parameters: (sess, global_step_tensor)
return_statement: return int(sess.run(global_step_tensor))
docstring: Small helper to get the global step.
  
    ```python
    # Creates a variable to hold the global_step.
    global_step_tensor = tf.Variable(10, trainable=False, name='global_step')
    # Creates a session.
    sess = tf.Session()
    # Initializes the variable.
    sess.run(global_step_tensor.initializer)
    print('global_step: %s' % tf.train.global_step(sess, global_step_tensor))
  
    global_step: 10
    ```
  
    Args:
      sess: A TensorFlow `Session` object.
      global_step_tensor:  `Tensor` or the `name` of the operation that contains
        the global step.
  
    Returns:
      The global step value.
docstring_summary: Small helper to get the global step.
docstring_tokens: Small helper to get the global step .
function: def global_step(sess, global_step_tensor):
    """Small helper to get the global step.
  
    ```python
    # Creates a variable to hold the global_step.
    global_step_tensor = tf.Variable(10, trainable=False, name='global_step')
    # Creates a session.
    sess = tf.Session()
    # Initializes the variable.
    sess.run(global_step_tensor.initializer)
    print('global_step: %s' % tf.train.global_step(sess, global_step_tensor))
  
    global_step: 10
    ```
  
    Args:
      sess: A TensorFlow `Session` object.
      global_step_tensor:  `Tensor` or the `name` of the operation that contains
        the global step.
  
    Returns:
      The global step value.
    """
    return int(sess.run(global_step_tensor))
function_tokens: def global_step ( sess , global_step_tensor ) : return int ( sess . run ( global_step_tensor ) )