Provide laptop and device build entry points, cache compatibility checks and developer tooling. Keep distribution assets and model packaging available before runtime consumers.
Keep official openpilot ancestry and dependency licenses. Store resources directly in Git, remove LFS setup requirements, and leave the downloadable big model outside the source tree.
* Remove model chunking and use LFS for Chestnut releases
* Check Git blob sizes once during release packaging
* Download the big model for Chestnut nightly builds
* Reuse published LFS models when pushing releases
* Preserve LFS configuration when copying Chestnut releases
* Detect release builds independently of LFS attributes
* Ship precompiled eGPU model and camera warps
Compile f78ed37d-afad-4dbc-8050-40ea885eedde/12864 through xx/ml_tools/openpilot_compile using the pinned tinygrad version.
* Precompile the existing master driving model
Use the unchanged master ONNX (SHA-256 6fee5937923c74848df4a63f6239eb6331c6274dd4bdb7a5d6ec0388a8b543d5) instead of updating the trained model.
* Compile camera warps on device
* Remove obsolete ONNX chunking and big model build check
* Chunk model artifacts only during release packaging
* Require model and camera warps for Chestnut readiness
* Recompile precompiled CPU helpers for the runtime host
* Ship the eGPU model with an ARM submission helper
* Exempt model pickles from the build product size limit
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