mirror of
https://github.com/huggingface/lerobot.git
synced 2026-05-11 14:49:43 +00:00
a147fa4439
* feat(ci): add RoboCerebra benchmark eval job - Docker image with robosuite/libero deps for RoboCerebra eval - CI workflow: 1-episode eval with pepijn223/smolvla_robocerebra - Reuses libero env with rename_map + empty_cameras=3 * docs(robocerebra): add benchmark page and toctree entry Add a dedicated docs page for RoboCerebra that points at the canonical dataset lerobot/robocerebra_unified and shows how to run eval + fine-tune against it. Wire it into the Benchmarks section of the toctree so doc-builder picks it up. * ci: point benchmark eval checkpoints at the lerobot/ org mirrors pepijn223/smolvla_* → lerobot/smolvla_* across every benchmark job in this branch (libero, metaworld, and the per-branch benchmark). The checkpoints were mirrored into the lerobot/ org and that's the canonical location going forward. * fix(robocerebra): drop alias extra + simplify docker image Two problems rolled up: 1. `uv sync --locked --extra test` was failing because pyproject.toml added a `robocerebra = ["lerobot[libero]"]` alias extra but uv.lock wasn't regenerated. Drop the alias — nothing in CI actually needs the extra name (the Dockerfile just installs what it needs directly), so this restores pyproject.toml and uv.lock to byte-exact origin/main. 2. Rebase docker/Dockerfile.benchmark.robocerebra on huggingface/lerobot-gpu:latest (same pattern as libero/metaworld/…). The nightly image already ships lerobot[all] which includes [libero], so the RoboCerebra image is essentially identical to the LIBERO one: fetch libero-assets, write ~/.libero/config.yaml, overlay source. 92 → 43 lines. Also repoint the CI workflow comment that referenced the removed extra. * ci: use dedicated lerobot/smolvla_robocerebra checkpoint for smoke eval Replace the generic pepijn223/smolvla_libero placeholder with the purpose-trained lerobot/smolvla_robocerebra model in the RoboCerebra CI smoke test. * fix(ci): align RoboCerebra eval with training pipeline Fixes 5 mismatches that caused 0% success rate: - env.type: robocerebra (unregistered) → libero - resolution: 360x360 (default) → 256x256 (matches dataset) - camera_name_mapping: map eye_in_hand → wrist_image (not image2) - empty_cameras: 3 → 1 (matches training) - add HF_USER_TOKEN guard on eval step * fix(ci): set env.fps=20 and explicit obs_type for RoboCerebra eval Match the dataset's 20 FPS (LiberoEnv defaults to 30) and make obs_type=pixels_agent_pos explicit for safety against future changes. * docs(robocerebra): align page with adding_benchmarks template Rework docs/source/robocerebra.mdx to follow the standard benchmark doc structure: intro + links + available tasks + installation + eval + recommended episodes + policy I/O + training + reproducing results. - Point everything at lerobot/smolvla_robocerebra (the released checkpoint), not the personal pepijn223 mirror. - Add the --env.fps=20 and --env.obs_type=pixels_agent_pos flags that CI actually uses, so copy-paste eval reproduces CI. - Split the "Training" block out of the recipe section into its own section with the feature table. - Add an explicit "Reproducing published results" section pointing at the CI smoke eval. * fix: integrate PR #3314 review feedback - ci(robocerebra): drop redundant hf auth login step (auth is already performed inside the eval step's container). - ci(robocerebra): add Docker Hub login before the image build to pick up the authenticated rate limit. - docs(robocerebra): align eval snippet with the CI command (observation size, camera_name_mapping, use_async_envs, device, empty_cameras=1). * fix(envs): preserve AsyncVectorEnv metadata/unwrapped in lazy eval envs Port of #3416 onto this branch. * ci: gate Docker Hub login on secret availability * Update .github/workflows/benchmark_tests.yml Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co> Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com> * Update .github/workflows/benchmark_tests.yml Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com> Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
635 lines
26 KiB
YAML
635 lines
26 KiB
YAML
# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Integration tests: build an isolated Docker image per benchmark and run a
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# 1-episode smoke eval. Each benchmark gets its own image so incompatible
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# dependency trees (e.g. hf-libero vs metaworld==3.0.0) can never collide.
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#
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# To add a new benchmark:
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# 1. Add docker/Dockerfile.benchmark.<name> (install only lerobot[<name>])
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# 2. Copy one of the jobs below and adjust the image name and eval command.
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name: Benchmark Integration Tests
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on:
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# Run manually from the Actions tab
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workflow_dispatch:
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# Run every Monday at 02:00 UTC.
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schedule:
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- cron: "0 2 * * 1"
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push:
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branches:
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- main
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paths:
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- "src/lerobot/envs/**"
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- "src/lerobot/scripts/lerobot_eval.py"
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- "docker/Dockerfile.benchmark.*"
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- ".github/workflows/benchmark_tests.yml"
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- "pyproject.toml"
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pull_request:
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branches:
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- main
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paths:
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- "src/lerobot/envs/**"
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- "src/lerobot/scripts/lerobot_eval.py"
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- "docker/Dockerfile.benchmark.*"
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- ".github/workflows/benchmark_tests.yml"
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- "pyproject.toml"
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permissions:
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contents: read
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env:
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UV_VERSION: "0.8.0"
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PYTHON_VERSION: "3.12"
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# Cancel in-flight runs for the same branch/PR.
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concurrency:
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group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
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cancel-in-progress: true
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jobs:
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# ── LIBERO ────────────────────────────────────────────────────────────────
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# Isolated image: lerobot[libero] only (hf-libero, dm-control, mujoco chain)
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libero-integration-test:
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name: Libero — 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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- name: Login to Docker Hub
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if: ${{ env.DOCKERHUB_USERNAME != '' }}
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uses: docker/login-action@v3 # zizmor: ignore[unpinned-uses]
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with:
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username: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
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password: ${{ secrets.DOCKERHUB_LEROBOT_PASSWORD }}
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env:
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DOCKERHUB_USERNAME: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
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# Build the benchmark-specific image. The Dockerfile separates dep-install
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# from source-copy, so code-only changes skip the slow uv-sync layer
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# when the runner has a warm Docker daemon cache.
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- name: Build Libero benchmark image
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uses: docker/build-push-action@v6 # zizmor: ignore[unpinned-uses]
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with:
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context: .
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file: docker/Dockerfile.benchmark.libero
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push: false
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load: true
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tags: lerobot-benchmark-libero:ci
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- name: Run Libero smoke eval (1 episode)
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if: env.HF_USER_TOKEN != ''
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run: |
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# Named container (no --rm) so we can docker cp artifacts out.
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# Output to /tmp inside the container — /artifacts doesn't exist
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# and user_lerobot cannot create root-level dirs.
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docker run --name libero-eval --gpus all \
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--shm-size=4g \
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-e HF_HOME=/tmp/hf \
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-e HF_USER_TOKEN="${HF_USER_TOKEN}" \
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-e HF_HUB_DOWNLOAD_TIMEOUT=300 \
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lerobot-benchmark-libero: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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lerobot-eval \
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--policy.path=lerobot/smolvla_libero \
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--env.type=libero \
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--env.task=libero_spatial \
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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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'--env.camera_name_mapping={\"agentview_image\": \"camera1\", \"robot0_eye_in_hand_image\": \"camera2\"}' \
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--policy.empty_cameras=1 \
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--output_dir=/tmp/eval-artifacts
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python scripts/ci/extract_task_descriptions.py \
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--env libero --task libero_spatial \
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--output /tmp/eval-artifacts/task_descriptions.json
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"
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- name: Copy Libero artifacts from container
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if: always()
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run: |
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mkdir -p /tmp/libero-artifacts
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docker cp libero-eval:/tmp/eval-artifacts/. /tmp/libero-artifacts/ 2>/dev/null || true
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docker rm -f libero-eval || true
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- name: Parse Libero 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/libero-artifacts \
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--env libero \
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--task libero_spatial \
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--policy lerobot/smolvla_libero
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- name: Upload Libero rollout video
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if: always()
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uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
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with:
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name: libero-rollout-video
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path: /tmp/libero-artifacts/videos/
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if-no-files-found: warn
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- name: Upload Libero eval metrics
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if: always()
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uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
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with:
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name: libero-metrics
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path: /tmp/libero-artifacts/metrics.json
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if-no-files-found: warn
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# ── LIBERO TRAIN+EVAL SMOKE ──────────────────────────────────────────────
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# Train SmolVLA for 1 step (batch_size=1, dataset episode 0 only) then
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# immediately runs eval inside the training loop (eval_freq=1, 1 episode).
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# Tests the full train→eval-within-training pipeline end-to-end.
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- name: Run Libero train+eval smoke (1 step, eval_freq=1)
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if: env.HF_USER_TOKEN != ''
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run: |
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docker run --name libero-train-smoke --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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-e HF_HUB_DOWNLOAD_TIMEOUT=300 \
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lerobot-benchmark-libero: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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accelerate launch --num_processes=1 \$(which lerobot-train) \
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--policy.path=lerobot/smolvla_base \
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--policy.load_vlm_weights=true \
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--policy.scheduler_decay_steps=25000 \
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--policy.freeze_vision_encoder=false \
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--policy.train_expert_only=false \
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--dataset.repo_id=lerobot/libero \
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--dataset.episodes=[0] \
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--dataset.use_imagenet_stats=false \
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--env.type=libero \
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--env.task=libero_spatial \
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'--env.camera_name_mapping={\"agentview_image\": \"camera1\", \"robot0_eye_in_hand_image\": \"camera2\"}' \
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--policy.empty_cameras=1 \
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--output_dir=/tmp/train-smoke \
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--steps=1 \
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--batch_size=1 \
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--eval_freq=1 \
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--eval.n_episodes=1 \
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--eval.batch_size=1 \
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--eval.use_async_envs=false \
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--save_freq=1 \
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--policy.push_to_hub=false \
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'--rename_map={\"observation.images.image\": \"observation.images.camera1\", \"observation.images.image2\": \"observation.images.camera2\"}'
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"
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- name: Copy Libero train-smoke artifacts from container
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if: always()
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run: |
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mkdir -p /tmp/libero-train-smoke-artifacts
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docker cp libero-train-smoke:/tmp/train-smoke/. /tmp/libero-train-smoke-artifacts/ 2>/dev/null || true
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docker rm -f libero-train-smoke || true
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- name: Upload Libero train-smoke eval video
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if: always()
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uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
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with:
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name: libero-train-smoke-video
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path: /tmp/libero-train-smoke-artifacts/eval/
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if-no-files-found: warn
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# ── METAWORLD ─────────────────────────────────────────────────────────────
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# Isolated image: lerobot[metaworld] only (metaworld==3.0.0, mujoco>=3 chain)
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metaworld-integration-test:
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name: MetaWorld — 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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- name: Login to Docker Hub
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if: ${{ env.DOCKERHUB_USERNAME != '' }}
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uses: docker/login-action@v3 # zizmor: ignore[unpinned-uses]
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with:
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username: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
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password: ${{ secrets.DOCKERHUB_LEROBOT_PASSWORD }}
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env:
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DOCKERHUB_USERNAME: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
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- name: Build MetaWorld benchmark image
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uses: docker/build-push-action@v6 # zizmor: ignore[unpinned-uses]
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with:
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context: .
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file: docker/Dockerfile.benchmark.metaworld
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push: false
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load: true
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tags: lerobot-benchmark-metaworld:ci
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- name: Run MetaWorld smoke eval (1 episode)
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if: env.HF_USER_TOKEN != ''
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run: |
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docker run --name metaworld-eval --gpus all \
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--shm-size=4g \
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-e HF_HOME=/tmp/hf \
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-e HF_USER_TOKEN="${HF_USER_TOKEN}" \
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-e HF_HUB_DOWNLOAD_TIMEOUT=300 \
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lerobot-benchmark-metaworld: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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lerobot-eval \
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--policy.path=lerobot/smolvla_metaworld \
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--env.type=metaworld \
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--env.task=metaworld-push-v3 \
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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.image\": \"observation.images.camera1\"}' \
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--policy.empty_cameras=2 \
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--output_dir=/tmp/eval-artifacts
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python scripts/ci/extract_task_descriptions.py \
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--env metaworld --task metaworld-push-v3 \
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--output /tmp/eval-artifacts/task_descriptions.json
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"
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- name: Copy MetaWorld artifacts from container
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if: always()
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run: |
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mkdir -p /tmp/metaworld-artifacts
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docker cp metaworld-eval:/tmp/eval-artifacts/. /tmp/metaworld-artifacts/ 2>/dev/null || true
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docker rm -f metaworld-eval || true
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- name: Parse MetaWorld 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/metaworld-artifacts \
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--env metaworld \
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--task metaworld-push-v3 \
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--policy lerobot/smolvla_metaworld
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- name: Upload MetaWorld rollout video
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if: always()
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uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
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with:
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name: metaworld-rollout-video
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path: /tmp/metaworld-artifacts/videos/
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if-no-files-found: warn
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- name: Upload MetaWorld eval metrics
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if: always()
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uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
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with:
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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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ROBOTWIN_POLICY: lerobot/smolvla_robotwin
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ROBOTWIN_TASKS: beat_block_hammer,click_bell,handover_block,stack_blocks_two,click_alarmclock,open_microwave,adjust_bottle,lift_pot,stamp_seal,turn_switch
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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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- name: Login to Docker Hub
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if: ${{ env.DOCKERHUB_USERNAME != '' }}
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uses: docker/login-action@v3 # zizmor: ignore[unpinned-uses]
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with:
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username: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
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password: ${{ secrets.DOCKERHUB_LEROBOT_PASSWORD }}
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env:
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DOCKERHUB_USERNAME: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
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# Build the full-install image: SAPIEN, mplib, CuRobo, pytorch3d +
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# simulation assets (~4 GB). Layer cache lives in the runner's local
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# Docker daemon — reused across re-runs on the same machine.
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- name: Build RoboTwin 2.0 benchmark image
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uses: docker/build-push-action@v6 # zizmor: ignore[unpinned-uses]
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with:
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context: .
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file: docker/Dockerfile.benchmark.robotwin
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push: false
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load: true
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tags: lerobot-benchmark-robotwin:ci
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cache-from: type=local,src=/tmp/.buildx-cache-robotwin
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cache-to: type=local,dest=/tmp/.buildx-cache-robotwin,mode=max
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- name: Run RoboTwin 2.0 smoke eval (10 tasks, 1 episode each)
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if: env.HF_USER_TOKEN != ''
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run: |
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# Named container (no --rm) so we can docker cp artifacts out.
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docker run --name robotwin-eval --gpus all \
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--shm-size=4g \
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-e HF_HOME=/tmp/hf \
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-e HF_USER_TOKEN="${HF_USER_TOKEN}" \
|
|
-e ROBOTWIN_POLICY="${ROBOTWIN_POLICY}" \
|
|
-e ROBOTWIN_TASKS="${ROBOTWIN_TASKS}" \
|
|
lerobot-benchmark-robotwin:ci \
|
|
bash -c "
|
|
hf auth login --token \"\$HF_USER_TOKEN\" --add-to-git-credential 2>/dev/null || true
|
|
cd /opt/robotwin && lerobot-eval \
|
|
--policy.path=\"\$ROBOTWIN_POLICY\" \
|
|
--env.type=robotwin \
|
|
--env.task=\"\$ROBOTWIN_TASKS\" \
|
|
--eval.batch_size=1 \
|
|
--eval.n_episodes=1 \
|
|
--eval.use_async_envs=false \
|
|
--policy.device=cuda \
|
|
'--rename_map={\"observation.images.head_camera\": \"observation.images.camera1\", \"observation.images.left_camera\": \"observation.images.camera2\", \"observation.images.right_camera\": \"observation.images.camera3\"}' \
|
|
--output_dir=/tmp/eval-artifacts
|
|
python /lerobot/scripts/ci/extract_task_descriptions.py \
|
|
--env robotwin \
|
|
--task \"\$ROBOTWIN_TASKS\" \
|
|
--output /tmp/eval-artifacts/task_descriptions.json
|
|
"
|
|
|
|
- name: Copy RoboTwin artifacts from container
|
|
if: always()
|
|
run: |
|
|
mkdir -p /tmp/robotwin-artifacts
|
|
docker cp robotwin-eval:/tmp/eval-artifacts/. /tmp/robotwin-artifacts/ 2>/dev/null || true
|
|
docker rm -f robotwin-eval || true
|
|
|
|
- name: Parse RoboTwin eval metrics
|
|
if: always()
|
|
run: |
|
|
python3 scripts/ci/parse_eval_metrics.py \
|
|
--artifacts-dir /tmp/robotwin-artifacts \
|
|
--env robotwin \
|
|
--task "${ROBOTWIN_TASKS}" \
|
|
--policy "${ROBOTWIN_POLICY}"
|
|
|
|
- name: Upload RoboTwin rollout video
|
|
if: always()
|
|
uses: actions/upload-artifact@v4
|
|
with:
|
|
name: robotwin-rollout-video
|
|
path: /tmp/robotwin-artifacts/videos/
|
|
if-no-files-found: warn
|
|
|
|
- name: Upload RoboTwin eval metrics
|
|
if: always()
|
|
uses: actions/upload-artifact@v4
|
|
with:
|
|
name: robotwin-metrics
|
|
path: /tmp/robotwin-artifacts/metrics.json
|
|
if-no-files-found: warn
|
|
|
|
# ── ROBOCASA365 ──────────────────────────────────────────────────────────
|
|
# Isolated image: robocasa + robosuite installed manually as editable
|
|
# clones (no `lerobot[robocasa]` extra — robocasa's setup.py pins
|
|
# `lerobot==0.3.3`, which would shadow this repo's lerobot).
|
|
robocasa-integration-test:
|
|
name: RoboCasa365 — build image + 1-episode eval
|
|
runs-on:
|
|
group: aws-g6-4xlarge-plus
|
|
env:
|
|
HF_USER_TOKEN: ${{ secrets.LEROBOT_HF_USER }}
|
|
|
|
steps:
|
|
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
|
|
with:
|
|
persist-credentials: false
|
|
lfs: true
|
|
|
|
- name: Set up Docker Buildx
|
|
uses: docker/setup-buildx-action@v3 # zizmor: ignore[unpinned-uses]
|
|
with:
|
|
cache-binary: false
|
|
|
|
- name: Login to Docker Hub
|
|
if: ${{ env.DOCKERHUB_USERNAME != '' }}
|
|
uses: docker/login-action@v3 # zizmor: ignore[unpinned-uses]
|
|
with:
|
|
username: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
|
|
password: ${{ secrets.DOCKERHUB_LEROBOT_PASSWORD }}
|
|
env:
|
|
DOCKERHUB_USERNAME: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
|
|
|
|
- name: Build RoboCasa365 benchmark image
|
|
uses: docker/build-push-action@v6 # zizmor: ignore[unpinned-uses]
|
|
with:
|
|
context: .
|
|
file: docker/Dockerfile.benchmark.robocasa
|
|
push: false
|
|
load: true
|
|
tags: lerobot-benchmark-robocasa:ci
|
|
|
|
- name: Run RoboCasa365 smoke eval (10 atomic tasks, 1 episode each)
|
|
if: env.HF_USER_TOKEN != ''
|
|
run: |
|
|
docker run --name robocasa-eval --gpus all \
|
|
--shm-size=4g \
|
|
-e HF_HOME=/tmp/hf \
|
|
-e HF_USER_TOKEN="${HF_USER_TOKEN}" \
|
|
-e HF_HUB_DOWNLOAD_TIMEOUT=300 \
|
|
-e MUJOCO_GL=egl \
|
|
lerobot-benchmark-robocasa:ci \
|
|
bash -c "
|
|
hf auth login --token \"\$HF_USER_TOKEN\" --add-to-git-credential 2>/dev/null || true
|
|
lerobot-eval \
|
|
--policy.path=lerobot/smolvla_robocasa \
|
|
--env.type=robocasa \
|
|
--env.task=CloseFridge,OpenCabinet,OpenDrawer,TurnOnMicrowave,TurnOffStove,CloseToasterOvenDoor,SlideDishwasherRack,TurnOnSinkFaucet,NavigateKitchen,TurnOnElectricKettle \
|
|
--eval.batch_size=1 \
|
|
--eval.n_episodes=1 \
|
|
--eval.use_async_envs=false \
|
|
--policy.device=cuda \
|
|
'--rename_map={\"observation.images.robot0_agentview_left\": \"observation.images.camera1\", \"observation.images.robot0_eye_in_hand\": \"observation.images.camera2\", \"observation.images.robot0_agentview_right\": \"observation.images.camera3\"}' \
|
|
--output_dir=/tmp/eval-artifacts
|
|
python scripts/ci/extract_task_descriptions.py \
|
|
--env robocasa \
|
|
--task CloseFridge,OpenCabinet,OpenDrawer,TurnOnMicrowave,TurnOffStove,CloseToasterOvenDoor,SlideDishwasherRack,TurnOnSinkFaucet,NavigateKitchen,TurnOnElectricKettle \
|
|
--output /tmp/eval-artifacts/task_descriptions.json
|
|
"
|
|
|
|
- name: Copy RoboCasa365 artifacts from container
|
|
if: always()
|
|
run: |
|
|
mkdir -p /tmp/robocasa-artifacts
|
|
docker cp robocasa-eval:/tmp/eval-artifacts/. /tmp/robocasa-artifacts/ 2>/dev/null || true
|
|
docker rm -f robocasa-eval || true
|
|
|
|
- name: Parse RoboCasa365 eval metrics
|
|
if: always()
|
|
run: |
|
|
python3 scripts/ci/parse_eval_metrics.py \
|
|
--artifacts-dir /tmp/robocasa-artifacts \
|
|
--env robocasa \
|
|
--task atomic_smoke_10 \
|
|
--policy lerobot/smolvla_robocasa
|
|
|
|
- name: Upload RoboCasa365 rollout video
|
|
if: always()
|
|
uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
|
|
with:
|
|
name: robocasa-rollout-video
|
|
path: /tmp/robocasa-artifacts/videos/
|
|
if-no-files-found: warn
|
|
|
|
- name: Upload RoboCasa365 eval metrics
|
|
if: always()
|
|
uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
|
|
with:
|
|
name: robocasa-metrics
|
|
path: /tmp/robocasa-artifacts/metrics.json
|
|
if-no-files-found: warn
|
|
|
|
# ── ROBOCEREBRA ───────────────────────────────────────────────────────────
|
|
# Reuses the LIBERO simulator (libero_10 suite) with RoboCerebra camera
|
|
# defaults (image/wrist_image). The image is layered on
|
|
# huggingface/lerobot-gpu, which already ships [libero] as part of [all].
|
|
robocerebra-integration-test:
|
|
name: RoboCerebra — build image + 1-episode eval
|
|
runs-on:
|
|
group: aws-g6-4xlarge-plus
|
|
env:
|
|
HF_USER_TOKEN: ${{ secrets.LEROBOT_HF_USER }}
|
|
|
|
steps:
|
|
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
|
|
with:
|
|
persist-credentials: false
|
|
lfs: true
|
|
|
|
- name: Set up Docker Buildx
|
|
uses: docker/setup-buildx-action@v3 # zizmor: ignore[unpinned-uses]
|
|
with:
|
|
cache-binary: false
|
|
|
|
- name: Login to Docker Hub
|
|
if: ${{ env.DOCKERHUB_USERNAME != '' }}
|
|
uses: docker/login-action@v3 # zizmor: ignore[unpinned-uses]
|
|
with:
|
|
username: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
|
|
password: ${{ secrets.DOCKERHUB_LEROBOT_PASSWORD }}
|
|
env:
|
|
DOCKERHUB_USERNAME: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
|
|
|
|
- name: Build RoboCerebra benchmark image
|
|
uses: docker/build-push-action@v6 # zizmor: ignore[unpinned-uses]
|
|
with:
|
|
context: .
|
|
file: docker/Dockerfile.benchmark.robocerebra
|
|
push: false
|
|
load: true
|
|
tags: lerobot-benchmark-robocerebra:ci
|
|
cache-from: type=local,src=/tmp/.buildx-cache-robocerebra
|
|
cache-to: type=local,dest=/tmp/.buildx-cache-robocerebra,mode=max
|
|
|
|
- name: Run RoboCerebra smoke eval (1 episode)
|
|
if: env.HF_USER_TOKEN != ''
|
|
run: |
|
|
docker run --name robocerebra-eval --gpus all \
|
|
--shm-size=4g \
|
|
-e HF_HOME=/tmp/hf \
|
|
-e HF_USER_TOKEN="${HF_USER_TOKEN}" \
|
|
-e HF_HUB_DOWNLOAD_TIMEOUT=300 \
|
|
-e LIBERO_DATA_FOLDER=/tmp/libero_data \
|
|
lerobot-benchmark-robocerebra:ci \
|
|
bash -c "
|
|
hf auth login --token \"\$HF_USER_TOKEN\" --add-to-git-credential 2>/dev/null || true
|
|
lerobot-eval \
|
|
--policy.path=lerobot/smolvla_robocerebra \
|
|
--env.type=libero \
|
|
--env.task=libero_10 \
|
|
--env.fps=20 \
|
|
--env.obs_type=pixels_agent_pos \
|
|
--env.observation_height=256 \
|
|
--env.observation_width=256 \
|
|
'--env.camera_name_mapping={\"agentview_image\": \"image\", \"robot0_eye_in_hand_image\": \"wrist_image\"}' \
|
|
--eval.batch_size=1 \
|
|
--eval.n_episodes=1 \
|
|
--eval.use_async_envs=false \
|
|
--policy.device=cuda \
|
|
'--rename_map={\"observation.images.image\": \"observation.images.camera1\", \"observation.images.wrist_image\": \"observation.images.camera2\"}' \
|
|
--policy.empty_cameras=1 \
|
|
--output_dir=/tmp/eval-artifacts
|
|
python scripts/ci/extract_task_descriptions.py \
|
|
--env libero --task libero_10 \
|
|
--output /tmp/eval-artifacts/task_descriptions.json
|
|
"
|
|
|
|
- name: Copy RoboCerebra artifacts from container
|
|
if: always()
|
|
run: |
|
|
mkdir -p /tmp/robocerebra-artifacts
|
|
docker cp robocerebra-eval:/tmp/eval-artifacts/. /tmp/robocerebra-artifacts/ 2>/dev/null || true
|
|
docker rm -f robocerebra-eval || true
|
|
|
|
- name: Parse RoboCerebra eval metrics
|
|
if: always()
|
|
run: |
|
|
python3 scripts/ci/parse_eval_metrics.py \
|
|
--artifacts-dir /tmp/robocerebra-artifacts \
|
|
--env robocerebra \
|
|
--task libero_10 \
|
|
--policy lerobot/smolvla_robocerebra
|
|
|
|
- name: Upload RoboCerebra rollout video
|
|
if: always()
|
|
uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
|
|
with:
|
|
name: robocerebra-rollout-video
|
|
path: /tmp/robocerebra-artifacts/videos/
|
|
if-no-files-found: warn
|
|
|
|
- name: Upload RoboCerebra eval metrics
|
|
if: always()
|
|
uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
|
|
with:
|
|
name: robocerebra-metrics
|
|
path: /tmp/robocerebra-artifacts/metrics.json
|
|
if-no-files-found: warn
|