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#!/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 | |
from funasr_detach.models.sanm.attention import MultiHeadedAttentionSANM | |
class MultiHeadedAttentionSANMwithMask(MultiHeadedAttentionSANM): | |
def __init__(self, *args, **kwargs): | |
super().__init__(*args, **kwargs) | |
def forward(self, x, mask, mask_shfit_chunk=None, mask_att_chunk_encoder=None): | |
q_h, k_h, v_h, v = self.forward_qkv(x) | |
fsmn_memory = self.forward_fsmn(v, mask[0], mask_shfit_chunk) | |
q_h = q_h * self.d_k ** (-0.5) | |
scores = torch.matmul(q_h, k_h.transpose(-2, -1)) | |
att_outs = self.forward_attention(v_h, scores, mask[1], mask_att_chunk_encoder) | |
return att_outs + fsmn_memory | |