code: def random_shuffle(value, seed=None, name=None):
      """Randomly shuffles a tensor along its first dimension.
  
      The tensor is shuffled along dimension 0, such that each `value[j]` is mapped
      to one and only one `output[i]`. For example, a mapping that might occur for a
      3x2 tensor is:
  
      ```python
      [[1, 2],       [[5, 6],
       [3, 4],  ==>   [1, 2],
       [5, 6]]        [3, 4]]
      ```
  
      Args:
        value: A Tensor to be shuffled.
        seed: A Python integer. Used to create a random seed for the distribution.
          See
          `tf.random.set_seed`
          for behavior.
        name: A name for the operation (optional).
  
      Returns:
        A tensor of same shape and type as `value`, shuffled along its first
        dimension.
      """
      seed1, seed2 = random_seed.get_seed(seed)
      return gen_random_ops.random_shuffle(
          value, seed=seed1, seed2=seed2, name=name
      )
  
imports: import numpy
  from tensorflow.python.eager import context
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import random_seed
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_random_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import shape_util
  from tensorflow.python.ops.gen_random_ops import *
  from tensorflow.python.util import deprecation
  from tensorflow.python.util import dispatch
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 5 for calling a global function with example usage: random_shuffle(value, seed, name) and returns: gen_random_ops