code: def audio_summary(audio, step, sample_rate=16000, name="audio"):
      """Update metrics dictionary given a batch of audio."""
      # Ensure there is a single channel dimension.
      batch_size = int(audio.shape[0])
      if len(audio.shape) == 2:
          audio = audio[:, :, tf.newaxis]
      tf.summary.audio(
          name,
          audio,
          sample_rate,
          step,
          max_outputs=batch_size,
          encoding="wav",
      )
  
imports: import io
  import ddsp
  from ddsp.core import tf_float32
  from ddsp.training.plotting import pianoroll_plot_setup
  import matplotlib.patches
  import matplotlib.pyplot
  from matplotlib.ticker import MaxNLocator
  import note_seq
  from note_seq import sequences_lib
  import numpy
  import tensorflow.compat.v2
label_desc: Use image node_id 6 for calling a global function with example usage: audio_summary(audio, step, sample_rate, name) without return types