OpenVLA Trajectory Head DAgger R2
This repository contains the DAgger round-2 trajectory draft head used for the OpenVLA + SimplerEnv fast trajectory policy.
Files
best.pt: TinyTrajectoryHead checkpointmetrics.json: training metrics for the selected checkpoint
Benchmark Snapshot
Matched SimplerEnv benchmark matrix:
- tasks: vertical/horizontal/standing coke-can
- x positions:
-0.3500,-0.2925,-0.2350 obj_init_y = -0.02- 3 episodes per setting, 27 episodes total
- hardware: 1x A100-SXM4-40GB, bfloat16
| Decoder | Success | Avg ms/step | Speedup |
|---|---|---|---|
| Baseline OpenVLA | 14/27 (51.9%) | 295.2 | 1.00x |
| Adaptive fast policy (gate v=5, h=6, s=6) | 16/27 (59.3%) | 105.0 | 2.81x |
Usage
Download best.pt to:
checkpoints/traj_head_dagger_r2/best.pt
Then run:
uv run python scripts/run_openvla_sim.py \
--decoder trajectory-spec \
--trajectory-head-checkpoint checkpoints/traj_head_dagger_r2/best.pt \
--trajectory-fast-draft-only \
--trajectory-head-threshold 0.2 \
--trajectory-fast-min-confident-tokens 5 \
--task google_robot_pick_vertical_coke_can \
--published-eval-setup \
--episodes 3 \
--steps 80
For full reproduction from data generation through benchmarking, use:
./scripts/reproduce_readme_speedup_local.sh