# Native preparation and direct-control boundary The inspected public source is [h-embodvis/DOMINO](https://github.com/h-embodvis/DOMINO) at `9c94f2d3a700fff3b65f041df4038d497139ed1f`. ```sh git clone https://github.com/h-embodvis/DOMINO.git /absolute/new-domino git -C /absolute/new-domino checkout --detach 9c94f2d3a700fff3b65f041df4038d497139ed1f git -C /absolute/new-domino diff --exit-code HEAD ``` Native `assets/_download.py` requests `background_texture.zip`, `embodiments.zip` and `objects.zip` from the public [TianxingChen/RoboTwin2.0 dataset](https://huggingface.co/datasets/TianxingChen/RoboTwin2.0). Training demonstrations and PUMA/model weights are not simulator assets. Matching existing assets can be verified and reused read-only. Otherwise pin the dataset revision, download the required archives, record their hashes and extract into a fresh asset root after checking archive paths and links. Never merge blindly over an existing deployment or assume a current dataset equals a historical local asset tree. Do not run the native installation script against an existing shared environment. It edits SAPIEN/MPLib package code and clones CuRobo without a fixed revision. A portable deployment needs its own environment, recorded native package/source identities, explicit path-only configuration derivations and a verified controller contract. The RoboTwin server's source pin is not a DOMINO source pin. ## Why assets alone do not complete the interface The pinned native evaluator normally executes an expert to screen candidate seeds and recover dynamic-motion information. Its optional fixed-episode manifest avoids online screening but still contains expert-screened scene/trajectory data. Neither mode is an unscreened once-per-selected-seed fast protocol. A direct-control service must freeze and document its scene distribution before evaluation, keep all dynamic-trajectory and metric-tracker data private, and never offer expert action proposals to the model. Do not replace the dynamic task with a static lookalike merely because its assets load. Preserving native SR/MS also requires the native route-completion, contact-stop, lifting and out-of-bounds logic, not only the task's cached success flag. The implemented service now selects the bounded `click_bell` fixed-manifest SM120 compatibility track. Native preparation and service validation remain unfinished; this is not a passed native-run claim. See the [evaluation protocol](../EVALUATION_PROTOCOL.md). ## Prepare a fresh owned deployment `deployment.py` verifies the public Git blob identities of DOMINO and CuRobo, copies only those verified source paths, copies the selected aloha/bell assets, and derives only the two native CuRobo asset-root substitutions. It captures selected compatibility package versions and SAPIEN/MPLib/TOPPRA file hashes. It never invokes an installer, expert, simulator or model. Existing destinations are refused. Untracked compiled CuRobo extensions are not copied; new JIT builds belong to an episode-owned cache, never source or a colleague's environment. With the declared compatibility interpreter and verified owned SAPIEN/OIDN2.3.3 overlay already selected on `PYTHONPATH`: ```sh python -B -m benchmarks.simBenchmarks.DOMINO.environment.deployment \ --source /absolute/pinned-domino-source \ --source-git /absolute/public-domino-git-reference \ --assets /absolute/verified-robotwin-assets \ --curobo /absolute/pinned-curobo-source \ --curobo-git /absolute/public-curobo-git-reference \ --destination /absolute/new-owned-domino-deployment ``` The Git references must contain DOMINO revision `9c94f2d3a700fff3b65f041df4038d497139ed1f` and CuRobo v0.7.8 revision `d64c4b005459db10c5dd867d8b30a87d5bda9bdb`. No global Git setting is modified. Retain the returned manifest SHA256 and do not change the captured deployment. Source verification includes unknown executable/bytecode detection at runtime; launch with `-B` and never add caches to source trees. The minimal asset closure is aloha-agilex plus bell variants0/1, including collision/visual geometry, robot meshes, SRDF and native configs. Native clean mode uses no randomized background/clutter textures. File closure does not prove release identity or successful rendering. More tasks require separately verified assets and declarations, not copying task names from the horizon file. ## Private fixed-episode preparation gate No ready-made DOMINO fixed manifests are shipped in the inspected source. Upstream `screen_episodes.py` can search many candidates and run multiple resets; do not execute it under permission for one diagnostic task attempt. A separately authorized, bounded preparation may inspect exactly one declared candidate and preserve rejection without scanning for a replacement. It must retain expert preparation and dynamic-validation reset counts, source/deployment identities and any failure, then freeze a trusted manifest before policy use. The server accepts only a manifest pinned to the native revision and checks the chosen seed and dynamic-motion payload. It never prepares, edits or searches the manifest while a policy runs. A manifest is private native reset data; pickle requires a trusted local origin and hash, not arbitrary policy input. The current native import path still initializes CuRobo planners even though policy controls use qpos/TOPP. The compatibility environment needs a compatible CUDA compiler for fresh JIT builds. GPU names alone do not establish architecture; verify compute capability and actual renderer device on the assigned node. The inspected SM120 track requires Torch2.7.1+CUDA12.8; substituting native Torch2.4.1 on that hardware is not a validated fix. For a Conda-layout CUDA toolkit, `nvcc` may find its own headers while the host C++ compiler cannot find `cuda_runtime_api.h`. Before claiming a task, verify the compiler and header locations, then select the existing toolkit only in the launch environment, for example: ```sh export CUDA_HOME=/absolute/verified-cuda-toolkit export PATH="$CUDA_HOME/bin:$PATH" export CPATH="$CUDA_HOME/targets/x86_64-linux/include${CPATH:+:$CPATH}" export TORCH_CUDA_ARCH_LIST=12.0 ``` Use the actual selected GPU architecture, not `12.0` on a different device. Do not patch a shared environment or copy unverified compiled CuRobo extensions into the native source. Record compiler and Torch CUDA versions independently: the inspected compatibility preflight used nvcc12.9.86 with Torch CUDA12.8, not an exact toolkit-version match. Build/import readiness, synthetic rendering, robot-only planner warmup and a task reset are separate checks. Native source and assets must remain unchanged; isolate JIT, Warp and driver caches in owned diagnostic storage. These setup checks are not policy trials or task scores.