Release robot execution validation data and code
Browse files- README.md +112 -0
- SHA256SUMS.json +6 -0
- confirmation.json +0 -0
- extension.json +0 -0
- reproduction.zip +3 -0
README.md
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---
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license: cc-by-4.0
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language:
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- en
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size_categories:
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- n<1K
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pretty_name: Robot Execution Validation
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tags:
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- robotics
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- vision-language-action
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- robot-manipulation
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- evaluation
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- reproducibility
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---
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# Robot Execution Validation
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VLABench execution records for released SmolVLA and Pi0 policies: 320 primary
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confirmation attempts, a prospectively specified 60-attempt family-matched native
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validation extension, and 37 separately reported development attempts. Each native
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trajectory is evaluated at 60 and 200 actions. Paired instructions use the same
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initial state and requested-versus-alternative goal predicates.
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| File | Contents |
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|---|---|
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| `confirmation.json` | Frozen primary results, per-trial measurements, summaries, and raw-file hashes |
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| `extension.json` | Frozen validation-extension results and the prospective configuration selection |
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| `reproduction.zip` | Evaluation/analysis code, tests, protocols, selected inputs, complete action traces, initial states, scene images, and environment versions |
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| `SHA256SUMS.json` | File checksums |
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## Reproduce the analysis
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Download the files from one fixed repository revision and extract `reproduction.zip`.
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The archive has its own file-level `SHA256SUMS.json`. Python 3.10 or later with NumPy,
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SciPy, Matplotlib, and pytest is sufficient for analysis; no GPU is required.
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Use the recorded package versions for exact regeneration.
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From the extracted directory:
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```bash
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cp /path/to/download/confirmation.json code/paper/reproduce/revision_results.json
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cp /path/to/download/extension.json code/paper/reproduce/validation_extension_results.json
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cd code
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export PYTHONPATH="$PWD/src:$PWD"
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python -m pytest tests -q
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python -m experiments.revision.freeze --root ../confirmation --out ../confirmation_check.json
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python -m experiments.revision.freeze_extension --root ../extension --out ../extension_check.json
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python -m paper.reproduce.revision_assets --out ../latex_assets
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python -m paper.reproduce.extension_assets --out ../latex_assets
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```
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The checked exports reproduce the downloaded JSON files. The generated assets include
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the original four-family native results, paired outcomes, progress, development results,
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family-matched extension and synthesis, and stopping-rule sensitivity. Technical errors
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remain distinct from observed goal outcomes. The paired first-goal analysis is post hoc;
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the original native-stop outcomes are retained alongside it.
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Extension validation compares the frozen selected configurations with the recorded inputs,
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undoing only VLABench's automatic expansion of relative XML asset paths. No raw record or
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prospective selection is changed. The extension retains three Pi0 numerical failures.
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## Rerun execution
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Use the package inventories in `environments/versions.json` and install these pinned
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upstream sources and their assets in separate simulator and policy environments:
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- [VLABench](https://github.com/OpenMOSS/VLABench), revision `cf588fe60c0c7282174fe979f5913170cfe69017`.
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- [SmolVLA checkpoint](https://huggingface.co/lerobot/smolvla_vlabench), revision `4fd586e12dc14b04d9d606ddbb77448df4f0ff29`.
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- [Pi0 checkpoint](https://huggingface.co/VLABench/pi0-primitive-10task), revision `1ad73753a74d5cd97e67856664350f3f0baa21dc`.
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- [Author OpenPI implementation](https://github.com/Shiduo-zh/openpi), revision `4483d1da6332da44115fe530e4e6fdd89bd57b13`; use the included `openpi_uv.lock`.
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Initialize a local Git checkout of `code/` before execution so the evaluator can
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record the reproduction's source revision. From `code/`, relocate archived asset
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references into a fresh directory:
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```bash
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python -m experiments.revision.prepare_reproduction --inputs ../inputs \
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--vlabench-root /path/to/VLABench/VLABench --out ../relocated
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```
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Set `PROJECT_STORAGE_ROOT` to the absolute path of `../relocated`, `VLABENCH_ROOT`
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to the installed benchmark package, and `PYTHONPATH` to `code/src:code` using absolute
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paths. Set `MUJOCO_GL=egl`, `OMP_NUM_THREADS=4`, and `OPENBLAS_NUM_THREADS=4`.
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The evaluator permits physical GPUs 0 through 4 and enforces one renderer at a time.
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Keep inference and rendering on separate GPUs.
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Start the services in their respective policy environments:
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```bash
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python -m experiments.e2a.smolvla_server --gpu 1 --port 5581
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python -m experiments.revision.pi0_server --gpu 3 --port 5583 \
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--repo /path/to/openpi --checkpoint /path/to/pi0-checkpoint
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```
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Run the evaluator in the simulator environment with `CUDA_VISIBLE_DEVICES=0`.
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For the extension, use `--tasks select_book,select_mahjong,select_poker` and the
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relocated published track. For the original native control, use
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`--tasks select_fruit,select_toy,select_chemistry_tube,select_drink`.
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```bash
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python -m experiments.revision.vlabench_control --out /path/to/fresh/run \
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--tasks select_book,select_mahjong,select_poker \
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--track-config ../relocated/track_1_in_distribution.json --episodes-per-task 10 \
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--policy-seed 17 --max-substeps 1 --max-steps 200 --port 5581 --chunk 50
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```
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Use `--port 5583 --chunk 5` for Pi0. For paired instructions, replace `--tasks` and
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`--track-config` with `--paired-spec ../relocated/final_study_command_spec.json`.
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Use fresh output directories and compare actual initial-state and observation hashes.
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The common 200-action diagnostic budget is not every task's official leaderboard budget.
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The separate synthetic-speech records are available in
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[multilingual-robot-grounding-causal-audit](https://huggingface.co/datasets/nur-dev/multilingual-robot-grounding-causal-audit/tree/0d82c875c6d58b1406b0217c9fc5deb0904df0f2).
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SHA256SUMS.json
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{
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"README.md": "2b5759cae3ac461519fdf4abc2ed3cbb951f83c46683d1856e8dc960f4d0110b",
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"confirmation.json": "7fb9e519d36d2dd48405f475b1f4edb7b804fdcbdd26f7fe30e4b990a90e18a3",
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"extension.json": "7ec8074aab116bd3dd8f41073a2bd856e62d98f2736028f5966e10f7cbd98f1f",
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"reproduction.zip": "d10a531056efe36ff092146e925c9fc3cc86a7cd821115ca4964d9abb1c7de96"
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}
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confirmation.json
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extension.json
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reproduction.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:d10a531056efe36ff092146e925c9fc3cc86a7cd821115ca4964d9abb1c7de96
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size 192841116
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