From 8d519b9dc66e0df35c15110ef23a26d07bc7f7c3 Mon Sep 17 00:00:00 2001
From: shixian.shi <shixian.shi@alibaba-inc.com>
Date: 星期二, 27 六月 2023 19:48:51 +0800
Subject: [PATCH] update

---
 funasr/models/e2e_asr_contextual_paraformer.py |    8 ++++----
 1 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/funasr/models/e2e_asr_contextual_paraformer.py b/funasr/models/e2e_asr_contextual_paraformer.py
index dc820db..b8ae951 100644
--- a/funasr/models/e2e_asr_contextual_paraformer.py
+++ b/funasr/models/e2e_asr_contextual_paraformer.py
@@ -43,9 +43,7 @@
         frontend: Optional[AbsFrontend],
         specaug: Optional[AbsSpecAug],
         normalize: Optional[AbsNormalize],
-        preencoder: Optional[AbsPreEncoder],
         encoder: AbsEncoder,
-        postencoder: Optional[AbsPostEncoder],
         decoder: AbsDecoder,
         ctc: CTC,
         ctc_weight: float = 0.5,
@@ -72,6 +70,8 @@
         crit_attn_weight: float = 0.0,
         crit_attn_smooth: float = 0.0,
         bias_encoder_dropout_rate: float = 0.0,
+        preencoder: Optional[AbsPreEncoder] = None,
+        postencoder: Optional[AbsPostEncoder] = None,
     ):
         assert check_argument_types()
         assert 0.0 <= ctc_weight <= 1.0, ctc_weight
@@ -343,7 +343,7 @@
             input_mask_expand_dim, 0)
         return sematic_embeds * tgt_mask, decoder_out * tgt_mask
 
-    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:
             hw_list = [torch.Tensor([1]).long().to(encoder_out.device)]  # empty hotword list
             hw_list_pad = pad_list(hw_list, 0)
@@ -365,7 +365,7 @@
             hw_embed = h_n.repeat(encoder_out.shape[0], 1, 1)
         
         decoder_outs = self.decoder(
-            encoder_out, encoder_out_lens, sematic_embeds, ys_pad_lens, contextual_info=hw_embed
+            encoder_out, encoder_out_lens, sematic_embeds, ys_pad_lens, contextual_info=hw_embed, clas_scale=clas_scale
         )
         decoder_out = decoder_outs[0]
         decoder_out = torch.log_softmax(decoder_out, dim=-1)

--
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