code: def _validate_experiment_id_type(experiment_id):
      """
      Check that a user-provided experiment_id is either a string, int, or None and raise an
      exception if it isn't.
      """
      if experiment_id is not None and not isinstance(
          experiment_id, (str, int)
      ):
          raise MlflowException(
              f"Invalid experiment id: {experiment_id} of type {type(experiment_id)}. "
              "Must be one of str, int, or None.",
              error_code=INVALID_PARAMETER_VALUE,
          )
  
imports: import numbers
  import posixpath
  import re
  from typing import List
  from mlflow.entities import Dataset, DatasetInput, InputTag
  from mlflow.exceptions import MlflowException
  from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE
  from mlflow.store.db.db_types import DATABASE_ENGINES
  from mlflow.utils.string_utils import is_string_type
label_desc: Use image node_id 22 for calling a global function with example usage: _validate_experiment_id_type(experiment_id) without return types