code: def get_client_environment_name() -> Text:
      """Identifies the local environment where tensorflow_cloud is running.
  
      Returns:
          ClientEnvironment Enum representing the environment type.
      """
      if _get_env_variable(_KAGGLE_ENV_VARIABLE):
          logging.info("Kaggle client environment detected.")
          return ClientEnvironment.KAGGLE_NOTEBOOK.name
  
      if _is_module_present("google.colab"):
          logging.info("Detected running in COLAB environment.")
          return ClientEnvironment.COLAB.name
  
      if _get_env_variable(_DL_ENV_PATH_VARIABLE):
          # TODO(b/171720710) Update logic based resolution of the issue.
          if _get_env_variable("USER") == "jupyter":
              logging.info(
                  "Detected running in HOSTED_NOTEBOOK environment."
              )
              return ClientEnvironment.HOSTED_NOTEBOOK.name
  
          # TODO(b/175815580) Update logic based resolution of the issue.
          logging.info("Detected running in DLVM environment.")
          return ClientEnvironment.DLVM.name
  
      # TODO(b/175815580) Update logic based resolution of the issue.
      if _is_module_present("google"):
          logging.info("Detected running in DL_CONTAINER environment.")
          return ClientEnvironment.DL_CONTAINER.name
  
      logging.info("Detected running in UNKNOWN environment.")
      return ClientEnvironment.UNKNOWN.name
  
imports: import enum
  import json
  import os
  import sys
  import time
  from typing import Dict, Text, Union
  from ..None import version
  from absl import logging
  from googleapiclient import discovery
  from googleapiclient import errors
  from googleapiclient import http
label_desc: Use image node_id 1 for calling a global function with example usage: get_client_environment_name() and returns: ClientEnvironment, ClientEnvironment, ClientEnvironment, ClientEnvironment, ClientEnvironment, ClientEnvironment