(
self,
token_values: torch.Tensor,
attn_bias: AttnBias,
cache: list[LayerCache],
)
| 267 | |
| 268 | @torch.no_grad() |
| 269 | def forward_with_attn_bias( |
| 270 | self, |
| 271 | token_values: torch.Tensor, |
| 272 | attn_bias: AttnBias, |
| 273 | cache: list[LayerCache], |
| 274 | ) -> torch.Tensor: |
| 275 | h = self.tok_embeddings(token_values) |
| 276 | |
| 277 | for i, layer in enumerate(self.layers): |
| 278 | h = layer(h, cache[i], attn_bias) |
| 279 | |
| 280 | logits = self.output(self.norm(h)) |
| 281 | return logits.float() |
| 282 | |
| 283 | def forward( |
| 284 | self, |
no outgoing calls
no test coverage detected