Minor imports cleaning (#402)

* code cleaning

* drop unused imports

* optimize imports

pytorch_lightning/root_module/decorators.py

@@ -17,9 +17,9 @@ def data_loader(fn):
             try:
                 value = fn(self)  # Lazy evaluation, done only once.
                 if (
-                    value is not None and
-                    not isinstance(value, list) and
-                    fn.__name__ in['test_dataloader', 'val_dataloader']
+                        value is not None and
+                        not isinstance(value, list) and
+                        fn.__name__ in ['test_dataloader', 'val_dataloader']
                 ):
                     value = [value]
             except AttributeError as e:

pytorch_lightning/root_module/memory.py

@@ -3,11 +3,11 @@ Generates a summary of a model's layers and dimensionality
 '''
 
 import gc
-
-import torch
 import subprocess
+
 import numpy as np
 import pandas as pd
+import torch
 
 
 class ModelSummary(object):
@@ -146,7 +146,6 @@ class ModelSummary(object):
         df['Params'] = df['Params'].map(get_human_readable_count)
 
         if self.model.example_input_array is not None:
-
             df['In_sizes'] = self.in_sizes
             df['Out_sizes'] = self.out_sizes
 

pytorch_lightning/root_module/root_module.py

@@ -1,13 +1,13 @@
+import warnings
+
 import torch
 
-from pytorch_lightning.root_module.memory import ModelSummary
-from pytorch_lightning.root_module.grads import GradInformation
-from pytorch_lightning.trainer.trainer_io import load_hparams_from_tags_csv
-from pytorch_lightning.root_module.model_saving import ModelIO
-from pytorch_lightning.root_module.hooks import ModelHooks
 from pytorch_lightning.root_module.decorators import data_loader
-
-import warnings
+from pytorch_lightning.root_module.grads import GradInformation
+from pytorch_lightning.root_module.hooks import ModelHooks
+from pytorch_lightning.root_module.memory import ModelSummary
+from pytorch_lightning.root_module.model_saving import ModelIO
+from pytorch_lightning.trainer.trainer_io import load_hparams_from_tags_csv
 
 
 class LightningModule(GradInformation, ModelIO, ModelHooks):