331 lines
134 KiB
Plaintext
Vendored
331 lines
134 KiB
Plaintext
Vendored
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Tutorial: One dimensional Helmholtz equation using Periodic Boundary Conditions\n",
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"\n",
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"[](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial9/tutorial.ipynb)\n",
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"\n",
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"This tutorial presents how to solve with Physics-Informed Neural Networks (PINNs)\n",
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"a one dimensional Helmholtz equation with periodic boundary conditions (PBC).\n",
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"We will train with standard PINN's training by augmenting the input with\n",
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"periodic expansion as presented in [*An expert’s guide to training\n",
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"physics-informed neural networks*](\n",
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"https://arxiv.org/abs/2308.08468).\n",
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"\n",
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"First of all, some useful imports."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"## routine needed to run the notebook on Google Colab\n",
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"try:\n",
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" import google.colab\n",
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" IN_COLAB = True\n",
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"except:\n",
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" IN_COLAB = False\n",
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"if IN_COLAB:\n",
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" !pip install \"pina-mathlab\"\n",
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"\n",
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"import torch\n",
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"import matplotlib.pyplot as plt\n",
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"plt.style.use('tableau-colorblind10')\n",
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"from pina import Condition#,Plotter as pl\n",
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"from pina.problem import SpatialProblem\n",
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"from pina.operator import laplacian\n",
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"from pina.model import FeedForward\n",
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"from pina.model.block import PeriodicBoundaryEmbedding # The PBC module\n",
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"from pina.solver import PINN\n",
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"from pina.trainer import Trainer\n",
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"from pina.domain import CartesianDomain\n",
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"from pina.equation import Equation"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## The problem definition\n",
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"\n",
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"The one-dimensional Helmholtz problem is mathematically written as:\n",
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"$$\n",
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"\\begin{cases}\n",
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"\\frac{d^2}{dx^2}u(x) - \\lambda u(x) -f(x) &= 0 \\quad x\\in(0,2)\\\\\n",
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"u^{(m)}(x=0) - u^{(m)}(x=2) &= 0 \\quad m\\in[0, 1, \\cdots]\\\\\n",
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"\\end{cases}\n",
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"$$\n",
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"In this case we are asking the solution to be $C^{\\infty}$ periodic with\n",
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"period $2$, on the infinite domain $x\\in(-\\infty, \\infty)$. Notice that the\n",
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"classical PINN would need infinite conditions to evaluate the PBC loss function,\n",
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"one for each derivative, which is of course infeasible... \n",
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"A possible solution, diverging from the original PINN formulation,\n",
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"is to use *coordinates augmentation*. In coordinates augmentation you seek for\n",
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"a coordinates transformation $v$ such that $x\\rightarrow v(x)$ such that\n",
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"the periodicity condition $ u^{(m)}(x=0) - u^{(m)}(x=2) = 0 \\quad m\\in[0, 1, \\cdots] $ is\n",
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"satisfied.\n",
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"\n",
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"For demonstration purposes, the problem specifics are $\\lambda=-10\\pi^2$,\n",
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"and $f(x)=-6\\pi^2\\sin(3\\pi x)\\cos(\\pi x)$ which give a solution that can be\n",
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"computed analytically $u(x) = \\sin(\\pi x)\\cos(3\\pi x)$."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"class Helmholtz(SpatialProblem):\n",
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" output_variables = ['u']\n",
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" spatial_domain = CartesianDomain({'x': [0, 2]})\n",
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"\n",
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" def Helmholtz_equation(input_, output_):\n",
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" x = input_.extract('x')\n",
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" u_xx = laplacian(output_, input_, components=['u'], d=['x'])\n",
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" f = - 6.*torch.pi**2 * torch.sin(3*torch.pi*x)*torch.cos(torch.pi*x)\n",
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" lambda_ = - 10. * torch.pi ** 2\n",
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" return u_xx - lambda_ * output_ - f\n",
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"\n",
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" # here we write the problem conditions\n",
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" conditions = {\n",
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" 'phys_cond': Condition(domain=spatial_domain,\n",
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" equation=Equation(Helmholtz_equation)),\n",
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" }\n",
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"\n",
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" def Helmholtz_sol(self, pts):\n",
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" return torch.sin(torch.pi * pts) * torch.cos(3. * torch.pi * pts)\n",
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" \n",
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" truth_solution = Helmholtz_sol\n",
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"\n",
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"problem = Helmholtz()\n",
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"\n",
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"# let's discretise the domain\n",
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"problem.discretise_domain(200, 'grid', domains=['phys_cond'])"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"As usual, the Helmholtz problem is written in **PINA** code as a class. \n",
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"The equations are written as `conditions` that should be satisfied in the\n",
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"corresponding domains. The `truth_solution`\n",
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"is the exact solution which will be compared with the predicted one. We used\n",
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"Latin Hypercube Sampling for choosing the collocation points."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Solving the problem with a Periodic Network"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Any $\\mathcal{C}^{\\infty}$ periodic function\n",
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"$u : \\mathbb{R} \\rightarrow \\mathbb{R}$ with period\n",
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"$L\\in\\mathbb{N}$ can be constructed by composition of an\n",
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"arbitrary smooth function $f : \\mathbb{R}^n \\rightarrow \\mathbb{R}$ and a\n",
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"given smooth periodic function $v : \\mathbb{R} \\rightarrow \\mathbb{R}^n$ with\n",
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"period $L$, that is $u(x) = f(v(x))$. The formulation is generalizable for\n",
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"arbitrary dimension, see [*A method for representing periodic functions and\n",
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"enforcing exactly periodic boundary conditions with\n",
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"deep neural networks*](https://arxiv.org/pdf/2007.07442).\n",
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"\n",
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"In our case, we rewrite\n",
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"$v(x) = \\left[1, \\cos\\left(\\frac{2\\pi}{L} x\\right),\n",
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"\\sin\\left(\\frac{2\\pi}{L} x\\right)\\right]$, i.e\n",
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"the coordinates augmentation, and $f(\\cdot) = NN_{\\theta}(\\cdot)$ i.e. a neural\n",
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"network. The resulting neural network obtained by composing $f$ with $v$ gives\n",
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"the PINN approximate solution, that is\n",
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"$u(x) \\approx u_{\\theta}(x)=NN_{\\theta}(v(x))$.\n",
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"\n",
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"In **PINA** this translates in using the `PeriodicBoundaryEmbedding` layer for $v$, and any\n",
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"`pina.model` for $NN_{\\theta}$. Let's see it in action! \n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"# we encapsulate all modules in a torch.nn.Sequential container\n",
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"model = torch.nn.Sequential(PeriodicBoundaryEmbedding(input_dimension=1,\n",
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" periods=2),\n",
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" FeedForward(input_dimensions=3, # output of PeriodicBoundaryEmbedding = 3 * input_dimension\n",
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" output_dimensions=1,\n",
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" layers=[10, 10]))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"As simple as that! Notice that in higher dimension you can specify different periods\n",
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"for all dimensions using a dictionary, e.g. `periods={'x':2, 'y':3, ...}`\n",
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"would indicate a periodicity of $2$ in $x$, $3$ in $y$, and so on...\n",
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"\n",
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"We will now solve the problem as usually with the `PINN` and `Trainer` class."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"GPU available: False, used: False\n",
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"TPU available: False, using: 0 TPU cores\n",
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"HPU available: False, using: 0 HPUs\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Epoch 4999: 100%|██████████| 1/1 [00:00<00:00, 20.17it/s, v_num=5, val_loss=0.255, phys_cond_loss=0.267, train_loss=0.267] "
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"`Trainer.fit` stopped: `max_epochs=5000` reached.\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Epoch 4999: 100%|██████████| 1/1 [00:00<00:00, 17.70it/s, v_num=5, val_loss=0.255, phys_cond_loss=0.267, train_loss=0.267]\n"
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]
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}
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],
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"source": [
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"pinn = PINN(problem=problem, model=model)\n",
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"trainer = Trainer(pinn, max_epochs=5000, accelerator='cpu', enable_model_summary=False) # we train on CPU and avoid model summary at beginning of training (optional)\n",
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"trainer.train()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"We are going to plot the solution now!"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"#pl = Plotter()\n",
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"#pl.plot(pinn)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"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 $(-\\infty, \\infty)$."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 1500x500 with 3 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# plotting solution\n",
|
||
"with torch.no_grad():\n",
|
||
" # Notice here we put [-4, 4]!!!\n",
|
||
" new_domain = CartesianDomain({'x' : [0, 4]})\n",
|
||
" x = new_domain.sample(1000, mode='grid')\n",
|
||
" fig, axes = plt.subplots(1, 3, figsize=(15, 5))\n",
|
||
" # Plot 1\n",
|
||
" axes[0].plot(x, problem.truth_solution(x), label=r'$u(x)$', color='blue')\n",
|
||
" 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].set_title(r'PINN solution $u_{\\theta}(x)$')\n",
|
||
" axes[1].legend(loc=\"upper right\")\n",
|
||
" # Plot 3\n",
|
||
" diff = torch.abs(problem.truth_solution(x) - pinn(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",
|
||
" # Adjust layout\n",
|
||
" plt.tight_layout()\n",
|
||
" # Show the plots\n",
|
||
" plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"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",
|
||
"## What's next?\n",
|
||
"\n",
|
||
"Congratulations on completing the one dimensional Helmholtz tutorial of **PINA**! There are multiple directions you can go now:\n",
|
||
"\n",
|
||
"1. Train the network for longer or with different layer sizes and assert the finaly accuracy\n",
|
||
"\n",
|
||
"2. Apply the `PeriodicBoundaryEmbedding` layer for a time-dependent problem (see reference in the documentation)\n",
|
||
"\n",
|
||
"3. Exploit extrafeature training ?\n",
|
||
"\n",
|
||
"4. Many more..."
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"language": "python",
|
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"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": "3.12.3"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
||
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|