typo

paddlespeech/audio/compliance/kaldi.py

@@ -174,8 +174,7 @@ def _get_window(waveform: Tensor,
             mode = 'replicate'
 
         offset_strided_input = paddle.nn.functional.pad(
-            strided_input.unsqueeze(0), (1, 0),
-            data_format='NCL',
+            strided_input.unsqueeze(0), (1, 0), data_format='NCL',
             mode=mode).squeeze(0)  # (m, window_size + 1)
         strided_input = strided_input - preemphasis_coefficient * offset_strided_input[:, :
                                                                                        -1]

paddlespeech/cli/cls/infer.py

@@ -160,8 +160,7 @@ class CLSExecutor(BaseExecutor):
             f_min=feat_conf['f_min'],
             f_max=feat_conf['f_max'],
             n_mels=feat_conf['n_mels'],
-            **pad_mode_kwarg,
-        )
+            **pad_mode_kwarg, )
         feats = feature_extractor(
             paddle.to_tensor(paddle.to_tensor(waveform).unsqueeze(0)))
         self._inputs['feats'] = paddle.transpose(feats, [0, 2, 1]).unsqueeze(

paddlespeech/t2s/exps/syn_utils.py

@@ -454,7 +454,9 @@ def get_voc_inference(
 
     # npu only support mode=constant right now
     # this code has been adapted to support 'paddlespeech.t2s.models.melgan.melgan.MelGANGenerator'
-    npu_pad_mode = {"mode": "constant"} if paddle.get_device().startswith('npu') else {}
+    npu_pad_mode = {
+        "mode": "constant"
+    } if paddle.get_device().startswith('npu') else {}
 
     if voc_name != 'wavernn':
         if npu_pad_mode: