class_docstr: A logger that is based on the absl logging module.
class_docstr_tok: ["A","logger","that","is","based","on","the","absl","logging","module","."]
code: def as_dataset(
      self,
      *,
      metadata: call_metadata.CallMetadata,
      name: str,
      config_name: Optional[str],
      version: str,
      data_path: str,
      split: Union[str, splits_lib.ReadInstruction],
      batch_size: Optional[int],
      shuffle_files: bool,
      read_config: tfds_read_config.ReadConfig,
      as_supervised: bool,
      decoders: Optional[TreeDict[decode.partial_decode.DecoderArg]],
  ):
      logging.info(
          "Constructing tf.data.Dataset %s for split %s, from %s",
          name,
          str(split),
          data_path,
      )
  
file_path: datasets/tensorflow_datasets/core/logging/logging_logger.py
imports: from typing import Optional, Union
  from absl import logging
  from tensorflow_datasets.core import decode
  from tensorflow_datasets.core import splits
  from tensorflow_datasets.core.logging import base_logger
  from tensorflow_datasets.core.logging import call_metadata
  from tensorflow_datasets.core.utils import read_config
  from tensorflow_datasets.core.utils import type_utils
label_desc: Use image node_id 1 for calling the LoggingLogger obj's underlying member method code with example usage: obj.as_dataset() without return types