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

Fix SupervisedSolver GPU bug and implement GraphSolver (#346)

Browse Source 
* Fix some bugs
* Solve bug with GPU and model_summary parameters in SupervisedSolver class
* Implement GraphSolver class
* Fix Tutorial 5
This commit is contained in:
FilippoOlivo
2024-09-21 18:55:57 +02:00
committed by Nicola Demo
parent 30f865d912
commit 2be57944ba
10 changed files with 334 additions and 164 deletions
Download Patch File Download Diff File Expand all files Collapse all files

23
pina/solvers/supervised.py
View File

@@ -82,7 +82,10 @@ class SupervisedSolver(SolverInterface):
# check consistency
check_consistency(loss, (LossInterface, _Loss), subclass=False)
self.loss = loss
self._loss = loss
self._model = self._pina_model[0]
self._optimizer = self._pina_optimizer[0]
self._scheduler = self._pina_scheduler[0]
def forward(self, x):
"""Forward pass implementation for the solver.
@@ -92,7 +95,7 @@ class SupervisedSolver(SolverInterface):
:rtype: torch.Tensor
"""
output = self._pina_model[0](x)
output = self._model(x)
output.labels = {
1: {
@@ -108,11 +111,11 @@ class SupervisedSolver(SolverInterface):
:return: The optimizers and the schedulers
:rtype: tuple(list, list)
"""
self._pina_optimizer[0].hook(self._pina_model[0].parameters())
self._pina_scheduler[0].hook(self._pina_optimizer[0])
self._optimizer.hook(self._model.parameters())
self._scheduler.hook(self._optimizer)
return (
[self._pina_optimizer[0].optimizer_instance],
[self._pina_scheduler[0].scheduler_instance]
[self._optimizer.optimizer_instance],
[self._scheduler.scheduler_instance]
)
def training_step(self, batch, batch_idx):
@@ -170,28 +173,28 @@ class SupervisedSolver(SolverInterface):
:return: The residual loss averaged on the input coordinates
:rtype: torch.Tensor
"""
return self.loss(self.forward(input_pts), output_pts)
return self._loss(self.forward(input_pts), output_pts)
@property
def scheduler(self):
"""
Scheduler for training.
"""
return self._pina_scheduler
return self._scheduler
@property
def optimizer(self):
"""
Optimizer for training.
"""
return self._pina_optimizer
return self._optimizer
@property
def model(self):
"""
Neural network for training.
"""
return self._pina_model
return self._model
@property
def loss(self):