Minor imports cleaning (#402)

* code cleaning

* drop unused imports

* optimize imports

pytorch_lightning/trainer/amp_mixin.py

@@ -1,5 +1,6 @@
 try:
     from apex import amp
+
     APEX_AVAILABLE = True
 except ImportError:
     APEX_AVAILABLE = False

pytorch_lightning/trainer/data_loading_mixin.py

@@ -1,13 +1,14 @@
 import warnings
 
-from torch.utils.data.distributed import DistributedSampler
 import torch.distributed as dist
 from torch.utils.data import IterableDataset
+from torch.utils.data.distributed import DistributedSampler
 
 from pytorch_lightning.utilities.debugging import MisconfigurationException
 
 try:
     from apex import amp
+
     APEX_AVAILABLE = True
 except ImportError:
     APEX_AVAILABLE = False

pytorch_lightning/trainer/ddp_mixin.py

@@ -4,12 +4,13 @@ import warnings
 
 import torch
 import torch.distributed as dist
+
 from pytorch_lightning.pt_overrides.override_data_parallel import LightningDistributedDataParallel
 from pytorch_lightning.utilities.debugging import MisconfigurationException
 
-
 try:
     from apex import amp
+
     APEX_AVAILABLE = True
 except ImportError:
     APEX_AVAILABLE = False

pytorch_lightning/trainer/dp_mixin.py

@@ -1,17 +1,12 @@
-import os
-import re
-import signal
-import pdb
-from subprocess import call
-
 import torch
-import torch.distributed as dist
+
 from pytorch_lightning.pt_overrides.override_data_parallel import (
     LightningDistributedDataParallel, LightningDataParallel)
 from pytorch_lightning.utilities.debugging import MisconfigurationException
 
 try:
     from apex import amp
+
     APEX_AVAILABLE = True
 except ImportError:
     APEX_AVAILABLE = False

pytorch_lightning/trainer/evaluation_loop_mixin.py

@@ -1,4 +1,5 @@
 import torch
+
 from pytorch_lightning.utilities.debugging import MisconfigurationException
 
 

pytorch_lightning/trainer/logging_mixin.py

@@ -1,4 +1,5 @@
 import torch
+
 from pytorch_lightning.root_module import memory
 
 

pytorch_lightning/trainer/train_loop_mixin.py

@@ -2,6 +2,7 @@ import numpy as np
 
 try:
     from apex import amp
+
     APEX_AVAILABLE = True
 except ImportError:
     APEX_AVAILABLE = False
@@ -112,7 +113,6 @@ class TrainerTrainLoopMixin(object):
             # when metrics should be logged
             should_log_metrics = batch_nb % self.row_log_interval == 0 or early_stop_epoch
             if should_log_metrics or self.fast_dev_run:
-
                 # logs user requested information to logger
                 self.log_metrics(batch_step_metrics, grad_norm_dic)
 

pytorch_lightning/trainer/trainer.py

@@ -5,29 +5,28 @@ The trainer handles all the logic for running a val loop, training loop, distrib
 import os
 import warnings
 
-import tqdm
 import torch
-import torch.multiprocessing as mp
 import torch.distributed as dist
+import torch.multiprocessing as mp
+import tqdm
 from torch.optim.optimizer import Optimizer
 
-from pytorch_lightning.trainer.trainer_io import TrainerIOMixin
+from pytorch_lightning.trainer.amp_mixin import TrainerAMPMixin
+from pytorch_lightning.trainer.callback_config_mixin import TrainerCallbackConfigMixin
+from pytorch_lightning.trainer.data_loading_mixin import TrainerDataLoadingMixin
 from pytorch_lightning.trainer.ddp_mixin import TrainerDDPMixin
 from pytorch_lightning.trainer.dp_mixin import TrainerDPMixin
-from pytorch_lightning.trainer.amp_mixin import TrainerAMPMixin
-from pytorch_lightning.trainer.data_loading_mixin import TrainerDataLoadingMixin
 from pytorch_lightning.trainer.evaluation_loop_mixin import TrainerEvaluationLoopMixin
-from pytorch_lightning.trainer.train_loop_mixin import TrainerTrainLoopMixin
 from pytorch_lightning.trainer.logging_mixin import TrainerLoggingMixin
-from pytorch_lightning.trainer.training_tricks_mixin import TrainerTrainingTricksMixin
-from pytorch_lightning.trainer.callback_config_mixin import TrainerCallbackConfigMixin
 from pytorch_lightning.trainer.model_hooks_mixin import TrainerModelHooksMixin
-
+from pytorch_lightning.trainer.train_loop_mixin import TrainerTrainLoopMixin
+from pytorch_lightning.trainer.trainer_io import TrainerIOMixin
+from pytorch_lightning.trainer.training_tricks_mixin import TrainerTrainingTricksMixin
 from pytorch_lightning.utilities.debugging import MisconfigurationException
-import pdb
 
 try:
     from apex import amp
+
     APEX_AVAILABLE = True
 except ImportError:
     APEX_AVAILABLE = False
@@ -332,7 +331,7 @@ class Trainer(TrainerIOMixin,
                 task = int(os.environ['SLURM_LOCALID'])
                 self.ddp_train(task, model)
             else:
-                mp.spawn(self.ddp_train, nprocs=self.num_gpus, args=(model, ))
+                mp.spawn(self.ddp_train, nprocs=self.num_gpus, args=(model,))
 
         # 1 gpu or dp option triggers training using DP module
         # easier to avoid NCCL issues

pytorch_lightning/trainer/trainer_io.py

@@ -1,11 +1,11 @@
 import os
 import re
 import signal
-import pdb
 from subprocess import call
 
 import torch
 import torch.distributed as dist
+
 from pytorch_lightning.pt_overrides.override_data_parallel import (
     LightningDistributedDataParallel, LightningDataParallel)