code: def _transform_per_example_beam(
      builder: dataset_builder.DatasetBuilder,
      split_info: splits_lib.SplitInfo,
      transformations: List[transform_lib.ExampleTransformFn],
      workers_per_shard: int = 1,
  ) -> split_builder_lib.SplitGenerator:
      split = split_info.name
      read_config = read_config_lib.ReadConfig(add_tfds_id=True)
      return (
          f"read_tfds_dataset@{split}"
          >> beam_utils.ReadFromTFDS(
              builder=builder,
              split=split,
              read_config=read_config,
              workers_per_shard=workers_per_shard,
          )
          | f"convert_to_numpy@{split}"
          >> beam.Map(dataset_utils.as_numpy)
          | f"transform_examples@{split}"
          >> beam.ParDo(
              _transform_example, transformations=transformations
          )
      )
  
imports: from __future__ import annotations
  import functools
  from typing import Callable, Dict, Iterator, List, Optional, Union
  from tensorflow_datasets.core import beam_utils
  from tensorflow_datasets.core import dataset_builder
  from tensorflow_datasets.core import dataset_utils
  from tensorflow_datasets.core import load
  from tensorflow_datasets.core import naming
  from tensorflow_datasets.core import registered
  from tensorflow_datasets.core import split_builder
  from tensorflow_datasets.core import splits
  from tensorflow_datasets.core import transform
  from tensorflow_datasets.core.download import download_manager
  from tensorflow_datasets.core.utils import read_config
  from tensorflow_datasets.core.utils.lazy_imports_utils import apache_beam
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
label_desc: Use image node_id 3 for calling a global function with example usage: _transform_per_example_beam(builder, split_info, transformations, workers_per_shard) and returns: unknown