FunASR/funasr/export/models/modules/decoder_layer.py
2023-02-27 16:55:06 +08:00

71 lines
1.9 KiB
Python

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import torch
from torch import nn
class DecoderLayerSANM(nn.Module):
def __init__(
self,
model
):
super().__init__()
self.self_attn = model.self_attn
self.src_attn = model.src_attn
self.feed_forward = model.feed_forward
self.norm1 = model.norm1
self.norm2 = model.norm2 if hasattr(model, 'norm2') else None
self.norm3 = model.norm3 if hasattr(model, 'norm3') else None
self.size = model.size
def forward(self, tgt, tgt_mask, memory, memory_mask=None, cache=None):
residual = tgt
tgt = self.norm1(tgt)
tgt = self.feed_forward(tgt)
x = tgt
if self.self_attn is not None:
tgt = self.norm2(tgt)
x, cache = self.self_attn(tgt, tgt_mask, cache=cache)
x = residual + x
if self.src_attn is not None:
residual = x
x = self.norm3(x)
x = residual + self.src_attn(x, memory, memory_mask)
return x, tgt_mask, memory, memory_mask, cache
class DecoderLayer(nn.Module):
def __init__(self, model):
super().__init__()
self.self_attn = model.self_attn
self.src_attn = model.src_attn
self.feed_forward = model.feed_forward
self.norm1 = model.norm1
self.norm2 = model.norm2
self.norm3 = model.norm3
def forward(self, tgt, tgt_mask, memory, memory_mask, cache=None):
residual = tgt
tgt_q = tgt
tgt_q_mask = tgt_mask
x = residual + self.self_attn(tgt_q, tgt, tgt, tgt_q_mask)
residual = x
x = self.norm2(x)
x = residual + self.src_attn(x, memory, memory, memory_mask)
residual = x
x = self.norm3(x)
x = residual + self.feed_forward(x)
return x, tgt_mask, memory, memory_mask