mirror of
https://github.com/modelscope/FunASR
synced 2025-09-15 14:48:36 +08:00
92 lines
2.3 KiB
Python
92 lines
2.3 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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import torch
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from torch import nn
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class EncoderLayerSANM(nn.Module):
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def __init__(
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self,
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model,
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):
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"""Construct an EncoderLayer object."""
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super().__init__()
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self.self_attn = model.self_attn
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self.feed_forward = model.feed_forward
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self.norm1 = model.norm1
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self.norm2 = model.norm2
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self.in_size = model.in_size
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self.size = model.size
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def forward(self, x, mask):
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residual = x
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x = self.norm1(x)
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x = self.self_attn(x, mask)
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if self.in_size == self.size:
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x = x + residual
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residual = x
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x = self.norm2(x)
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x = self.feed_forward(x)
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x = x + residual
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return x, mask
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class EncoderLayerConformer(nn.Module):
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def __init__(
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self,
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model,
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):
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"""Construct an EncoderLayer object."""
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super().__init__()
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self.self_attn = model.self_attn
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self.feed_forward = model.feed_forward
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self.feed_forward_macaron = model.feed_forward_macaron
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self.conv_module = model.conv_module
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self.norm_ff = model.norm_ff
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self.norm_mha = model.norm_mha
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self.norm_ff_macaron = model.norm_ff_macaron
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self.norm_conv = model.norm_conv
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self.norm_final = model.norm_final
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self.size = model.size
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def forward(self, x, mask):
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if isinstance(x, tuple):
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x, pos_emb = x[0], x[1]
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else:
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x, pos_emb = x, None
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if self.feed_forward_macaron is not None:
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residual = x
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x = self.norm_ff_macaron(x)
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x = residual + self.feed_forward_macaron(x) * 0.5
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residual = x
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x = self.norm_mha(x)
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x_q = x
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if pos_emb is not None:
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x_att = self.self_attn(x_q, x, x, pos_emb, mask)
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else:
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x_att = self.self_attn(x_q, x, x, mask)
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x = residual + x_att
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if self.conv_module is not None:
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residual = x
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x = self.norm_conv(x)
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x = residual + self.conv_module(x)
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residual = x
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x = self.norm_ff(x)
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x = residual + self.feed_forward(x) * 0.5
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x = self.norm_final(x)
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if pos_emb is not None:
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return (x, pos_emb), mask
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return x, mask
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