| --- |
| license: other |
| tags: |
| - trajectory-prediction |
| - diffusion |
| - flow-matching |
| --- |
| |
| # SRA — Spatial Reasoning Adapter (code) |
|
|
| Code for running **SRA**, a modular future-interaction graph that plugs into three stochastic |
| trajectory predictors — **MID** (DDPM), **LED** (leapfrog-DDPM) and **MoFlow** (flow matching) — |
| on **NBA**, **Soccer** and **Football**. |
|
|
| ## 👉 Start here: [`SETUP.md`](SETUP.md) — download, install, run |
|
|
| It covers the required directory layout, environment setup, the exact training command for each |
| host × dataset, the E2 ablation settings, environment-variable switches, the adapter contract, |
| and known gotchas. |
|
|
| ## Documents |
|
|
| - [`SETUP.md`](SETUP.md) — end-to-end setup from scratch (env, data, paths, first run) |
| - [`RUNNING.md`](RUNNING.md) — how to run every host × dataset |
| - [`GAMEFORMER_SRA.md`](GAMEFORMER_SRA.md) — GameFormer+SRA negative result (does SRA generalize to feedforward models?) |
| - [`sample_data/README.md`](sample_data/README.md) — bundled 100-scene NBA smoke-test subset |
|
|
| ## Contents |
|
|
| ``` |
| MoFlow/ flow-matching host + the SRA graph module + E4 baseline modules |
| MID/ DDPM host |
| LED/ leapfrog-DDPM host |
| ``` |
|
|
| **Important:** `MID/` and `LED/` import the SRA graph from a *sibling* `MoFlow/` directory at |
| runtime — keep the three folders side by side. See §0 of `RUNNING.md`. |
|
|
| ## Not included |
|
|
| - **Datasets** (NBA / soccer / football `.npy` files) — see §2 of `RUNNING.md` for the expected paths. |
| - **Checkpoints and training logs** — code only. |
|
|
