code: def __init__(
      self,
      device,
      batch_size,
      iterator,
      axis=0,
      dct_type=2,
      lifter=1.0,
      n_mfcc=20,
      norm=None,
      num_threads=1,
      device_id=0,
      func=mfcc_func,
  ):
      super(MFCCPythonPipeline, self).__init__(
          batch_size,
          num_threads,
          device_id,
          seed=12345,
          exec_async=False,
          exec_pipelined=False,
      )
      self.device = "cpu"
      self.iterator = iterator
      self.inputs = ops.ExternalSource()
  
      function = partial(func, axis, dct_type, lifter, n_mfcc, norm)
      self.mfcc = ops.PythonFunction(function=function)
  
imports: from nvidia.dali.pipeline import Pipeline
  import nvidia.dali.ops
  import numpy
  from functools import partial
  from test_utils import compare_pipelines
  from test_utils import RandomDataIterator
  import librosa
  from nose_utils import assert_raises
label_desc: Use image node_id 1 to create a new MFCCPythonPipeline object from inherited base classes: Pipeline with example: obj = MFCCPythonPipeline(device, batch_size, iterator, axis, dct_type, lifter, n_mfcc, norm, num_threads, device_id, func)