class_docstr: Shuffles / writes Examples beam collection to sharded TFRecord files.
  
  The given examples are not directly writen to the final tfrecord file, but to
  temporary files.
class_docstr_tok: ["Shuffles","\/","writes","Examples","beam","collection","to","sharded","TFRecord","files",".","The","given","examples","are","not","directly","writen","to","the","final","tfrecord","file",",","but","to","temporary","files","."]
code: def _check_num_examples(self, num_examples: int) -> int:
      if num_examples <= 0:
          raise ValueError(
              f"The total number of generated examples is {num_examples}. This"
              " should be >0!"
          )
      return num_examples
  
imports: import dataclasses
  import functools
  import itertools
  import json
  import os
  from typing import Any, Iterable, List, Optional, Tuple
  from absl import logging
  from etils import epath
  from tensorflow_datasets.core import example_parser
  from tensorflow_datasets.core import example_serializer
  from tensorflow_datasets.core import file_adapters
  from tensorflow_datasets.core import hashing
  from tensorflow_datasets.core import lazy_imports_lib
  from tensorflow_datasets.core import naming
  from tensorflow_datasets.core import shuffle
  from tensorflow_datasets.core import utils
  from tensorflow_datasets.core.utils import file_utils
  from tensorflow_datasets.core.utils import shard_utils
  from tensorflow_datasets.core.utils import type_utils
  from tensorflow_datasets.core.utils.lazy_imports_utils import apache_beam
label_desc: Use image node_id 8 for calling the BeamWriter obj's underlying member method code with example usage: obj._check_num_examples(num_examples) and returns: num_examples