fix bug

paddlespeech/s2t/exps/u2/bin/quant.py

@@ -18,6 +18,7 @@ from pathlib import Path
 
 import paddle
 import soundfile
+from paddleslim import PTQ
 from yacs.config import CfgNode
 
 from paddlespeech.audio.transform.transformation import Transformation
@@ -26,7 +27,6 @@ from paddlespeech.s2t.models.u2 import U2Model
 from paddlespeech.s2t.training.cli import default_argument_parser
 from paddlespeech.s2t.utils.log import Log
 from paddlespeech.s2t.utils.utility import UpdateConfig
-from paddleslim import PTQ
 logger = Log(__name__).getlog()
 
 
@@ -90,7 +90,7 @@ class U2Infer():
                 ctc_weight=decode_config.ctc_weight,
                 decoding_chunk_size=decode_config.decoding_chunk_size,
                 num_decoding_left_chunks=decode_config.num_decoding_left_chunks,
-                simulate_streaming=decode_config.simulate_streaming
+                simulate_streaming=decode_config.simulate_streaming,
                 reverse_weight=decode_config.reverse_weight)
             rsl = result_transcripts[0][0]
             utt = Path(self.audio_file).name
@@ -161,7 +161,11 @@ class U2Infer():
 
             # jit save
             logger.info(f"export save: {self.args.export_path}")
-            config = {'is_static': True, 'combine_params':True, 'skip_forward':True}
+            config = {
+                'is_static': True,
+                'combine_params': True,
+                'skip_forward': True
+            }
             self.ptq.save_quantized_model(self.model, self.args.export_path)
             # paddle.jit.save(
             #     self.model,
@@ -170,7 +174,6 @@ class U2Infer():
             #     skip_forward=True)
 
 
-
 def check(audio_file):
     if not os.path.isfile(audio_file):
         print("Please input the right audio file path")
@@ -201,7 +204,10 @@ if __name__ == "__main__":
     parser.add_argument(
         "--audio_file", type=str, help="path of the input audio file")
     parser.add_argument(
-        "--export_path", type=str, default='export', help="path of the input audio file")
+        "--export_path",
+        type=str,
+        default='export',
+        help="path of the input audio file")
     args = parser.parse_args()
 
     config = CfgNode(new_allowed=True)

paddlespeech/s2t/models/u2/u2.py

@@ -131,7 +131,8 @@ class U2BaseModel(ASRInterface, nn.Layer):
         if self.ctc_weight != 1.0:
             start = time.time()
             loss_att, acc_att = self._calc_att_loss(encoder_out, encoder_mask,
-                                                    text, text_lengths, self.reverse_weight)
+                                                    text, text_lengths,
+                                                    self.reverse_weight)
             decoder_time = time.time() - start
             #logger.debug(f"decoder time: {decoder_time}")
 
@@ -152,8 +153,7 @@ class U2BaseModel(ASRInterface, nn.Layer):
             loss = self.ctc_weight * loss_ctc + (1 - self.ctc_weight) * loss_att
         return loss, loss_att, loss_ctc
 
-    def _calc_att_loss(
-            self,
+    def _calc_att_loss(self,
                        encoder_out: paddle.Tensor,
                        encoder_mask: paddle.Tensor,
                        ys_pad: paddle.Tensor,
@@ -188,8 +188,7 @@ class U2BaseModel(ASRInterface, nn.Layer):
         r_loss_att = paddle.to_tensor(0.0)
         if reverse_weight > 0.0:
             r_loss_att = self.criterion_att(r_decoder_out, r_ys_out_pad)
-        loss_att = loss_att * (1 - reverse_weight
-                               ) + r_loss_att * reverse_weight
+        loss_att = loss_att * (1 - reverse_weight) + r_loss_att * reverse_weight
         acc_att = th_accuracy(
             decoder_out.view(-1, self.vocab_size),
             ys_out_pad,
@@ -599,8 +598,7 @@ class U2BaseModel(ASRInterface, nn.Layer):
                     f"hyp {i} len {len(hyp[0])} r2l score: {r_score} ctc_score: {hyp[1]} reverse_weight: {reverse_weight}"
                 )
 
-                score = score * (1 - reverse_weight
-                                 ) + r_score * reverse_weight
+                score = score * (1 - reverse_weight) + r_score * reverse_weight
             # add ctc score (which in ln domain)
             score += hyp[1] * ctc_weight
             if score > best_score:

paddlespeech/server/engine/asr/online/python/asr_engine.py

@@ -22,7 +22,6 @@ from numpy import float32
 from yacs.config import CfgNode
 
 from paddlespeech.audio.transform.transformation import Transformation
-from paddlespeech.audio.utils.tensor_utils import st_reverse_pad_list
 from paddlespeech.cli.asr.infer import ASRExecutor
 from paddlespeech.cli.log import logger
 from paddlespeech.resource import CommonTaskResource