code: def _validate_input_tag(input_tag: InputTag):
      if input_tag is None:
          raise MlflowException(
              "InputTag cannot be None", INVALID_PARAMETER_VALUE
          )
      if input_tag.key is None:
          raise MlflowException(
              "InputTag key cannot be None", INVALID_PARAMETER_VALUE
          )
      if input_tag.value is None:
          raise MlflowException(
              "InputTag value cannot be None", INVALID_PARAMETER_VALUE
          )
      if len(input_tag.key) > MAX_INPUT_TAG_KEY_SIZE:
          raise MlflowException(
              f"InputTag key exceeds the maximum length of {MAX_INPUT_TAG_KEY_SIZE}",
              INVALID_PARAMETER_VALUE,
          )
      if len(input_tag.value) > MAX_INPUT_TAG_VALUE_SIZE:
          raise MlflowException(
              f"InputTag value exceeds the maximum length of {MAX_INPUT_TAG_VALUE_SIZE}",
              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 33 for calling a global function with example usage: _validate_input_tag(input_tag) without return types