pkg relative imports

* split requirements.txt
* pytest verbose

pytorch_lightning/root_module/grads.py

@@ -1,9 +1,8 @@
-from torch import nn
-
 """
 Module to describe gradients
 """
 
+from torch import nn
 
 class GradInformation(nn.Module):
 

pytorch_lightning/root_module/memory.py

@@ -1,14 +1,14 @@
-import torch
-import gc
-import subprocess
-import numpy as np
-import pandas as pd
-
-
 '''
 Generates a summary of a model's layers and dimensionality
 '''
 
+import gc
+
+import torch
+import subprocess
+import numpy as np
+import pandas as pd
+
 
 class ModelSummary(object):
 

pytorch_lightning/root_module/model_saving.py

@@ -1,7 +1,9 @@
-import torch
 import os
 import re
-from pytorch_lightning.pt_overrides.override_data_parallel import LightningDistributedDataParallel, LightningDataParallel
+
+import torch
+
+from ..pt_overrides.override_data_parallel import LightningDistributedDataParallel, LightningDataParallel
 
 
 class ModelIO(object):

pytorch_lightning/root_module/root_module.py

@@ -1,9 +1,10 @@
 import torch
-from pytorch_lightning.root_module.memory import ModelSummary
-from pytorch_lightning.root_module.grads import GradInformation
-from pytorch_lightning.root_module.model_saving import ModelIO, load_hparams_from_tags_csv
-from pytorch_lightning.root_module.hooks import ModelHooks
-from pytorch_lightning.root_module.decorators import data_loader
+
+from .memory import ModelSummary
+from .grads import GradInformation
+from .model_saving import ModelIO, load_hparams_from_tags_csv
+from .hooks import ModelHooks
+from .decorators import data_loader
 
 
 class LightningModule(GradInformation, ModelIO, ModelHooks):