folivo/PINA
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

fix rendering part 2

Browse Source
This commit is contained in:
giovanni
2025-03-14 00:10:18 +01:00
committed by FilippoOlivo
parent 3d842cb9ec
commit 76f5be85ea
17 changed files with 217 additions and 147 deletions
Download Patch File Download Diff File Expand all files Collapse all files

26
pina/solver/physic_informed_solver/gradient_pinn.py
View File

@@ -46,15 +46,15 @@ class GradientPINN(PINN):
.. seealso::
**Original reference**: Yu, Jeremy, et al. "Gradient-enhanced
physics-informed neural networks for forward and inverse
PDE problems." Computer Methods in Applied Mechanics
and Engineering 393 (2022): 114823.
**Original reference**: Yu, Jeremy, et al.
*Gradient-enhanced physics-informed neural networks for forward and
inverse PDE problems.*
Computer Methods in Applied Mechanics and Engineering 393 (2022):114823.
DOI: `10.1016 <https://doi.org/10.1016/j.cma.2022.114823>`_.
.. note::
This class is only compatible with problems that inherit from the
:class:`~pina.problem.SpatialProblem` class.
:class:`~pina.problem.spatial_problem.SpatialProblem` class.
"""
def __init__(
@@ -70,18 +70,20 @@ class GradientPINN(PINN):
Initialization of the :class:`GradientPINN` class.
:param AbstractProblem problem: The problem to be solved.
It must inherit from at least :class:`~pina.problem.SpatialProblem`
to compute the gradient of the loss.
It must inherit from at least
:class:`~pina.problem.spatial_problem.SpatialProblem` to compute the
gradient of the loss.
:param torch.nn.Module model: The neural network model to be used.
:param torch.optim.Optimizer optimizer: The optimizer to be used.
If `None`, the Adam optimizer is used. Default is ``None``.
:param torch.optim.LRScheduler scheduler: Learning rate scheduler.
If `None`, the constant learning rate scheduler is used.
:param Optimizer optimizer: The optimizer to be used.
If `None`, the :class:`torch.optim.Adam` optimizer is used.
Default is ``None``.
:param Scheduler scheduler: Learning rate scheduler.
If `None`, the :class:`torch.optim.lr_scheduler.ConstantLR`
scheduler is used. Default is ``None``.
:param WeightingInterface weighting: The weighting schema to be used.
If `None`, no weighting schema is used. Default is ``None``.
:param torch.nn.Module loss: The loss function to be minimized.
If `None`, the Mean Squared Error (MSE) loss is used.
If `None`, the :class:`torch.nn.MSELoss` loss is used.
Default is `None`.
:raises ValueError: If the problem is not a SpatialProblem.
"""