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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _make_builder_configs():
 """Make built-in Librispeech BuilderConfigs. Uses 4 text encodings (plain text, bytes, subwords with 8k vocab, subwords with 32k vocab) crossed with the data subsets (clean100, clean360, all). Returns: `list<tfds.audio.LibrispeechConfig>` """

  text_encoder_configs = [
      None,
      tfds.features.text.TextEncoderConfig(
          name="bytes", encoder=tfds.features.text.ByteTextEncoder()),
      tfds.features.text.TextEncoderConfig(
          name="subwords8k",
          encoder_cls=tfds.features.text.SubwordTextEncoder,
          vocab_size=2**13),
      tfds.features.text.TextEncoderConfig(
          name="subwords32k",
          encoder_cls=tfds.features.text.SubwordTextEncoder,
          vocab_size=2**15),
  ]
  version = "0.1.0"
  configs = []
  for text_encoder_config in text_encoder_configs:
    for data in _DATA_OPTIONS:
      config = LibrispeechConfig(
          version=version, text_encoder_config=text_encoder_config, data=data)
      configs.append(config)
  return configs