| | |
| | | assert False, "Only support samn encode." |
| | | # self.encoder = model.encoder |
| | | self.decoder = model.decoder |
| | | self.model_name = model_name |
| | | |
| | | |
| | | |
| | |
| | | """ |
| | | x = self.embed(input) |
| | | # mask = self._target_mask(input) |
| | | h, _, _ = self.encoder(x, text_lengths, vad_indexes) |
| | | h, _ = self.encoder(x, text_lengths, vad_indexes) |
| | | y = self.decoder(h) |
| | | return y |
| | | |
| | |
| | | length = 120 |
| | | text_indexes = torch.randint(0, self.embed.num_embeddings, (1, length)) |
| | | text_lengths = torch.tensor([length], dtype=torch.int32) |
| | | vad_mask = torch.ones(length, length)[None, None, :, :] |
| | | vad_mask = torch.ones(length, length, dtype=torch.float32)[None, None, :, :] |
| | | return (text_indexes, text_lengths, vad_mask) |
| | | |
| | | def get_input_names(self): |