34 lines
1.6 KiB
Markdown
34 lines
1.6 KiB
Markdown
# MODELING DOMAIN KNOWLEDGE BASE
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## OVERVIEW
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`opengait/modeling/` defines model contracts and algorithm implementations: `BaseModel`, loss aggregation, backbones, concrete model classes.
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## STRUCTURE
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```text
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opengait/modeling/
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├── base_model.py # canonical train/test lifecycle
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├── loss_aggregator.py # training_feat -> weighted summed loss
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├── modules.py # shared NN building blocks
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├── backbones/ # backbone registry + implementations
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├── losses/ # loss registry + implementations
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└── models/ # concrete methods (Baseline, ScoNet, DeepGaitV2, ...)
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```
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## WHERE TO LOOK
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| Task | Location | Notes |
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|------|----------|-------|
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| Add new model | `models/*.py` + `docs/4.how_to_create_your_model.md` | must inherit `BaseModel` |
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| Add new loss | `losses/*.py` | expose via dynamic registry |
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| Change training lifecycle | `base_model.py` | affects every model |
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| Debug feature/loss key mismatches | `loss_aggregator.py` | checks `training_feat` keys vs `loss_cfg.log_prefix` |
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## CONVENTIONS
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- `forward()` output contract is fixed dict with keys: `training_feat`, `visual_summary`, `inference_feat`.
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- `training_feat` subkeys must align with configured `loss_cfg[*].log_prefix`.
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- Backbones/losses/models are discovered dynamically via package `__init__.py`; filenames matter operationally.
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## ANTI-PATTERNS
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- Do not return arbitrary forward outputs; `LossAggregator` and evaluator assume fixed contract.
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- Do not put model classes outside `models/`; config lookup by `getattr(models, name)` depends on registry.
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- Do not ignore DDP loss wrapping (`get_ddp_module`) in loss construction.
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