(
self,
hidden_size,
num_layers,
num_attention_heads,
padded_vocab_size,
max_position_embeddings,
)
| 833 | """ |
| 834 | |
| 835 | def __init__( |
| 836 | self, |
| 837 | hidden_size, |
| 838 | num_layers, |
| 839 | num_attention_heads, |
| 840 | padded_vocab_size, |
| 841 | max_position_embeddings, |
| 842 | ): |
| 843 | super(TransformerLanguageModel, self).__init__() |
| 844 | self.hidden_size = hidden_size |
| 845 | self.num_layers = num_layers |
| 846 | self.num_attention_heads = num_attention_heads |
| 847 | self.padded_vocab_size = padded_vocab_size |
| 848 | self.max_position_embeddings = max_position_embeddings |
| 849 | |
| 850 | # Embeddings |
| 851 | self.embedding = Embedding(self.hidden_size, |
| 852 | self.padded_vocab_size, |
| 853 | self.max_position_embeddings) |
| 854 | self._embedding_key = 'embedding' |
| 855 | |
| 856 | # Query embeddings |
| 857 | self.topQueryEmbedding = QueryEmbedding(self.hidden_size, |
| 858 | self.padded_vocab_size, |
| 859 | self.max_position_embeddings) |
| 860 | self._topQueryEmbedding_key = 'topQueryEmbedding' |
| 861 | |
| 862 | # Transformer |
| 863 | self.transformer = Transformer(self.hidden_size, |
| 864 | self.num_attention_heads, |
| 865 | self.num_layers) |
| 866 | self._transformer_key = 'transformer' |
| 867 | |
| 868 | def forward( |
| 869 | self, |
nothing calls this directly
no test coverage detected