class_docstr: Compute mfcc features of every frame in speech, return a float tensor
  with size (num_channels, num_frames, num_frequencies).
docstr: Caculate mfcc features of audio data.
  :param audio_data: the audio signal from which to compute spectrum.
                     Should be an (1, N) tensor.
  :param sample_rate: the samplerate of the signal we working with.
  :return: A float tensor of size (num_channels, num_frames, num_frequencies)
          containing mfcc features of every frame in speech.
code: def call(self, audio_data, sample_rate=None):
      """
      Caculate mfcc features of audio data.
      :param audio_data: the audio signal from which to compute spectrum.
                         Should be an (1, N) tensor.
      :param sample_rate: the samplerate of the signal we working with.
      :return: A float tensor of size (num_channels, num_frames, num_frequencies)
              containing mfcc features of every frame in speech.
      """
      p = self.config
      with tf.name_scope("mfcc"):
          if sample_rate == None:
              sample_rate = tf.constant(p.sample_rate, dtype=tf.int32)
  
          assert_op = tf.assert_equal(
              tf.constant(p.sample_rate),
              tf.cast(sample_rate, dtype=tf.int32),
          )
          with tf.control_dependencies([assert_op]):
              fbank_feats = self.fbank(audio_data, sample_rate)
              sample_rate = tf.cast(sample_rate, dtype=tf.int32)
              shape = tf.shape(fbank_feats)
              nframe = shape[0]
              nfbank = shape[1]
              fbank_feats = tf.reshape(fbank_feats, (1, nframe, nfbank))
              framepow_feats = self.framepow(audio_data, sample_rate)
              mfcc = py_x_ops.mfcc(
                  fbank_feats,
                  framepow_feats,
                  sample_rate,
                  use_energy=p.use_energy,
                  cepstral_lifter=p.cepstral_lifter,
                  coefficient_count=p.coefficient_count,
              )
              return mfcc
  
file_path: delta/delta/data/frontend/mfcc.py
imports: import delta.compat
  from core.ops import py_x_ops
  from delta.utils.hparam import HParams
  from delta.data.frontend.base_frontend import BaseFrontend
  from delta.data.frontend.fbank import Fbank
  from delta.data.frontend.framepow import Framepow
  import copy
label_desc: Use image node_id 3 for calling the Mfcc obj's underlying member method code with example usage: obj.call(audio_data, sample_rate) and returns: mfcc