mirror of https://github.com/llvm/torch-mlir
77c14ab22b
Per the RFC and numerous conversations on Discord, this rebuilds the torch-mlir CI and discontinues the infra and coupling to the binary releases (https://discourse.llvm.org/t/rfc-discontinuing-pytorch-1-binary-releases/76371). I iterated on this to get latency back to about what it was with the old (much larger and non-ephemeral) runners: About 4m - 4.5m for an incremental change. Behind the scenes changes: * Uses a new runner pool operated by AMD. It is currently set to manual scaling and has two runners (32-core, 64GiB RAM) while we get some traction. We can either fiddle with some auto-scaling or use a schedule to give it an increase during certain high traffic hours. * Builds are now completely isolated and cannot have run-to-run interference like we were getting before (i.e. lock file/permissions stuff). * The GHA runner is installed directly into a manylinux 2.28 container with upgraded dev tools. This eliminates the need to do sub-invocations of docker on Linux in order to run on the same OS that is used to build wheels. * While not using it now, this setup was cloned from another project that posts the built artifacts to the job and fans out testing. Might be useful here later. * Uses a special git cache that lets us have ephemeral runners and still check out the repo and deps (incl. llvm) in ~13s. * Running in an Azure VM Scale Set. In-repo changes: * Disables (but does not yet delete): * Old buildAndTest.yml jobs * releaseSnapshotPackage.yml * Adds a new `ci.yml` pipeline and scripts the steps in `build_tools/ci` (by decomposing the existing `build_linux_packages.sh` for in-tree builds and modularizing it a bit better). * Test framework changes: * Adds a `TORCH_MLIR_TEST_CONCURRENCY` env var that can be used to bound the multiprocess concurrency. Ended up not using this in the final version but is useful to have as a knob. * Changes the default concurrency to `nproc * 0.8 + 1` vs `nproc * 1.1`. We're running on systems with significantly less virtual memory and I did a bit of fiddling to find a good tradeoff. * Changed multiprocess mode to spawn instead of fork. Otherwise, I was getting instability (as discussed on discord). * Added MLIR configuration to disable multithreaded contexts globally for the project. Constantly spawning `nproc * nproc` threads (more than that actually) was OOM'ing. * Added a test timeout of 5 minutes. If a multiprocess worker crashes, the framework can get wedged indefinitely (and then will just be reaped after multiple hours). We should fix this, but this at least keeps the CI pool from wedging with stuck jobs. Functional changes needing followup: * No matter what I did, I couldn't get the LTC tests to work, and I'm not 100% sure they were being run in the old setup as the scripts were a bit twisty. I disabled them and left a comment. * Dropped out-of-tree build variants. These were not providing much signal and increase CI needs by 50%. * Dropped MacOS and Windows builds. Now that we are "just a library" and not building releases, there is less pressure to test these commit by commit. Further, since we bump torch-mlir to known good commits on these platforms, it has been a long time since either of these jobs have provided much signal (and they take ~an hour+ to run). We can add them back later post-submit if ever needed. |
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_site_initialize_0.py |