path: "tensorflow.queue.RandomShuffleQueue"
tf_class {
  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.RandomShuffleQueue\'>"
  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.QueueBase\'>"
  is_instance: "<type \'object\'>"
  member {
    name: "dtypes"
    mtype: "<type \'property\'>"
  }
  member {
    name: "name"
    mtype: "<type \'property\'>"
  }
  member {
    name: "names"
    mtype: "<type \'property\'>"
  }
  member {
    name: "queue_ref"
    mtype: "<type \'property\'>"
  }
  member {
    name: "shapes"
    mtype: "<type \'property\'>"
  }
  member_method {
    name: "__init__"
    argspec: "args=[\'self\', \'capacity\', \'min_after_dequeue\', \'dtypes\', \'shapes\', \'names\', \'seed\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'random_shuffle_queue\'], "
  }
  member_method {
    name: "close"
    argspec: "args=[\'self\', \'cancel_pending_enqueues\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
  }
  member_method {
    name: "dequeue"
    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
  }
  member_method {
    name: "dequeue_many"
    argspec: "args=[\'self\', \'n\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
  }
  member_method {
    name: "dequeue_up_to"
    argspec: "args=[\'self\', \'n\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
  }
  member_method {
    name: "enqueue"
    argspec: "args=[\'self\', \'vals\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
  }
  member_method {
    name: "enqueue_many"
    argspec: "args=[\'self\', \'vals\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
  }
  member_method {
    name: "from_list"
    argspec: "args=[\'index\', \'queues\'], varargs=None, keywords=None, defaults=None"
  }
  member_method {
    name: "is_closed"
    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
  }
  member_method {
    name: "size"
    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
  }
}