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/decoder/contextual_decoder.py | 5 +++--
1 files changed, 3 insertions(+), 2 deletions(-)
diff --git a/funasr/models/decoder/contextual_decoder.py b/funasr/models/decoder/contextual_decoder.py
index 3b462e7..18d4861 100644
--- a/funasr/models/decoder/contextual_decoder.py
+++ b/funasr/models/decoder/contextual_decoder.py
@@ -102,7 +102,7 @@
class ContextualParaformerDecoder(ParaformerSANMDecoder):
"""
- author: Speech Lab, Alibaba Group, China
+ Author: Speech Lab of DAMO Academy, Alibaba Group
Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition
https://arxiv.org/abs/2006.01713
"""
@@ -246,6 +246,7 @@
ys_in_pad: torch.Tensor,
ys_in_lens: torch.Tensor,
contextual_info: torch.Tensor,
+ clas_scale: float = 1.0,
return_hidden: bool = False,
) -> Tuple[torch.Tensor, torch.Tensor]:
"""Forward decoder.
@@ -285,7 +286,7 @@
cx, tgt_mask, _, _, _ = self.bias_decoder(x_self_attn, tgt_mask, contextual_info, memory_mask=contextual_mask)
if self.bias_output is not None:
- x = torch.cat([x_src_attn, cx], dim=2)
+ x = torch.cat([x_src_attn, cx*clas_scale], dim=2)
x = self.bias_output(x.transpose(1, 2)).transpose(1, 2) # 2D -> D
x = x_self_attn + self.dropout(x)
--
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