code: def embed_check_nonnegative_integer_form(
      x, name="embed_check_nonnegative_integer_form"
  ):
      """Assert x is a non-negative tensor, and optionally of integers."""
      with ops.name_scope(name, values=[x]):
          x = ops.convert_to_tensor(x, name="x")
          assertions = [
              check_ops.assert_non_negative(
                  x, message="'{}' must be non-negative.".format(x)
              ),
          ]
          if not x.dtype.is_integer:
              assertions += [
                  assert_integer_form(
                      x,
                      message="'{}' cannot contain fractional components.".format(
                          x
                      ),
                  ),
              ]
          return control_flow_ops.with_dependencies(assertions, x)
  
imports: import functools
  import hashlib
  import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import linalg_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn
  from tensorflow.python.util import tf_inspect
label_desc: Use image node_id 3 for calling a global function with example usage: embed_check_nonnegative_integer_form(x, name) and returns: control_flow_ops