code: def non_deterministic_ints(shape, dtype=dtypes.int64):
      """Non-deterministically generates some integers.
  
      This op may use some OS-provided source of non-determinism (e.g. an RNG), so
      each execution will give different results.
  
      Args:
        shape: the shape of the result.
        dtype: (optional) the dtype of the result.
  
      Returns:
        a tensor whose element values are non-deterministically chosen.
      """
      return gen_stateful_random_ops.non_deterministic_ints(
          shape=shape, dtype=dtype
      )
  
imports: from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.distribute import sharded_variable
  from tensorflow.python.distribute import values_util
  from tensorflow.python.eager import context
  from tensorflow.python.framework import config
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import gen_stateful_random_ops
  from tensorflow.python.ops import gen_stateless_random_ops_v2
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops_util
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import stateless_random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.trackable import autotrackable
  from tensorflow.python.util import nest
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 1 for calling a global function with example usage: non_deterministic_ints(shape, dtype) and returns: gen_stateful_random_ops