(
self, source_hidden_states, target_input_ids, target_attention_mask=None, source_attention_mask=None
)
| 1375 | return self.forward_mini_train_dit(x, timesteps, context, fps=fps, padding_mask=padding_mask, **kwargs) |
| 1376 | |
| 1377 | def _preprocess_text_embeds( |
| 1378 | self, source_hidden_states, target_input_ids, target_attention_mask=None, source_attention_mask=None |
| 1379 | ): |
| 1380 | if target_input_ids is not None: |
| 1381 | context = self.llm_adapter( |
| 1382 | source_hidden_states, |
| 1383 | target_input_ids, |
| 1384 | target_attention_mask=target_attention_mask, |
| 1385 | source_attention_mask=source_attention_mask, |
| 1386 | ) |
| 1387 | context[~target_attention_mask.bool()] = 0 # zero out padding tokens |
| 1388 | return context |
| 1389 | else: |
| 1390 | return source_hidden_states |
| 1391 | |
| 1392 | |
| 1393 | # LLM Adapter: Bridges Qwen3 embeddings to T5-compatible space |
no outgoing calls
no test coverage detected