po03087/sra-trajectory-code

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 — 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 — end-to-end setup from scratch (env, data, paths, first run)
• RUNNING.md — how to run every host × dataset
• GAMEFORMER_SRA.md — GameFormer+SRA negative result (does SRA generalize to feedforward models?)
• 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.