optimize imports

pl_bolts/datamodules/stl10_dataloaders.py

@@ -2,8 +2,8 @@
 from torchvision import transforms as transform_lib
 from torchvision.datasets import STL10
 
-from pl_bolts.datamodules.concat_dataset import ConcatDataset
 from pl_bolts.datamodules.bolts_dataloaders_base import BoltDataLoaders
+from pl_bolts.datamodules.concat_dataset import ConcatDataset
 from pl_bolts.transforms.dataset_normalizations import stl10_normalization
 
 

pl_bolts/losses/self_supervised_learning.py

@@ -1,6 +1,6 @@
+import numpy as np
 import torch
 from torch import nn
-import numpy as np
 
 from pl_bolts.models.vision import PixelCNN
 

pl_bolts/models/self_supervised/cpc/cpc_module.py

@@ -14,10 +14,10 @@
 from pl_bolts import metrics
 from pl_bolts.datamodules import CIFAR10DataLoaders, STL10DataLoaders
 from pl_bolts.datamodules.ssl_imagenet_dataloaders import SSLImagenetDataLoaders
+from pl_bolts.losses.self_supervised_learning import InfoNCE
 from pl_bolts.models.self_supervised.cpc import transforms as cpc_transforms
 from pl_bolts.models.self_supervised.cpc.networks import CPCResNet101
 from pl_bolts.models.self_supervised.evaluator import SSLEvaluator
-from pl_bolts.losses.self_supervised_learning import InfoNCE
 
 __all__ = [
     'CPCV2'

pl_bolts/models/self_supervised/moco/callbacks.py

@@ -1,6 +1,7 @@
-from pytorch_lightning import Callback
 import math
 
+from pytorch_lightning import Callback
+
 
 class MocoLRScheduler(Callback):
 

pl_bolts/models/self_supervised/moco/moco2_module.py

@@ -2,16 +2,17 @@
 Adapted from: https://github.com/facebookresearch/moco
 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
 """
+from argparse import Namespace
+
 import pytorch_lightning as pl
 import torch
-from torch import nn
 import torch.nn.functional as F
 import torchvision
-from argparse import Namespace
+from torch import nn
 
 from pl_bolts.datamodules import CIFAR10DataLoaders, STL10DataLoaders
-from pl_bolts.metrics import precision_at_k, mean
 from pl_bolts.datamodules.ssl_imagenet_dataloaders import SSLImagenetDataLoaders
+from pl_bolts.metrics import precision_at_k, mean
 from pl_bolts.models.self_supervised.moco.transforms import \
     Moco2Imagenet128Transforms, Moco2CIFAR10Transforms, Moco2STL10Transforms
 
@@ -339,6 +340,7 @@ def concat_all_gather(tensor):
 
 if __name__ == '__main__':
     from argparse import ArgumentParser
+
     parser = ArgumentParser()
 
     # trainer args

pl_bolts/models/self_supervised/simclr/simclr_module.py

@@ -4,11 +4,12 @@
 from torch.nn import functional as F
 from torch.optim.lr_scheduler import StepLR
 from torchvision.models import densenet
-from pl_bolts.losses.self_supervised_learning import nt_xent_loss
-from pl_bolts.optimizers.layer_adaptive_scaling import LARS
+
 from pl_bolts.datamodules import CIFAR10DataLoaders, STL10DataLoaders
 from pl_bolts.datamodules.ssl_imagenet_dataloaders import SSLImagenetDataLoaders
+from pl_bolts.losses.self_supervised_learning import nt_xent_loss
 from pl_bolts.models.self_supervised.simclr.simclr_transforms import SimCLRDataTransform
+from pl_bolts.optimizers.layer_adaptive_scaling import LARS
 
 
 class EncoderModel(nn.Module):
@@ -167,6 +168,7 @@ def add_model_specific_args(parent_parser):
 
 if __name__ == '__main__':
     from argparse import ArgumentParser
+
     parser = ArgumentParser()
     parser = pl.Trainer.add_argparse_args(parser)
     parser = SimCLR.add_model_specific_args(parser)

pl_bolts/models/self_supervised/simclr/simclr_transforms.py

@@ -1,6 +1,6 @@
-import torchvision.transforms as transforms
-import numpy as np
 import cv2
+import numpy as np
+import torchvision.transforms as transforms
 
 
 class SimCLRDataTransform(object):

pl_bolts/optimizers/layer_adaptive_scaling.py

@@ -10,6 +10,7 @@
 
 class _RequiredParameter(object):
     """Singleton class representing a required parameter for an Optimizer."""
+
     def __repr__(self):
         return "<required parameter>"
 
@@ -40,6 +41,7 @@ class LARS(Optimizer):
         optimizer.step()
 
     """
+
     def __init__(self,
                  params: Iterable,
                  lr: float = REQUIRED,

pl_bolts/submit.py

@@ -18,5 +18,4 @@ def submit(master_address, master_port, world_size, node_rank, local_rank):
     parser.add_argument('world_size', default=str)
     parser.add_argument('local_rank', default=str)
 
-
 # grid train main.py --local --world_size 16 --local_gpus '0,1,2,3' --node_rank 0