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/paraformer/decoder.py | 33 +++++++++++++++++----------------
1 files changed, 17 insertions(+), 16 deletions(-)
diff --git a/funasr/models/paraformer/decoder.py b/funasr/models/paraformer/decoder.py
index 1df27e8..68018a0 100644
--- a/funasr/models/paraformer/decoder.py
+++ b/funasr/models/paraformer/decoder.py
@@ -1,25 +1,26 @@
-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 numpy as np
+from typing import List, Tuple
+from funasr.register import tables
from funasr.models.scama import utils as myutils
-from funasr.models.transformer.decoder import BaseTransformerDecoder
-
-from funasr.models.sanm.attention import MultiHeadedAttentionSANMDecoder, MultiHeadedAttentionCrossAtt
-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.transformer.decoder import DecoderLayer
-from funasr.models.transformer.attention import MultiHeadedAttention
+from funasr.models.transformer.layer_norm import LayerNorm
from funasr.models.transformer.embedding import PositionalEncoding
+from funasr.models.transformer.attention import MultiHeadedAttention
from funasr.models.transformer.utils.nets_utils import make_pad_mask
+from funasr.models.transformer.decoder import BaseTransformerDecoder
from funasr.models.transformer.positionwise_feed_forward import PositionwiseFeedForward
-from funasr.register import tables
+from funasr.models.sanm.positionwise_feed_forward import PositionwiseFeedForwardDecoderSANM
+from funasr.models.sanm.attention import MultiHeadedAttentionSANMDecoder, MultiHeadedAttentionCrossAtt
-class DecoderLayerSANM(nn.Module):
+
+class DecoderLayerSANM(torch.nn.Module):
"""Single decoder layer module.
Args:
@@ -62,12 +63,12 @@
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)
self.reserve_attn=False
self.attn_mat = []
--
Gitblit v1.9.1