chore(deps): move to self-contained pixi.toml to avoid mixed-pypi-pixi environments#551
chore(deps): move to self-contained pixi.toml to avoid mixed-pypi-pixi environments#551cpcloud merged 1 commit intoNVIDIA:mainfrom
Conversation
|
Auto-sync is disabled for ready for review pull requests in this repository. Workflows must be run manually. Contributors can view more details about this message here. |
|
/ok to test |
|
/ok to test |
| cuda-compiler = "*" | ||
| make = "*" | ||
| cxx-compiler = "*" |
There was a problem hiding this comment.
nitpick: the cxx-compiler / c-compiler metapackages touch a bunch of compiler / linker flags related to things like RPATHs and whatnot that can really mess with a local development flow. I personally make it a point to avoid them in my local environments for this reason.
I.E. when building test executables it sets RPATH to point into the conda environment before $ORIGIN which makes it find an installed conda package before the built DSO in the working dir.
Not as much of a concern for numba-cuda but some food for thought.
There was a problem hiding this comment.
Yeah, the RPATH behavior isn't my favorite, but I understand why it works that way.
Is the main concern development workflows for pseudo-monorepos like cuda-python where dependencies are native and they live in the same repo?
In the case of numba-cuda I think it's worth it to bring as much in to the env as possible to ensure that devs have a good day 1 (and day N 😄!) experience.
There was a problem hiding this comment.
I've mostly run into issues with C++ projects where you're building a DSO, say mylib.so and then building various test executables, but like to have a stable version of mylib installed in the environment as well. Given how the state of tooling has improved so vastly, maybe this is less of a concern and these should just be separate environments nowadays.
I'm more than happy to move forward as is and we can always course correct if we find pain / issues.
| cuda-nvcc = "12.*" | ||
| cuda-nvvm = "12.*" | ||
| cuda-runtime = "12.*" | ||
| cuda-nvrtc = "*" | ||
| libnvjitlink = "12.*" | ||
| cuda-cccl = "12.*" | ||
| libcurand = "*" |
There was a problem hiding this comment.
Instead of specifying 12.* for all of these dependencies we should be able to use cuda-version=12 which all of these packages constrain themselves to.
There was a problem hiding this comment.
I will try to make this change in the follow-up I have to replace conda ci with pixi (#554), to avoid lots of conflicts in that PR.
There was a problem hiding this comment.
Actually, it turns out I already did that in that PR 👌🏻
| cuda-nvvm = "13.*" | ||
| cuda-runtime = "13.*" | ||
| cuda-nvrtc = "*" | ||
| libnvjitlink = "13.*" | ||
| cuda-cccl = "13.*" | ||
| libcurand = "10.4.*" |
| cupy = "*" | ||
|
|
||
| [feature.test.dependencies] | ||
| pre-commit = "*" | ||
| psutil = "*" | ||
| cffi = "*" | ||
| pytest = "*" | ||
| pytest-xdist = "*" | ||
| pytest-benchmark = "*" |
There was a problem hiding this comment.
Do we not want to version these and then use pixi update or whatever command to upgrade them?
There was a problem hiding this comment.
We can, I was just replicating what was there before. I'll make that change in a follow-up.
|
/ok to test |
|
Not entirely sure why that job is hanging. This PR doesn't touch anything CI related. |
|
/ok to test |
|
/ok to test |
- Add support for cache-hinted load and store operations (NVIDIA#587) - Add more thirdparty tests (NVIDIA#586) - Add sphinx-lint to pre-commit and fix errors (NVIDIA#597) - Add DWARF variant part support for polymorphic variables in CUDA debug info (NVIDIA#544) - chore: clean up dead workaround for unavailable `lru_cache` (NVIDIA#598) - chore(docs): format types docs (NVIDIA#596) - refactor: decouple `Context` from `Stream` and `Event` objects (NVIDIA#579) - Fix freezing in of constant arrays with negative strides (NVIDIA#589) - Update tests to accept variants of generated PTX (NVIDIA#585) - refactor: replace device functionality with `cuda.core` APIs (NVIDIA#581) - Move frontend tests to `cudapy` namespace (NVIDIA#558) - Generalize the concurrency group for main merges (NVIDIA#582) - ci: move pre-commit checks to pre commit action (NVIDIA#577) - chore(pixi): set up doc builds; remove most `build-conda` dependencies (NVIDIA#574) - ci: ensure that python version in ci matches matrix (NVIDIA#575) - Fix the `cuda.is_supported_version()` API (NVIDIA#571) - Fix checks on main (NVIDIA#576) - feat: add `math.nextafter` (NVIDIA#543) - ci: replace conda testing with pixi (NVIDIA#554) - [CI] Run PR workflow on merge to main (NVIDIA#572) - Propose Alternative Module Path for `ext_types` and Maintain `numba.cuda.types.bfloat16` Import API (NVIDIA#569) - test: enable fail-on-warn and clean up resulting failures (NVIDIA#529) - [Refactor][NFC] Vendor-in compiler_lock for future CUDA-specific changes (NVIDIA#565) - Fix registration with Numba, vendor MakeFunctionToJITFunction tests (NVIDIA#566) - [Refactor][NFC][Cleanups] Update imports to upstream numba to use the numba.cuda modules (NVIDIA#561) - test: refactor process-based tests to use concurrent futures in order to simplify tests (NVIDIA#550) - test: revert back to ipc futures that await each iteration (NVIDIA#564) - chore(deps): move to self-contained pixi.toml to avoid mixed-pypi-pixi environments (NVIDIA#551) - [Refactor][NFC] Vendor-in errors for future CUDA-specific changes (NVIDIA#534) - Remove dependencies on target_extension for CUDA target (NVIDIA#555) - Relax the pinning to `cuda-core` to allow it floating across minor releases (NVIDIA#559) - [WIP] Port numpy reduction tests to CUDA (NVIDIA#523) - ci: add timeout to avoid blocking the job queue (NVIDIA#556) - Handle `cuda.core.Stream` in driver operations (NVIDIA#401) - feat: add support for `math.exp2` (NVIDIA#541) - Vendor in types and datamodel for CUDA-specific changes (NVIDIA#533) - refactor: cleanup device constructor (NVIDIA#548) - bench: add cupy to array constructor kernel launch benchmarks (NVIDIA#547) - perf: cache dimension computations (NVIDIA#542) - perf: remove duplicated size computation (NVIDIA#537) - chore(perf): add torch to benchmark (NVIDIA#539) - test: speed up ipc tests by ~6.5x (NVIDIA#527) - perf: speed up kernel launch (NVIDIA#510) - perf: remove context threading in various pointer abstractions (NVIDIA#536) - perf: reduce the number of `__cuda_array_interface__` accesses (NVIDIA#538) - refactor: remove unnecessary custom map and set implementations (NVIDIA#530) - [Refactor][NFC] Vendor-in vectorize decorators for future CUDA-specific changes (NVIDIA#513) - test: add benchmarks for kernel launch for reproducibility (NVIDIA#528) - test(pixi): update pixi testing command to work with the new `testing` directory (NVIDIA#522) - refactor: fully remove `USE_NV_BINDING` (NVIDIA#525) - Draft: Vendor in the IR module (NVIDIA#439) - pyproject.toml: add search path for Pyrefly (NVIDIA#524) - Vendor in numba.core.typing for CUDA-specific changes (NVIDIA#473) - Use numba.config when available, otherwise use numba.cuda.config (NVIDIA#497) - [MNT] Drop NUMBA_CUDA_USE_NVIDIA_BINDING; always use cuda.core and cuda.bindings as fallback (NVIDIA#479) - Vendor in dispatcher, entrypoints, pretty_annotate for CUDA-specific changes (NVIDIA#502) - build: allow parallelization of nvcc testing builds (NVIDIA#521) - chore(dev-deps): add pixi (NVIDIA#505) - Vendor the imputils module for CUDA refactoring (NVIDIA#448) - Don't use `MemoryLeakMixin` for tests that don't use NRT (NVIDIA#519) - Switch back to stable cuDF release in thirdparty tests (NVIDIA#518) - Updating .gitignore with binaries in the `testing` folder (NVIDIA#516) - Remove some unnecessary uses of ContextResettingTestCase (NVIDIA#507) - Vendor in _helperlib cext for CUDA-specific changes (NVIDIA#512) - Vendor in typeconv for future CUDA-specific changes (NVIDIA#499) - [Refactor][NFC] Vendor-in numba.cpython modules for future CUDA-specific changes (NVIDIA#493) - [Refactor][NFC] Vendor-in numba.np modules for future CUDA-specific changes (NVIDIA#494) - Make the CUDA target the default for CUDA overload decorators (NVIDIA#511) - Remove C extension loading hacks (NVIDIA#506) - Ensure NUMBA can manipulate memory from CUDA graphs before the graph is launched (NVIDIA#437) - [Refactor][NFC] Vendor-in core Numba analysis utils for CUDA-specific changes (NVIDIA#433) - Fix Bf16 Test OB Error (NVIDIA#509) - Vendor in components from numba.core.runtime for CUDA-specific changes (NVIDIA#498) - [Refactor] Vendor in _dispatcher, _devicearray, mviewbuf C extension for CUDA-specific customization (NVIDIA#373) - [MNT] Managed UM memset fallback and skip CUDA IPC tests on WSL2 (NVIDIA#488) - Improve debug value range coverage (NVIDIA#461) - Add `compile_all` API (NVIDIA#484) - Vendor in core.registry for CUDA-specific changes (NVIDIA#485) - [Refactor][NFC] Vendor in numba.misc for CUDA-specific changes (NVIDIA#457) - Vendor in optional, boxing for CUDA-specific changes, fix dangling imports (NVIDIA#476) - [test] Remove dependency on cpu_target (NVIDIA#490) - Change dangling imports of numba.core.lowering to numba.cuda.lowering (NVIDIA#475) - [test] Use numpy's tolerance for float16 (NVIDIA#491) - [Refactor][NFC] Vendor-in numba.extending for future CUDA-specific changes (NVIDIA#466) - [Refactor][NFC] Vendor-in more cpython registries for future CUDA-specific changes (NVIDIA#478)
- Add support for cache-hinted load and store operations (#587) - Add more thirdparty tests (#586) - Add sphinx-lint to pre-commit and fix errors (#597) - Add DWARF variant part support for polymorphic variables in CUDA debug info (#544) - chore: clean up dead workaround for unavailable `lru_cache` (#598) - chore(docs): format types docs (#596) - refactor: decouple `Context` from `Stream` and `Event` objects (#579) - Fix freezing in of constant arrays with negative strides (#589) - Update tests to accept variants of generated PTX (#585) - refactor: replace device functionality with `cuda.core` APIs (#581) - Move frontend tests to `cudapy` namespace (#558) - Generalize the concurrency group for main merges (#582) - ci: move pre-commit checks to pre commit action (#577) - chore(pixi): set up doc builds; remove most `build-conda` dependencies (#574) - ci: ensure that python version in ci matches matrix (#575) - Fix the `cuda.is_supported_version()` API (#571) - Fix checks on main (#576) - feat: add `math.nextafter` (#543) - ci: replace conda testing with pixi (#554) - [CI] Run PR workflow on merge to main (#572) - Propose Alternative Module Path for `ext_types` and Maintain `numba.cuda.types.bfloat16` Import API (#569) - test: enable fail-on-warn and clean up resulting failures (#529) - [Refactor][NFC] Vendor-in compiler_lock for future CUDA-specific changes (#565) - Fix registration with Numba, vendor MakeFunctionToJITFunction tests (#566) - [Refactor][NFC][Cleanups] Update imports to upstream numba to use the numba.cuda modules (#561) - test: refactor process-based tests to use concurrent futures in order to simplify tests (#550) - test: revert back to ipc futures that await each iteration (#564) - chore(deps): move to self-contained pixi.toml to avoid mixed-pypi-pixi environments (#551) - [Refactor][NFC] Vendor-in errors for future CUDA-specific changes (#534) - Remove dependencies on target_extension for CUDA target (#555) - Relax the pinning to `cuda-core` to allow it floating across minor releases (#559) - [WIP] Port numpy reduction tests to CUDA (#523) - ci: add timeout to avoid blocking the job queue (#556) - Handle `cuda.core.Stream` in driver operations (#401) - feat: add support for `math.exp2` (#541) - Vendor in types and datamodel for CUDA-specific changes (#533) - refactor: cleanup device constructor (#548) - bench: add cupy to array constructor kernel launch benchmarks (#547) - perf: cache dimension computations (#542) - perf: remove duplicated size computation (#537) - chore(perf): add torch to benchmark (#539) - test: speed up ipc tests by ~6.5x (#527) - perf: speed up kernel launch (#510) - perf: remove context threading in various pointer abstractions (#536) - perf: reduce the number of `__cuda_array_interface__` accesses (#538) - refactor: remove unnecessary custom map and set implementations (#530) - [Refactor][NFC] Vendor-in vectorize decorators for future CUDA-specific changes (#513) - test: add benchmarks for kernel launch for reproducibility (#528) - test(pixi): update pixi testing command to work with the new `testing` directory (#522) - refactor: fully remove `USE_NV_BINDING` (#525) - Draft: Vendor in the IR module (#439) - pyproject.toml: add search path for Pyrefly (#524) - Vendor in numba.core.typing for CUDA-specific changes (#473) - Use numba.config when available, otherwise use numba.cuda.config (#497) - [MNT] Drop NUMBA_CUDA_USE_NVIDIA_BINDING; always use cuda.core and cuda.bindings as fallback (#479) - Vendor in dispatcher, entrypoints, pretty_annotate for CUDA-specific changes (#502) - build: allow parallelization of nvcc testing builds (#521) - chore(dev-deps): add pixi (#505) - Vendor the imputils module for CUDA refactoring (#448) - Don't use `MemoryLeakMixin` for tests that don't use NRT (#519) - Switch back to stable cuDF release in thirdparty tests (#518) - Updating .gitignore with binaries in the `testing` folder (#516) - Remove some unnecessary uses of ContextResettingTestCase (#507) - Vendor in _helperlib cext for CUDA-specific changes (#512) - Vendor in typeconv for future CUDA-specific changes (#499) - [Refactor][NFC] Vendor-in numba.cpython modules for future CUDA-specific changes (#493) - [Refactor][NFC] Vendor-in numba.np modules for future CUDA-specific changes (#494) - Make the CUDA target the default for CUDA overload decorators (#511) - Remove C extension loading hacks (#506) - Ensure NUMBA can manipulate memory from CUDA graphs before the graph is launched (#437) - [Refactor][NFC] Vendor-in core Numba analysis utils for CUDA-specific changes (#433) - Fix Bf16 Test OB Error (#509) - Vendor in components from numba.core.runtime for CUDA-specific changes (#498) - [Refactor] Vendor in _dispatcher, _devicearray, mviewbuf C extension for CUDA-specific customization (#373) - [MNT] Managed UM memset fallback and skip CUDA IPC tests on WSL2 (#488) - Improve debug value range coverage (#461) - Add `compile_all` API (#484) - Vendor in core.registry for CUDA-specific changes (#485) - [Refactor][NFC] Vendor in numba.misc for CUDA-specific changes (#457) - Vendor in optional, boxing for CUDA-specific changes, fix dangling imports (#476) - [test] Remove dependency on cpu_target (#490) - Change dangling imports of numba.core.lowering to numba.cuda.lowering (#475) - [test] Use numpy's tolerance for float16 (#491) - [Refactor][NFC] Vendor-in numba.extending for future CUDA-specific changes (#466) - [Refactor][NFC] Vendor-in more cpython registries for future CUDA-specific changes (#478) <!-- Thank you for contributing to numba-cuda :) Here are some guidelines to help the review process go smoothly. 1. Please write a description in this text box of the changes that are being made. 2. Please ensure that you have written units tests for the changes made/features added. 3. If you are closing an issue please use one of the automatic closing words as noted here: https://help.github.com/articles/closing-issues-using-keywords/ 4. If your pull request is not ready for review but you want to make use of the continuous integration testing facilities please label it with `[WIP]`. 5. If your pull request is ready to be reviewed without requiring additional work on top of it, then remove the `[WIP]` label (if present) and replace it with `[REVIEW]`. If assistance is required to complete the functionality, for example when the C/C++ code of a feature is complete but Python bindings are still required, then add the label `[HELP-REQ]` so that others can triage and assist. The additional changes then can be implemented on top of the same PR. If the assistance is done by members of the rapidsAI team, then no additional actions are required by the creator of the original PR for this, otherwise the original author of the PR needs to give permission to the person(s) assisting to commit to their personal fork of the project. If that doesn't happen then a new PR based on the code of the original PR can be opened by the person assisting, which then will be the PR that will be merged. 6. Once all work has been done and review has taken place please do not add features or make changes out of the scope of those requested by the reviewer (doing this just add delays as already reviewed code ends up having to be re-reviewed/it is hard to tell what is new etc!). Further, please do not rebase your branch on main/force push/rewrite history, doing any of these causes the context of any comments made by reviewers to be lost. If conflicts occur against main they should be resolved by merging main into the branch used for making the pull request. Many thanks in advance for your cooperation! -->
This PR moves our pixi environment to be self-contained in order to avoid mixing cuda dependencies between pypi and conda(-forge).