code: def construct_pipeline(hparams, pipeline):
      """Construct an audio transform pipeline from hyperparameters.
  
      Args:
        hparams: A tf.contrib.training.HParams object specifying hyperparameters to
            use for audio transformation. These hyperparameters affect the min and
            max values for audio transform parameters.
        pipeline: A list of pipeline stages, each specified as a tuple of stage
            name (SoX method) and a dictionary of parameters.
  
      Returns:
        The resulting pipeline, a list of AudioTransformStage objects.
      """
      return [
          AudioTransformStage(
              name=stage_name,
              params=[
                  AudioTransformParameter(
                      param_name,
                      getattr(
                          hparams,
                          "audio_transform_min_%s_%s"
                          % (stage_name, param_name),
                      ),
                      getattr(
                          hparams,
                          "audio_transform_max_%s_%s"
                          % (stage_name, param_name),
                      ),
                      scale,
                  )
                  for param_name, (_, _, scale) in params_dict.items()
              ],
          )
          for stage_name, params_dict in pipeline
      ]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import random
  import subprocess
  import tempfile
  from magenta.contrib import training
  import sox
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling a global function with example usage: construct_pipeline(hparams, pipeline) and returns: unknown