refactor(robotwin): rebase docker image on huggingface/lerobot-gpu

Mirror the libero/metaworld/libero_plus/robomme pattern: start from the
nightly GPU image (apt deps, python, uv, venv, lerobot[all] already
there) and layer on only what RoboTwin 2.0 uniquely needs —
cuda-nvcc + cuda-cudart-dev (CuRobo builds from source), Vulkan libs +
NVIDIA ICD (SAPIEN renderer), sapien/mplib/open3d/pytorch3d/curobo
installs, the mplib + sapien upstream patches, and the TianxingChen
asset download.

Drops ~90 lines of duplicated base setup (CUDA FROM, apt python, uv
install, user creation, venv init, base lerobot install). 199 → 110.

Also repoint the docs + env docstring dataset link from
hxma/RoboTwin-LeRobot-v3.0 to the canonical lerobot/robotwin_unified.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

docker/Dockerfile.benchmark.robotwin

@@ -12,188 +12,99 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Isolated benchmark image for RoboTwin 2.0 integration tests.
+# Benchmark image for RoboTwin 2.0 integration tests.
-# Full installation: SAPIEN, mplib, CuRobo, pytorch3d + simulation assets.
+# Extends the nightly GPU image with the RoboTwin simulator stack:
-#
+#   sapien/mplib/pytorch3d + NVlabs CuRobo + embodiments.zip + objects.zip
-# RoboTwin install guide: https://robotwin-platform.github.io/doc/usage/robotwin-install.html
+# (~3.96 GB of assets; background_texture.zip ~11 GB skipped for smoke eval).
-# Assets from: https://huggingface.co/datasets/TianxingChen/RoboTwin2.0
-#   - embodiments.zip  ~220 MB
-#   - objects.zip      ~3.74 GB
-#   (background_texture.zip ~11 GB is skipped — not required for a smoke eval)
 #
 # Build: docker build -f docker/Dockerfile.benchmark.robotwin -t lerobot-benchmark-robotwin .
 # Run:   docker run --gpus all --rm lerobot-benchmark-robotwin \
 #            lerobot-eval --env.type=robotwin --env.task=beat_block_hammer ...
 
-# RoboTwin requires CUDA devel image for CuRobo compilation (nvcc needed).
+FROM huggingface/lerobot-gpu:latest
-# Python 3.12 required by lerobot (type alias syntax). open3d 0.19.0 has cp312 wheels.
-ARG CUDA_VERSION=12.1.1
-ARG OS_VERSION=22.04
-FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${OS_VERSION}
 
-ARG PYTHON_VERSION=3.12
+ENV NVIDIA_DRIVER_CAPABILITIES=all \
-
-ENV DEBIAN_FRONTEND=noninteractive \
-    PATH=/lerobot/.venv/bin:$PATH \
-    CUDA_VISIBLE_DEVICES=0 \
-    DEVICE=cuda \
-    # NVIDIA Container Toolkit: expose all driver capabilities (includes Vulkan)
-    NVIDIA_DRIVER_CAPABILITIES=all \
-    # SAPIEN uses Vulkan; point at the NVIDIA ICD we create below
     VK_ICD_FILENAMES=/usr/share/vulkan/icd.d/nvidia_icd.json \
-    # RoboTwin task modules live in <repo>/envs/; add to PYTHONPATH after clone.
     ROBOTWIN_ROOT=/opt/robotwin
 
-# System deps — extended with cmake/ninja for CuRobo and pytorch3d compilation.
+# The nightly base is CUDA -base (no compiler, no Vulkan loader). CuRobo's
-RUN apt-get update && apt-get install -y --no-install-recommends \
+# `pip install -e .` runs nvcc, and SAPIEN renders via Vulkan — add both.
-    software-properties-common build-essential git curl \
+USER root
-    libglib2.0-0 libgl1-mesa-glx libegl1-mesa ffmpeg \
+RUN apt-get update \
-    libusb-1.0-0-dev speech-dispatcher libgeos-dev portaudio19-dev \
-    cmake pkg-config ninja-build \
-    libvulkan1 vulkan-tools \
-    && add-apt-repository -y ppa:deadsnakes/ppa \
-    && apt-get update \
     && apt-get install -y --no-install-recommends \
-       python${PYTHON_VERSION} \
+         cuda-nvcc-12-4 cuda-cudart-dev-12-4 \
-       python${PYTHON_VERSION}-venv \
+         libvulkan1 vulkan-tools \
-       python${PYTHON_VERSION}-dev \
-    && curl -LsSf https://astral.sh/uv/0.8.0/install.sh | sh \
-    && mv /root/.local/bin/uv /usr/local/bin/uv \
     && mkdir -p /usr/share/vulkan/icd.d \
     && echo '{"file_format_version":"1.0.0","ICD":{"library_path":"libGLX_nvidia.so.0","api_version":"1.3.0"}}' \
        > /usr/share/vulkan/icd.d/nvidia_icd.json \
-    && useradd --create-home --shell /bin/bash user_lerobot \
+    && git clone --depth=1 https://github.com/RoboTwin-Platform/RoboTwin.git ${ROBOTWIN_ROOT} \
-    && usermod -aG sudo user_lerobot \
+    && chown -R user_lerobot:user_lerobot ${ROBOTWIN_ROOT} \
     && apt-get clean && rm -rf /var/lib/apt/lists/*
-
-WORKDIR /lerobot
-RUN chown -R user_lerobot:user_lerobot /lerobot
 USER user_lerobot
 
-ENV HOME=/home/user_lerobot \
+# RoboTwin runtime deps (av is already in the base via [av-dep]).
-    HF_HOME=/home/user_lerobot/.cache/huggingface \
+RUN uv pip install --no-cache \
-    HF_LEROBOT_HOME=/home/user_lerobot/.cache/huggingface/lerobot \
+        "sapien==3.0.0b1" "mplib==0.2.1" "transforms3d==0.4.2" "trimesh==4.4.3" \
-    TORCH_HOME=/home/user_lerobot/.cache/torch \
+        "open3d==0.19.0" "imageio==2.34.2" termcolor zarr pydantic h5py
-    TRITON_CACHE_DIR=/home/user_lerobot/.cache/triton
 
-RUN uv venv --python python${PYTHON_VERSION}
+# pytorch3d has no universal wheel; must be built from source (~10 min, cached).
+RUN uv pip install --no-cache --no-build-isolation \
+        "git+https://github.com/facebookresearch/pytorch3d.git@stable"
 
-# ── 1. Install base lerobot ────────────────────────────────────────────────
+# CuRobo — NVlabs motion generator; TORCH_CUDA_ARCH_LIST must be set or the
-COPY --chown=user_lerobot:user_lerobot setup.py pyproject.toml uv.lock README.md MANIFEST.in ./
+# build aborts on an empty arch list.
-COPY --chown=user_lerobot:user_lerobot src/ src/
-
-# Install lerobot base only (no benchmark extras — RoboTwin is source-only).
-# smolvla → transformers for SmolVLA policy; av-dep → PyAV for MP4 rollout videos.
-RUN uv pip install --no-cache -e ".[smolvla,av-dep]"
-
-# ── 2. Install RoboTwin 2.0 simulator stack ────────────────────────────────
-# Clone at a pinned commit for reproducibility.
-USER root
-RUN git clone --depth=1 https://github.com/RoboTwin-Platform/RoboTwin.git ${ROBOTWIN_ROOT} \
-    && chown -R user_lerobot:user_lerobot ${ROBOTWIN_ROOT}
-USER user_lerobot
-
-# Install RoboTwin-specific packages on top of the lerobot venv.
-# We intentionally skip: torch/torchvision (already in lerobot), gymnasium
-# (lerobot uses 1.x; RoboTwin's API is wrapped so 0.29 is not needed), scipy
-# (version-pinned by lerobot), huggingface_hub (pinned by lerobot), wandb,
-# azure, openai, pyglet (UI only).
-# Install RoboTwin-specific packages. Use --python to pin resolution to the
-# venv's Python 3.10 (uv sync --locked may have changed the default target).
-RUN uv pip install --no-cache --python .venv/bin/python \
-    "sapien==3.0.0b1" \
-    "mplib==0.2.1" \
-    "transforms3d==0.4.2" \
-    "trimesh==4.4.3" \
-    "open3d==0.19.0" \
-    "imageio==2.34.2" \
-    "termcolor" \
-    "zarr" \
-    "pydantic" \
-    "h5py"
-
-# pytorch3d — must be built from source (no universal wheel available).
-# This is the slowest step (~10 min); cached in subsequent builds.
-RUN uv pip install --no-cache --no-build-isolation --python .venv/bin/python \
-    "git+https://github.com/facebookresearch/pytorch3d.git@stable"
-
-# CuRobo — NVIDIA motion generation library; requires nvcc (devel image).
-# TORCH_CUDA_ARCH_LIST must be set or the build fails with empty arch list.
 RUN cd ${ROBOTWIN_ROOT}/envs \
     && git clone --depth=1 https://github.com/NVlabs/curobo.git \
     && cd curobo \
     && TORCH_CUDA_ARCH_LIST="7.0;7.5;8.0;8.6;8.9;9.0" \
        uv pip install -e . --no-build-isolation --no-cache
 
-# ── 3. Apply upstream patches (mirrors script/_install.sh) ─────────────────
+# Upstream patches (mirror RoboTwin's script/_install.sh).
-# patch 1: mplib — remove `or collide` from planner.py line 807.
+# mplib: drop a broken `or collide` clause in planner.py.
+# sapien: fix URDF loader encoding + .srdf extension check.
 RUN python - <<'EOF'
-import re, pathlib, site
+import pathlib, re, site
 for d in site.getsitepackages():
     p = pathlib.Path(d) / "mplib" / "planner.py"
     if p.exists():
-        src = p.read_text()
+        p.write_text(re.sub(r"\bor collide\b", "", p.read_text(), count=1))
-        patched = re.sub(r"\bor collide\b", "", src, count=1)
-        p.write_text(patched)
         print(f"mplib patch applied: {p}")
-        break
-EOF
-
-# patch 2: sapien URDF loader — add UTF-8 encoding + fix .srdf extension.
-RUN python - <<'EOF'
-import pathlib, site
-for d in site.getsitepackages():
     p = pathlib.Path(d) / "sapien" / "wrapper" / "urdf_loader.py"
     if p.exists():
-        src = p.read_text()
+        src = p.read_text().replace(
-        # add encoding='utf-8' to open() calls that lack it
+            "with open(srdf_path) as f:", 'with open(srdf_path, encoding="utf-8") as f:'
-        patched = src.replace("open(", "open(").replace(
-            'with open(srdf_path) as f:', 'with open(srdf_path, encoding="utf-8") as f:'
         ).replace('"srdf"', '".srdf"')
-        p.write_text(patched)
+        p.write_text(src)
         print(f"sapien patch applied: {p}")
-        break
 EOF
 
-# ── 4. Download simulation assets from HuggingFace ─────────────────────────
+# Simulation assets from TianxingChen/RoboTwin2.0: embodiments (~220 MB) +
-# embodiments.zip (~220 MB) + objects.zip (~3.74 GB).
+# objects (~3.74 GB). background_texture (~11 GB) is intentionally skipped.
-# background_texture.zip (~11 GB) is skipped — not required for a smoke eval.
-# Set HF_TOKEN (passed as --build-arg or via --secret) for authenticated access.
 ARG HF_TOKEN=""
 RUN python - <<'EOF'
 import os, pathlib, zipfile
 from huggingface_hub import hf_hub_download
 
-token = os.environ.get("HF_TOKEN") or None
 assets_dir = pathlib.Path(os.environ["ROBOTWIN_ROOT"]) / "assets"
 assets_dir.mkdir(parents=True, exist_ok=True)
-
 for fname in ("embodiments.zip", "objects.zip"):
-    print(f"Downloading {fname} ...")
     local = hf_hub_download(
         repo_id="TianxingChen/RoboTwin2.0",
         repo_type="dataset",
         filename=fname,
-        token=token,
+        token=os.environ.get("HF_TOKEN") or None,
         local_dir=str(assets_dir),
     )
-    print(f"Extracting {fname} ...")
     with zipfile.ZipFile(local, "r") as z:
         z.extractall(str(assets_dir))
-    pathlib.Path(local).unlink()  # remove zip after extraction
+    pathlib.Path(local).unlink()
-    print(f"{fname} done.")
 EOF
 
-# Update embodiment config paths to reflect the installation directory.
+RUN cd ${ROBOTWIN_ROOT} && python script/update_embodiment_config_path.py
-RUN cd ${ROBOTWIN_ROOT} \
-    && python script/update_embodiment_config_path.py
 
-# ── 5. Finalise ────────────────────────────────────────────────────────────
-# Expose RoboTwin task modules on PYTHONPATH so `import envs.<task>` works.
 ENV PYTHONPATH="${ROBOTWIN_ROOT}:${PYTHONPATH}"
 
+# Overlay the PR's source code on top of the nightly image.
 COPY --chown=user_lerobot:user_lerobot . .
 
-RUN chmod +x /lerobot/.venv/lib/python${PYTHON_VERSION}/site-packages/triton/backends/nvidia/bin/ptxas 2>/dev/null || true
-
 CMD ["/bin/bash"]

docs/source/robotwin.mdx

@@ -5,7 +5,7 @@ RoboTwin 2.0 is a **large-scale dual-arm manipulation benchmark** built on the S
 - Paper: [RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation](https://robotwin-platform.github.io)
 - GitHub: [RoboTwin-Platform/RoboTwin](https://github.com/RoboTwin-Platform/RoboTwin)
 - Leaderboard: [robotwin-platform.github.io/leaderboard](https://robotwin-platform.github.io/leaderboard)
-- Dataset: [hxma/RoboTwin-LeRobot-v3.0](https://huggingface.co/datasets/hxma/RoboTwin-LeRobot-v3.0)
+- Dataset: [lerobot/robotwin_unified](https://huggingface.co/datasets/lerobot/robotwin_unified)
 
 ## Overview
 
@@ -41,7 +41,7 @@ Pass a comma-separated list to `--env.task` to run multiple tasks in a single ev
 The RoboTwin 2.0 dataset is available in **LeRobot v3.0 format** on the Hugging Face Hub:
 
 ```
-hxma/RoboTwin-LeRobot-v3.0
+lerobot/robotwin_unified
 ```
 
 It contains over 100,000 pre-collected trajectories across all 60 tasks (79.6 GB, Apache 2.0 license). No format conversion is needed — it is already in the correct LeRobot v3.0 schema with video observations and action labels.
@@ -51,7 +51,7 @@ You can load it directly with the HF Datasets library:
 ```python
 from datasets import load_dataset
 
-ds = load_dataset("hxma/RoboTwin-LeRobot-v3.0", split="train")
+ds = load_dataset("lerobot/robotwin_unified", split="train")
 ```
 
 ## Installation

src/lerobot/envs/configs.py

@@ -586,7 +586,7 @@ class RoboTwinEnvConfig(EnvConfig):
     (7 per arm). All four cameras are enabled by default.
 
     See: https://robotwin-platform.github.io
-    Dataset: https://huggingface.co/datasets/hxma/RoboTwin-LeRobot-v3.0
+    Dataset: https://huggingface.co/datasets/lerobot/robotwin_unified
     """
 
     task: str = "beat_block_hammer"  # single task or comma-separated list