code: def compute_audio_features(audio, frame_rate=250):
      """Compute features from audio."""
      audio_feats = {"audio": audio}
      audio = squeeze(audio)
  
      # Requires 16kHz for CREPE.
      sample_rate = ddsp.spectral_ops.CREPE_SAMPLE_RATE
      audio_feats["loudness_db"] = ddsp.spectral_ops.compute_loudness(
          audio, sample_rate, frame_rate
      )
  
      (
          audio_feats["f0_hz"],
          audio_feats["f0_confidence"],
      ) = ddsp.spectral_ops.compute_f0(audio, frame_rate)
  
      return audio_feats
  
imports: import dataclasses
  from absl import logging
  import ddsp
  import librosa
  import mir_eval
  import note_seq
  from note_seq import sequences_lib
  import numpy
  import tensorflow.compat.v2
label_desc: Use image node_id 4 for calling a global function with example usage: compute_audio_features(audio, frame_rate) and returns: audio_feats