formatting fix

Signed-off-by: Tomasz Kornuta <[email protected]>
NVIDIA · Jun 2, 2020 · 3730537 · 3730537
1 parent ee6ec4a
commit 3730537
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Showing 10 changed files with 16 additions and 51 deletions.
diff --git a/nemo/collections/cv/examples/cifar100_vgg16_ffn_image_classification.py b/nemo/collections/cv/examples/cifar100_vgg16_ffn_image_classification.py
@@ -21,13 +21,7 @@
 from nemo.collections.cv.modules.losses import NLLLoss
 from nemo.collections.cv.modules.non_trainables import NonLinearity, ReshapeTensor
 from nemo.collections.cv.modules.trainables import FeedForwardNetwork, GenericImageEncoder
-from nemo.core import (
-    DeviceType,
-    NeuralGraph,
-    NeuralModuleFactory,
-    OperationMode,
-    SimpleLossLoggerCallback,
-)
+from nemo.core import DeviceType, NeuralGraph, NeuralModuleFactory, OperationMode, SimpleLossLoggerCallback
 from nemo.utils import logging
 
 if __name__ == "__main__":
@@ -51,7 +45,7 @@
 
     # Create a training graph.
     with NeuralGraph(operation_mode=OperationMode.training) as training_graph:
-        _, img, _, _, fine_target, _  = cifar100_dl()
+        _, img, _, _, fine_target, _ = cifar100_dl()
         feat_map = image_encoder(inputs=img)
         res_img = reshaper(inputs=feat_map)
         logits = ffn(inputs=res_img)

diff --git a/nemo/collections/cv/examples/cifar10_convnet_ffn_image_classification.py b/nemo/collections/cv/examples/cifar10_convnet_ffn_image_classification.py
@@ -21,13 +21,7 @@
 from nemo.collections.cv.modules.losses import NLLLoss
 from nemo.collections.cv.modules.non_trainables import NonLinearity, ReshapeTensor
 from nemo.collections.cv.modules.trainables import ConvNetEncoder, FeedForwardNetwork
-from nemo.core import (
-    DeviceType,
-    NeuralGraph,
-    NeuralModuleFactory,
-    OperationMode,
-    SimpleLossLoggerCallback,
-)
+from nemo.core import DeviceType, NeuralGraph, NeuralModuleFactory, OperationMode, SimpleLossLoggerCallback
 from nemo.utils import logging
 
 if __name__ == "__main__":

diff --git a/nemo/collections/cv/examples/cifar10_resnet50_image_classification.py b/nemo/collections/cv/examples/cifar10_resnet50_image_classification.py
@@ -21,13 +21,7 @@
 from nemo.collections.cv.modules.losses import NLLLoss
 from nemo.collections.cv.modules.non_trainables import NonLinearity
 from nemo.collections.cv.modules.trainables import GenericImageEncoder
-from nemo.core import (
-    DeviceType,
-    NeuralGraph,
-    NeuralModuleFactory,
-    OperationMode,
-    SimpleLossLoggerCallback,
-)
+from nemo.core import DeviceType, NeuralGraph, NeuralModuleFactory, OperationMode, SimpleLossLoggerCallback
 from nemo.utils import logging
 
 if __name__ == "__main__":

diff --git a/nemo/collections/cv/examples/mnist_convnet_ffn_image_classification.py b/nemo/collections/cv/examples/mnist_convnet_ffn_image_classification.py
@@ -21,13 +21,7 @@
 from nemo.collections.cv.modules.losses import NLLLoss
 from nemo.collections.cv.modules.non_trainables import NonLinearity, ReshapeTensor
 from nemo.collections.cv.modules.trainables import ConvNetEncoder, FeedForwardNetwork
-from nemo.core import (
-    DeviceType,
-    NeuralGraph,
-    NeuralModuleFactory,
-    OperationMode,
-    SimpleLossLoggerCallback,
-)
+from nemo.core import DeviceType, NeuralGraph, NeuralModuleFactory, OperationMode, SimpleLossLoggerCallback
 from nemo.utils import logging
 
 if __name__ == "__main__":

diff --git a/nemo/collections/cv/examples/mnist_ffn_image_classification.py b/nemo/collections/cv/examples/mnist_ffn_image_classification.py
@@ -21,13 +21,7 @@
 from nemo.collections.cv.modules.losses import NLLLoss
 from nemo.collections.cv.modules.non_trainables import NonLinearity, ReshapeTensor
 from nemo.collections.cv.modules.trainables import FeedForwardNetwork
-from nemo.core import (
-    DeviceType,
-    NeuralGraph,
-    NeuralModuleFactory,
-    OperationMode,
-    SimpleLossLoggerCallback,
-)
+from nemo.core import DeviceType, NeuralGraph, NeuralModuleFactory, OperationMode, SimpleLossLoggerCallback
 from nemo.utils import logging
 
 if __name__ == "__main__":

diff --git a/nemo/collections/cv/examples/mnist_lenet5_image_classification.py b/nemo/collections/cv/examples/mnist_lenet5_image_classification.py
@@ -62,7 +62,7 @@
 
     # Create a validation graph, starting from the second data layer.
     with NeuralGraph(operation_mode=OperationMode.evaluation) as evaluation_graph:
-        _, x, y, _  = dl_e()
+        _, x, y, _ = dl_e()
         p = lenet5(images=x)
         loss_e = nll_loss(predictions=p, targets=y)
 

diff --git a/nemo/collections/cv/modules/data_layers/cifar100_datalayer.py b/nemo/collections/cv/modules/data_layers/cifar100_datalayer.py
@@ -44,15 +44,7 @@
 from torchvision.transforms import Compose, Resize, ToTensor
 
 from nemo.backends.pytorch.nm import DataLayerNM
-from nemo.core.neural_types import (
-    AxisKind,
-    AxisType,
-    ClassificationTarget,
-    ImageValue,
-    Index,
-    Label,
-    NeuralType,
-)
+from nemo.core.neural_types import AxisKind, AxisType, ClassificationTarget, ImageValue, Index, Label, NeuralType
 from nemo.utils.decorators import add_port_docs
 
 __all__ = ['CIFAR100DataLayer']
@@ -204,7 +196,7 @@ def __getitem__(self, index: int):
         img, fine_target = self._dataset.__getitem__(index)
         # Get coarse target.
         coarse_target = self._fine_to_coarse_id_mapping[fine_target]
-        
+
         # Labels.
         fine_label = self._fine_ix_to_word[fine_target]
         coarse_label = self._coarse_ix_to_word[self._fine_to_coarse_id_mapping[fine_target]]

diff --git a/nemo/collections/cv/modules/data_layers/cifar10_datalayer.py b/nemo/collections/cv/modules/data_layers/cifar10_datalayer.py
@@ -115,7 +115,7 @@ def __getitem__(self, index: int):
         """
         # Get image and target.
         img, target = self._dataset.__getitem__(index)
-  
+
         # Return sample.
         return index, img, target
 

diff --git a/nemo/collections/cv/modules/data_layers/mnist_datalayer.py b/nemo/collections/cv/modules/data_layers/mnist_datalayer.py
@@ -28,9 +28,9 @@
     AxisType,
     ClassificationTarget,
     Index,
+    Label,
     NeuralType,
     NormalizedImageValue,
-    Label,
 )
 from nemo.utils.decorators import add_port_docs
 
@@ -129,7 +129,7 @@ def __getitem__(self, index: int):
         """
         # Get image and target.
         img, target = self._dataset.__getitem__(index)
-  
+
         # Return sample.
         return index, img, target, self._ix_to_word[target]
 
@@ -149,4 +149,3 @@ def dataset(self):
             Self - just to be "compatible" with the current NeMo train action.
         """
         return self  # ! Important - as we want to use this __getitem__ method!
-
diff --git a/nemo/core/neural_types/elements.py b/nemo/core/neural_types/elements.py
@@ -212,16 +212,19 @@ class Target(ElementType):
         Type representing an element being a target value.
     """
 
+
 class ClassificationTarget(Target):
     """
         Type representing an element being target value in the classification task, i.e. identifier of a desired class.
     """
 
+
 class Label(ElementType):
     """
         Type representing an element being a target value.
     """
 
+
 class ImageValue(ElementType):
     """
         Type representing an element/value of a single image channel,
@@ -235,5 +238,6 @@ class NormalizedImageValue(ImageValue):
         e.g. a single element (R) of normalized RGB image.
     """
 
+
 class ImageFeatureValue(ImageValue):
     """Type representing an element (single value) of a (image) feature maps."""