code: def remove_padding(max_lengths, samples, controls=None):
      """Remove padding."""
      if not max_lengths:
          return samples, controls
      unpadded_samples = [
          sample.reshape(max_lengths + [-1]) for sample in samples
      ]
      unpadded_controls = None
      if controls is not None:
          unpadded_controls = [
              control.reshape(max_lengths + [-1])
              for control in controls
          ]
      return unpadded_samples, unpadded_controls
  
imports: import abc
  import random
  from magenta.models.music_vae import data
  from magenta.pipelines import performance_pipeline
  import note_seq
  from note_seq import chords_lib
  from note_seq import performance_lib
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling a global function with example usage: remove_padding(max_lengths, samples, controls) and returns: unpadded_samples,  unpadded_controls, samples,  controls