From 33d3d2084403fd34b79c835d2f2fe04f6cd8f738 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期三, 13 九月 2023 09:33:54 +0800
Subject: [PATCH] Merge branch 'main' of github.com:alibaba-damo-academy/FunASR add

---
 funasr/models/e2e_asr_paraformer.py |   10 ++--------
 1 files changed, 2 insertions(+), 8 deletions(-)

diff --git a/funasr/models/e2e_asr_paraformer.py b/funasr/models/e2e_asr_paraformer.py
index fcd6503..e157454 100644
--- a/funasr/models/e2e_asr_paraformer.py
+++ b/funasr/models/e2e_asr_paraformer.py
@@ -10,7 +10,6 @@
 import torch
 import random
 import numpy as np
-from typeguard import check_argument_types
 
 from funasr.layers.abs_normalize import AbsNormalize
 from funasr.losses.label_smoothing_loss import (
@@ -80,7 +79,6 @@
             postencoder: Optional[AbsPostEncoder] = None,
             use_1st_decoder_loss: bool = False,
     ):
-        assert check_argument_types()
         assert 0.0 <= ctc_weight <= 1.0, ctc_weight
         assert 0.0 <= interctc_weight < 1.0, interctc_weight
 
@@ -242,7 +240,7 @@
             loss = self.ctc_weight * loss_ctc + (1 - self.ctc_weight) * loss_att + loss_pre * self.predictor_weight
 
         if self.use_1st_decoder_loss and pre_loss_att is not None:
-            loss = loss + pre_loss_att
+            loss = loss + (1 - self.ctc_weight) * pre_loss_att
 
         # Collect Attn branch stats
         stats["loss_att"] = loss_att.detach() if loss_att is not None else None
@@ -645,7 +643,6 @@
             postencoder: Optional[AbsPostEncoder] = None,
             use_1st_decoder_loss: bool = False,
     ):
-        assert check_argument_types()
         assert 0.0 <= ctc_weight <= 1.0, ctc_weight
         assert 0.0 <= interctc_weight < 1.0, interctc_weight
 
@@ -1255,7 +1252,6 @@
             preencoder: Optional[AbsPreEncoder] = None,
             postencoder: Optional[AbsPostEncoder] = None,
     ):
-        assert check_argument_types()
         assert 0.0 <= ctc_weight <= 1.0, ctc_weight
         assert 0.0 <= interctc_weight < 1.0, interctc_weight
 
@@ -1528,7 +1524,6 @@
             preencoder: Optional[AbsPreEncoder] = None,
             postencoder: Optional[AbsPostEncoder] = None,
     ):
-        assert check_argument_types()
         assert 0.0 <= ctc_weight <= 1.0, ctc_weight
         assert 0.0 <= interctc_weight < 1.0, interctc_weight
 
@@ -1806,7 +1801,6 @@
             preencoder: Optional[AbsPreEncoder] = None,
             postencoder: Optional[AbsPostEncoder] = None,
     ):
-        assert check_argument_types()
         assert 0.0 <= ctc_weight <= 1.0, ctc_weight
         assert 0.0 <= interctc_weight < 1.0, interctc_weight
 
@@ -2113,7 +2107,7 @@
 
         return loss_att, acc_att, cer_att, wer_att, loss_pre
 
-    def cal_decoder_with_predictor(self, encoder_out, encoder_out_lens, sematic_embeds, ys_pad_lens, hw_list=None):
+    def cal_decoder_with_predictor(self, encoder_out, encoder_out_lens, sematic_embeds, ys_pad_lens, hw_list=None, clas_scale=1.0):
         if hw_list is None:
             # default hotword list
             hw_list = [torch.Tensor([self.sos]).long().to(encoder_out.device)]  # empty hotword list

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