Formatting

* Adding black as dev dependency
* Formatting pina code
* Formatting tests

pina/solver/physic_informed_solver/pinn.py

@@ -1,4 +1,4 @@
-""" Module for Physics Informed Neural Network. """
+"""Module for Physics Informed Neural Network."""
 
 import torch
 
@@ -48,13 +48,15 @@ class PINN(PINNInterface, SingleSolverInterface):
         DOI: `10.1038 <https://doi.org/10.1038/s42254-021-00314-5>`_.
     """
 
-    def __init__(self,
-                 problem,
-                 model,
-                 optimizer=None,
-                 scheduler=None,
-                 weighting=None,
-                 loss=None):
+    def __init__(
+        self,
+        problem,
+        model,
+        optimizer=None,
+        scheduler=None,
+        weighting=None,
+        loss=None,
+    ):
         """
         :param torch.nn.Module model: The neural network model to use.
         :param AbstractProblem problem: The formulation of the problem.
@@ -67,12 +69,14 @@ class PINN(PINNInterface, SingleSolverInterface):
         :param torch.nn.Module loss: The loss function to be minimized;
             default `None`.
         """
-        super().__init__(model=model,
-                         problem=problem,
-                         optimizer=optimizer,
-                         scheduler=scheduler,
-                         weighting=weighting,
-                         loss=loss)
+        super().__init__(
+            model=model,
+            problem=problem,
+            optimizer=optimizer,
+            scheduler=scheduler,
+            weighting=weighting,
+            loss=loss,
+        )
 
     def loss_phys(self, samples, equation):
         """
@@ -112,7 +116,4 @@ class PINN(PINNInterface, SingleSolverInterface):
                 }
             )
         self.scheduler.hook(self.optimizer)
-        return (
-            [self.optimizer.instance],
-            [self.scheduler.instance]
-        )
+        return ([self.optimizer.instance], [self.scheduler.instance])