---

name: training-and-evaluation description: "Train, evaluate, and export HumanoidVerse policies with PPO, PPODeltaA, Hydra overrides, simulator selection, motion tracking, locomotion, and delta-action workflows." disable-model-invocation: true metadata: disco-role: operating license: MIT

training-and-evaluation

Use this sub-skill when a user asks for HumanoidVerse policy training, checkpoint evaluation, ONNX export, simulator/backend choice, Hydra override selection, phase-based motion tracking, locomotion, open-loop delta-action training, or closed-loop delta-action finetuning.

Run ASAP training/evaluation entry points from the repository checkout root. The bundled helper scripts are skill-root-relative and accept --repo-root <asap-checkout>. The repo entry points are scripts, not package modules: python humanoidverse/train_agent.py ... and python humanoidverse/eval_agent.py .... Do not use python -m humanoidverse.train_agent, because the source imports utils.config_utils relative to the humanoidverse/ script directory.

Do not use this sub-skill for

• SMPL/AMASS shape fitting, motion retargeting, robot XML fitting, or MuJoCo retargeting visualization. Use ../motion-retargeting/SKILL.md.
• Sim2sim or sim2real runtime control, ROS2/Unitree bridges, joystick control, and live robot deployment. Use ../sim2real-deployment/SKILL.md.
• Generic PPO theory or unrelated simulator stacks that are not launched through this repository's HumanoidVerse Hydra configs.

Required reading order

1. Read the root router: ../../SKILL.md.
2. Read root install/backend guidance before choosing a simulator: ../../references/install-and-backends.md.
3. Read this sub-skill's command recipes: references/workflows.md.
4. Read CLI/config/class behavior before changing Hydra groups or checkpoint/export assumptions: references/api-reference.md.
5. If anything fails, read this sub-skill's predictable failures first: references/troubleshooting.md, then root troubleshooting ../../references/troubleshooting.md.

Safe preflight checks

These checks do not start simulator training:

# Confirm that Hydra can list config groups.
python humanoidverse/train_agent.py --help
python humanoidverse/eval_agent.py --help

# Build a command without executing it.
python sub-skills/training-and-evaluation/scripts/build_training_command.py \
  --repo-root <asap-checkout> \
  --workflow motion-tracking \
  --motion-file humanoidverse/data/motions/g1_29dof_anneal_23dof/TairanTestbed/singles/0-TairanTestbed_TairanTestbed_CR7_video_CR7_level1_filter_amass.pkl

# Turn a training command into a Hydra composition-only smoke check.
python sub-skills/training-and-evaluation/scripts/build_training_command.py \
  --repo-root <asap-checkout> \
  --workflow motion-tracking \
  --motion-file humanoidverse/data/motions/g1_29dof_anneal_23dof/TairanTestbed/singles/0-TairanTestbed_TairanTestbed_CR7_video_CR7_level1_filter_amass.pkl \
  --cfg-job

Run the root doctor script before runtime commands to get a single import/help report:

python scripts/asap_doctor.py --repo-root <asap-checkout> --section core

Route by prompt

User asks for	Use	Primary recipe
"train motion tracking", "imitate this motion", "CR7 policy"	train_agent.py with +exp=motion_tracking	references/workflows.md#motion-tracking-training
"train locomotion" or "test IsaacGym install with locomotion"	train_agent.py with +exp=locomotion	references/workflows.md#locomotion-training-and-smoke-test
"train delta action model"	train_agent.py with +exp=train_delta_a_open_loop	references/workflows.md#open-loop-delta-action-training
"finetune with delta A" or "closed-loop delta action"	train_agent.py with +exp=train_delta_a_closed_loop and algo.config.policy_checkpoint=...	references/workflows.md#closed-loop-delta-action-finetuning
"evaluate checkpoint", "visualize policy"	eval_agent.py +checkpoint=...	references/workflows.md#checkpoint-evaluation
"export ONNX"	eval_agent.py +checkpoint=...; export happens before the eval loop	references/workflows.md#onnx-export
"which Hydra overrides?"	Choose config groups and scalar overrides from the workflow table	references/api-reference.md#hydra-config-groups

Backend selection rules

• Default to +simulator=isaacgym for README-aligned training recipes when IsaacGym Preview 4 is installed and CUDA is available.
• Use +simulator=isaacsim only in an IsaacLab/IsaacSim environment with omni.isaac.lab; the entry points launch an IsaacSim app before importing Torch.
• Use +simulator=genesis only after installing genesis-world in the same environment.
• +simulator=mujoco is present as a Hydra config, but deployment/control recipes live in ../sim2real-deployment/SKILL.md; do not infer that every training recipe has been validated on MuJoCo.
• The verified inspection environment had CUDA-capable Torch, Hydra, humanoidverse, asap distribution metadata, onnx, and onnxruntime, but did not have IsaacGym, Genesis, or IsaacLab installed. Treat actual simulator launch as backend-gated.

Common outputs

• Training experiment directory: logs/<project_name>/<timestamp>-<experiment_name>-<log_task_name>-<robot_type>/.
• Training checkpoints: model_<iteration>.pt in the experiment directory; PPO.save() writes actor, critic, optimizer states, iteration, and infos.
• Saved training config: config.yaml in the experiment directory; Hydra's own run directory is <experiment_dir>/.hydra/ and train.log is written there.
• Training renderings: <experiment_dir>/renderings_training/ when the simulator records them.
• Evaluation logs: logs_eval/<eval_name>/<eval_timestamp>/config.yaml and eval.log under the Hydra eval run directory.
• Evaluation renderings: <checkpoint_dir>/renderings/ckpt_<N>/, where <N> comes from model_<N>.pt.
• ONNX export: <checkpoint_dir>/exported/model_<N>.onnx; eval_agent.py exports before it enters the infinite evaluation loop.
• Evaluation motion recording with +opt=record: <checkpoint_dir>/motions/<save_note>_<eval_timestamp>.pkl or <eval_timestamp>_<dump_motion_name>.pkl; those dumps include an action key useful for delta-action datasets.

Cross-links

• Root router: ../../SKILL.md.
• Root install and backend notes: ../../references/install-and-backends.md.
• Root troubleshooting: ../../references/troubleshooting.md.
• Motion retargeting: ../motion-retargeting/SKILL.md for producing motion .pkl files consumed by motion-tracking training.
• Sim2real deployment: ../sim2real-deployment/SKILL.md for using exported ONNX policies in MuJoCo/ROS2/Unitree runtime flows.