code: def _validate_batch_limit(entity_name, limit, length):
      if length > limit:
          error_msg = (
              f"A batch logging request can contain at most {limit} {entity_name}. "
              f"Got {length} {entity_name}. Please split up {entity_name} across multiple"
              " requests and try again."
          )
          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 17 for calling a global function with example usage: _validate_batch_limit(entity_name, limit, length) without return types