Files
lerobot/.github/workflows/benchmark_tests.yml
T
Pepijn a147fa4439 feat(envs): add RoboCerebra long-horizon manipulation benchmark (#3314)
* 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>
2026-04-20 19:12:15 +02:00

635 lines
26 KiB
YAML

# 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