code: def product(*lists):
      """Makes a product of names parameters list."""
      # Each element lists should be a tuple of tuples of the form
      # (("test1", ...), ("test2", ...), ...).
      # Function returns the product of the lists with the labels concatenated.
      return [  # pylint: disable=g-complex-comprehension
          ("".join(p[0] for p in elt), *sum((p[1:] for p in elt), ()))
          for elt in itertools.product(*lists)
      ]
  
imports: import collections
  import copy
  import itertools
  import json
  import os
  import typing
  from absl import flags
  from absl.testing import parameterized
  import numpy
  from tensorflow.dtensor.python import accelerator_util
  from tensorflow.dtensor.python import api
  from tensorflow.dtensor.python import config
  from tensorflow.dtensor.python import layout
  from tensorflow.dtensor.python import numpy_util
  from tensorflow.dtensor.python.config import is_gpu_present
  from tensorflow.dtensor.python.config import is_tpu_present
  from tensorflow.dtensor.python.config import preferred_device_type
  from tensorflow.dtensor.python.config import use_multi_device_mode
  from tensorflow.dtensor.python.tests import test_backend_util
  from tensorflow.dtensor.python.tests.test_backend_name import DTENSOR_TEST_UTIL_BACKEND
  from tensorflow.dtensor.python.tests.test_backend_name import DTensorTestUtilBackend
  from tensorflow.dtensor.python.tests.test_backend_util import DTensorTestBackendConfigurator
  from tensorflow.python.compat import v2_compat
  from tensorflow.python.eager import context
  from tensorflow.python.framework import config
  from tensorflow.python.framework import device
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 9 for calling a global function with example usage: product() and returns: unknown