class_docstr: Problem to train on full 960h, but evaluate on clean data only.
docstr: Get filepattern for data files for mode.
  
  Matches mode to a suffix.
  * DatasetSplit.TRAIN: train
  * DatasetSplit.EVAL: dev
  * DatasetSplit.TEST: test
  * tf.estimator.ModeKeys.PREDICT: dev
  
  Args:
    data_dir: str, data directory.
    mode: DatasetSplit
    shard: int, if provided, will only read data from the specified shard.
  
  Returns:
    filepattern str
code: def filepattern(self, data_dir, mode, shard=None):
      """Get filepattern for data files for mode.
  
      Matches mode to a suffix.
      * DatasetSplit.TRAIN: train
      * DatasetSplit.EVAL: dev
      * DatasetSplit.TEST: test
      * tf.estimator.ModeKeys.PREDICT: dev
  
      Args:
        data_dir: str, data directory.
        mode: DatasetSplit
        shard: int, if provided, will only read data from the specified shard.
  
      Returns:
        filepattern str
      """
      shard_str = "-%05d" % shard if shard is not None else ""
      if mode == problem.DatasetSplit.TRAIN:
          path = os.path.join(data_dir, "librispeech")
          suffix = "train"
      elif mode in [
          problem.DatasetSplit.EVAL,
          tf_estimator.ModeKeys.PREDICT,
      ]:
          path = os.path.join(data_dir, "librispeech_clean")
          suffix = "dev"
      else:
          assert mode == problem.DatasetSplit.TEST
          path = os.path.join(data_dir, "librispeech_clean")
          suffix = "test"
  
      return "%s-%s%s*" % (path, suffix, shard_str)
  
imports: import os
  import tarfile
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import speech_recognition
  from tensor2tensor.utils import registry
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 5 for calling the LibrispeechTrainFullTestClean obj's underlying member method code with example usage: obj.filepattern(data_dir, mode, shard) and returns: unknown