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lerobot/.github/workflows/benchmark_tests.yml
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Pepijn 5adad11128 feat(sim): VLABench benchmark integration (#3396)
feat(sim): add VLABench benchmark integration
Add VLABench as a new simulation benchmark in LeRobot, following the existing LIBERO and MetaWorld patterns.
This PR wires VLABench end-to-end across environment integration, Docker setup, CI smoke evaluation, and documentation. It also fixes a number of upstream packaging and runtime issues required to make VLABench usable and reproducible in CI.
What’s included
Benchmark integration
Add VLABench as a new simulation benchmark.
Expose supported VLABench tasks through the LeRobot env interface.
Follow the established LIBERO / MetaWorld factory patterns.
Preserve lazy async-env metadata so env.unwrapped.metadata["render_fps"] continues to work.
CI smoke evaluation
Add a VLABench smoke-eval job using lerobot/smolvla_vlabench.
Use the correct rename_map for the 3-camera dataset layout.
Expand smoke coverage from 1 to 10 primitive tasks.
Extract task descriptions after eval so metrics artifacts include per-task labels.
Skip Docker Hub login when secrets are unavailable (e.g. fork PRs).
Docker / install fixes
Install VLABench from GitHub rather than PyPI.
Use uv pip, not pip, in the base image.
Fail loudly on install errors instead of masking them.
Clone VLABench into the non-root user’s home directory.
Use shallow editable installs for VLABench and rrt-algorithms to work around missing __init__.py issues.
Pin upstream clones to exact commit SHAs for reproducibility.
Add undeclared runtime dependencies required by VLABench (open3d, colorlog, scikit-learn, openai).
Unpin open3d so Python 3.12 wheels resolve.
Assets
Support downloading VLABench assets from a Hugging Face Hub mirror via VLABENCH_ASSETS_REPO.
Keep Google Drive download support as fallback.
Install huggingface_hub[hf_xet] so Xet-backed assets download correctly.
Validate required mesh/XML asset subtrees at build time.
Patch VLABench constants to tolerate missing asset directories at import time.
Runtime / env correctness
Import VLABench robots and tasks explicitly so decorator-based registry population happens.
Resize and normalize camera observations so they always match the declared (H, W, 3) uint8 observation space.
Reinstall LeRobot editably inside the image so the new env code is actually used.
Coerce agent_pos / ee_state to the expected shape.
Pad actions when needed to match data.ctrl.
Replace zero-padding fallback with proper dm_control IK for 7D end-effector actions.
Refetch dm_control physics on each step instead of caching weakrefs.
Retry unstable resets with reseeding and handle PhysicsError gracefully at step time.
Dataset / policy alignment
Align VLABench observations and actions with Hugging Face dataset conventions used by lerobot/vlabench_unified:
convert EE position between world frame and robot-base frame at the env boundary,
expose / consume Euler XYZ instead of raw quaternion layout,
align gripper semantics with dataset convention (1 = open, 0 = closed).
This fixes policy/env mismatches that previously caused incorrect IK targets and unstable behavior at evaluation time.
Docs
Add a full docs/source/vlabench.mdx page aligned with the standard benchmark template.
Document task selection forms (single task, comma list, suite shortcut).
Document installation, evaluation, training, and result reproduction.
Point examples at lerobot/smolvla_vlabench.
Add a benchmark banner image.
Remove outdated / misleading references to upstream evaluation tracks.
Document manual install flow instead of a broken vlabench extra.
Packaging cleanup
Remove the unresolvable vlabench extra from pyproject.toml.
Remove the no-op VLABench processor step.
Remove the obsolete env unit test that only covered the dropped gripper remap helper.
Apply formatting / logging / style cleanup from review feedback.
Why this is needed
VLABench is not currently consumable as a normal Python dependency and requires several upstream workarounds:
no PyPI release,
missing package declarations,
undeclared runtime deps,
SSH-only submodule references,
asset downloads outside normal package install flow,
registry population that depends on import side effects,
env outputs that do not always match declared observation shapes,
task resets that can diverge under some random layouts.
This PR makes the benchmark usable in LeRobot despite those constraints, and ensures CI runs are reproducible and informative.
If you want a much shorter squash commit message, I’d use this:
feat(sim): integrate VLABench benchmark with CI, Docker, and docs
Add VLABench as a new LeRobot simulation benchmark, following the existing LIBERO / MetaWorld patterns.
This includes:
LeRobot env integration and task exposure,
CI smoke eval with lerobot/smolvla_vlabench,
Docker install and asset-download fixes,
runtime fixes for registry loading, assets, camera obs, action handling, dm_control IK, and PhysicsError recovery,
alignment of obs/action semantics with HF VLABench datasets,
docs and packaging cleanup.
The PR also incorporates review feedback, improves reproducibility by pinning upstream commits, and makes VLABench usable in CI despite upstream packaging and asset-management issues.
2026-04-21 17:54:11 +02:00

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# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# Integration tests: build an isolated Docker image per benchmark and run a
# 1-episode smoke eval. Each benchmark gets its own image so incompatible
# dependency trees (e.g. hf-libero vs metaworld==3.0.0) can never collide.
#
# To add a new benchmark:
# 1. Add docker/Dockerfile.benchmark.<name> (install only lerobot[<name>])
# 2. Copy one of the jobs below and adjust the image name and eval command.
name: Benchmark Integration Tests
on:
# Run manually from the Actions tab
workflow_dispatch:
# Run every Monday at 02:00 UTC.
schedule:
- cron: "0 2 * * 1"
push:
branches:
- main
paths:
- "src/lerobot/envs/**"
- "src/lerobot/scripts/lerobot_eval.py"
- "docker/Dockerfile.benchmark.*"
- ".github/workflows/benchmark_tests.yml"
- "pyproject.toml"
pull_request:
branches:
- main
paths:
- "src/lerobot/envs/**"
- "src/lerobot/scripts/lerobot_eval.py"
- "docker/Dockerfile.benchmark.*"
- ".github/workflows/benchmark_tests.yml"
- "pyproject.toml"
permissions:
contents: read
env:
UV_VERSION: "0.8.0"
PYTHON_VERSION: "3.12"
# Cancel in-flight runs for the same branch/PR.
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
# ── LIBERO ────────────────────────────────────────────────────────────────
# Isolated image: lerobot[libero] only (hf-libero, dm-control, mujoco chain)
libero-integration-test:
name: Libero — 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: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
# Build the benchmark-specific image. The Dockerfile separates dep-install
# from source-copy, so code-only changes skip the slow uv-sync layer
# when the runner has a warm Docker daemon cache.
- name: Build Libero benchmark image
uses: docker/build-push-action@v6 # zizmor: ignore[unpinned-uses]
with:
context: .
file: docker/Dockerfile.benchmark.libero
push: false
load: true
tags: lerobot-benchmark-libero:ci
- name: Run Libero smoke eval (1 episode)
if: env.HF_USER_TOKEN != ''
run: |
# Named container (no --rm) so we can docker cp artifacts out.
# Output to /tmp inside the container — /artifacts doesn't exist
# and user_lerobot cannot create root-level dirs.
docker run --name libero-eval --gpus all \
--shm-size=4g \
-e HF_HOME=/tmp/hf \
-e HF_USER_TOKEN="${HF_USER_TOKEN}" \
-e HF_HUB_DOWNLOAD_TIMEOUT=300 \
lerobot-benchmark-libero:ci \
bash -c "
hf auth login --token \"\$HF_USER_TOKEN\" --add-to-git-credential 2>/dev/null || true
lerobot-eval \
--policy.path=lerobot/smolvla_libero \
--env.type=libero \
--env.task=libero_spatial \
--eval.batch_size=1 \
--eval.n_episodes=1 \
--eval.use_async_envs=false \
--policy.device=cuda \
'--env.camera_name_mapping={\"agentview_image\": \"camera1\", \"robot0_eye_in_hand_image\": \"camera2\"}' \
--policy.empty_cameras=1 \
--output_dir=/tmp/eval-artifacts
python scripts/ci/extract_task_descriptions.py \
--env libero --task libero_spatial \
--output /tmp/eval-artifacts/task_descriptions.json
"
- name: Copy Libero artifacts from container
if: always()
run: |
mkdir -p /tmp/libero-artifacts
docker cp libero-eval:/tmp/eval-artifacts/. /tmp/libero-artifacts/ 2>/dev/null || true
docker rm -f libero-eval || true
- name: Parse Libero eval metrics
if: always()
run: |
python3 scripts/ci/parse_eval_metrics.py \
--artifacts-dir /tmp/libero-artifacts \
--env libero \
--task libero_spatial \
--policy lerobot/smolvla_libero
- name: Upload Libero rollout video
if: always()
uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
with:
name: libero-rollout-video
path: /tmp/libero-artifacts/videos/
if-no-files-found: warn
- name: Upload Libero eval metrics
if: always()
uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
with:
name: libero-metrics
path: /tmp/libero-artifacts/metrics.json
if-no-files-found: warn
# ── LIBERO TRAIN+EVAL SMOKE ──────────────────────────────────────────────
# Train SmolVLA for 1 step (batch_size=1, dataset episode 0 only) then
# immediately runs eval inside the training loop (eval_freq=1, 1 episode).
# Tests the full train→eval-within-training pipeline end-to-end.
- name: Run Libero train+eval smoke (1 step, eval_freq=1)
if: env.HF_USER_TOKEN != ''
run: |
docker run --name libero-train-smoke --gpus all \
--shm-size=4g \
-e HF_HOME=/tmp/hf \
-e HF_USER_TOKEN="${HF_USER_TOKEN}" \
-e HF_HUB_DOWNLOAD_TIMEOUT=300 \
lerobot-benchmark-libero:ci \
bash -c "
hf auth login --token \"\$HF_USER_TOKEN\" --add-to-git-credential 2>/dev/null || true
accelerate launch --num_processes=1 \$(which lerobot-train) \
--policy.path=lerobot/smolvla_base \
--policy.load_vlm_weights=true \
--policy.scheduler_decay_steps=25000 \
--policy.freeze_vision_encoder=false \
--policy.train_expert_only=false \
--dataset.repo_id=lerobot/libero \
--dataset.episodes=[0] \
--dataset.use_imagenet_stats=false \
--env.type=libero \
--env.task=libero_spatial \
'--env.camera_name_mapping={\"agentview_image\": \"camera1\", \"robot0_eye_in_hand_image\": \"camera2\"}' \
--policy.empty_cameras=1 \
--output_dir=/tmp/train-smoke \
--steps=1 \
--batch_size=1 \
--eval_freq=1 \
--eval.n_episodes=1 \
--eval.batch_size=1 \
--eval.use_async_envs=false \
--save_freq=1 \
--policy.push_to_hub=false \
'--rename_map={\"observation.images.image\": \"observation.images.camera1\", \"observation.images.image2\": \"observation.images.camera2\"}'
"
- name: Copy Libero train-smoke artifacts from container
if: always()
run: |
mkdir -p /tmp/libero-train-smoke-artifacts
docker cp libero-train-smoke:/tmp/train-smoke/. /tmp/libero-train-smoke-artifacts/ 2>/dev/null || true
docker rm -f libero-train-smoke || true
- name: Upload Libero train-smoke eval video
if: always()
uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
with:
name: libero-train-smoke-video
path: /tmp/libero-train-smoke-artifacts/eval/
if-no-files-found: warn
# ── METAWORLD ─────────────────────────────────────────────────────────────
# Isolated image: lerobot[metaworld] only (metaworld==3.0.0, mujoco>=3 chain)
metaworld-integration-test:
name: MetaWorld — 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: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
- name: Build MetaWorld benchmark image
uses: docker/build-push-action@v6 # zizmor: ignore[unpinned-uses]
with:
context: .
file: docker/Dockerfile.benchmark.metaworld
push: false
load: true
tags: lerobot-benchmark-metaworld:ci
- name: Run MetaWorld smoke eval (1 episode)
if: env.HF_USER_TOKEN != ''
run: |
docker run --name metaworld-eval --gpus all \
--shm-size=4g \
-e HF_HOME=/tmp/hf \
-e HF_USER_TOKEN="${HF_USER_TOKEN}" \
-e HF_HUB_DOWNLOAD_TIMEOUT=300 \
lerobot-benchmark-metaworld:ci \
bash -c "
hf auth login --token \"\$HF_USER_TOKEN\" --add-to-git-credential 2>/dev/null || true
lerobot-eval \
--policy.path=lerobot/smolvla_metaworld \
--env.type=metaworld \
--env.task=metaworld-push-v3 \
--eval.batch_size=1 \
--eval.n_episodes=1 \
--eval.use_async_envs=false \
--policy.device=cuda \
'--rename_map={\"observation.image\": \"observation.images.camera1\"}' \
--policy.empty_cameras=2 \
--output_dir=/tmp/eval-artifacts
python scripts/ci/extract_task_descriptions.py \
--env metaworld --task metaworld-push-v3 \
--output /tmp/eval-artifacts/task_descriptions.json
"
- name: Copy MetaWorld artifacts from container
if: always()
run: |
mkdir -p /tmp/metaworld-artifacts
docker cp metaworld-eval:/tmp/eval-artifacts/. /tmp/metaworld-artifacts/ 2>/dev/null || true
docker rm -f metaworld-eval || true
- name: Parse MetaWorld eval metrics
if: always()
run: |
python3 scripts/ci/parse_eval_metrics.py \
--artifacts-dir /tmp/metaworld-artifacts \
--env metaworld \
--task metaworld-push-v3 \
--policy lerobot/smolvla_metaworld
- name: Upload MetaWorld rollout video
if: always()
uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
with:
name: metaworld-rollout-video
path: /tmp/metaworld-artifacts/videos/
if-no-files-found: warn
- name: Upload MetaWorld eval metrics
if: always()
uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
with:
name: metaworld-metrics
path: /tmp/metaworld-artifacts/metrics.json
if-no-files-found: warn
# ── ROBOTWIN 2.0 ──────────────────────────────────────────────────────────
# Isolated image: full RoboTwin 2.0 stack — SAPIEN, mplib, CuRobo,
# pytorch3d, + simulation assets (~4 GB).
# Build takes ~20 min on first run; subsequent runs hit the layer cache.
# Requires an NVIDIA GPU runner with CUDA 12.1 drivers.
robotwin-integration-test:
name: RoboTwin 2.0 — build image + 1-episode eval
runs-on:
group: aws-g6-4xlarge-plus
env:
HF_USER_TOKEN: ${{ secrets.LEROBOT_HF_USER }}
ROBOTWIN_POLICY: lerobot/smolvla_robotwin
ROBOTWIN_TASKS: beat_block_hammer,click_bell,handover_block,stack_blocks_two,click_alarmclock,open_microwave,adjust_bottle,lift_pot,stamp_seal,turn_switch
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: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
# Build the full-install image: SAPIEN, mplib, CuRobo, pytorch3d +
# simulation assets (~4 GB). Layer cache lives in the runner's local
# Docker daemon — reused across re-runs on the same machine.
- name: Build RoboTwin 2.0 benchmark image
uses: docker/build-push-action@v6 # zizmor: ignore[unpinned-uses]
with:
context: .
file: docker/Dockerfile.benchmark.robotwin
push: false
load: true
tags: lerobot-benchmark-robotwin:ci
cache-from: type=local,src=/tmp/.buildx-cache-robotwin
cache-to: type=local,dest=/tmp/.buildx-cache-robotwin,mode=max
- name: Run RoboTwin 2.0 smoke eval (10 tasks, 1 episode each)
if: env.HF_USER_TOKEN != ''
run: |
# Named container (no --rm) so we can docker cp artifacts out.
docker run --name robotwin-eval --gpus all \
--shm-size=4g \
-e HF_HOME=/tmp/hf \
-e HF_USER_TOKEN="${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
# ── ROBOMME ───────────────────────────────────────────────────────────────
# Isolated image: mani-skill/SAPIEN/Vulkan chain with gymnasium and numpy
# overrides (robomme can't be a pyproject extra due to numpy<2 pin).
robomme-integration-test:
name: RoboMME — build image + 1-episode eval
runs-on:
group: aws-g6-4xlarge-plus
env:
HF_USER_TOKEN: ${{ secrets.LEROBOT_HF_USER }}
ROBOMME_POLICY: lerobot/smolvla_robomme
ROBOMME_TASKS: PickXtimes,BinFill,StopCube,MoveCube,InsertPeg,SwingXtimes,VideoUnmask,ButtonUnmask,PickHighlight,PatternLock
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: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
- name: Build RoboMME benchmark image
uses: docker/build-push-action@v6 # zizmor: ignore[unpinned-uses]
with:
context: .
file: docker/Dockerfile.benchmark.robomme
push: false
load: true
tags: lerobot-benchmark-robomme:ci
- name: Run RoboMME smoke eval (10 tasks, 1 episode each)
if: env.HF_USER_TOKEN != ''
run: |
docker run --name robomme-eval --gpus all \
--shm-size=4g \
-e HF_HOME=/tmp/hf \
-e HF_USER_TOKEN="${HF_USER_TOKEN}" \
-e HF_HUB_DOWNLOAD_TIMEOUT=300 \
-e ROBOMME_POLICY="${ROBOMME_POLICY}" \
-e ROBOMME_TASKS="${ROBOMME_TASKS}" \
lerobot-benchmark-robomme:ci \
bash -c "
hf auth login --token \"\$HF_USER_TOKEN\" --add-to-git-credential 2>/dev/null || true
lerobot-eval \
--policy.path=\"\$ROBOMME_POLICY\" \
--env.type=robomme \
--env.task=\"\$ROBOMME_TASKS\" \
--env.dataset_split=test \
--env.task_ids=[0] \
--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=3 \
--output_dir=/tmp/eval-artifacts
python scripts/ci/extract_task_descriptions.py \
--env robomme --task \"\$ROBOMME_TASKS\" \
--output /tmp/eval-artifacts/task_descriptions.json
"
- name: Copy RoboMME artifacts from container
if: always()
run: |
mkdir -p /tmp/robomme-artifacts
docker cp robomme-eval:/tmp/eval-artifacts/. /tmp/robomme-artifacts/ 2>/dev/null || true
docker rm -f robomme-eval || true
- name: Parse RoboMME eval metrics
if: always()
run: |
python3 scripts/ci/parse_eval_metrics.py \
--artifacts-dir /tmp/robomme-artifacts \
--env robomme \
--task "${ROBOMME_TASKS}" \
--policy "${ROBOMME_POLICY}"
- name: Upload RoboMME rollout video
if: always()
uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
with:
name: robomme-rollout-video
path: /tmp/robomme-artifacts/videos/
if-no-files-found: warn
- name: Upload RoboMME eval metrics
if: always()
uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
with:
name: robomme-metrics
path: /tmp/robomme-artifacts/metrics.json
if-no-files-found: warn
# ── LIBERO-plus ───────────────────────────────────────────────────────────
# Isolated image: LIBERO-plus fork cloned into /home/user_lerobot on top of
# huggingface/lerobot-gpu (see docker/Dockerfile.benchmark.libero_plus).
libero-plus-integration-test:
name: LIBERO-plus — build image + 1-episode eval
runs-on:
group: aws-g6-4xlarge-plus
env:
HF_USER_TOKEN: ${{ secrets.LEROBOT_HF_USER }}
LIBERO_PLUS_SUITE: libero_spatial
LIBERO_PLUS_POLICY: lerobot/smolvla_libero_plus
LIBERO_PLUS_TASK_IDS: "[0,100,260,500,1000,1500,2000,2400]"
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: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
- name: Build LIBERO-plus benchmark image
uses: docker/build-push-action@v6 # zizmor: ignore[unpinned-uses]
with:
context: .
file: docker/Dockerfile.benchmark.libero_plus
push: false
load: true
tags: lerobot-benchmark-libero-plus:ci
cache-from: type=local,src=/tmp/.buildx-cache-libero-plus
cache-to: type=local,dest=/tmp/.buildx-cache-libero-plus,mode=max
- name: Run LIBERO-plus smoke eval (1 episode)
if: env.HF_USER_TOKEN != ''
run: |
docker run --name libero-plus-eval --gpus all \
--shm-size=4g \
-e HF_HOME=/tmp/hf \
-e HF_USER_TOKEN="${HF_USER_TOKEN}" \
-e HF_HUB_DOWNLOAD_TIMEOUT=300 \
-e LIBERO_PLUS_SUITE="${LIBERO_PLUS_SUITE}" \
-e LIBERO_PLUS_POLICY="${LIBERO_PLUS_POLICY}" \
-e LIBERO_PLUS_TASK_IDS="${LIBERO_PLUS_TASK_IDS}" \
lerobot-benchmark-libero-plus:ci \
bash -c "
hf auth login --token \"\$HF_USER_TOKEN\" --add-to-git-credential 2>/dev/null || true
lerobot-eval \
--policy.path=\"\$LIBERO_PLUS_POLICY\" \
--env.type=libero_plus \
--env.task=\"\$LIBERO_PLUS_SUITE\" \
--env.task_ids=\"\$LIBERO_PLUS_TASK_IDS\" \
--eval.batch_size=1 \
--eval.n_episodes=1 \
--eval.use_async_envs=false \
--policy.device=cuda \
'--env.camera_name_mapping={\"agentview_image\": \"camera1\", \"robot0_eye_in_hand_image\": \"camera2\"}' \
--policy.empty_cameras=1 \
--output_dir=/tmp/eval-artifacts
python scripts/ci/extract_task_descriptions.py \
--env libero_plus --task \"\$LIBERO_PLUS_SUITE\" \
--output /tmp/eval-artifacts/task_descriptions.json
"
- name: Copy LIBERO-plus artifacts from container
if: always()
run: |
mkdir -p /tmp/libero-plus-artifacts
docker cp libero-plus-eval:/tmp/eval-artifacts/. /tmp/libero-plus-artifacts/ 2>/dev/null || true
docker rm -f libero-plus-eval || true
- name: Parse LIBERO-plus eval metrics
if: always()
run: |
python3 scripts/ci/parse_eval_metrics.py \
--artifacts-dir /tmp/libero-plus-artifacts \
--env libero_plus \
--task "${LIBERO_PLUS_SUITE}" \
--policy "${LIBERO_PLUS_POLICY}"
- name: Upload LIBERO-plus rollout video
if: always()
uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
with:
name: libero-plus-rollout-video
path: /tmp/libero-plus-artifacts/videos/
if-no-files-found: warn
- name: Upload LIBERO-plus eval metrics
if: always()
uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
with:
name: libero-plus-metrics
path: /tmp/libero-plus-artifacts/metrics.json
if-no-files-found: warn
# ── VLABENCH ─────────────────────────────────────────────────────────────
# Isolated image: lerobot[vlabench] only (VLABench, mujoco==3.2.2, dm-control chain)
vlabench-integration-test:
name: VLABench — 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: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
- name: Build VLABench benchmark image
uses: docker/build-push-action@v6 # zizmor: ignore[unpinned-uses]
with:
context: .
file: docker/Dockerfile.benchmark.vlabench
push: false
load: true
tags: lerobot-benchmark-vlabench:ci
build-args: |
VLABENCH_ASSETS_REPO=lerobot/vlabench-assets
- name: Run VLABench smoke eval (10 tasks, 1 episode each)
if: env.HF_USER_TOKEN != ''
run: |
docker run --name vlabench-eval --gpus all \
--shm-size=4g \
-e HF_HOME=/tmp/hf \
-e HF_USER_TOKEN="${HF_USER_TOKEN}" \
-e HF_HUB_DOWNLOAD_TIMEOUT=300 \
-e MUJOCO_GL=egl \
lerobot-benchmark-vlabench:ci \
bash -c "
hf auth login --token \"\$HF_USER_TOKEN\" --add-to-git-credential 2>/dev/null || true
lerobot-eval \
--policy.path=lerobot/smolvla_vlabench \
--env.type=vlabench \
--env.task=select_fruit,select_toy,select_book,select_painting,select_drink,select_ingredient,select_billiards,select_poker,add_condiment,insert_flower \
--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.second_image\": \"observation.images.camera2\", \"observation.images.wrist_image\": \"observation.images.camera3\"}' \
--output_dir=/tmp/eval-artifacts
python scripts/ci/extract_task_descriptions.py \
--env vlabench \
--task select_fruit,select_toy,select_book,select_painting,select_drink,select_ingredient,select_billiards,select_poker,add_condiment,insert_flower \
--output /tmp/eval-artifacts/task_descriptions.json
"
- name: Copy VLABench artifacts from container
if: always()
run: |
mkdir -p /tmp/vlabench-artifacts
docker cp vlabench-eval:/tmp/eval-artifacts/. /tmp/vlabench-artifacts/ 2>/dev/null || true
docker rm -f vlabench-eval || true
- name: Parse VLABench eval metrics
if: always()
run: |
python3 scripts/ci/parse_eval_metrics.py \
--artifacts-dir /tmp/vlabench-artifacts \
--env vlabench \
--task select_fruit,select_toy,select_book,select_painting,select_drink,select_ingredient,select_billiards,select_poker,add_condiment,insert_flower \
--policy lerobot/smolvla_vlabench
- name: Upload VLABench rollout video
if: always()
uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
with:
name: vlabench-rollout-video
path: /tmp/vlabench-artifacts/videos/
if-no-files-found: warn
- name: Upload VLABench eval metrics
if: always()
uses: actions/upload-artifact@v4 # zizmor: ignore[unpinned-uses]
with:
name: vlabench-metrics
path: /tmp/vlabench-artifacts/metrics.json
if-no-files-found: warn