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feat(envs): add RoboTwin 2.0 benchmark integration
- RoboTwinEnvConfig with 4-camera setup (head/front/left_wrist/right_wrist) - Docker image with SAPIEN, mplib, CuRobo, pytorch3d (Python 3.12) - CI workflow: 1-episode smoke eval with pepijn223/smolvla_robotwin - RoboTwinProcessorStep for state float32 casting - Camera rename_map: head_camera/front_camera/left_wrist -> camera1/2/3 Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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@@ -310,3 +310,94 @@ jobs:
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name: metaworld-metrics
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path: /tmp/metaworld-artifacts/metrics.json
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if-no-files-found: warn
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# ── ROBOTWIN 2.0 ──────────────────────────────────────────────────────────
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# Isolated image: full RoboTwin 2.0 stack — SAPIEN, mplib, CuRobo,
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# pytorch3d, + simulation assets (~4 GB).
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# Build takes ~20 min on first run; subsequent runs hit the layer cache.
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# Requires an NVIDIA GPU runner with CUDA 12.1 drivers.
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robotwin-integration-test:
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name: RoboTwin 2.0 — build image + 1-episode eval
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runs-on:
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group: aws-g6-4xlarge-plus
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env:
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HF_USER_TOKEN: ${{ secrets.LEROBOT_HF_USER }}
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steps:
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- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
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with:
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persist-credentials: false
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lfs: true
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3 # zizmor: ignore[unpinned-uses]
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with:
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cache-binary: false
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# Build the full-install image: SAPIEN, mplib, CuRobo, pytorch3d +
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# simulation assets (~4 GB). Layer cache lives in the runner's local
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# Docker daemon — reused across re-runs on the same machine.
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- name: Build RoboTwin 2.0 benchmark image
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uses: docker/build-push-action@v6 # zizmor: ignore[unpinned-uses]
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with:
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context: .
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file: docker/Dockerfile.benchmark.robotwin
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push: false
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load: true
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tags: lerobot-benchmark-robotwin:ci
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cache-from: type=local,src=/tmp/.buildx-cache-robotwin
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cache-to: type=local,dest=/tmp/.buildx-cache-robotwin,mode=max
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- name: Run RoboTwin 2.0 smoke eval (1 episode)
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run: |
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# Named container (no --rm) so we can docker cp artifacts out.
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docker run --name robotwin-eval --gpus all \
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--shm-size=4g \
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-e HF_HOME=/tmp/hf \
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-e HF_USER_TOKEN="${HF_USER_TOKEN}" \
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lerobot-benchmark-robotwin:ci \
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bash -c "
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hf auth login --token \"\$HF_USER_TOKEN\" --add-to-git-credential 2>/dev/null || true
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cd /opt/robotwin && lerobot-eval \
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--policy.path=pepijn223/smolvla_robotwin \
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--env.type=robotwin \
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--env.task=beat_block_hammer \
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--eval.batch_size=1 \
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--eval.n_episodes=1 \
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--eval.use_async_envs=false \
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--policy.device=cuda \
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'--rename_map={\"observation.images.head_camera\": \"observation.images.camera1\", \"observation.images.front_camera\": \"observation.images.camera2\", \"observation.images.left_wrist\": \"observation.images.camera3\"}' \
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--output_dir=/tmp/eval-artifacts
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"
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- name: Copy RoboTwin artifacts from container
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if: always()
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run: |
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mkdir -p /tmp/robotwin-artifacts
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docker cp robotwin-eval:/tmp/eval-artifacts/. /tmp/robotwin-artifacts/ 2>/dev/null || true
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docker rm -f robotwin-eval || true
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- name: Parse RoboTwin eval metrics
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if: always()
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run: |
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python3 scripts/ci/parse_eval_metrics.py \
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--artifacts-dir /tmp/robotwin-artifacts \
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--env robotwin \
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--task beat_block_hammer \
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--policy pepijn223/smolvla_robotwin
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- name: Upload RoboTwin rollout video
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if: always()
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uses: actions/upload-artifact@v4
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with:
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name: robotwin-rollout-video
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path: /tmp/robotwin-artifacts/videos/
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if-no-files-found: warn
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- name: Upload RoboTwin eval metrics
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if: always()
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uses: actions/upload-artifact@v4
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with:
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name: robotwin-metrics
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path: /tmp/robotwin-artifacts/metrics.json
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if-no-files-found: warn
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