Lightining update (#104)

* multiple functions for version 0.0
* lightining update
* minor changes
* data pinn  loss added
---------

Co-authored-by: Nicola Demo <demo.nicola@gmail.com>
Co-authored-by: Dario Coscia <dariocoscia@cli-10-110-3-125.WIFIeduroamSTUD.units.it>
Co-authored-by: Dario Coscia <dariocoscia@Dario-Coscia.station>
Co-authored-by: Dario Coscia <dariocoscia@Dario-Coscia.local>
Co-authored-by: Dario Coscia <dariocoscia@192.168.1.38>

pina/solver.py

@@ -0,0 +1,65 @@
+""" Solver module. """
+
+from abc import ABCMeta, abstractmethod
+from .model.network import Network
+import lightning.pytorch as pl
+from .utils import check_consistency
+from .problem import AbstractProblem
+
+class SolverInterface(pl.LightningModule, metaclass=ABCMeta):
+    """ Solver base class. """
+    def __init__(self, model, problem, extra_features=None):
+        """
+        :param model: A torch neural network model instance.
+        :type model: torch.nn.Module
+        :param problem: A problem definition instance.
+        :type problem: AbstractProblem
+        :param list(torch.nn.Module) extra_features: the additional input
+        features to use as augmented input.
+        """
+        super().__init__()
+        
+        # check inheritance for pina problem
+        check_consistency(problem, AbstractProblem, 'pina problem')
+
+        # assigning class variables (check consistency inside Network class)
+        self._pina_model = Network(model=model, extra_features=extra_features)
+        self._problem = problem
+
+    @abstractmethod
+    def forward(self):
+        pass
+    
+    @abstractmethod
+    def training_step(self):
+        pass
+
+    @abstractmethod
+    def configure_optimizers(self):
+        pass
+
+    @property
+    def model(self):
+        """
+        The torch model."""
+        return self._pina_model
+
+    @property
+    def problem(self):
+        """
+        The problem formulation."""
+        return self._problem
+
+    # @model.setter
+    # def model(self, new_model):
+    #     """
+    #     Set the torch."""
+    #     check_consistency(new_model, nn.Module, 'torch model')
+    #     self._model= new_model
+
+    # @problem.setter
+    # def problem(self, problem):
+    #     """
+    #     Set the problem formulation."""
+    #     check_consistency(problem, AbstractProblem, 'pina problem')
+    #     self._problem = problem