Format with isort

autoencoder.py

@@ -1,13 +1,13 @@
 #!/usr/bin/env python
 
-from __future__ import division, print_function, absolute_import
+from __future__ import absolute_import, division, print_function
 
-import tensorflow as tf
-import numpy as np
 import matplotlib.pyplot as plt
-
+import numpy as np
+import tensorflow as tf
 # Import MINST data
 from tensorflow.examples.tutorials.mnist import input_data
+
 mnist = input_data.read_data_sets("./mnist/", one_hot=True)
 
 # Parameters

check_variable_conflict/assign_variable.py

@@ -1,8 +1,9 @@
 #!/usr/bin/env python
 
-import tensorflow as tf
 import time
 
+import tensorflow as tf
+
 var1 = tf.Variable(0.0, name="var1")
 init_op = tf.initialize_all_variables()
 assign_op = tf.assign(var1, 2.0)

check_variable_conflict/print_variable.py

@@ -1,8 +1,9 @@
 #!/usr/bin/env python
 
-import tensorflow as tf
 import time
 
+import tensorflow as tf
+
 var1 = tf.Variable(0.0, name="var1")
 init_op = tf.initialize_all_variables()
 

convolution_network.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 
-import tensorflow as tf
 import numpy as np
+import tensorflow as tf
 from tensorflow.examples.tutorials.mnist import input_data
 
 mnist = input_data.read_data_sets("data/", one_hot=True)

distributed_tensorflow/distributed_supervisor.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 
-import tensorflow as tf
 import numpy as np
+import tensorflow as tf
 
 # Flags for defining the tf.train.ClusterSpec
 tf.app.flags.DEFINE_string("ps_hosts", "",

embedding_lookup_demo.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 
-import tensorflow as tf
 import numpy as np
+import tensorflow as tf
 
 # 1:1 3:0.7 7:2.5
 # 0:1.3 3:0 8:2.8

linear_regression.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 
-import tensorflow as tf
 import numpy as np
+import tensorflow as tf
 
 # Prepare train data
 train_X = np.linspace(-1, 1, 100)

logistic_regression.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 
-import tensorflow as tf
 import numpy as np
+import tensorflow as tf
 from tensorflow.examples.tutorials.mnist import input_data
 
 # Train data

lstm_demo.py

@@ -1,12 +1,11 @@
 #!/usr/bin/env python
 
-import tensorflow as tf
 import numpy as np
-
+import tensorflow as tf
+from tensorflow.examples.tutorials.mnist import input_data
 from tensorflow.python.ops import rnn, rnn_cell
 
 print("Start to download and extract mnist data")
-from tensorflow.examples.tutorials.mnist import input_data
 mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
 
 # Parameters

mlp.py

@@ -1,10 +1,11 @@
 #!/usr/bin/env python
 
-import tensorflow as tf
 import math
 import os
 
+import tensorflow as tf
 from tensorflow.examples.tutorials.mnist import input_data
+
 mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
 
 # Define the model

multiple_numbers.py

@@ -2,7 +2,6 @@
 
 import tensorflow as tf
 
-
 import pudb;pudb.set_trace()
 
 number1 = tf.constant(1.5)
@@ -11,4 +10,3 @@
 
 with tf.Session() as sess:
   print(sess.run(add_op))
-

neural_network.py

@@ -1,7 +1,8 @@
 #!/usr/bin/env python
 
-import tensorflow as tf
 import numpy as np
+import tensorflow as tf
+
 import input_data
 
 

polynomial_regression.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 
-import tensorflow as tf
 import numpy as np
+import tensorflow as tf
 
 # Prepare train data
 train_X = np.linspace(-1, 1, 100)

resnet/model.py

@@ -1,4 +1,5 @@
 import sys
+
 import numpy as np
 import tensorflow as tf
 

resnet/train.py

@@ -1,9 +1,10 @@
 #!/usr/bin/env python
 
-import tensorflow as tf
-import numpy as np
 import cPickle
 
+import numpy as np
+import tensorflow as tf
+
 import model
 
 

test_tensorflow.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 
-import tensorflow as tf
 import numpy as np
+import tensorflow as tf
 
 train_X = np.linspace(-1, 1, 100)
 train_Y = 2 * train_X + np.random.randn(*train_X.shape) * 0.33 + 10