code: def slice_host_devices_for_multiworker(num_clients, client_id, ports):
      """Configure the current process to only use a slice of devices."""
      if num_clients == 0:
          # All GPUs are visible to the client.
          del os.environ["CUDA_VISIBLE_DEVICES"]
          del os.environ["HIP_VISIBLE_DEVICES"]
      else:
          # Make the client_id-th GPU visible to the client.
          os.environ["CUDA_VISIBLE_DEVICES"] = f"{client_id}"
          os.environ["HIP_VISIBLE_DEVICES"] = f"{client_id}"
          # Make the client_id-th (4x) TPU cores visible to the client.
          os.environ["CLOUD_TPU_TASK_ID"] = f"{client_id}"
          if "tpu" in DTENSOR_TEST_UTIL_BACKEND.value:
              del ports  # Unused due to lack of implementation.
              # We need to find out if there is a way to slice a CloudTPU host to
              # multiple workers.
              raise NotImplementedError(
                  "OSS multi-client tests of TPU is not supported."
              )
  
file_path: tensorflow/tensorflow/dtensor/python/tests/test_backend_util.py
imports: import multiprocessing
  import os
  from tensorflow.dtensor.python import accelerator_util
  from tensorflow.dtensor.python import config
  from tensorflow.dtensor.python import layout
  from tensorflow.dtensor.python.tests.test_backend_name import DTENSOR_TEST_UTIL_BACKEND
  from tensorflow.python.platform import test
label_desc: Use image node_id 2 for calling a global function with example usage: slice_host_devices_for_multiworker(num_clients, client_id, ports) without return types