message: Fix the default value doc string of global_step in contrib.slim
diff: @@ -389,7 +389,7 @@ def create_train_op(total_loss,
  total_loss: A `Tensor` representing the total loss.
  optimizer: A tf.Optimizer to use for computing the gradients.
  global_step: A `Tensor` representing the global step variable. If left as
  - `_USE_GLOBAL_STEP`, then slim.variables.global_step() is used.
  + `_USE_GLOBAL_STEP`, then tf.contrib.framework.global_step() is used.
  update_ops: An optional list of updates to execute. If `update_ops` is
  `None`, then the update ops are set to the contents of the
  `tf.GraphKeys.UPDATE_OPS` collection. If `update_ops` is not `None`, but
  @@ -578,7 +578,8 @@ def train(train_op,
  is_chief: Specifies whether or not the training is being run by the primary
  replica during replica training.
  global_step: The `Tensor` representing the global step. If left as `None`,
  - then slim.variables.get_or_create_global_step() is used.
  + then training_util.get_or_create_global_step(), that is,
  + tf.contrib.framework.global_step() is used.
  number_of_steps: The max number of gradient steps to take during training,
  as measured by 'global_step': training will stop if global_step is
  greater than 'number_of_steps'. If the value is left as None, training
  