Codacy correction

pina/trainer.py

@@ -9,8 +9,13 @@ from .solvers.solver import SolverInterface
 
 class Trainer(pytorch_lightning.Trainer):
 
-    def __init__(self, solver, batch_size=None, train_size=.7, test_size=.2,
-                 eval_size=.1, **kwargs):
+    def __init__(self,
+                 solver,
+                 batch_size=None,
+                 train_size=.7,
+                 test_size=.2,
+                 eval_size=.1,
+                 **kwargs):
         """
         PINA Trainer class for costumizing every aspect of training via flags.
 
@@ -48,8 +53,7 @@ class Trainer(pytorch_lightning.Trainer):
         if hasattr(pb, "unknown_parameters"):
             for key in pb.unknown_parameters:
                 pb.unknown_parameters[key] = torch.nn.Parameter(
-                    pb.unknown_parameters[key].data.to(device)
-                )
+                    pb.unknown_parameters[key].data.to(device))
 
     def _create_loader(self):
         """
@@ -58,14 +62,11 @@ class Trainer(pytorch_lightning.Trainer):
         trainer dataloader, just call the method.
         """
         if not self.solver.problem.collector.full:
-            error_message = '\n'.join(
-                [
-                    f"""{" " * 13} ---> Condition {key} {"sampled" if value else
-                    "not sampled"}"""
-                    for key, value in
-                    self._solver.problem.collector._is_conditions_ready.items()
-                ]
-            )
+            error_message = '\n'.join([
+                f"""{" " * 13} ---> Condition {key} {"sampled" if value else
+                    "not sampled"}""" for key, value in
+                self._solver.problem.collector._is_conditions_ready.items()
+            ])
             raise RuntimeError('Cannot create Trainer if not all conditions '
                                'are sampled. The Trainer got the following:\n'
                                f'{error_message}')
@@ -76,7 +77,8 @@ class Trainer(pytorch_lightning.Trainer):
 
         device = devices[0]
 
-        data_module = PinaDataModule(problem=self.solver.problem, device=device,
+        data_module = PinaDataModule(problem=self.solver.problem,
+                                     device=device,
                                      train_size=self.train_size,
                                      test_size=self.test_size,
                                      val_size=self.eval_size)
@@ -87,9 +89,9 @@ class Trainer(pytorch_lightning.Trainer):
         """
         Train the solver method.
         """
-        return super().fit(
-            self.solver, train_dataloaders=self._loader, **kwargs
-        )
+        return super().fit(self.solver,
+                           train_dataloaders=self._loader,
+                           **kwargs)
 
     @property
     def solver(self):