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name: "training" description: "Route X1 DH stand PPO training, configuration inspection, checkpoint lifecycle, and algorithm-only shape checks with explicit Isaac Gym backend limits." disable-model-invocation: true metadata: disco-role: operating license: NO_LICENSE

X1 DH training

Use this sub-skill for the registered x1_dh_stand task: installing the training stack, inspecting its configuration and observation contract, building a bounded training command, running DH PPO, resuming from a checkpoint, and triaging runner or tensor-shape failures.

Backend boundary

The environment is an Isaac Gym Preview 4 task and its native environment, terrain, asset, and train.py execution require Isaac Gym plus a compatible CUDA/PhysX setup. Isaac Gym Preview 4 is unavailable in the current Creator environment. Mark native training as BLOCKED_REQUIRED_BACKEND: Isaac Gym Preview 4 unavailable unless the user provides and verifies that dependency. Never replace it with a fake simulator. CPU/Torch checks in this route validate only configuration arithmetic, policy wiring, and rollout-buffer shapes; they do not validate Isaac Gym behavior. MuJoCo playback is outside this route; after a checkpoint, hand off to playback or sim2sim. For JIT or ONNX artifacts, use export.

Start here

1. Read workflows for install, bounded launch, resume, checkpoint, and logging procedures.
2. Read configuration before changing any dimension, history stack, command, gait, terrain, PD, reward, or randomization field.
3. Read algorithm API for DH actor/critic, DHPPO, runner, and RolloutStorage contracts.
4. Use troubleshooting for backend, import, shape, OOM, checkpoint, and logging symptoms.
5. Run the safe helper first: python scripts/training_preflight.py --help, then python scripts/training_preflight.py --print-command --num-envs 1 --max-iterations 1. The helper never starts training. --shape-smoke is a CPU-only algorithm check; --check-config attempts a real config import and may report the required-backend block.

Task and install contract

• The only registered training task covered here is x1_dh_stand; pass it explicitly because the generic parser's default task is not this task.
• The README's intended stack is Python 3.8, PyTorch 1.13.1 with CUDA 11.7, NumPy 1.23.x, Isaac Gym Preview 4, and pip install -e .. The package metadata also requests TensorBoard and several playback/export dependencies. Treat exact legacy versions as compatibility requirements, not as proof that they are installed.
• Install Isaac Gym Preview 4 separately according to its license/distribution instructions, install its Python package, verify an Isaac Gym example, and only then install this package. If that artifact is absent, stop at static inspection or the CPU algorithm smoke.
• The native command is python humanoid/scripts/train.py --task=x1_dh_stand --run_name=<run_name> --headless from the repository root. Isaac Gym's gymutil parser supplies simulator flags in addition to the custom flags; keep --rl_device and simulator device choices explicit on multi-device systems.

Operating rules

• Treat env.frame_stack=66, short_frame_stack=5, and c_frame_stack=3 as coupled invariants. The actor consumes 66 frames of 47 features; the critic consumes 3 frames of 73 privileged features.
• Keep env.num_single_obs=47, num_observations=3102, num_privileged_obs=219, and num_actions=12 aligned with the network and rollout storage. See the full feature accounting in configuration.
• Raw commands are four values (lin_vel_x, lin_vel_y, ang_vel_yaw, heading); this task uses heading_command=False, so the effective commanded triple is (x, y, yaw). The five command-related observation values are gait sine, gait cosine, and the three scaled velocity commands—not five user commands.
• Use bounded command ranges and preserve the stand threshold. Do not invent a fifth action or bypass the policy's action clipping and PD torque limits.
• Keep domain randomization enabled unless an experiment explicitly studies a controlled ablation. Record changes to friction, pushes, mass/COM, gains, torque, joint friction/damping/armature, motor offsets, Coulomb friction, and action/DOF lag because they change the sim-to-real assumptions.
• Do not call task_registry.make_env merely to inspect a config on a machine without Isaac Gym: environment construction creates a PhysX simulation and loads the X1 asset. Prefer the bundled helper and static values first.
• Do not treat a successful CPU network/storage smoke as native training verification. Record backend status separately in any handoff.

Checkpoints and handoff

The runner writes TensorBoard and checkpoint files under the project log root, by default in logs/x1_dh_stand/exported_data/<timestamp><run_name>/. Checkpoints are model_<iteration>.pt; the runner saves at iteration 0 and then every save_interval=100, and saves one final checkpoint after the loop. Each checkpoint contains model_state_dict, optimizer states, estimator optimizer state, iter, and infos. --resume --load_run <run> --checkpoint <N> selects a run/checkpoint. In the config object load_run=-1 means latest, but the source CLI declares --load_run as a string and can pass literal -1 as a directory name; omit that flag for configured latest behavior or pass an exact run name. --checkpoint=-1 is an integer sentinel for the latest model. Resume loading intentionally omits optimizer state in the registry path, so report that when comparing resumed runs.

After training, route only the resulting artifact to playback, export, or sim2sim. Do not make this sub-skill perform interactive playback, export, or MuJoCo behavior.

Verification and hard cases

Run static frontmatter/link checks, the preflight --help and invariant output, and --shape-smoke when Torch is available. A native train command is a required-backend candidate and must be labeled blocked when Isaac Gym Preview 4 is unavailable. Proposed difficult usability cases for verification are:

1. A user requests num_single_obs=48 or frame_stack=5: the agent must detect the 47/66/5 observation and CNN reshape contract, explain every dependent field, and refuse to launch until all dimensions are reconciled.
2. A user resumes with --load_run -1 --checkpoint -1 after a run directory contains model_0.pt, sparse periodic checkpoints, and a stale exported directory: the agent must select the sorted latest model, distinguish the model's stored iter from its filename, and explain the optimizer-state omission before continuing.