linting and formatting code

.style.yapf

@@ -1,8 +1,6 @@
 [style]
 BASED_ON_STYLE = pep8
 BLANK_LINE_BEFORE_NESTED_CLASS_OR_DEF = true
-BLANK_LINE_BEFORE_MODULE_DOCSTRING = true
-BLANK_LINE_BEFORE_CLASS_DOCSTRING = true
 SPLIT_BEFORE_EXPRESSION_AFTER_OPENING_PAREN = true
 DEDENT_CLOSING_BRACKETS = true
 SPACES_BEFORE_COMMENT = 1

projects/OSNet_AIN/osnet_child.py

@@ -7,7 +7,6 @@
 # Basic layers
 ##########
 class ConvLayer(nn.Module):
-
     """Convolution layer (conv + bn + relu)."""
 
     def __init__(
@@ -43,7 +42,6 @@ def forward(self, x):
 
 
 class Conv1x1(nn.Module):
-
     """1x1 convolution + bn + relu."""
 
     def __init__(self, in_channels, out_channels, stride=1, groups=1):
@@ -67,7 +65,6 @@ def forward(self, x):
 
 
 class Conv1x1Linear(nn.Module):
-
     """1x1 convolution + bn (w/o non-linearity)."""
 
     def __init__(self, in_channels, out_channels, stride=1, bn=True):
@@ -87,7 +84,6 @@ def forward(self, x):
 
 
 class Conv3x3(nn.Module):
-
     """3x3 convolution + bn + relu."""
 
     def __init__(self, in_channels, out_channels, stride=1, groups=1):
@@ -111,7 +107,6 @@ def forward(self, x):
 
 
 class LightConv3x3(nn.Module):
-
     """Lightweight 3x3 convolution.
 
     1x1 (linear) + dw 3x3 (nonlinear).
@@ -142,7 +137,6 @@ def forward(self, x):
 
 
 class LightConvStream(nn.Module):
-
     """Lightweight convolution stream."""
 
     def __init__(self, in_channels, out_channels, depth):
@@ -164,7 +158,6 @@ def forward(self, x):
 # Building blocks for omni-scale feature learning
 ##########
 class ChannelGate(nn.Module):
-
     """A mini-network that generates channel-wise gates conditioned on input tensor."""
 
     def __init__(
@@ -226,7 +219,6 @@ def forward(self, x):
 
 
 class OSBlock(nn.Module):
-
     """Omni-scale feature learning block."""
 
     def __init__(self, in_channels, out_channels, reduction=4, T=4, **kwargs):
@@ -260,7 +252,6 @@ def forward(self, x):
 
 
 class OSBlockINv1(nn.Module):
-
     """Omni-scale feature learning block with instance normalization."""
 
     def __init__(self, in_channels, out_channels, reduction=4, T=4, **kwargs):
@@ -296,7 +287,6 @@ def forward(self, x):
 
 
 class OSBlockINv2(nn.Module):
-
     """Omni-scale feature learning block with instance normalization."""
 
     def __init__(self, in_channels, out_channels, reduction=4, T=4, **kwargs):
@@ -332,7 +322,6 @@ def forward(self, x):
 
 
 class OSBlockINv3(nn.Module):
-
     """Omni-scale feature learning block with instance normalization."""
 
     def __init__(self, in_channels, out_channels, reduction=4, T=4, **kwargs):
@@ -373,7 +362,6 @@ def forward(self, x):
 # Network architecture
 ##########
 class OSNet(nn.Module):
-
     """Omni-Scale Network.
     
     Reference:

projects/OSNet_AIN/osnet_search.py

@@ -11,7 +11,6 @@
 # Basic layers
 ##########
 class ConvLayer(nn.Module):
-
     """Convolution layer (conv + bn + relu)."""
 
     def __init__(
@@ -47,7 +46,6 @@ def forward(self, x):
 
 
 class Conv1x1(nn.Module):
-
     """1x1 convolution + bn + relu."""
 
     def __init__(
@@ -76,7 +74,6 @@ def forward(self, x):
 
 
 class Conv1x1Linear(nn.Module):
-
     """1x1 convolution + bn (w/o non-linearity)."""
 
     def __init__(self, in_channels, out_channels, stride=1, bn=True):
@@ -96,7 +93,6 @@ def forward(self, x):
 
 
 class Conv3x3(nn.Module):
-
     """3x3 convolution + bn + relu."""
 
     def __init__(self, in_channels, out_channels, stride=1, groups=1):
@@ -120,7 +116,6 @@ def forward(self, x):
 
 
 class LightConv3x3(nn.Module):
-
     """Lightweight 3x3 convolution.
 
     1x1 (linear) + dw 3x3 (nonlinear).
@@ -151,7 +146,6 @@ def forward(self, x):
 
 
 class LightConvStream(nn.Module):
-
     """Lightweight convolution stream."""
 
     def __init__(self, in_channels, out_channels, depth):
@@ -173,7 +167,6 @@ def forward(self, x):
 # Building blocks for omni-scale feature learning
 ##########
 class ChannelGate(nn.Module):
-
     """A mini-network that generates channel-wise gates conditioned on input tensor."""
 
     def __init__(
@@ -235,7 +228,6 @@ def forward(self, x):
 
 
 class OSBlock(nn.Module):
-
     """Omni-scale feature learning block."""
 
     def __init__(self, in_channels, out_channels, reduction=4, T=4, **kwargs):
@@ -269,7 +261,6 @@ def forward(self, x):
 
 
 class OSBlockINv1(nn.Module):
-
     """Omni-scale feature learning block with instance normalization."""
 
     def __init__(self, in_channels, out_channels, reduction=4, T=4, **kwargs):
@@ -305,7 +296,6 @@ def forward(self, x):
 
 
 class OSBlockINv2(nn.Module):
-
     """Omni-scale feature learning block with instance normalization."""
 
     def __init__(self, in_channels, out_channels, reduction=4, T=4, **kwargs):
@@ -341,7 +331,6 @@ def forward(self, x):
 
 
 class OSBlockINv3(nn.Module):
-
     """Omni-scale feature learning block with instance normalization."""
 
     def __init__(self, in_channels, out_channels, reduction=4, T=4, **kwargs):
@@ -379,7 +368,6 @@ def forward(self, x):
 
 
 class NASBlock(nn.Module):
-
     """Neural architecture search layer."""
 
     def __init__(self, in_channels, out_channels, search_space=None):
@@ -425,7 +413,6 @@ def forward(self, x, lmda=1.):
 # Network architecture
 ##########
 class OSNet(nn.Module):
-
     """Omni-Scale Network.
     
     Reference:

torchreid/data/datamanager.py

@@ -7,7 +7,6 @@
 
 
 class DataManager(object):
-
     r"""Base data manager.
 
     Args:
@@ -87,7 +86,6 @@ def preprocess_pil_img(self, img):
 
 
 class ImageDataManager(DataManager):
-
     r"""Image data manager.
 
     Args:
@@ -330,7 +328,6 @@ def __init__(
 
 
 class VideoDataManager(DataManager):
-
     r"""Video data manager.
 
     Args:

torchreid/data/datasets/dataset.py

@@ -10,7 +10,6 @@
 
 
 class Dataset(object):
-
     """An abstract class representing a Dataset.
 
     This is the base class for ``ImageDataset`` and ``VideoDataset``.
@@ -248,7 +247,6 @@ def __repr__(self):
 
 
 class ImageDataset(Dataset):
-
     """A base class representing ImageDataset.
 
     All other image datasets should subclass it.
@@ -297,7 +295,6 @@ def show_summary(self):
 
 
 class VideoDataset(Dataset):
-
     """A base class representing VideoDataset.
 
     All other video datasets should subclass it.

torchreid/data/datasets/image/cuhk01.py

@@ -10,7 +10,6 @@
 
 
 class CUHK01(ImageDataset):
-
     """CUHK01.
 
     Reference:

torchreid/data/datasets/image/cuhk02.py

@@ -6,7 +6,6 @@
 
 
 class CUHK02(ImageDataset):
-
     """CUHK02.
 
     Reference:

torchreid/data/datasets/image/cuhk03.py

@@ -7,7 +7,6 @@
 
 
 class CUHK03(ImageDataset):
-
     """CUHK03.
 
     Reference:

torchreid/data/datasets/image/dukemtmcreid.py

@@ -7,7 +7,6 @@
 
 
 class DukeMTMCreID(ImageDataset):
-
     """DukeMTMC-reID.
 
     Reference:

torchreid/data/datasets/image/grid.py

@@ -9,7 +9,6 @@
 
 
 class GRID(ImageDataset):
-
     """GRID.
 
     Reference:

torchreid/data/datasets/image/ilids.py

@@ -11,7 +11,6 @@
 
 
 class iLIDS(ImageDataset):
-
     """QMUL-iLIDS.
 
     Reference:

torchreid/data/datasets/image/market1501.py

@@ -8,7 +8,6 @@
 
 
 class Market1501(ImageDataset):
-
     """Market1501.
 
     Reference:

torchreid/data/datasets/image/msmt17.py

@@ -23,7 +23,6 @@
 
 
 class MSMT17(ImageDataset):
-
     """MSMT17.
 
     Reference:

torchreid/data/datasets/image/prid.py

@@ -8,7 +8,6 @@
 
 
 class PRID(ImageDataset):
-
     """PRID (single-shot version of prid-2011)
 
     Reference:

torchreid/data/datasets/image/sensereid.py

@@ -7,7 +7,6 @@
 
 
 class SenseReID(ImageDataset):
-
     """SenseReID.
 
     This dataset is used for test purpose only.

torchreid/data/datasets/image/viper.py

@@ -9,7 +9,6 @@
 
 
 class VIPeR(ImageDataset):
-
     """VIPeR.
 
     Reference:

torchreid/data/datasets/video/dukemtmcvidreid.py

@@ -9,7 +9,6 @@
 
 
 class DukeMTMCVidReID(VideoDataset):
-
     """DukeMTMCVidReID.
 
     Reference:

torchreid/data/datasets/video/ilidsvid.py

@@ -9,7 +9,6 @@
 
 
 class iLIDSVID(VideoDataset):
-
     """iLIDS-VID.
 
     Reference:

torchreid/data/datasets/video/mars.py

@@ -7,7 +7,6 @@
 
 
 class Mars(VideoDataset):
-
     """MARS.
 
     Reference:

torchreid/data/datasets/video/prid2011.py

@@ -8,7 +8,6 @@
 
 
 class PRID2011(VideoDataset):
-
     """PRID2011.
 
     Reference:

torchreid/data/sampler.py

@@ -9,7 +9,6 @@
 
 
 class RandomIdentitySampler(Sampler):
-
     """Randomly samples N identities each with K instances.
 
     Args: