class_docstr: Class for reading TFRecords and returning a dataset.
class_docstr_tok: ["Class","for","reading","TFRecords","and","returning","a","dataset","."]
docstr: RecordProvider constructor.
code: def __init__(
      self,
      file_pattern=None,
      example_secs=4,
      sample_rate=16000,
      frame_rate=250,
      centered=False,
  ):
      """RecordProvider constructor."""
      super().__init__(sample_rate, frame_rate)
      self._file_pattern = file_pattern or self.default_file_pattern
      self._audio_length = example_secs * sample_rate
      self._audio_16k_length = example_secs * CREPE_SAMPLE_RATE
      self._feature_length = self.get_feature_length(centered)
  
imports: import os
  from absl import logging
  from ddsp.spectral_ops import CREPE_FRAME_SIZE
  from ddsp.spectral_ops import CREPE_SAMPLE_RATE
  from ddsp.spectral_ops import get_framed_lengths
  import gin
  import tensorflow.compat.v2
  import tensorflow_datasets
label_desc: Use image node_id 1 to create a new TFRecordProvider object from inherited base classes: DataProvider with example: obj = TFRecordProvider(file_pattern, example_secs, sample_rate, frame_rate, centered)