Connect shared feature owners to vehicle and control processes. Migrate retired settings once before startup consumers while preserving effective preferences and vehicle-specific numeric adjustments.
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.
* Update tinygrad to latest upstream with minimal openpilot patches
* Rebase tinygrad on latest upstream with one remaining patch
* Use retargetable model and warp artifacts
* Pack compiled model weights to reduce startup time
* Memory-map out-of-band model weights
* Use unmodified upstream tinygrad master
* Keep locally built model artifacts native
* 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
* not worth 1m
* saves 24s
* save 13s
* parallelize model compilation
* explain compiler affinity
* full cpufreq
* rm that for now
* cmt
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Co-authored-by: elkoled <elkoled@gmail.com>
* 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
* Use tinygrad generic ONNX compiler artifacts
* Keep compiler temporary model buffers off device tmpfs
* Keep recurrent model state updates on the GPU
* Use compiled output buffers and swap recurrent state inputs
* Note when ONNX chunk reassembly can be removed
* Bump tinygrad to rebased compilers and AMD queue fix
* Keep recurrent buffers fixed and use faster USB argument updates
* Bump tinygrad for faster model startup
* modeld: use tinygrad ONNX and warp compilers for driving and DM
* Bump tinygrad with current openpilot model compile tests
* modeld: prioritize tinygrad compiler imports in build environment
* Use compiler branch based on openpilot's pinned tinygrad
* modeld: invoke tinygrad compilers without firmware patch
* modeld: move history queues into ONNX
* Move ONNX history export into xx exporter
* Rename ONNX image input to new_img
* Combine ONNX model history state
* Revert model history README addition
* Keep float32 input packing from master
* Rename model input specs to input shapes
* modeld: build DM warp and model JITs for all camera configs
In #38684, camera_configs on comma_arm64 was restricted to only the host device
running SCons (selecting either _os_fisheye or _ar_ox_fisheye).
However, prebuilt release and nightly bundles are built on TICI/tizi runners
in Jenkins and distributed to both Comma 3/3X (TICI) and Comma 4 (MICI) devices.
Because the build machine was TICI, dm_warp_1344x760_tinygrad.pkl was omitted
from the packaged bundle, causing dmonitoringmodeld to fail with FileNotFoundError
on Comma 4 and leaving driver-monitoring calibration stuck at 0%.
Restore CAMERA_CONFIGS so both camera resolutions (1928x1208 and 1344x760)
are built for all platforms.
Fixes#38762
* simplify
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Co-authored-by: ZwX1616 <zwx1616@gmail.com>
* system: add chestnut offroad alerts
* system: refine chestnut offroad alerts
* system: refine chestnut power alerts
* system: confirm chestnut power recovery from PCIe
* system: detect missing chestnut power from INA voltage
firestar5683