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lerobot/docker/Dockerfile.benchmark.robotwin
T
Pepijn 1157fb11e6 fix: integrate PR #3315 review feedback
- envs(robotwin): default `observation_height/width` in
  `create_robotwin_envs` to `DEFAULT_CAMERA_H/W` (240/320) so they
  match the D435 dims baked into `task_config/demo_clean.yml`.
- envs(robotwin): resolve `task_config/demo_clean.yml` via
  `CONFIGS_PATH` instead of a cwd-relative path; works regardless
  of where `lerobot-eval` is invoked.
- envs(robotwin): replace `print()` calls in `create_robotwin_envs`
  with `logger.info(...)` (module-level `logger = logging.getLogger`).
- envs(robotwin): use `_LazyAsyncVectorEnv` for the async path so
  async workers start lazily (matches LIBERO / RoboCasa / VLABench).
- envs(robotwin): cast `agent_pos` space + joint-state output to
  float32 end-to-end (was mixed float64/float32).
- envs(configs): use the existing `_make_vec_env_cls(use_async,
  n_envs)` helper in `RoboTwinEnvConfig.create_envs`; drop the
  `get_env_processors` override so RoboTwin uses the identity
  processor inherited from `EnvConfig`.
- processor: delete `RoboTwinProcessorStep` — the float32 cast now
  happens in the wrapper itself, so the processor is redundant.
- tests: drop the `TestRoboTwinProcessorStep` suite; update the
  mock obs fixture to use float32 `joint_action.vector`.
- ci: hoist `ROBOTWIN_POLICY` and `ROBOTWIN_TASKS` to job-level
  env vars so the task list and policy aren't duplicated across
  eval / extract / parse steps.
- docker: pin RoboTwin + CuRobo upstream clones to commit SHAs
  (`RoboTwin@0aeea2d6`, `curobo@ca941586`) for reproducibility.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-20 15:18:41 +02:00

123 lines
5.2 KiB
Docker

# 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.
# Benchmark image for RoboTwin 2.0 integration tests.
# Extends the nightly GPU image with the RoboTwin simulator stack:
# sapien/mplib/pytorch3d + NVlabs CuRobo + embodiments.zip + objects.zip
# (~3.96 GB of assets; background_texture.zip ~11 GB skipped for 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 ...
FROM huggingface/lerobot-gpu:latest
ENV NVIDIA_DRIVER_CAPABILITIES=all \
VK_ICD_FILENAMES=/usr/share/vulkan/icd.d/nvidia_icd.json \
ROBOTWIN_ROOT=/opt/robotwin
# The nightly base is CUDA -base (no compiler, no Vulkan loader). CuRobo's
# `pip install -e .` runs nvcc, and SAPIEN renders via Vulkan — add both.
USER root
# Pinned upstream SHA for reproducible benchmark runs. Bump when we need
# an upstream fix; don't rely on `main` drift.
ARG ROBOTWIN_SHA=0aeea2d669c0f8516f4d5785f0aa33ba812c14b4
RUN apt-get update \
&& apt-get install -y --no-install-recommends \
cuda-nvcc-12-4 cuda-cudart-dev-12-4 \
libvulkan1 vulkan-tools \
&& 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 \
&& git clone https://github.com/RoboTwin-Platform/RoboTwin.git ${ROBOTWIN_ROOT} \
&& git -C ${ROBOTWIN_ROOT} checkout ${ROBOTWIN_SHA} \
&& chown -R user_lerobot:user_lerobot ${ROBOTWIN_ROOT} \
&& apt-get clean && rm -rf /var/lib/apt/lists/*
USER user_lerobot
# RoboTwin runtime deps (av is already in the base via [av-dep]).
RUN uv pip install --no-cache \
"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 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"
# CuRobo — NVlabs motion generator; TORCH_CUDA_ARCH_LIST must be set or the
# build aborts on an empty arch list. Pinned SHA for reproducibility.
ARG CUROBO_SHA=ca941586c33b8482ed9c0e74d60f23efd64b516a
RUN cd ${ROBOTWIN_ROOT}/envs \
&& git clone https://github.com/NVlabs/curobo.git \
&& git -C curobo checkout ${CUROBO_SHA} \
&& 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
# Upstream patches (mirror RoboTwin's script/_install.sh).
# These patches target the exact versions pinned above; re-check when upgrading.
# mplib==0.2.1: drop a broken `or collide` clause in planner.py.
# Safe to remove once mplib > 0.2.1 ships with the fix upstream.
# sapien==3.0.0b1: fix URDF loader encoding + .srdf extension check.
# Safe to remove once sapien > 3.0.0b1 ships with the fix upstream.
RUN python - <<'EOF'
import pathlib, re, site
for d in site.getsitepackages():
p = pathlib.Path(d) / "mplib" / "planner.py"
if p.exists():
p.write_text(re.sub(r"\bor collide\b", "", p.read_text(), count=1))
print(f"mplib patch applied: {p}")
p = pathlib.Path(d) / "sapien" / "wrapper" / "urdf_loader.py"
if p.exists():
src = p.read_text().replace(
"with open(srdf_path) as f:", 'with open(srdf_path, encoding="utf-8") as f:'
).replace('"srdf"', '".srdf"')
p.write_text(src)
print(f"sapien patch applied: {p}")
EOF
# Simulation assets from TianxingChen/RoboTwin2.0: embodiments (~220 MB) +
# objects (~3.74 GB). background_texture (~11 GB) is intentionally skipped.
# The dataset is public — no auth token needed.
RUN python - <<'EOF'
import os, pathlib, zipfile
from huggingface_hub import hf_hub_download
assets_dir = pathlib.Path(os.environ["ROBOTWIN_ROOT"]) / "assets"
assets_dir.mkdir(parents=True, exist_ok=True)
for fname in ("embodiments.zip", "objects.zip"):
local = hf_hub_download(
repo_id="TianxingChen/RoboTwin2.0",
repo_type="dataset",
filename=fname,
local_dir=str(assets_dir),
)
with zipfile.ZipFile(local, "r") as z:
z.extractall(str(assets_dir))
pathlib.Path(local).unlink()
EOF
WORKDIR ${ROBOTWIN_ROOT}
RUN python script/update_embodiment_config_path.py
ENV PYTHONPATH="${ROBOTWIN_ROOT}:${PYTHONPATH}"
# Return to the lerobot source directory (set by base image) before overlaying.
WORKDIR /lerobot
# Overlay the PR's source code on top of the nightly image.
COPY --chown=user_lerobot:user_lerobot . .
CMD ["/bin/bash"]