this example, we use a simple multilayer perceptron, but the plenty of different architectures can be plugged as well. - -# Let's start with the necessary imports. -# It's important to note the minimum PINA version to run this tutorial is the `0.1`. - -# In[ ]: - - -## routine needed to run the notebook on Google Colab -try: - import google.colab - - IN_COLAB = True -except: - IN_COLAB = False -if IN_COLAB: - get_ipython().system('pip install "pina-mathlab"') - -get_ipython().run_line_magic('matplotlib', 'inline') - -import matplotlib -import matplotlib.pyplot as plt -import torch -import numpy as np -import warnings - -from pina import Trainer -from pina.model import FeedForward -from pina.solver import SupervisedSolver -from pina.optim import TorchOptimizer -from pina.problem.zoo import SupervisedProblem -from pina.model.block import PODBlock, RBFBlock - -warnings.filterwarnings("ignore") - - -# We exploit the [Smithers](https://github.com/mathLab/Smithers) library to collect the parametric snapshots. In particular, we use the `NavierStokesDataset` class that contains a set of parametric solutions of the Navier-Stokes equations in a 2D L-shape domain. The parameter is the inflow velocity. -# The dataset is composed by 500 snapshots of the velocity (along $x$, $y$, and the magnitude) and pressure fields, and the corresponding parameter values. -# -# To visually check the snapshots, let's plot also the data points and the reference solution: this is the expected output of our model. - -# In[83]: - - -from smithers.dataset import NavierStokesDataset - -dataset = NavierStokesDataset() - -fig, axs = plt.subplots(1, 4, figsize=(14, 3)) -for ax, p, u in zip(axs, dataset.params[:4], dataset.snapshots["mag(v)"][:4]): - ax.tricontourf(dataset.triang, u, levels=16) - ax.set_title(f"$\mu$ = {p[0]:.2f}") - - -# The *snapshots* - aka the numerical solutions computed for several parameters - and the corresponding parameters are the only data we need to train the model, in order to predict the solution for any new test parameter. To properly validate the accuracy, we will split the 500 snapshots into the training dataset (90% of the original data) and the testing one (the reamining 10%) inside the `Trainer`. -# -# It is now time to define the problem! - -# In[84]: - - -u = torch.tensor(dataset.snapshots["mag(v)"]).float() -p = torch.tensor(dataset.params).float() -problem = SupervisedProblem(input_=p, output_=u) - - -# We can then build a `POD-NN` model (using an MLP architecture as approximation) and compare it with a `POD-RBF` model (using a Radial Basis Function interpolation as approximation). - -# ## POD-NN reduced order model - -# Let's build the `PODNN` class - -# In[85]: - - -class PODNN(torch.nn.Module): - """ - Proper orthogonal decomposition with neural network model. - """ - - def __init__(self, pod_rank, layers, func): - """ """ - super().__init__() - - self.pod = PODBlock(pod_rank) - self.nn = FeedForward( - input_dimensions=1, - output_dimensions=pod_rank, - layers=layers, - func=func, - ) - - def forward(self, x): - """ - Defines the computation performed at every call. - - :param x: The tensor to apply the forward pass. - :type x: torch.Tensor - :return: the output computed by the model. - :rtype: torch.Tensor - """ - coefficents = self.nn(x) - return self.pod.expand(coefficents) - - def fit_pod(self, x): - """ - Just call the :meth:`pina.model.layers.PODBlock.fit` method of the - :attr:`pina.model.layers.PODBlock` attribute. - """ - self.pod.fit(x) - - -# We highlight that the POD modes are directly computed by means of the singular value decomposition (computed over the input data), and not trained using the backpropagation approach. Only the weights of the MLP are actually trained during the optimization loop. - -# In[86]: - - -pod_nn = PODNN(pod_rank=20, layers=[10, 10, 10], func=torch.nn.Tanh) -pod_nn_stokes = SupervisedSolver( - problem=problem, - model=pod_nn, - optimizer=TorchOptimizer(torch.optim.Adam, lr=0.0001), - use_lt=False, -) - - -# Before starting we need to fit the POD basis on the training dataset, this can be easily done in PINA as well: - -# In[87]: - - -trainer = Trainer( - solver=pod_nn_stokes, - max_epochs=1000, - batch_size=None, - accelerator="cpu", - train_size=0.9, - val_size=0.0, - test_size=0.1, -) - -# fit the pod basis -trainer.data_module.setup("fit") # set up the dataset -x_train = trainer.data_module.train_dataset.conditions_dict["data"][ - "target" -] # extract data for training -pod_nn.fit_pod(x=x_train) - -# now train -trainer.train() - - -# Done! Now that the computational expensive part is over, we can load in future the model to infer new parameters (simply loading the checkpoint file automatically created by `Lightning`) or test its performances. We measure the relative error for the training and test datasets, printing the mean one. - -# In[ ]: - - -# extract train and test data -trainer.data_module.setup("test") # set up the dataset -p_train = trainer.data_module.train_dataset.conditions_dict["data"]["input"] -u_train = trainer.data_module.train_dataset.conditions_dict["data"]["target"] -p_test = trainer.data_module.test_dataset.conditions_dict["data"]["input"] -u_test = trainer.data_module.test_dataset.conditions_dict["data"]["target"] - -# compute statistics -u_test_nn = pod_nn_stokes(p_test) -u_train_nn = pod_nn_stokes(p_train) - -relative_error_train = torch.norm(u_train_nn - u_train) / torch.norm(u_train) -relative_error_test = torch.norm(u_test_nn - u_test) / torch.norm(u_test) - -print("Error summary for POD-NN model:") -print(f" Train: {relative_error_train.item():e}") -print(f" Test: {relative_error_test.item():e}") - - -# ## POD-RBF reduced order model - -# Then, we define the model we want to use, with the POD (`PODBlock`) and the RBF (`RBFBlock`) objects. - -# In[89]: - - -class PODRBF(torch.nn.Module): - """ - Proper orthogonal decomposition with Radial Basis Function interpolation model. - """ - - def __init__(self, pod_rank, rbf_kernel): - """ """ - super().__init__() - - self.pod = PODBlock(pod_rank) - self.rbf = RBFBlock(kernel=rbf_kernel) - - def forward(self, x): - """ - Defines the computation performed at every call. - - :param x: The tensor to apply the forward pass. - :type x: torch.Tensor - :return: the output computed by the model. - :rtype: torch.Tensor - """ - coefficents = self.rbf(x) - return self.pod.expand(coefficents) - - def fit(self, p, x): - """ - Call the :meth:`pina.model.layers.PODBlock.fit` method of the - :attr:`pina.model.layers.PODBlock` attribute to perform the POD, - and the :meth:`pina.model.layers.RBFBlock.fit` method of the - :attr:`pina.model.layers.RBFBlock` attribute to fit the interpolation. - """ - self.pod.fit(x) - self.rbf.fit(p, self.pod.reduce(x)) - - -# We can then fit the model and ask it to predict the required field for unseen values of the parameters. Note that this model does not need a `Trainer` since it does not include any neural network or learnable parameters. - -# In[90]: - - -pod_rbf = PODRBF(pod_rank=20, rbf_kernel="thin_plate_spline") -pod_rbf.fit(p_train, u_train) - - -# Compute errors - -# In[91]: - - -u_test_rbf = pod_rbf(p_test) -u_train_rbf = pod_rbf(p_train) - -relative_error_train = torch.norm(u_train_rbf - u_train) / torch.norm(u_train) -relative_error_test = torch.norm(u_test_rbf - u_test) / torch.norm(u_test) - -print("Error summary for POD-RBF model:") -print(f" Train: {relative_error_train.item():e}") -print(f" Test: {relative_error_test.item():e}") - - -# ## POD-RBF vs POD-NN - -# We can of course also plot the solutions predicted by the `PODRBF` and by the `PODNN` model, comparing them to the original ones. We can note here, in the `PODNN` model and for low velocities, some differences, but improvements can be accomplished thanks to longer training. - -# In[92]: - - -idx = torch.randint(0, len(u_test), (4,)) -u_idx_rbf = pod_rbf(p_test[idx]) -u_idx_nn = pod_nn_stokes(p_test[idx]) - - -fig, axs = plt.subplots(4, 5, figsize=(14, 9)) - -relative_error_rbf = np.abs(u_test[idx] - u_idx_rbf.detach()) -relative_error_rbf = np.where( - u_test[idx] < 1e-7, 1e-7, relative_error_rbf / u_test[idx] -) - -relative_error_nn = np.abs(u_test[idx] - u_idx_nn.detach()) -relative_error_nn = np.where( - u_test[idx] < 1e-7, 1e-7, relative_error_nn / u_test[idx] -) - -for i, (idx_, rbf_, nn_, rbf_err_, nn_err_) in enumerate( - zip(idx, u_idx_rbf, u_idx_nn, relative_error_rbf, relative_error_nn) -): - - axs[0, 0].set_title(f"Real Snapshots") - axs[0, 1].set_title(f"POD-RBF") - axs[0, 2].set_title(f"POD-NN") - axs[0, 3].set_title(f"Error POD-RBF") - axs[0, 4].set_title(f"Error POD-NN") - - cm = axs[i, 0].tricontourf( - dataset.triang, rbf_.detach() - ) # POD-RBF prediction - plt.colorbar(cm, ax=axs[i, 0]) - - cm = axs[i, 1].tricontourf( - dataset.triang, nn_.detach() - ) # POD-NN prediction - plt.colorbar(cm, ax=axs[i, 1]) - - cm = axs[i, 2].tricontourf(dataset.triang, u_test[idx_].flatten()) # Truth - plt.colorbar(cm, ax=axs[i, 2]) - - cm = axs[i, 3].tripcolor( - dataset.triang, rbf_err_, norm=matplotlib.colors.LogNorm() - ) # Error for POD-RBF - plt.colorbar(cm, ax=axs[i, 3]) - - cm = axs[i, 4].tripcolor( - dataset.triang, nn_err_, norm=matplotlib.colors.LogNorm() - ) # Error for POD-NN - plt.colorbar(cm, ax=axs[i, 4]) - -plt.show() - - -# #### References -# 1. Rozza G., Stabile G., Ballarin F. (2022). Advanced Reduced Order Methods and Applications in Computational Fluid Dynamics, Society for Industrial and Applied Mathematics. -# 2. Hesthaven, J. S., & Ubbiali, S. (2018). Non-intrusive reduced order modeling of nonlinear problems using neural networks. Journal of Computational Physics, 363, 55-78. diff --git a/tutorials/tutorial9/tutorial.ipynb b/tutorials/tutorial9/tutorial.ipynb index daf81ec..d93e9c4 100644 --- a/tutorials/tutorial9/tutorial.ipynb +++ b/tutorials/tutorial9/tutorial.ipynb @@ -4,18 +4,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Tutorial: One dimensional Helmholtz equation using Periodic Boundary Conditions\n", + "# Tutorial: Applying Periodic Boundary Conditions in PINNs to solve the Helmotz Problem\n", "\n", "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial9/tutorial.ipynb)\n", "\n", - "This tutorial presents how to solve with Physics-Informed Neural Networks (PINNs)\n", - "a one dimensional Helmholtz equation with periodic boundary conditions (PBC).\n", - "We will train with standard PINN's training by augmenting the input with\n", - "periodic expansion as presented in [*An expert’s guide to training\n", - "physics-informed neural networks*](\n", - "https://arxiv.org/abs/2308.08468).\n", + "This tutorial demonstrates how to solve a one-dimensional Helmholtz equation with periodic boundary conditions (PBC) using Physics-Informed Neural Networks (PINNs). \n", + "We will use standard PINN training, augmented with a periodic input expansion as introduced in [*An Expert’s Guide to Training Physics-Informed Neural Networks*](https://arxiv.org/abs/2308.08468).\n", "\n", - "First of all, some useful imports." + "Let's start with some useful imports:\n" ] }, { @@ -32,7 +28,7 @@ "except:\n", " IN_COLAB = False\n", "if IN_COLAB:\n", - " !pip install \"pina-mathlab\"\n", + " !pip install \"pina-mathlab[tutorial]\"\n", "\n", "import torch\n", "import matplotlib.pyplot as plt\n", @@ -55,33 +51,42 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## The problem definition\n", + "## Problem Definition\n", + "\n", + "The one-dimensional Helmholtz problem is mathematically expressed as:\n", "\n", - "The one-dimensional Helmholtz problem is mathematically written as:\n", "$$\n", "\\begin{cases}\n", - "\\frac{d^2}{dx^2}u(x) - \\lambda u(x) -f(x) &= 0 \\quad x\\in(0,2)\\\\\n", - "u^{(m)}(x=0) - u^{(m)}(x=2) &= 0 \\quad m\\in[0, 1, \\cdots]\\\\\n", + "\\frac{d^2}{dx^2}u(x) - \\lambda u(x) - f(x) &= 0 \\quad \\text{for } x \\in (0, 2) \\\\\n", + "u^{(m)}(x = 0) - u^{(m)}(x = 2) &= 0 \\quad \\text{for } m \\in \\{0, 1, \\dots\\}\n", "\\end{cases}\n", "$$\n", - "In this case we are asking the solution to be $C^{\\infty}$ periodic with\n", - "period $2$, on the infinite domain $x\\in(-\\infty, \\infty)$. Notice that the\n", - "classical PINN would need infinite conditions to evaluate the PBC loss function,\n", - "one for each derivative, which is of course infeasible... \n", - "A possible solution, diverging from the original PINN formulation,\n", - "is to use *coordinates augmentation*. In coordinates augmentation you seek for\n", - "a coordinates transformation $v$ such that $x\\rightarrow v(x)$ such that\n", - "the periodicity condition $ u^{(m)}(x=0) - u^{(m)}(x=2) = 0 \\quad m\\in[0, 1, \\cdots] $ is\n", - "satisfied.\n", "\n", - "For demonstration purposes, the problem specifics are $\\lambda=-10\\pi^2$,\n", - "and $f(x)=-6\\pi^2\\sin(3\\pi x)\\cos(\\pi x)$ which give a solution that can be\n", - "computed analytically $u(x) = \\sin(\\pi x)\\cos(3\\pi x)$." + "In this case, we seek a solution that is $C^{\\infty}$ (infinitely differentiable) and periodic with period 2, over the infinite domain $x \\in (-\\infty, \\infty)$. \n", + "\n", + "A classical PINN approach would require enforcing periodic boundary conditions (PBC) for all derivatives—an infinite set of constraints—which is clearly infeasible.\n", + "\n", + "To address this, we adopt a strategy known as *coordinate augmentation*. In this approach, we apply a coordinate transformation $v(x)$ such that the transformed inputs naturally satisfy the periodicity condition:\n", + "\n", + "$$\n", + "u^{(m)}(x = 0) - u^{(m)}(x = 2) = 0 \\quad \\text{for } m \\in \\{0, 1, \\dots\\}\n", + "$$\n", + "\n", + "For demonstration purposes, we choose the specific parameters:\n", + "\n", + "- $\\lambda = -10\\pi^2$\n", + "- $f(x) = -6\\pi^2 \\sin(3\\pi x) \\cos(\\pi x)$\n", + "\n", + "These yield an analytical solution:\n", + "\n", + "$$\n", + "u(x) = \\sin(\\pi x) \\cos(3\\pi x)\n", + "$$" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -123,49 +128,44 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "As usual, the Helmholtz problem is written in **PINA** code as a class. \n", - "The equations are written as `conditions` that should be satisfied in the\n", - "corresponding domains. The `solution`\n", - "is the exact solution which will be compared with the predicted one. We used\n", - "Latin Hypercube Sampling for choosing the collocation points." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Solving the problem with a Periodic Network" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Any $\\mathcal{C}^{\\infty}$ periodic function\n", - "$u : \\mathbb{R} \\rightarrow \\mathbb{R}$ with period\n", - "$L\\in\\mathbb{N}$ can be constructed by composition of an\n", - "arbitrary smooth function $f : \\mathbb{R}^n \\rightarrow \\mathbb{R}$ and a\n", - "given smooth periodic function $v : \\mathbb{R} \\rightarrow \\mathbb{R}^n$ with\n", - "period $L$, that is $u(x) = f(v(x))$. The formulation is generalizable for\n", - "arbitrary dimension, see [*A method for representing periodic functions and\n", - "enforcing exactly periodic boundary conditions with\n", - "deep neural networks*](https://arxiv.org/pdf/2007.07442).\n", + "As usual, the Helmholtz problem is implemented in **PINA** as a class. The governing equations are defined as `conditions`, which must be satisfied within their respective domains. The `solution` represents the exact analytical solution, which will be used to evaluate the accuracy of the predicted solution.\n", "\n", - "In our case, we rewrite\n", - "$v(x) = \\left[1, \\cos\\left(\\frac{2\\pi}{L} x\\right),\n", - "\\sin\\left(\\frac{2\\pi}{L} x\\right)\\right]$, i.e\n", - "the coordinates augmentation, and $f(\\cdot) = NN_{\\theta}(\\cdot)$ i.e. a neural\n", - "network. The resulting neural network obtained by composing $f$ with $v$ gives\n", - "the PINN approximate solution, that is\n", - "$u(x) \\approx u_{\\theta}(x)=NN_{\\theta}(v(x))$.\n", + "For selecting collocation points, we use Latin Hypercube Sampling (LHS), a common strategy for efficient space-filling in high-dimensional domains \n", "\n", - "In **PINA** this translates in using the `PeriodicBoundaryEmbedding` layer for $v$, and any\n", - "`pina.model` for $NN_{\\theta}$. Let's see it in action! \n" + "## Solving the Problem with a Periodic Network\n", + "\n", + "Any $\\mathcal{C}^{\\infty}$ periodic function $u : \\mathbb{R} \\rightarrow \\mathbb{R}$ with period $L \\in \\mathbb{N}$ \n", + "can be constructed by composing an arbitrary smooth function $f : \\mathbb{R}^n \\rightarrow \\mathbb{R}$ with a smooth, periodic mapping$v : \\mathbb{R} \\rightarrow \\mathbb{R}^n$ of the same period $L$. That is,\n", + "\n", + "$$\n", + "u(x) = f(v(x)).\n", + "$$\n", + "\n", + "This formulation is general and can be extended to arbitrary dimensions. \n", + "For more details, see [*A Method for Representing Periodic Functions and Enforcing Exactly Periodic Boundary Conditions with Deep Neural Networks*](https://arxiv.org/pdf/2007.07442).\n", + "\n", + "In our specific case, we define the periodic embedding as:\n", + "\n", + "$$\n", + "v(x) = \\left[1, \\cos\\left(\\frac{2\\pi}{L} x\\right), \\sin\\left(\\frac{2\\pi}{L} x\\right)\\right],\n", + "$$\n", + "\n", + "which constitutes the coordinate augmentation. The function $f(\\cdot)$ is approximated by a neural network $NN_{\\theta}(\\cdot)$, resulting in the approximate PINN solution:\n", + "\n", + "$$\n", + "u(x) \\approx u_{\\theta}(x) = NN_{\\theta}(v(x)).\n", + "$$\n", + "\n", + "In **PINA**, this is implemented using the `PeriodicBoundaryEmbedding` layer for $v(x)$, \n", + "paired with any `pina.model` to define the neural network $NN_{\\theta}$. \n", + "\n", + "Let’s see how this is put into practice!\n", + "\n" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -184,16 +184,18 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "As simple as that! Notice that in higher dimension you can specify different periods\n", - "for all dimensions using a dictionary, e.g. `periods={'x':2, 'y':3, ...}`\n", - "would indicate a periodicity of $2$ in $x$, $3$ in $y$, and so on...\n", + "As simple as that!\n", "\n", - "We will now solve the problem as usually with the `PINN` and `Trainer` class, then we will look at the losses using the `MetricTracker` callback from `pina.callback`." + "In higher dimensions, you can specify different periods for each coordinate using a dictionary. \n", + "For example, `periods = {'x': 2, 'y': 3, ...}` indicates a periodicity of 2 in the $x$ direction, \n", + "3 in the $y$ direction, and so on.\n", + "\n", + "We will now solve the problem using the usual `PINN` and `Trainer` classes. After training, we'll examine the losses using the `MetricTracker` callback from `pina.callback`." ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -206,11 +208,18 @@ ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 4999: 100%|██████████| 1/1 [00:00<00:00, 154.88it/s, v_num=1, phys_cond_loss=0.033, train_loss=0.033] " - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "89a9749dc755477aa6ed7b5aa4dc3698", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" ] @@ -282,22 +278,22 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 19, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -307,9 +303,9 @@ } ], "source": [ - "pts = pinn.problem.spatial_domain.sample(256, \"grid\", variables=\"x\")\n", - "predicted_output = pinn.forward(pts).extract(\"u\").tensor.detach()\n", - "true_output = pinn.problem.solution(pts)\n", + "pts = solver.problem.spatial_domain.sample(256, \"grid\", variables=\"x\")\n", + "predicted_output = solver(pts).extract(\"u\").tensor.detach()\n", + "true_output = solver.problem.solution(pts)\n", "plt.plot(pts.extract([\"x\"]), predicted_output, label=\"Neural Network solution\")\n", "plt.plot(pts.extract([\"x\"]), true_output, label=\"True solution\")\n", "plt.legend()" @@ -324,12 +320,12 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { - "image/png": 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" ] @@ -350,11 +346,11 @@ " axes[0].set_title(r\"True solution $u(x)$\")\n", " axes[0].legend(loc=\"upper right\")\n", " # Plot 2\n", - " axes[1].plot(x, pinn(x), label=r\"$u_{\\theta}(x)$\", color=\"green\")\n", + " axes[1].plot(x, solver(x), label=r\"$u_{\\theta}(x)$\", color=\"green\")\n", " axes[1].set_title(r\"PINN solution $u_{\\theta}(x)$\")\n", " axes[1].legend(loc=\"upper right\")\n", " # Plot 3\n", - " diff = torch.abs(problem.solution(x) - pinn(x))\n", + " diff = torch.abs(problem.solution(x) - solver(x))\n", " axes[2].plot(x, diff, label=r\"$|u(x) - u_{\\theta}(x)|$\", color=\"red\")\n", " axes[2].set_title(r\"Absolute difference $|u(x) - u_{\\theta}(x)|$\")\n", " axes[2].legend(loc=\"upper right\")\n", @@ -368,19 +364,20 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "It is pretty clear that the network is periodic, with also the error following a periodic pattern. Obviously a longer training and a more expressive neural network could improve the results!\n", - "\n", + "It's clear that the network successfully captures the periodicity of the solution, with the error also exhibiting a periodic pattern. Naturally, training for a longer duration or using a more expressive neural network could further improve the results.\n", "## What's next?\n", "\n", - "Congratulations on completing the one dimensional Helmholtz tutorial of **PINA**! There are multiple directions you can go now:\n", + "Congratulations on completing the one-dimensional Helmholtz tutorial with **PINA**! Here are a few directions you can explore next:\n", "\n", - "1. Train the network for longer or with different layer sizes and assert the finaly accuracy\n", + "1. **Train longer or with different architectures**: Experiment with extended training or modify the network's depth and width to evaluate improvements in accuracy.\n", "\n", - "2. Apply the `PeriodicBoundaryEmbedding` layer for a time-dependent problem (see reference in the documentation)\n", + "2. **Apply `PeriodicBoundaryEmbedding` to time-dependent problems**: Explore more complex scenarios such as spatiotemporal PDEs (see the official documentation for examples).\n", "\n", - "3. Exploit extrafeature training ?\n", + "3. **Try extra feature training**: Integrate additional physical or domain-specific features to guide the learning process more effectively.\n", "\n", - "4. Many more..." + "4. **...and many more!**: Extend to higher dimensions, test on other PDEs, or even develop custom embeddings tailored to your problem.\n", + "\n", + "For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/)." ] } ], diff --git a/tutorials/tutorial9/tutorial.py b/tutorials/tutorial9/tutorial.py deleted file mode 100644 index 311e9b7..0000000 --- a/tutorials/tutorial9/tutorial.py +++ /dev/null @@ -1,246 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# # Tutorial: One dimensional Helmholtz equation using Periodic Boundary Conditions -# -# [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial9/tutorial.ipynb) -# -# This tutorial presents how to solve with Physics-Informed Neural Networks (PINNs) -# a one dimensional Helmholtz equation with periodic boundary conditions (PBC). -# We will train with standard PINN's training by augmenting the input with -# periodic expansion as presented in [*An expert’s guide to training -# physics-informed neural networks*]( -# https://arxiv.org/abs/2308.08468). -# -# First of all, some useful imports. - -# In[ ]: - - -## routine needed to run the notebook on Google Colab -try: - import google.colab - - IN_COLAB = True -except: - IN_COLAB = False -if IN_COLAB: - get_ipython().system('pip install "pina-mathlab"') - -import torch -import matplotlib.pyplot as plt -import warnings - -from pina import Condition, Trainer -from pina.problem import SpatialProblem -from pina.operator import laplacian -from pina.model import FeedForward -from pina.model.block import PeriodicBoundaryEmbedding # The PBC module -from pina.solver import PINN -from pina.domain import CartesianDomain -from pina.equation import Equation -from pina.callback import MetricTracker - -warnings.filterwarnings("ignore") - - -# ## The problem definition -# -# The one-dimensional Helmholtz problem is mathematically written as: -# $$ -# \begin{cases} -# \frac{d^2}{dx^2}u(x) - \lambda u(x) -f(x) &= 0 \quad x\in(0,2)\\ -# u^{(m)}(x=0) - u^{(m)}(x=2) &= 0 \quad m\in[0, 1, \cdots]\\ -# \end{cases} -# $$ -# In this case we are asking the solution to be $C^{\infty}$ periodic with -# period $2$, on the infinite domain $x\in(-\infty, \infty)$. Notice that the -# classical PINN would need infinite conditions to evaluate the PBC loss function, -# one for each derivative, which is of course infeasible... -# A possible solution, diverging from the original PINN formulation, -# is to use *coordinates augmentation*. In coordinates augmentation you seek for -# a coordinates transformation $v$ such that $x\rightarrow v(x)$ such that -# the periodicity condition $ u^{(m)}(x=0) - u^{(m)}(x=2) = 0 \quad m\in[0, 1, \cdots] $ is -# satisfied. -# -# For demonstration purposes, the problem specifics are $\lambda=-10\pi^2$, -# and $f(x)=-6\pi^2\sin(3\pi x)\cos(\pi x)$ which give a solution that can be -# computed analytically $u(x) = \sin(\pi x)\cos(3\pi x)$. - -# In[15]: - - -def helmholtz_equation(input_, output_): - x = input_.extract("x") - u_xx = laplacian(output_, input_, components=["u"], d=["x"]) - f = ( - -6.0 - * torch.pi**2 - * torch.sin(3 * torch.pi * x) - * torch.cos(torch.pi * x) - ) - lambda_ = -10.0 * torch.pi**2 - return u_xx - lambda_ * output_ - f - - -class Helmholtz(SpatialProblem): - output_variables = ["u"] - spatial_domain = CartesianDomain({"x": [0, 2]}) - - # here we write the problem conditions - conditions = { - "phys_cond": Condition( - domain=spatial_domain, equation=Equation(helmholtz_equation) - ), - } - - def solution(self, pts): - return torch.sin(torch.pi * pts) * torch.cos(3.0 * torch.pi * pts) - - -problem = Helmholtz() - -# let's discretise the domain -problem.discretise_domain(200, "grid", domains=["phys_cond"]) - - -# As usual, the Helmholtz problem is written in **PINA** code as a class. -# The equations are written as `conditions` that should be satisfied in the -# corresponding domains. The `solution` -# is the exact solution which will be compared with the predicted one. We used -# Latin Hypercube Sampling for choosing the collocation points. - -# ## Solving the problem with a Periodic Network - -# Any $\mathcal{C}^{\infty}$ periodic function -# $u : \mathbb{R} \rightarrow \mathbb{R}$ with period -# $L\in\mathbb{N}$ can be constructed by composition of an -# arbitrary smooth function $f : \mathbb{R}^n \rightarrow \mathbb{R}$ and a -# given smooth periodic function $v : \mathbb{R} \rightarrow \mathbb{R}^n$ with -# period $L$, that is $u(x) = f(v(x))$. The formulation is generalizable for -# arbitrary dimension, see [*A method for representing periodic functions and -# enforcing exactly periodic boundary conditions with -# deep neural networks*](https://arxiv.org/pdf/2007.07442). -# -# In our case, we rewrite -# $v(x) = \left[1, \cos\left(\frac{2\pi}{L} x\right), -# \sin\left(\frac{2\pi}{L} x\right)\right]$, i.e -# the coordinates augmentation, and $f(\cdot) = NN_{\theta}(\cdot)$ i.e. a neural -# network. The resulting neural network obtained by composing $f$ with $v$ gives -# the PINN approximate solution, that is -# $u(x) \approx u_{\theta}(x)=NN_{\theta}(v(x))$. -# -# In **PINA** this translates in using the `PeriodicBoundaryEmbedding` layer for $v$, and any -# `pina.model` for $NN_{\theta}$. Let's see it in action! -# - -# In[16]: - - -# we encapsulate all modules in a torch.nn.Sequential container -model = torch.nn.Sequential( - PeriodicBoundaryEmbedding(input_dimension=1, periods=2), - FeedForward( - input_dimensions=3, # output of PeriodicBoundaryEmbedding = 3 * input_dimension - output_dimensions=1, - layers=[10, 10], - ), -) - - -# As simple as that! Notice that in higher dimension you can specify different periods -# for all dimensions using a dictionary, e.g. `periods={'x':2, 'y':3, ...}` -# would indicate a periodicity of $2$ in $x$, $3$ in $y$, and so on... -# -# We will now solve the problem as usually with the `PINN` and `Trainer` class, then we will look at the losses using the `MetricTracker` callback from `pina.callback`. - -# In[17]: - - -pinn = PINN( - problem=problem, - model=model, -) -trainer = Trainer( - pinn, - max_epochs=5000, - accelerator="cpu", - enable_model_summary=False, - callbacks=[MetricTracker()], - train_size=1.0, - val_size=0.0, - test_size=0.0, -) -trainer.train() - - -# In[18]: - - -# plot loss -trainer_metrics = trainer.callbacks[0].metrics -plt.plot( - range(len(trainer_metrics["train_loss"])), trainer_metrics["train_loss"] -) -# plotting -plt.xlabel("epoch") -plt.ylabel("loss") -plt.yscale("log") - - -# We are going to plot the solution now! - -# In[19]: - - -pts = pinn.problem.spatial_domain.sample(256, "grid", variables="x") -predicted_output = pinn.forward(pts).extract("u").tensor.detach() -true_output = pinn.problem.solution(pts) -plt.plot(pts.extract(["x"]), predicted_output, label="Neural Network solution") -plt.plot(pts.extract(["x"]), true_output, label="True solution") -plt.legend() - - -# Great, they overlap perfectly! This seems a good result, considering the simple neural network used to some this (complex) problem. We will now test the neural network on the domain $[-4, 4]$ without retraining. In principle the periodicity should be present since the $v$ function ensures the periodicity in $(-\infty, \infty)$. - -# In[20]: - - -# plotting solution -with torch.no_grad(): - # Notice here we put [-4, 4]!!! - new_domain = CartesianDomain({"x": [0, 4]}) - x = new_domain.sample(1000, mode="grid") - fig, axes = plt.subplots(1, 3, figsize=(15, 5)) - # Plot 1 - axes[0].plot(x, problem.solution(x), label=r"$u(x)$", color="blue") - axes[0].set_title(r"True solution $u(x)$") - axes[0].legend(loc="upper right") - # Plot 2 - axes[1].plot(x, pinn(x), label=r"$u_{\theta}(x)$", color="green") - axes[1].set_title(r"PINN solution $u_{\theta}(x)$") - axes[1].legend(loc="upper right") - # Plot 3 - diff = torch.abs(problem.solution(x) - pinn(x)) - axes[2].plot(x, diff, label=r"$|u(x) - u_{\theta}(x)|$", color="red") - axes[2].set_title(r"Absolute difference $|u(x) - u_{\theta}(x)|$") - axes[2].legend(loc="upper right") - # Adjust layout - plt.tight_layout() - # Show the plots - plt.show() - - -# It is pretty clear that the network is periodic, with also the error following a periodic pattern. Obviously a longer training and a more expressive neural network could improve the results! -# -# ## What's next? -# -# Congratulations on completing the one dimensional Helmholtz tutorial of **PINA**! There are multiple directions you can go now: -# -# 1. Train the network for longer or with different layer sizes and assert the finaly accuracy -# -# 2. Apply the `PeriodicBoundaryEmbedding` layer for a time-dependent problem (see reference in the documentation) -# -# 3. Exploit extrafeature training ? -# -# 4. Many more...