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Refactoring solvers (#541)

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* Refactoring solvers

* Simplify logic compile
* Improve and update doc
* Create SupervisedSolverInterface
* Specialize SupervisedSolver and ReducedOrderModelSolver
* Create EnsembleSolverInterface + EnsembleSupervisedSolver
* Create tests ensemble solvers

* formatter

* codacy

* fix issues + speedup test
This commit is contained in:
Dario Coscia
2025-04-09 14:51:42 +02:00
parent 485c8dd789
commit 6dd7bd2825
37 changed files with 1514 additions and 510 deletions
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10
pina/solver/physics_informed_solver/causal_pinn.py
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@@ -83,15 +83,15 @@ class CausalPINN(PINN):
:class:`~pina.problem.time_dependent_problem.TimeDependentProblem`.
:param torch.nn.Module model: The neural network model to be used.
:param Optimizer optimizer: The optimizer to be used.
If `None`, the :class:`torch.optim.Adam` optimizer is used.
If ``None``, the :class:`torch.optim.Adam` optimizer is used.
Default is ``None``.
:param torch.optim.LRScheduler scheduler: Learning rate scheduler.
If `None`, the :class:`torch.optim.lr_scheduler.ConstantLR`
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``.
If ``None``, no weighting schema is used. Default is ``None``.
:param torch.nn.Module loss: The loss function to be minimized.
If `None`, the :class:`torch.nn.MSELoss` loss is used.
If ``None``, the :class:`torch.nn.MSELoss` loss is used.
Default is `None`.
:param float eps: The exponential decay parameter. Default is ``100``.
:raises ValueError: If the problem is not a TimeDependentProblem.
@@ -134,7 +134,7 @@ class CausalPINN(PINN):
chunk.labels = labels
# classical PINN loss
residual = self.compute_residual(samples=chunk, equation=equation)
loss_val = self.loss(
loss_val = self._loss_fn(
torch.zeros_like(residual, requires_grad=True), residual
)
time_loss.append(loss_val)