class_docstr: File adapter for TFRecord file format.
docstr: Returns TensorFlow Dataset comprising given record file.
docstr_tok: ["Returns","TensorFlow","Dataset","comprising","given","record","file","."]
code: def make_tf_data(
      cls,
      filename: epath.PathLike,
      buffer_size: Optional[int] = None,
  ) -> tf.data.Dataset:
      """Returns TensorFlow Dataset comprising given record file."""
      buffer_size = buffer_size or cls.BUFFER_SIZE
      return tf.data.TFRecordDataset(filename, buffer_size=buffer_size)
  
imports: from __future__ import annotations
  import abc
  from collections.abc import Iterator
  import enum
  import itertools
  import os
  from typing import Any, ClassVar, Dict, Iterable, List, Optional, Type, TypeVar, Union
  import uuid
  from etils import epath
  from tensorflow_datasets.core.utils import type_utils
  from tensorflow_datasets.core.utils.lazy_imports_utils import array_record_module
  from tensorflow_datasets.core.utils.lazy_imports_utils import pyarrow
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
label_desc: Use image node_id 1 for calling the TfRecordFileAdapter obj's underlying member method code with example usage: obj.make_tf_data(cls, filename, buffer_size) and returns: tf