export

# X1 DH policy export Use this sub-skill only for the registered `x1_dh_stand` model conversion pipeline and its serialized artifacts. Keep the two stages distinct: 1. **Checkpoint → JIT:** `model_<iteration>.pt` → `policy_dh.jit`. 2. **JIT → ONNX:** `policy_dh.jit` → `x1_policy.onnx`. The ONNX stage never reopens a training checkpoint, and its `--checkpoint` argument does not select one. ## Route by intent | Intent | Route | | --- | --- | | Select a runner checkpoint and convert it to JIT | Stay here; use [export workflows](references/workflows.md#3-checkpoint--jit) | | Convert an existing JIT policy to ONNX | Stay here; use [export workflows](references/workflows.md#4-jit--onnx) | | Check paths, checkpoint structure, or a serialized artifact | Stay here; use [preflight_export.py](scripts/preflight_export.py) and the [artifact contract](references/artifact-contract.md) | | Produce or resume a training checkpoint | Use [training](../training/SKILL.md) | | Run a runner checkpoint interactively in Isaac Gym | Use [playback](../playback/SKILL.md) | | Run an exported policy in MuJoCo | Use [sim2sim](../sim2sim/SKILL.md) after JIT validation | Do not use this route to train, launch Isaac Gym playback, run MuJoCo, or claim robot/simulation safety. ## Required backend boundary Both repository export entry points import `humanoid.envs`; their parser/helper import chain also requires **Isaac Gym Preview 4**. That backend is unavailable in the verified construction environment. Therefore full source checkpoint → JIT and JIT → ONNX execution remains: **BLOCKED_REQUIRED_BACKEND: Isaac Gym Preview 4 unavailable** Do not stub Isaac Gym, bypass task registration, or promote a bundled-helper pass to full source-export verification. A compatible source environment must provide the repository's documented Python 3.8, PyTorch 1.13.1/CUDA 11.7, NumPy 1.23.x, editable project install, and verified Isaac Gym Preview 4. ONNX conversion additionally needs a compatible `onnx` installation. The bundled preflight deliberately avoids project and Isaac Gym imports. It can perform path checks everywhere and can inspect trusted local artifacts only when the corresponding already-installed model library is available. ## Safe operating sequence 1. Obtain an exact run/checkpoint handoff from [training](../training/SKILL.md#checkpoints-and-handoff). Prefer explicit run names and checkpoint numbers; do not let “latest” select an unrelated artifact. 2. From this sub-skill directory, inspect the helper interface: ```bash python scripts/preflight_export.py --help ``` 3. Follow [export workflows](references/workflows.md) for stage-specific preflight, source commands, destination paths, and validation. Deserialize only trusted checkpoints; `torch.load` may execute pickle payloads. 4. Enforce the fixed X1 contract in [artifact contract](references/artifact-contract.md): input `(1, 3102)`, deterministic output `(1, 12)`, and exact artifact type for the requested stage. 5. Preserve the source script's printed input/output paths, explicit task, run, checkpoint or JIT timestamp, and package/backend versions in the handoff. 6. On failure, use [export troubleshooting](references/troubleshooting.md) and keep backend, missing-input, and failed-artifact states distinct. ## Non-negotiable artifact rules - `x1_dh_stand` is the only verified task contract in this sub-skill. - Checkpoint → JIT reconstructs `ActorCriticDH`, strictly loads `model_state_dict`, and scripts a CPU wrapper containing the actor, state estimator, and long-history encoder. - JIT → ONNX loads a prior `policy_dh.jit`; select its timestamp with `--load_run`. The shared `--checkpoint` flag is ignored by that converter. - Source outputs use `logs/`, not the README's stale singular `log/` spelling. JIT and ONNX go to different trees; see [artifact contract](references/artifact-contract.md). - A CPU load/shape check validates serialization only. It does not verify training-time observation construction, Isaac Gym behavior, MuJoCo behavior, controller integration, or robot safety.