(**kwargs)
return lib.training_scope(**kwargs)
Defines MobilenetV2 training scope.

  Usage:
     with tf.contrib.slim.arg_scope(mobilenet_v2.training_scope()):
       logits, endpoints = mobilenet_v2.mobilenet(input_tensor)

  with slim.

  Args:
    **kwargs: Passed to mobilenet.training_scope. The following parameters
    are supported:
      weight_decay- The weight decay to use for regularizing the model.
      stddev-  Standard deviation for initialization, if negative uses xavier.
      dropout_keep_prob- dropout keep probability
      bn_decay- decay for the batch norm moving averages.

  Returns:
    An `arg_scope` to use for the mobilenet v2 model.
Defines MobilenetV2 training scope.
Defines MobilenetV2 training scope .
def training_scope(**kwargs):
  """Defines MobilenetV2 training scope.

  Usage:
     with tf.contrib.slim.arg_scope(mobilenet_v2.training_scope()):
       logits, endpoints = mobilenet_v2.mobilenet(input_tensor)

  with slim.

  Args:
    **kwargs: Passed to mobilenet.training_scope. The following parameters
    are supported:
      weight_decay- The weight decay to use for regularizing the model.
      stddev-  Standard deviation for initialization, if negative uses xavier.
      dropout_keep_prob- dropout keep probability
      bn_decay- decay for the batch norm moving averages.

  Returns:
    An `arg_scope` to use for the mobilenet v2 model.
  """
  return lib.training_scope(**kwargs)
def training_scope ( * * kwargs ) : return lib . training_scope ( * * kwargs )