| """ |
| CODI + Direct Soft Matching (Ablation: No Prototypes) |
| |
| Inherits from CODI_CT and replaces PMPSLatentSupervisor with |
| DirectMatchSupervisor. The forward() method is fully reused — only |
| the pmps_module is swapped at init time. |
| |
| Usage: |
| from src.model_direct_match import CODI_DirectMatch |
| model = CODI_DirectMatch(model_args, training_args, lora_config) |
| """ |
|
|
| from .model import CODI_CT |
| from .direct_match_loss import DirectMatchSupervisor |
|
|
|
|
| class CODI_DirectMatch(CODI_CT): |
| """CODI with direct soft matching (no prototypes). |
| |
| Ablation variant: replaces the prototype-mediated PMPS module with |
| DirectMatchSupervisor, which computes soft many-to-many matching |
| directly in the projected embedding space via cosine similarity. |
| |
| All other components (base model, LoRA, projector, PSA, diversity |
| loss, distillation loss, CE losses) remain identical. |
| """ |
|
|
| def __init__(self, model_args, training_args, lora_config): |
| super().__init__(model_args, training_args, lora_config) |
|
|
| if self.pmps_loss_factor > 0: |
| del self.pmps_module |
| self.pmps_module = DirectMatchSupervisor( |
| hidden_dim=self.dim, |
| feat_dim=training_args.pmps_feat_dim, |
| hidden_mlp=training_args.pmps_hidden_mlp, |
| match_temperature=training_args.pmps_match_temperature, |
| use_projector=training_args.pmps_use_projector, |
| position_bias_strength=training_args.pmps_position_bias_max, |
| ) |
|
|
