IndexError：使用多值命令行参数时列表索引之外的范围

Question

我有两个代码：一个用于预处理音频文件，另一个用于生成MFCC。 MFCC代码具有3个多值命令行参数（帧长度，帧步长和FFT长度）。我将MFCC定义为：

def mfcc(audio,sample_rate,pre_emp):      
    for fl in args['frame_length']:
        for fs in args['frame_step']:
            for fft in args['fft_length']:
                audio = np.pad(audio,(Paddinggg(fl,fs,sample_rate),0),mode='reflect')
                audio = audio.astype('float32')
  #Normalization
                audio = tf.keras.utils.normalize(audio)
  #Preemphasis
                audio = Preemphasis(audio,pre_emp)
                
                stfts = tf.signal.stft(audio,fl,fs,fft,window_fn=tf.signal.hann_window)
                spectrograms = tf.abs(stfts)
                
                num_spectrogram_bins = stfts.shape[-1]
                lower_edge_hertz, upper_edge_hertz, num_mel_bins = 0.0, sample_rate/2.0, 32
                linear_to_mel_weight_matrix = tf.signal.linear_to_mel_weight_matrix(num_mel_bins, num_spectrogram_bins, sample_rate, lower_edge_hertz,upper_edge_hertz)
                mel_spectrograms = tf.tensordot(spectrograms, linear_to_mel_weight_matrix, 1)
                mel_spectrograms.set_shape(spectrograms.shape[:-1].concatenate(linear_to_mel_weight_matrix.shape[-1:]))
  
  # Compute a stabilized log to get log-magnitude mel-scale spectrograms.
                log_mel_spectrograms = tf.math.log(mel_spectrograms + 1e-6)
  
                return log_mel_spectrograms

用于预处理的代码使用上述函数，如下所示：

  X = []
  Y = []
  preemphasis = 0.985
  print("Feature Extraction Started")
  for i,class_list in enumerate(data_list): #datalist = all files, class list = folder name in datalist, sample = path to the audio file in that particular class list
      for j,samples in enumerate(class_list):    #samples are of the form classes_name/audio file
        if(samples.endswith('.wav')):
          sample_rate,audio = wavfile.read(os.path.join(C["dire"],samples))
          if(audio.size<sample_rate):
            audio = np.pad(audio,(sample_rate-audio.size,0),mode="constant")

          coeff = mfccwithpaddingandcmd.mfcc(audio,sample_rate,preemphasis) # 0.985 = preemphasis

          X.append(coeff)
          #print(X)
          if(samples.split('/')[0] in classes):
            Y.append(samples.split('/')[0])
          elif(samples.split('/')[0]=='_background_noise_'):
            Y.append('silence')
          
# #X= coefficient array and Y = name of the class


  A = np.zeros((len(X),X[0].shape[0],X[0][0].shape[0]),dtype='object')
  for i in range(0,len(X)):
    A[i] = np.array(X[i])      #Converting list X into array A
    # print(A.shape)

现在，当我尝试定义A时，我遇到了错误，

Traceback (most recent call last):

  File "C:\Users\Aarti\.spyder-py3\preprocessingwithpaddingandcmd.py", line 151, in <module>
    pp()

  File "C:\Users\Aarti\.spyder-py3\preprocessingwithpaddingandcmd.py", line 104, in pp
    A = np.zeros((len(X),X[0].shape[0],X[0][0].shape[0]),dtype='object')

IndexError: list index out of range

我怀疑这是因为多价值命令行参数。我正确吗？我如何解决这个问题，其中有多价命令行参数以及a的多个值？