code: def compute_rms_energy(
      audio,
      sample_rate=16000,
      frame_rate=250,
      frame_size=512,
      padding="center",
  ):
      """Compute root mean squared energy of audio."""
      audio = tf_float32(audio)
      hop_size = sample_rate // frame_rate
      audio = pad(audio, frame_size, hop_size, padding=padding)
      audio_frames = tf.signal.frame(
          audio, frame_size, hop_size, pad_end=False
      )
      rms_energy = tf.reduce_mean(audio_frames**2.0, axis=-1) ** 0.5
      return rms_energy
  
imports: import crepe
  from ddsp import core
  from ddsp.core import safe_log
  from ddsp.core import tf_float32
  import gin
  import librosa
  import numpy
  import tensorflow.compat.v2
  import tensorflow_probability
label_desc: Use image node_id 10 for calling a global function with example usage: compute_rms_energy(audio, sample_rate, frame_rate, frame_size, padding) and returns: rms_energy