code: def load_batch_audio(files, sample_length=64000):
      """Load a batch of audio from either .wav files.
  
      Args:
        files: A list of filepaths to .wav files.
        sample_length: Maximum sample length
  
      Returns:
        batch: A padded array of audio [n_files, sample_length]
      """
      batch = []
      # Load the data
      for f in files:
          data = utils.load_audio(f, sample_length, sr=16000)
          length = data.shape[0]
          # Add padding if less than sample length
          if length < sample_length:
              padded = np.zeros([sample_length])
              padded[:length] = data
              batch.append(padded)
          else:
              batch.append(data)
      # Return as an numpy array
      batch = np.array(batch)
      return batch
  
file_path: magenta/magenta/models/nsynth/wavenet/fastgen.py
imports: from magenta.models.nsynth import utils
  from magenta.models.nsynth.wavenet.h512_bo16 import Config
  from magenta.models.nsynth.wavenet.h512_bo16 import FastGenerationConfig
  import numpy
  from scipy.io import wavfile
  import tensorflow.compat.v1
label_desc: Use image node_id 5 for calling a global function with example usage: load_batch_audio(files, sample_length) and returns: batch