Merge branch 'master' of https://github.com/awni/cinc17

network.py

@@ -32,7 +32,7 @@ def init_inference(self, config):
  stride = layer['stride']
  bn = layer.get('enable_batch_norm', None)
  ln = layer.get('enable_layer_norm', None)
- 
+
  if bn is not None or ln is not None:
  acts = tf.contrib.layers.convolution2d(acts, num_outputs=num_filters,
  kernel_size=[filter_size, 1],
@@ -43,16 +43,16 @@ def init_inference(self, config):
 
  if bn == True:
  logger.debug("Adding Batch Norm Layer")
- acts = tf.contrib.layers.batch_norm(acts, decay=0.9, center=True, 
- scale=True, epsilon=1e-8, 
- activation_fn=tf.nn.relu, 
+ acts = tf.contrib.layers.batch_norm(acts, decay=0.9, center=True,
+ scale=True, epsilon=1e-8,
+ activation_fn=tf.nn.relu,
  is_training=True)
- 
+
  elif ln == True:
  logger.debug("Adding Layer Norm Layer")
- acts = tf.contrib.layers.layer_norm(acts, center=True, 
- scale=True, 
- activation_fn=tf.nn.relu) 
+ acts = tf.contrib.layers.layer_norm(acts, center=True,
+ scale=True,
+ activation_fn=tf.nn.relu)
  else:
  assert True, "Batch or Layer norm must be specified as True"
  else: