| | |
| | | # x = residual + self.dropout(self.src_attn(x, memory, memory_mask)) |
| | | |
| | | return x, tgt_mask, memory, memory_mask, cache |
| | | |
| | | def get_attn_mat(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 |
| | | |
| | | residual = x |
| | | x = self.norm3(x) |
| | | x_src_attn, attn_mat = self.src_attn(x, memory, memory_mask, ret_attn=True) |
| | | return attn_mat |
| | | |
| | | def forward_one_step(self, tgt, tgt_mask, memory, memory_mask=None, cache=None): |
| | | """Compute decoded features. |
| | |
| | | ys.unsqueeze(0), ys_mask, x.unsqueeze(0), cache=state |
| | | ) |
| | | return logp.squeeze(0), state |
| | | |
| | | def forward_asf2( |
| | | self, |
| | | hs_pad: torch.Tensor, |
| | | hlens: torch.Tensor, |
| | | ys_in_pad: torch.Tensor, |
| | | ys_in_lens: torch.Tensor, |
| | | ): |
| | | |
| | | tgt = ys_in_pad |
| | | tgt_mask = myutils.sequence_mask(ys_in_lens, device=tgt.device)[:, :, None] |
| | | |
| | | memory = hs_pad |
| | | memory_mask = myutils.sequence_mask(hlens, device=memory.device)[:, None, :] |
| | | |
| | | tgt, tgt_mask, memory, memory_mask, _ = self.decoders[0](tgt, tgt_mask, memory, memory_mask) |
| | | attn_mat = self.model.decoders[1].get_attn_mat(tgt, tgt_mask, memory, memory_mask) |
| | | return attn_mat |
| | | |
| | | def forward_asf6( |
| | | self, |
| | | hs_pad: torch.Tensor, |
| | | hlens: torch.Tensor, |
| | | ys_in_pad: torch.Tensor, |
| | | ys_in_lens: torch.Tensor, |
| | | ): |
| | | |
| | | tgt = ys_in_pad |
| | | tgt_mask = myutils.sequence_mask(ys_in_lens, device=tgt.device)[:, :, None] |
| | | |
| | | memory = hs_pad |
| | | memory_mask = myutils.sequence_mask(hlens, device=memory.device)[:, None, :] |
| | | |
| | | tgt, tgt_mask, memory, memory_mask, _ = self.decoders[0](tgt, tgt_mask, memory, memory_mask) |
| | | tgt, tgt_mask, memory, memory_mask, _ = self.decoders[1](tgt, tgt_mask, memory, memory_mask) |
| | | tgt, tgt_mask, memory, memory_mask, _ = self.decoders[2](tgt, tgt_mask, memory, memory_mask) |
| | | tgt, tgt_mask, memory, memory_mask, _ = self.decoders[3](tgt, tgt_mask, memory, memory_mask) |
| | | tgt, tgt_mask, memory, memory_mask, _ = self.decoders[4](tgt, tgt_mask, memory, memory_mask) |
| | | attn_mat = self.decoders[5].get_attn_mat(tgt, tgt_mask, memory, memory_mask) |
| | | return attn_mat |
| | | |
| | | def forward_chunk( |
| | | self, |