Quickstart: install → convert → train → play

Quickstart: install → convert → train → play#

After this page you can train and play a policy on the bundled ``samples`` clips. Requires Linux + NVIDIA GPU for training; CPU works for conversion and short smoke tests.

No GPU? Try the live web demo, Google Colab notebook, or Demo & Colab (wbc-mjlab-demo) — no training required.

Which task should I use?#

Goal

Start with

First train (default stack)

Wbc-G1 + --dataset samples

ZEST-style paper stack

Wbc-G1-Zest

Deploy-friendly actor obs

Wbc-G1 (apply_wbc)

BeyondMimic-style binary-failure RSI

Wbc-G1-BinaryFailure

State-estimation actor terms

Wbc-G1-SE / Wbc-G1-Zest-SE

Full catalog: Tasks and presets. Stuck? Troubleshooting.

1. Install#

Follow Installation (uv or pip from source), then verify:

uv run wbc-mjlab-list-envs

You should see registered tasks (e.g. Wbc-G1, Wbc-G1-Zest, Wbc-G1-BinaryFailure on the in-tree g1 entity).

2. Convert motion → NPZ#

uv run wbc-mjlab-data-to-npz --robot g1 --dataset samples --batch-size 8

Tip

Preview clips before training: uv run wbc-mjlab-data-vis --robot g1 --dataset samples.

3. Train#

Default task ``Wbc-G1``:

uv run wbc-mjlab-train --task Wbc-G1 --dataset samples

Logs: logs/rsl_rl/wbc_g1/<timestamp>/.

Tip

Full training is long. For a smoke run (pipeline check only):

uv run wbc-mjlab-train --task Wbc-G1 --dataset samples \
  --agent.max-iterations 1000

Resume a real run later with --agent.resume True — see Training.

4. Play / evaluate#

uv run wbc-mjlab-play --task Wbc-G1 --dataset samples --viewer viser

Play writes params/policy.onnx and params/config.yaml before the viewer opens. Use --checkpoint-file /path/to/model_*.pt to pick a specific checkpoint.

5. What you get in params/#

train / play
     │
     ▼
logs/rsl_rl/<experiment>/<run>/params/
     ├── policy.onnx      ← deploy policy
     ├── config.yaml      ← obs layout, joints, PD (wbc_tracking_params_v1)
     ├── env.yaml
     └── agent.yaml
     │
     ▼
deploy runtime (e.g. wbc-g1-deploy)

Copy policy.onnx + config.yaml into your runtime — see Deploy export.

Next steps#