(self, sequence_output, pooled_output)
| 676 | self.seq_relationship = nn.Linear(config.hidden_size, 2) |
| 677 | |
| 678 | def forward(self, sequence_output, pooled_output): |
| 679 | prediction_scores = self.predictions(sequence_output) |
| 680 | for p in self.seq_relationship.parameters(): |
| 681 | if p is None: |
| 682 | continue |
| 683 | pooled_output = pooled_output.type_as(p) |
| 684 | seq_relationship_score = self.seq_relationship(pooled_output) |
| 685 | return prediction_scores, seq_relationship_score |
| 686 | |
| 687 | |
| 688 | class PreTrainedBertModel(nn.Module): |
nothing calls this directly
no outgoing calls
no test coverage detected