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08846b5c0e
* refactor draw model * rebase master * correct valid_len * rename function * rename variables * white space * rebase to master * e16c13ac-927d-455e-ae0a-81b482a2c787 * start rewriting * save proress * compiles! * oops * many fixes * seems to work * fix desires * finally cleaned * wrong std for ll * dont pulse none * compiles! * ready to test * WIP does not compile * compiles * various fixes * does something! * full 3d * not needed * draw up to 100m * fix segfault * wrong sign * fix flicker * add road edges * finish v2 packet * Added pytorch supercombo * fix rebase * no more keras * Hacky solution to the NCHW/NHWC incompatibility between SNPE and our frame data * dont break dmonitoringd, final model 229e3ce1-7259-412b-85e6-cc646d70f1d8/430 * fix hack * Revert "fix hack" This reverts commit 5550fc01a7881d065a5eddbbb42dac55ef7ec36c. * Removed axis permutation hack * Folded padding layers into conv layers * Removed the last pad layer from the dlc * Revert "Removed the last pad layer from the dlc" This reverts commit b85f24b9e1d04abf64e85901a7ff49e00d82020a. * Revert "Folded padding layers into conv layers" This reverts commit b8d1773e4e76dea481acebbfad6a6235fbb58463. * vision model: 5034ac8b-5703-4a49-948b-11c064d10880/780 temporal model: 229e3ce1-7259-412b-85e6-cc646d70f1d8/430 with permute + pool opt * fix ui drawing with clips * ./compile_torch.py 5034ac8b-5703-4a49-948b-11c064d10880/780 dfcd2375-81d8-49df-95bf-1d2d6ad86010/450 with variable history length * std::clamp * not sure how this compiled before * 2895ace6-a296-47ac-86e6-17ea800a74e5/550 * db090195-8810-42de-ab38-bb835d775d87/601 * 5m is very little * onnx runner * add onnxruntime to pipfile * run in real time without using the whole CPU * bump cereal; * add stds * set road edge opacity based on stddev * don't access the model packet in paint * convert mat.h to a c++ header file (#2499) * update tests * safety first Co-authored-by: deanlee <deanlee3@gmail.com> Co-authored-by: mitchell <mitchell@comma.ai> Co-authored-by: Comma Device <device@comma.ai> Co-authored-by: George Hotz <george@comma.ai> Co-authored-by: Adeeb Shihadeh <adeebshihadeh@gmail.com>
process replay
Process replay is a regression test designed to identify any changes in the output of a process. This test replays a segment through individual processes and compares the output to a known good replay. Each make is represented in the test with a segment.
If the test fails, make sure that you didn't unintentionally change anything. If there are intentional changes, the reference logs will be updated.
Use test_processes.py to run the test locally.
Currently the following processes are tested:
- controlsd
- radard
- plannerd
- calibrationd
- ubloxd
Forks
openpilot forks can use this test with their own reference logs
To generate new logs:
./update_refs.py --no-upload
Then, check in the new logs using git-lfs. Make sure to also include the updated ref_commit file.