class_docstr: Decorator to call `load` method on registered loggers.
code: def _call_logger_method(
      self,
      logger_method: _LoggerMethod,
      args: Any,
      kwargs: Any,
  ):
      logger_method(
          name=args[0] if args else kwargs["name"],
          split=kwargs.get("split"),
          data_dir=kwargs.get("data_dir"),
          batch_size=kwargs.get("batch_size"),
          shuffle_files=kwargs.get("shuffle_files"),
          download=kwargs.get("download"),
          as_supervised=kwargs.get("as_supervised"),
          decoders=kwargs.get("decoders"),
          read_config=kwargs.get("read_config"),
          with_info=kwargs.get("with_info"),
          try_gcs=kwargs.get("try_gcs"),
      )
  
imports: import abc
  import atexit
  import collections
  import functools
  import threading
  from typing import Any, Callable, Dict, List, Optional, Tuple, TypeVar
  from absl import flags
  from tensorflow_datasets.core.logging import base_logger
  from tensorflow_datasets.core.logging import call_metadata
  from tensorflow_datasets.core.logging import logging_logger
  import wrapt
label_desc: Use image node_id 1 for calling the load obj's underlying member method code with example usage: obj._call_logger_method(logger_method, args, kwargs) without return types