Octo: ALOHA simulation policy rollout

Pinned Octo rollout entrypoint for a fine-tuned ALOHA simulation checkpoint in the upstream Gym environment. Statically reviewed source only; not run and no Hub preparation adapter.

octo-examples-03-eval-finetuned-py | Record version: source-00536ee90b51db9f8e2bd3f1429c0bdb2fa973765ff415d562401709894c00bb

Record JSON | Markdown | Pinned upstream source

Access

Fetch the pinned repository, verify this source checksum, and use upstream installation and invocation. This record does not install or execute code.

Hub preparation adapter: false. Follow the upstream setup and invocation contract.

Source and license

Repository: https://github.com/octo-models/octo
Revision: 241fb3514b7c40957a86d869fecb7c7fc353f540
Path: examples/03_eval_finetuned.py
Source SHA256: 00536ee90b51db9f8e2bd3f1429c0bdb2fa973765ff415d562401709894c00bb
Original authors: Octo Model Team, Robotic AI & Learning Lab Berkeley
License: MIT
License scope: Selected first-party Python workflow source only. Preserve upstream copyright and per-file notices. Model weights, datasets, third-party code, robot drivers/firmware and services retain separate terms; no rights for those assets are inferred.
License SHA256: 8c891a7dd06fdaa873aa011ff0b2773a3ccfe6d123f6b9a9fc589db718aec1d1
Hub commit: 1d6d9eb134e397d910265a8d6e7d8f257f9e8d7f

Artifact

{
  "kind": "workflow",
  "format": "python",
  "workflow_role": "policy-evaluation"
}

Requirements

{
  "python": "Python3.10 in README setup; no packaging minimum asserted.",
  "packages": [
    "Pinned Octo checkout",
    "JAX0.4.20, Flax0.7.5 and TensorFlow2.15.0 from requirements.txt",
    "Per-example simulator/robot-controller dependencies and reviewed checkpoints/data"
  ],
  "display": "Hardware: Requires separately installed ACT/MuJoCo/dm_control environment and appropriate rendering/display setup. Docstring supplies an Xvfb path for headless servers. No GPU-memory minimum or CPU validation is declared. Weights: Requires the fine-tuned ALOHA checkpoint produced by the preceding adaptation example or an otherwise reviewed matching local checkpoint. Datasets: Evaluation uses the configured ALOHA simulation environment; source refers to the previous example's training data but does not download a dataset itself. Services/auth: Unconditionally initializes W&B and logs rollout video. No specific API-key variable is named.",
  "execution_domain": "simulation",
  "source_imports": [
    "absl",
    "envs.aloha_sim_env",
    "functools",
    "gym",
    "jax",
    "numpy",
    "octo.model.octo_model",
    "octo.utils.gym_wrappers",
    "octo.utils.train_callbacks",
    "sys",
    "wandb"
  ],
  "notes": "Didactic source contains a path/to/your/act placeholder that must be edited to match an independently reviewed ACT checkout; it is not a turnkey Hub recipe. Code licensing does not establish model, checkpoint, dataset or service permission.",
  "declared_requirements": {
    "python": "Python3.10 in README setup; no packaging minimum asserted.",
    "weights": "Requires the fine-tuned ALOHA checkpoint produced by the preceding adaptation example or an otherwise reviewed matching local checkpoint.",
    "datasets": "Evaluation uses the configured ALOHA simulation environment; source refers to the previous example's training data but does not download a dataset itself.",
    "hardware": "Requires separately installed ACT/MuJoCo/dm_control environment and appropriate rendering/display setup. Docstring supplies an Xvfb path for headless servers. No GPU-memory minimum or CPU validation is declared.",
    "external_services_and_auth": "Unconditionally initializes W&B and logs rollout video. No specific API-key variable is named.",
    "evidence": [
      {
        "anchor": "sys.path.append(\"path/to/your/act\")",
        "line": 27
      },
      {
        "anchor": "gym.make(\"aloha-sim-cube-v0\")",
        "line": 65
      },
      {
        "anchor": "wandb.init(name=\"eval_aloha\"",
        "line": 45
      }
    ],
    "license_scopes": {
      "code": "MIT for selected first-party workflow source.",
      "weights": "README links separately hosted rail-berkeley Octo checkpoints. This bounded repository review did not inspect model cards or establish a weight license; repository MIT is limited to selected code.",
      "datasets": "README references Open X-Embodiment and an example ALOHA simulation dataset. Their individual terms were not inspected and are not covered by the code-license assertion.",
      "third_party_code": "External dependencies retain their own licenses."
    },
    "interpretation": "Pinned upstream declarations only; no dependency resolution, model/data access, compatibility inference or runtime validation was performed."
  }
}

Invocation

{
  "entrypoint": "cd examples && python 03_eval_finetuned.py --finetuned_path=<approved-aloha-checkpoint>",
  "notes": "Didactic source contains a path/to/your/act placeholder that must be edited to match an independently reviewed ACT checkout; it is not a turnkey Hub recipe."
}

Explicit compatibility

[]

Missing environment fields remain unknown. Discovery labels do not establish robot compatibility.

Evidence

Level: source_reviewed; runtime verification: not_run.

Verified exact source, applicable license and author/setup document bytes at a full Git commit; parsed the Python AST and reviewed this guarded operational entrypoint and its explicit license notices. No upstream code, installation, robot command, dataset, mesh or checkpoint was executed or loaded.

Source review and contributor reports do not establish task completion. Preserve upstream attribution and licenses.