code: def stateless_random_shuffle(input_tensor, seed, name=None):
      """Produces stateless random shuffle of the 1st dimension of an input Tensor.
  
      This is a stateless version of `tf.random_shuffle`. If run twice with the same
      seed, produces the same result.
  
      Example
      ```python
      identity_shuffle = tf.range(100)
      random_shuffle = stateless_random_shuffle(identity_shuffle, seed=(42, 2))
      ```
  
      Args:
        input_tensor: float32, float64, int32 or int64 1-D Tensor.
        seed: int32 or int64 Tensor of shape [2].
        name: Python `str` name prefixed to ops created by this function.
  
      Returns:
        A Tensor of the same shape and dtype as `input_tensor`.
      """
      with tf.compat.v1.name_scope(
          name,
          default_name="stateless_random_shuffle",
          values=[input_tensor, seed],
      ):
          input_tensor = tf.convert_to_tensor(
              input_tensor, name="input_tensor"
          )
          seed = tf.convert_to_tensor(seed, name="random_seed")
          uniforms = tf.random.stateless_uniform(
              shape=[tf.shape(input_tensor)[0]],
              seed=seed,
              dtype=tf.float64,
          )
      return tf.gather(
          input_tensor, tf.argsort(uniforms, stable=True, axis=0)
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: stateless_random_shuffle(input_tensor, seed, name) and returns: tf