simplify feature pipeline graph

paddlespeech/audio/compliance/kaldi.py

@@ -357,10 +357,13 @@ def _get_mel_banks(num_bins: int,
         ('Bad values in options: vtln-low {} and vtln-high {}, versus '
          'low-freq {} and high-freq {}'.format(vtln_low, vtln_high, low_freq, high_freq))
 
-    bin = paddle.arange(num_bins).unsqueeze(1)
+    bin = paddle.arange(num_bins, dtype=paddle.float32).unsqueeze(1)
+    # left_mel = mel_low_freq + bin * mel_freq_delta  # (num_bins, 1)
+    # center_mel = mel_low_freq + (bin + 1.0) * mel_freq_delta  # (num_bins, 1)
+    # right_mel = mel_low_freq + (bin + 2.0) * mel_freq_delta  # (num_bins, 1)
     left_mel = mel_low_freq + bin * mel_freq_delta  # (num_bins, 1)
-    center_mel = mel_low_freq + (bin + 1.0) * mel_freq_delta  # (num_bins, 1)
+    center_mel = left_mel + mel_freq_delta
-    right_mel = mel_low_freq + (bin + 2.0) * mel_freq_delta  # (num_bins, 1)
+    right_mel = center_mel + mel_freq_delta
 
     if vtln_warp_factor != 1.0:
         left_mel = _vtln_warp_mel_freq(vtln_low, vtln_high, low_freq, high_freq,
@@ -373,7 +376,7 @@ def _get_mel_banks(num_bins: int,
 
     center_freqs = _inverse_mel_scale(center_mel)  # (num_bins)
     # (1, num_fft_bins)
-    mel = _mel_scale(fft_bin_width * paddle.arange(num_fft_bins)).unsqueeze(0)
+    mel = _mel_scale(fft_bin_width * paddle.arange(num_fft_bins, dtype=paddle.float32)).unsqueeze(0)
 
     # (num_bins, num_fft_bins)
     up_slope = (mel - left_mel) / (center_mel - left_mel)
@@ -472,7 +475,8 @@ def fbank(waveform: Tensor,
     # (n_mels, padded_window_size // 2)
     mel_energies, _ = _get_mel_banks(n_mels, padded_window_size, sr, low_freq,
                                      high_freq, vtln_low, vtln_high, vtln_warp)
-    mel_energies = mel_energies.astype(dtype)
+    # mel_energies = mel_energies.astype(dtype)
+    assert mel_energies.dtype == dtype
 
     # (n_mels, padded_window_size // 2 + 1)
     mel_energies = paddle.nn.functional.pad(