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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
committed by FilippoOlivo
parent fa6fda0bd5
commit 1bb3c125ac
37 changed files with 1514 additions and 510 deletions
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8
pina/solver/physics_informed_solver/rba_pinn.py
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@@ -83,15 +83,15 @@ class RBAPINN(PINN):
:param AbstractProblem problem: The problem to be solved.
: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 Scheduler 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 | int eta: The learning rate for the weights of the
residuals. Default is ``0.001``.