affordance-deployment

# Affordance Deployment Use the repository installer first. It initializes both submodules, builds `torch-scatter`, `flash-attn==2.8.2`, and GraspGen's `pointnet2_ops`, then restores the supported OpenCV versions. ```bash bash install.sh affordance affordance-cli --help img3d-cli --help ``` ## CUDA Architecture Load the CUDA hook before rebuilding extensions and verify the selected target: ```bash echo "$CUDA_HOME" echo "$TORCH_CUDA_ARCH_LIST" nvcc --version ``` - RTX 4090: `TORCH_CUDA_ARCH_LIST=8.9`. - RTX 5090: `TORCH_CUDA_ARCH_LIST=12.0` and nvcc 12.8 or newer. If `pointnet2_ops` was built for the wrong architecture, rebuild the package directly instead of running `thirdparty/GraspGen/install_pointnet.sh`, which hardcodes an older target: ```bash python -m pip install --no-build-isolation --force-reinstall --no-deps \ thirdparty/GraspGen/pointnet2_ops ``` ## Flash Attention Keep `flash-attn` at 2.8.2 because the installed diffusers version rejects newer releases. Rebuild from source with the GPU-specific target when needed: ```bash export FLASH_ATTENTION_FORCE_BUILD=TRUE export FLASH_ATTN_CUDA_ARCHS=89 # use 120 on RTX 5090 with nvcc >= 12.8 python -m pip install --no-cache-dir --no-build-isolation \ --no-binary flash-attn --force-reinstall --no-deps flash-attn==2.8.2 ``` If the source checkout lacks CUTLASS or composable-kernel files, initialize its submodules before retrying. Reduce `MAX_JOBS` when compilation runs out of RAM. ## Quick Reference | Error | Root Cause | Fix | |---|---|---| | `Unsupported gpu architecture 'compute_120'` | nvcc is older than 12.8 | Use the cu128 hook or target the actual GPU | | `no kernel image` in pointnet2 | Extension built for another GPU | Rebuild `pointnet2_ops` directly | | diffusers rejects flash-attn | Version is newer than 2.8.2 | Reinstall 2.8.2 | | Build OOM | Too many compiler jobs | Set `MAX_JOBS=4` |