code: def _validate_batch_log_api_req(json_req):
      if len(json_req) > MAX_BATCH_LOG_REQUEST_SIZE:
          error_msg = (
              "Batched logging API requests must be at most {limit} bytes, got a "
              "request of size {size}."
          ).format(limit=MAX_BATCH_LOG_REQUEST_SIZE, size=len(json_req))
          raise MlflowException(
              error_msg, 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 20 for calling a global function with example usage: _validate_batch_log_api_req(json_req) without return types