Add check conditions-solver compatibility

pina/solvers/pinns/basepinn.py

@@ -3,6 +3,8 @@
 from abc import ABCMeta, abstractmethod
 import torch
 from torch.nn.modules.loss import _Loss
+from ...condition import InputOutputPointsCondition, \
+    InputPointsEquationCondition, DomainEquationCondition
 from ...solvers.solver import SolverInterface
 from ...utils import check_consistency
 from ...loss.loss_interface import LossInterface
@@ -24,6 +26,8 @@ class PINNInterface(SolverInterface, metaclass=ABCMeta):
     to the user to choose which problem the implemented solver inheriting from
     this class is suitable for.
     """
+    accepted_conditions_types = (InputOutputPointsCondition,
+                        InputPointsEquationCondition, DomainEquationCondition)
 
     def __init__(
             self,

pina/solvers/solver.py

@@ -9,8 +9,6 @@
 import torch
 import sys
 
-
-
 class SolverInterface(lightning.pytorch.LightningModule, metaclass=ABCMeta):
     """
     Solver base class. This class inherits is a wrapper of
@@ -134,18 +132,9 @@ def on_train_start(self):
         return super().on_train_start()
 
     def _check_solver_consistency(self, problem):
-        pass
-        #TODO : Implement this method for the conditions
-        '''
-
-
-        for _, condition in problem.conditions.items():
-            if not set(condition.condition_type).issubset(
-                    set(self.accepted_condition_types)):
-                raise ValueError(
-                    f'{self.__name__} dose not support condition '
-                    f'{condition.condition_type}')
-        '''
+        for condition in problem.conditions.values():
+            check_consistency(condition, self.accepted_conditions_types)
+
     @staticmethod
     def get_batch_size(batch):
         # Assuming batch is your custom Batch object

pina/solvers/supervised.py

@@ -2,6 +2,8 @@
 import torch
 from pytorch_lightning.utilities.types import STEP_OUTPUT
 from torch.nn.modules.loss import _Loss
+
+from ..condition import InputOutputPointsCondition
 from ..optim import TorchOptimizer, TorchScheduler
 from .solver import SolverInterface
 from ..label_tensor import LabelTensor
@@ -37,7 +39,7 @@ class SupervisedSolver(SolverInterface):
     we are seeking to approximate multiple (discretised) functions given
     multiple (discretised) input functions.
     """
-    __name__ = 'SupervisedSolver'
+    accepted_conditions_types = InputOutputPointsCondition
 
     def __init__(self,
                  problem,