code: def _load_audio(audio_path, sample_rate):
      """Load audio file."""
      logging.info("Loading '%s'.", audio_path)
      beam.metrics.Metrics.counter(
          "prepare-tfrecord", "load-audio"
      ).inc()
      audio = _load_audio_as_array(audio_path, sample_rate)
      if sample_rate != CREPE_SAMPLE_RATE:
          audio_16k = _load_audio_as_array(
              audio_path, CREPE_SAMPLE_RATE
          )
      else:
          audio_16k = audio
      return {"audio": audio, "audio_16k": audio_16k}
  
file_path: ddsp/ddsp/training/data_preparation/prepare_tfrecord_lib.py
imports: from absl import logging
  import apache_beam
  from ddsp import spectral_ops
  import numpy
  import pydub
  import tensorflow.compat.v2
label_desc: Use image node_id 2 for calling a global function with example usage: _load_audio(audio_path, sample_rate) and returns: dict