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minor fix rendering rst tutorial

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2024-06-07 18:14:37 +02:00
committed by Nicola Demo
parent e514969a43
commit 6c3adfb03d
1 changed files with 9 additions and 47 deletions
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docs/source/_rst/tutorials/tutorial13/tutorial.rst
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@@ -34,12 +34,14 @@ networks <https://doi.org/10.1016/j.cma.2021.113938>`__. The
one-dimensional Poisson problem we aim to solve is mathematically
written as:
:raw-latex:`\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}`
.. math::
\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
:math:`u(x) = \sin(2\pi x) + 0.1 \sin(50\pi x)` and obtain the force
@@ -95,8 +97,7 @@ 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. We used a ``MultiStepLR`` scheduler to decrease the learning rate
``FeedForward`` model. We used a ``MultiStepLR`` scheduler to decrease the learning rate
slowly during training (it takes around 2 minutes to run on CPU).
.. code:: ipython3
@@ -130,19 +131,6 @@ slowly during training (it takes around 2 minutes to run on CPU).
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
.. parsed-literal::
Epoch 4999: 100%|██████████| 1/1 [00:00<00:00, 150.58it/s, v_num=69, gamma0_loss=2.61e+3, gamma1_loss=2.61e+3, D_loss=409.0, mean_loss=1.88e+3]
.. parsed-literal::
`Trainer.fit` stopped: `max_epochs=5000` reached.
.. parsed-literal::
Epoch 4999: 100%|██████████| 1/1 [00:00<00:00, 97.66it/s, v_num=69, gamma0_loss=2.61e+3, gamma1_loss=2.61e+3, D_loss=409.0, mean_loss=1.88e+3]
@@ -152,19 +140,6 @@ slowly during training (it takes around 2 minutes to run on CPU).
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
.. parsed-literal::
Epoch 4999: 100%|██████████| 1/1 [00:00<00:00, 88.18it/s, v_num=70, gamma0_loss=151.0, gamma1_loss=148.0, D_loss=6.38e+5, mean_loss=2.13e+5]
.. parsed-literal::
`Trainer.fit` stopped: `max_epochs=5000` reached.
.. parsed-literal::
Epoch 4999: 100%|██████████| 1/1 [00:00<00:00, 65.77it/s, v_num=70, gamma0_loss=151.0, gamma1_loss=148.0, D_loss=6.38e+5, mean_loss=2.13e+5]
@@ -290,19 +265,6 @@ feel free to try also with our PINN variants (``SAPINN``, ``GPINN``,
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
.. parsed-literal::
Epoch 4999: 100%|██████████| 1/1 [00:00<00:00, 94.64it/s, v_num=71, gamma0_loss=3.91e-5, gamma1_loss=3.91e-5, D_loss=0.000151, mean_loss=0.000113]
.. parsed-literal::
`Trainer.fit` stopped: `max_epochs=5000` reached.
.. parsed-literal::
Epoch 4999: 100%|██████████| 1/1 [00:00<00:00, 72.21it/s, v_num=71, gamma0_loss=3.91e-5, gamma1_loss=3.91e-5, D_loss=0.000151, mean_loss=0.000113]