code: def client_config_function(config_params):
      client_id = config_params["client_id"]
      worker_jobs = config_params["worker_jobs"]
      num_devices = config_params["num_devices"]
  
      os.environ["TF_CONFIG"] = json.dumps(
          {
              "cluster": {"worker": worker_jobs},
              "task": {"type": "worker", "index": f"{client_id}"},
          }
      )
  
      if config.list_physical_devices("GPU"):
          device_type = "GPU"
      elif test_util.is_tpu_present():
          device_type = "TPU"
      else:
          device_type = "CPU"
  
      # reset_logical_devices
      test_util.reset_context()
      if device_type != "TPU":
          # Configure virtual devices. This does not initialize the TensorFlow
          # context.
          test_util.reset_logical_devices(device_type, num_devices)
  
      # Validates the correct number of devices are created.
      logical_devices = test_util.list_local_logical_devices(
          device_type
      )
      assert len(logical_devices) == num_devices, (
          logical_devices,
          f"Test is mis-configured: expecting {num_devices} logical_devices.",
      )
  
imports: import json
  import os
  from absl import flags
  from absl.testing import parameterized
  import numpy
  from tensorflow.dtensor.python import api
  from tensorflow.dtensor.python import d_variable
  from tensorflow.dtensor.python import layout
  from tensorflow.dtensor.python.tests import multi_client_test_util
  from tensorflow.dtensor.python.tests import test_backend_util
  from tensorflow.dtensor.python.tests import test_util
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.distribute import reduce_util
  from tensorflow.python.distribute.cluster_resolver import tfconfig_cluster_resolver
  from tensorflow.python.distribute.experimental import dtensor_util
  from tensorflow.python.distribute.experimental import multi_worker_mirrored_strategy
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import config
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import stateless_random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling a global function with example usage: client_config_function(config_params) without return types