isort -sl -rc .

bob/learn/tensorflow/dataset/__init__.py

-import tensorflow as tf
-import numpy
 import os
+
+import numpy
+import tensorflow as tf
+
 import bob.io.base
 
 DEFAULT_FEATURE = {

bob/learn/tensorflow/dataset/generator.py

-import tensorflow as tf
-import random
 import logging
+import random
+
+import tensorflow as tf
 
 logger = logging.getLogger(__name__)
 

bob/learn/tensorflow/dataset/image.py

@@ -2,9 +2,12 @@
 # vim: set fileencoding=utf-8 :
 # @author: Tiago de Freitas Pereira <tiago.pereira@idiap.ch>
 
-import tensorflow as tf
 from functools import partial
-from . import append_image_augmentation, from_filename_to_tensor
+
+import tensorflow as tf
+
+from . import append_image_augmentation
+from . import from_filename_to_tensor
 
 
 def shuffle_data_and_labels_image_augmentation(

bob/learn/tensorflow/dataset/tfrecords.py

@@ -4,16 +4,15 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-from functools import partial
 import json
 import logging
 import os
+from functools import partial
 
 import tensorflow as tf
 
 from . import DEFAULT_FEATURE
 
-
 logger = logging.getLogger(__name__)
 TFRECORDS_EXT = ".tfrecords"
 

bob/learn/tensorflow/gan/__init__.py

-from . import spectral_normalization
 from . import losses
+from . import spectral_normalization

bob/learn/tensorflow/gan/spectral_normalization.py

@@ -29,7 +29,8 @@ import re
 
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
-from tensorflow.python.keras.engine import base_layer_utils as keras_base_layer_utils
+from tensorflow.python.keras.engine import \
+    base_layer_utils as keras_base_layer_utils
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import init_ops
 from tensorflow.python.ops import math_ops

bob/learn/tensorflow/image/__init__.py

-from .filter import gaussian_kernel, GaussianFilter
+from .filter import GaussianFilter
+from .filter import gaussian_kernel
+
 
 # gets sphinx autodoc done right - don't remove it
 def __appropriate__(*args):

bob/learn/tensorflow/loss/BaseLoss.py

@@ -3,6 +3,7 @@
 # @author: Tiago de Freitas Pereira <tiago.pereira@idiap.ch>
 
 import logging
+
 import tensorflow as tf
 
 logger = logging.getLogger(__name__)

bob/learn/tensorflow/loss/ContrastiveLoss.py

@@ -3,7 +3,9 @@
 # @author: Tiago de Freitas Pereira <tiago.pereira@idiap.ch>
 
 import logging
+
 import tensorflow as tf
+
 from bob.learn.tensorflow.utils import compute_euclidean_distance
 
 logger = logging.getLogger(__name__)

bob/learn/tensorflow/loss/StyleLoss.py

@@ -2,9 +2,10 @@
 # vim: set fileencoding=utf-8 :
 # @author: Tiago de Freitas Pereira <tiago.pereira@idiap.ch>
 
+import functools
 import logging
+
 import tensorflow as tf
-import functools
 
 logger = logging.getLogger(__name__)
 

bob/learn/tensorflow/loss/__init__.py

 # from .BaseLoss import mean_cross_entropy_loss, mean_cross_entropy_center_loss
-from .ContrastiveLoss import contrastive_loss
-from .TripletLoss import triplet_loss, triplet_average_loss, triplet_fisher_loss
-from .StyleLoss import linear_gram_style_loss, content_loss, denoising_loss
-from .vat import VATLoss
-from .pixel_wise import PixelWise
 from .center_loss import CenterLoss
+from .ContrastiveLoss import contrastive_loss
 from .mmd import *
 from .pairwise_confusion import total_pairwise_confusion
+from .pixel_wise import PixelWise
+from .StyleLoss import content_loss
+from .StyleLoss import denoising_loss
+from .StyleLoss import linear_gram_style_loss
+from .TripletLoss import triplet_average_loss
+from .TripletLoss import triplet_fisher_loss
+from .TripletLoss import triplet_loss
 from .utils import *
+from .vat import VATLoss
 
 
 # gets sphinx autodoc done right - don't remove it

bob/learn/tensorflow/loss/center_loss.py

 import tensorflow as tf
 
+
 # TODO(amir): replace parent class with tf.Module in tensorflow 1.14 and above.
 # * pass ``name`` to parent class
 # * replace get_variable with tf.Variable

bob/learn/tensorflow/loss/pairwise_confusion.py

 import tensorflow as tf
-from ..utils import pdist_safe, upper_triangle
+
+from ..utils import pdist_safe
+from ..utils import upper_triangle
 
 
 def total_pairwise_confusion(prelogits, name=None):

bob/learn/tensorflow/loss/pixel_wise.py

-from ..dataset import tf_repeat
-from .utils import (
-    balanced_softmax_cross_entropy_loss_weights,
-    balanced_sigmoid_cross_entropy_loss_weights,
-)
 import tensorflow as tf
 
+from ..dataset import tf_repeat
+from .utils import balanced_sigmoid_cross_entropy_loss_weights
+from .utils import balanced_softmax_cross_entropy_loss_weights
+
 
 class PixelWise:
     """A pixel wise loss which is just a cross entropy loss but applied to all pixels"""

bob/learn/tensorflow/loss/vat.py

@@ -23,9 +23,10 @@
 # SOFTWARE.
 
 
-import tensorflow as tf
 from functools import partial
 
+import tensorflow as tf
+
 
 def get_normalized_vector(d):
     d /= 1e-12 + tf.reduce_max(

bob/learn/tensorflow/models/alexnet.py

@@ -62,6 +62,7 @@ def AlexNet_simplified(name="AlexNet", **kwargs):
 
 if __name__ == "__main__":
     import pkg_resources
+
     from bob.learn.tensorflow.utils import model_summary
 
     model = AlexNet_simplified()

bob/learn/tensorflow/models/autoencoder_face.py

@@ -4,6 +4,7 @@ Mohammadi, Amir and Bhattacharjee, Sushil and Marcel, Sebastien, ICASSP 2020
 """
 
 import tensorflow as tf
+
 from bob.learn.tensorflow.models.densenet import densenet161
 
 
@@ -114,6 +115,7 @@ def autoencoder_face(z_dim=256, weight_decay=1e-10, decoder_last_act="tanh"):
 if __name__ == "__main__":
     import pkg_resources
     from tabulate import tabulate
+
     from bob.learn.tensorflow.utils import model_summary
 
     model = ConvDecoder(z_dim=256, weight_decay=1e-9, last_act="tanh", name="Decoder")

bob/learn/tensorflow/models/densenet.py

@@ -3,6 +3,7 @@ Reference [Densely Connected Convolutional Networks](https://arxiv.org/abs/1608.
 """
 
 import tensorflow as tf
+
 from bob.extension import rc
 
 l2 = tf.keras.regularizers.l2
@@ -448,6 +449,7 @@ class DeepPixBiS(tf.keras.Model):
 if __name__ == "__main__":
     import pkg_resources
     from tabulate import tabulate
+
     from bob.learn.tensorflow.utils import model_summary
 
     def print_model(inputs, outputs):

bob/learn/tensorflow/models/inception.py

@@ -144,6 +144,7 @@ def GoogLeNet(*, num_classes=1000, name="GoogLeNet", **kwargs):
 if __name__ == "__main__":
     import pkg_resources
     from tabulate import tabulate
+
     from bob.learn.tensorflow.utils import model_summary
 
     inputs = tf.keras.Input((28, 28, 192), name="input")

bob/learn/tensorflow/models/inception_resnet_v2.py

 # -*- coding: utf-8 -*-
 """Inception-ResNet-V2 MultiScale-Inception-ResNet-V2 models for Keras.
 """
-from tensorflow.keras.models import Model
-from tensorflow.keras.layers import (
-    Activation,
-    BatchNormalization,
-    Concatenate,
-    Conv2D,
-    Dense,
-    Dropout,
-    Input,
-    Lambda,
-    MaxPool2D,
-    AvgPool2D,
-    GlobalAvgPool2D,
-    GlobalMaxPool2D,
-)
-from tensorflow.keras import backend as K
-import tensorflow as tf
 import logging
 
+import tensorflow as tf
+from tensorflow.keras import backend as K
+from tensorflow.keras.layers import Activation
+from tensorflow.keras.layers import AvgPool2D
+from tensorflow.keras.layers import BatchNormalization
+from tensorflow.keras.layers import Concatenate
+from tensorflow.keras.layers import Conv2D
+from tensorflow.keras.layers import Dense
+from tensorflow.keras.layers import Dropout
+from tensorflow.keras.layers import GlobalAvgPool2D
+from tensorflow.keras.layers import GlobalMaxPool2D
+from tensorflow.keras.layers import Input
+from tensorflow.keras.layers import Lambda
+from tensorflow.keras.layers import MaxPool2D
+from tensorflow.keras.models import Model
+
 logger = logging.getLogger(__name__)
 
 
@@ -696,6 +695,7 @@ def MultiScaleInceptionResNetV2(
 if __name__ == "__main__":
     import pkg_resources
     from tabulate import tabulate
+
     from bob.learn.tensorflow.utils import model_summary
 
     def print_model(inputs, outputs, name=None):