<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def global_step(device=''):
 """Returns the global step variable. Args: device: Optional device to place the variable. It can be an string or a function that is called to get the device for the variable. Returns: the tensor representing the global step variable. """

  global_step_ref = tf.get_collection(tf.GraphKeys.GLOBAL_STEP)
  if global_step_ref:
    return global_step_ref[0]
  else:
    collections = [
        VARIABLES_TO_RESTORE,
        tf.GraphKeys.GLOBAL_VARIABLES,
        tf.GraphKeys.GLOBAL_STEP,
    ]
    # Get the device for the variable.
    with tf.device(variable_device(device, 'global_step')):
      return tf.get_variable('global_step', shape=[], dtype=tf.int64,
                             initializer=tf.zeros_initializer(),
                             trainable=False, collections=collections)