You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Depend on cuda-core[cu12]/[cu13] in the respective wheel.
cuda-core 1.3.0 (released 2026-11-11) refuses to import unless cuda-bindings meets a minimum version (>=12.9.8 for CUDA 12, >=13.5.0 for CUDA 13). Its metadata declares that minimum only under the `cu12`/`cu13` extras. nvforest wheels depend on plain `cuda-core`, so pip can install cuda-core 1.3.0 next to an older cuda-bindings, and then `import cuda.core` fails:
```text
ImportError: cuda.core 1.3.0 requires cuda-bindings >= 12.9.8 for CUDA 12, but cuda-bindings 12.9.3 is installed.
```
This breaks cuML's nightly wheel tests in two ways:
- In the oldest-deps jobs, cuML pins `cuda-bindings==12.9.3`.
- In the CUDA 12 integrations job, `torch==2.10.0+cu129` pins `cuda-bindings==12.9.4`.
Examples:
- https://github.com/NVIDIA/cuml/actions/runs/43171195643/job/131024721358
- https://github.com/NVIDIA/cuml/actions/runs/43171195643/job/131024702175
This PR makes the wheels depend on `cuda-core[cu12]` / `cuda-core[cu13]`, so pip sees the minimum and falls back to cuda-core 1.2.x (the version before what was just released) when cuda-bindings is pinned below 12..9.8. dask-cuda already does this, and cuML's oldest-deps dask job, which gets cuda-core through dask-cuda, resolved cuda-core 1.2.2 and passed.
We could bump the cuda-binding in the oldest job instead, but we'd still be stuck for CUDA 12 in general I think (because pytorch pins things exactly).
I think with this we get the "best of all worlds" where you get the newer cuda-core if there is nothing in your env that keeps cuda-bindings pinned low. And if there is you get the older version of cuda-core. I don't know what the downside of sometimes having cuda-core 1.2.x and sometimes having 1.3.0 is.
One downside is that through `cuda-bindings[all]`, the extra also installs the nvcc, nvrtc, nvjitlink and cufile wheels. This isn't great but for cuml these would anyway get installed.
Authors:
- Tim Head (https://github.com/betatim)
Approvers:
- James Lamb (https://github.com/jameslamb)
URL: rapidsai#277
No actionable comments were generated in the recent review.
Summary
Summary by CodeRabbit
Bug Fixes
CUDA dependency selection now follows the configured CUDA version in requirements and project metadata: CUDA 12 selects the CUDA 12 package, while other or unspecified versions select the CUDA 13 package.
Disabling CUDA wheels selects the base package for these outputs.
Conda and constraints outputs continue to use the base package.
The dependency rules now select the base cuda-core package or its cu12 or cu13 extra for requirements and pyproject outputs, based on configuration. The nvforest project dependency now requests the cu13 extra.
For requirements and pyproject outputs, the rules select the base package when use_cuda_wheels is "false", the cu12 extra for CUDA 12, and the cu13 extra otherwise. The nvforest dependency now requests the cu13 extra. The version range is unchanged.
rapidsai/nvforest#277: Changes the same cuda-core output rules and the nvforest dependency to use the cu13 extra.
rapidsai/nvforest#193: Adds the depends_on_cuda_core group and changes the nvforest dependency line touched here.
Suggested reviewers:msarahan, bdice
Merge Risk: Minimal · up to 26027
This change makes the wheels depend on the CUDA-version-specific cuda-core extras so pip can resolve compatible cuda-bindings versions. No concrete merge-blocking risk was identified.
Pre-merge checks: 2 · 2
Failed checks: 2 inconclusive
Check name
Status
Explanation
Resolution
Title check
The title names a forward-merge of release/26.12 into main, which is a real and specific operation. It does not describe the content of the merge. The raw summary shows the merged change makes the cud…
Rewrite the title to name the main change, for example: "Select cuda-core cu12 or cu13 extra by CUDA version". Alternatively, keep the merge wording and add the main change, for example: "Forward-merge release/26.12 into main: use cuda-core…
Description check
The description reads "See #279" and gives no detail about the changeset. It refers to another issue number, which is related to the merge, but it does not describe any part of the change. The check i…
Add a short description of the changes. Name the affected files (dependencies.yaml and python/nvforest/pyproject.toml) and state the purpose, for example: cuda-core now selects the cu12 or cu13 extra based on the cuda setting, so pip resolv…
Passed checks: 2 passed
Check name
Status
Explanation
Linked Issues check
Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check
Check skipped because no linked issues were found for this pull request.
Full details: Title check
Explanation
The title names a forward-merge of release/26.12 into main, which is a real and specific operation. It does not describe the content of the merge. The raw summary shows the merged change makes the cuda-core dependency select CUDA-version-specific extras (cu12/cu13) in requirements and pyproject outputs, so the title does not name the main technical change. The title is partially related because it identifies the merge, but it is not a clear summary of the primary change.
Resolution
Rewrite the title to name the main change, for example: "Select cuda-core cu12 or cu13 extra by CUDA version". Alternatively, keep the merge wording and add the main change, for example: "Forward-merge release/26.12 into main: use cuda-core CUDA-specific extras".
Full details: Description check
Explanation
The description reads "See #279" and gives no detail about the changeset. It refers to another issue number, which is related to the merge, but it does not describe any part of the change. The check is lenient, but the text is too vague to confirm relevance on its own. The objectives section links the PR to #279 but does not state what #279 covers.
Resolution
Add a short description of the changes. Name the affected files (dependencies.yaml and python/nvforest/pyproject.toml) and state the purpose, for example: cuda-core now selects the cu12 or cu13 extra based on the cuda setting, so pip resolves compatible cuda-bindings versions.
Finishing Touches
Generate unit tests (beta)
Create a new PR
Autofix · Keep fixing CodeRabbit findings and required CI, and resolving merge conflicts
Reviewing files that changed from the base of the PR and between 3ccb8c9 and 26027d2.
Files selected for processing: 2
dependencies.yaml
python/nvforest/pyproject.toml
Included review availability: This review used your included allowance. Your plan provides up to 12 included reviews per hour; 11 remain after this review.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
See #279