From 97d648c255316ec1fff5d82e46749076faabdd2d Mon Sep 17 00:00:00 2001
From: shixian.shi <shixian.shi@alibaba-inc.com>
Date: 星期一, 15 一月 2024 15:41:25 +0800
Subject: [PATCH] code optimize, model update, scripts

---
 funasr/models/contextual_paraformer/decoder.py |   42 ++++++++++++++++++++++--------------------
 1 files changed, 22 insertions(+), 20 deletions(-)

diff --git a/funasr/models/contextual_paraformer/decoder.py b/funasr/models/contextual_paraformer/decoder.py
index 5ec2756..c872547 100644
--- a/funasr/models/contextual_paraformer/decoder.py
+++ b/funasr/models/contextual_paraformer/decoder.py
@@ -1,22 +1,24 @@
-from typing import List
-from typing import Tuple
-import logging
+#!/usr/bin/env python3
+# -*- encoding: utf-8 -*-
+# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
+#  MIT License  (https://opensource.org/licenses/MIT)
+
 import torch
-import torch.nn as nn
+import logging
 import numpy as np
-
-from funasr.models.scama import utils as myutils
-
-from funasr.models.sanm.attention import MultiHeadedAttentionSANMDecoder, MultiHeadedAttentionCrossAtt
-from funasr.models.transformer.embedding import PositionalEncoding
-from funasr.models.transformer.layer_norm import LayerNorm
-from funasr.models.sanm.positionwise_feed_forward import PositionwiseFeedForwardDecoderSANM
-from funasr.models.transformer.utils.repeat import repeat
-from funasr.models.paraformer.decoder import DecoderLayerSANM, ParaformerSANMDecoder
+from typing import Tuple
 
 from funasr.register import tables
+from funasr.models.scama import utils as myutils
+from funasr.models.transformer.utils.repeat import repeat
+from funasr.models.transformer.layer_norm import LayerNorm
+from funasr.models.transformer.embedding import PositionalEncoding
+from funasr.models.paraformer.decoder import DecoderLayerSANM, ParaformerSANMDecoder
+from funasr.models.sanm.positionwise_feed_forward import PositionwiseFeedForwardDecoderSANM
+from funasr.models.sanm.attention import MultiHeadedAttentionSANMDecoder, MultiHeadedAttentionCrossAtt
 
-class ContextualDecoderLayer(nn.Module):
+
+class ContextualDecoderLayer(torch.nn.Module):
     def __init__(
         self,
         size,
@@ -38,12 +40,12 @@
             self.norm2 = LayerNorm(size)
         if src_attn is not None:
             self.norm3 = LayerNorm(size)
-        self.dropout = nn.Dropout(dropout_rate)
+        self.dropout = torch.nn.Dropout(dropout_rate)
         self.normalize_before = normalize_before
         self.concat_after = concat_after
         if self.concat_after:
-            self.concat_linear1 = nn.Linear(size + size, size)
-            self.concat_linear2 = nn.Linear(size + size, size)
+            self.concat_linear1 = torch.nn.Linear(size + size, size)
+            self.concat_linear2 = torch.nn.Linear(size + size, size)
 
     def forward(self, tgt, tgt_mask, memory, memory_mask, cache=None,):
         # tgt = self.dropout(tgt)
@@ -73,7 +75,7 @@
         return x, tgt_mask, x_self_attn, x_src_attn
 
 
-class ContextualBiasDecoder(nn.Module):
+class ContextualBiasDecoder(torch.nn.Module):
     def __init__(
         self,
         size,
@@ -87,7 +89,7 @@
         self.src_attn = src_attn
         if src_attn is not None:
             self.norm3 = LayerNorm(size)
-        self.dropout = nn.Dropout(dropout_rate)
+        self.dropout = torch.nn.Dropout(dropout_rate)
         self.normalize_before = normalize_before
 
     def forward(self, tgt, tgt_mask, memory, memory_mask=None, cache=None):
@@ -183,7 +185,7 @@
                 concat_after,
             ),
         )
-        self.dropout = nn.Dropout(dropout_rate)
+        self.dropout = torch.nn.Dropout(dropout_rate)
         self.bias_decoder = ContextualBiasDecoder(
             size=attention_dim,
             src_attn=MultiHeadedAttentionCrossAtt(

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