class_docstr: Compute Cepstrum features of every frame in speech, return a float tensor
  with size (num_frames, ceps_subband_num).
docstr: Caculate cepstrum of audio data.
  :param audio_data: the audio signal from which to compute spectrum.
                      Should be an (1, N) tensor.
  :param sample_rate: [option]the samplerate of the signal we working with,
                      default is 16kHz.
  :return:A float tensor of size (num_frames, ceps_subband_num) containing
          normalized cepstrum (tag_ceps_mean_norm = True) or cepstrum
          (tag_ceps_mean_norm = False) of every frame in speech.
docstr_tok: ["Caculate","cepstrum","of","audio","data",".",":","param","audio_data",":","the","audio","signal","from","which","to","compute","spectrum",".","Should","be","an","(","1",",","N",")","tensor",".",":","param","sample_rate",":","[","option","]","the","samplerate","of","the","signal","we","working","with",",","default","is","16kHz",".",":","return",":","A","float","tensor","of","size","(","num_frames",",","ceps_subband_num",")","containing","normalized","cepstrum","(","tag_ceps_mean_norm","=","True",")","or","cepstrum","(","tag_ceps_mean_norm","=","False",")","of","every","frame","in","speech","."]
code: def call(self, audio_data, sample_rate=None):
      """
      Caculate cepstrum of audio data.
      :param audio_data: the audio signal from which to compute spectrum.
                          Should be an (1, N) tensor.
      :param sample_rate: [option]the samplerate of the signal we working with,
                          default is 16kHz.
      :return:A float tensor of size (num_frames, ceps_subband_num) containing
              normalized cepstrum (tag_ceps_mean_norm = True) or cepstrum
              (tag_ceps_mean_norm = False) of every frame in speech.
      """
  
      p = self.config
  
      with tf.name_scope("cepstrum"):
          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]):
              sample_rate = tf.cast(sample_rate, dtype=float)
              cepstrum = py_x_ops.cepstrum(
                  audio_data,
                  sample_rate,
                  window_length=p.window_length,
                  frame_length=p.frame_length,
                  ceps_subband_num=p.ceps_subband_num,
                  tag_ceps_mean_norm=p.tag_ceps_mean_norm,
              )
  
              return cepstrum
  
file_path: delta/delta/data/frontend/cepstrum.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
label_desc: Use image node_id 3 for calling the Cepstrum obj's underlying member method code with example usage: obj.call(audio_data, sample_rate) and returns: cepstrum