class_docstr: File adapter for the [Parquet](https://parquet.apache.org) file format.
  
  This FileAdapter requires `pyarrow` as a dependency and builds upon
  `pyarrow.parquet`.
  
  At the moment, the Parquet adapter doesn't leverage Parquet's columnar
  features and behaves like any other adapter. Instead of saving the features in
  the columns, we use one single `data` column where we store the serialized
  tf.Example proto.
  
  TODO(b/317277518): Let Parquet handle the serialization/deserialization.
docstr: Reads a Parquet file as a tf.data.Dataset.
  
  Args:
    filename: Path to the Parquet file.
    buffer_size: Unused buffer size.
  
  Returns:
    A tf.data.Dataset with the serialized examples.
docstr_tok: ["Reads","a","Parquet","file","as","a","tf.data.Dataset",".","Args",":","filename",":","Path","to","the","Parquet","file",".","buffer_size",":","Unused","buffer","size",".","Returns",":","A","tf.data.Dataset","with","the","serialized","examples","."]
code: def make_tf_data(
      cls,
      filename: epath.PathLike,
      buffer_size: int | None = None,
  ) -> tf.data.Dataset:
      """Reads a Parquet file as a tf.data.Dataset.
  
      Args:
        filename: Path to the Parquet file.
        buffer_size: Unused buffer size.
  
      Returns:
        A tf.data.Dataset with the serialized examples.
      """
      del buffer_size  # unused
      import pyarrow.parquet as pq  # pylint: disable=g-import-not-at-top
  
      def get_data(py_filename: bytes) -> Iterator[tf.Tensor]:
          table = pq.read_table(
              py_filename.decode(), schema=cls._schema()
          )
          for batch in table.to_batches():
              for example in batch.to_pylist():
                  yield tf.constant(example[cls._PARQUET_FIELD])
  
      return tf.data.Dataset.from_generator(
          get_data,
          args=(filename,),
          output_signature=tf.TensorSpec(shape=(), dtype=tf.string),
      )
  
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 2 for calling the ParquetFileAdapter obj's underlying member method code with example usage: obj.make_tf_data(cls, filename, buffer_size) and returns: tf