| 687 | """ |
| 688 | |
| 689 | def __init__( |
| 690 | self, |
| 691 | hidden_size, |
| 692 | vocab_size, |
| 693 | max_sequence_length, |
| 694 | ): |
| 695 | super(Embedding, self).__init__() |
| 696 | self.hidden_size = hidden_size |
| 697 | self.vocab_size = vocab_size |
| 698 | self.max_sequence_length = max_sequence_length |
| 699 | |
| 700 | # Word embeddings. |
| 701 | self.word_embeddings = torch.nn.Embedding(self.vocab_size, self.hidden_size) |
| 702 | self._word_embeddings_key = 'word_embeddings' |
| 703 | |
| 704 | # Position embedding. |
| 705 | self.position_embeddings = torch.nn.Embedding(self.max_sequence_length, self.hidden_size) |
| 706 | self.position_embeddings = self.position_embeddings.half() |
| 707 | self._position_embeddings_key = 'position_embeddings' |
| 708 | |
| 709 | def forward(self, input_ids, position_ids): |
| 710 | # Embeddings. |