class_docstr: Splits wav and midi files for the dataset.
class_docstr_tok: ["Splits","wav","and","midi","files","for","the","dataset","."]
code: def __init__(
      self,
      wav_dir,
      midi_dir,
      add_wav_glob,
      *unused_args,
      **unused_kwargs,
  ):
      self._wav_dir = wav_dir
      self._midi_dir = midi_dir
      self._add_wav_glob = add_wav_glob
      super(CreateExampleDoFn, self).__init__(
          *unused_args, **unused_kwargs
      )
  
file_path: magenta/magenta/models/onsets_frames_transcription/onsets_frames_transcription_create_tfrecords.py
imports: import collections
  import copy
  import csv
  import os
  from absl import app
  from absl import flags
  from absl import logging
  import apache_beam
  from apache_beam.metrics import Metrics
  from magenta.models.onsets_frames_transcription import audio_label_data_utils
  from note_seq import midi_io
  from note_seq.protobuf import music_pb2
  import tensorflow.compat.v1
label_desc: Use image node_id 1 to create a new CreateExampleDoFn object from inherited base classes: beam with example: obj = CreateExampleDoFn(wav_dir, midi_dir, add_wav_glob)