| 767 | """ |
| 768 | |
| 769 | def __init__( |
| 770 | self, |
| 771 | hidden_size, |
| 772 | vocab_size, |
| 773 | max_sequence_length, |
| 774 | ): |
| 775 | super(QueryEmbedding, self).__init__() |
| 776 | |
| 777 | self.hidden_size = hidden_size |
| 778 | self.vocab_size = vocab_size |
| 779 | self.max_sequence_length = max_sequence_length |
| 780 | |
| 781 | # Top query position embedding (serial). |
| 782 | self.top_query_embeddings = torch.nn.Embedding(self.max_sequence_length, self.hidden_size) |
| 783 | self.top_query_embeddings = self.top_query_embeddings.half() |
| 784 | self._top_query_embeddings_key = 'top_query_embeddings' |
| 785 | |
| 786 | def forward(self, position_ids): |
| 787 | # Embeddings. |