(self,
hidden_states: torch.Tensor,
attention_mask: Optional[torch.Tensor] = None,
position_ids: Optional[torch.LongTensor] = None)
| 14 | self.block_list.append(block) |
| 15 | |
| 16 | def forward(self, |
| 17 | hidden_states: torch.Tensor, |
| 18 | attention_mask: Optional[torch.Tensor] = None, |
| 19 | position_ids: Optional[torch.LongTensor] = None): |
| 20 | for block in self.block_list: |
| 21 | hidden_states = block(hidden_states, attention_mask=attention_mask,position_ids=position_ids)[0] |
| 22 | return (hidden_states, ) |
| 23 | |
| 24 | |
| 25 | def set_weight_parameters(model, requires_grad): |
nothing calls this directly
no outgoing calls
no test coverage detected