Merge branch 'main' into bypass-data-gpu-alloc-umap #6115
pr.yaml
on: push
telemetry-setup
8s
check-nightly-ci
9s
Matrix: devcontainer / build
Matrix: conda-cpp-build / build
Matrix: wheel-build-libcuml / build
Matrix: conda-cpp-tests / tests
Waiting for pending jobs
Matrix: conda-python-build / build
Matrix: wheel-build-cuml / build
conda-python-cuml-accel-upstream-tests
/
compute-matrix
6s
conda-python-scikit-learn-accel-tests
/
compute-matrix
4s
optional-job-conda-python-tests-cudf-pandas-integration
/
compute-matrix
2s
Matrix: conda-python-cuml-accel-upstream-tests / tests
Matrix: conda-python-scikit-learn-accel-tests / tests
Matrix: conda-python-tests-dask / tests
Matrix: conda-python-tests-singlegpu / tests
Matrix: optional-job-conda-python-tests-cudf-pandas-integration / tests
Matrix: wheel-tests-cuml-dask / test
Matrix: wheel-tests-cuml / test
telemetry-summarize
26s
Annotations
3 errors and 2 warnings
|
conda-notebook-tests / build
unable to access 'https://github.com/rapidsai/shared-actions/': Could not resolve host: github.com
|
|
conda-python-tests-singlegpu / 12.9.1, 3.13, amd64, ubuntu24.04, l4, latest-driver, latest-deps
Process completed with exit code 1.
|
|
pr-builder / run
Process completed with exit code 1.
|
|
conda-python-tests-singlegpu / 12.9.1, 3.13, amd64, ubuntu24.04, l4, latest-driver, latest-deps
Docker network rm failed with exit code 1
|
|
conda-python-tests-singlegpu / 12.9.1, 3.13, amd64, ubuntu24.04, l4, latest-driver, latest-deps
Docker rm fail with exit code 1
|
Artifacts
Produced during runtime
| Name | Size | Digest | |
|---|---|---|---|
|
cuml_conda_cpp_cuda12_aarch64
|
114 MB |
sha256:6a4fc1d2019f7a9caea018bf07dff776290aba9d3a11c9f8524b3eb620f0e6f0
|
|
|
cuml_conda_cpp_cuda12_x86_64
|
113 MB |
sha256:22a5f4f63fc13f6e7743cf360015c7a16b21324ca2d5817a6fbdbab38375cb8c
|
|
|
cuml_conda_cpp_cuda13_aarch64
|
80.1 MB |
sha256:30b3effaa8db6bb9af71fe10cf24f1db5868034c94cdcb161e6b4f92f3f91171
|
|
|
cuml_conda_cpp_cuda13_x86_64
|
80.4 MB |
sha256:709e4cb423cf4ba85b5e9e33ee0c77d1774795c2d9d8a03140f70ee8192d1b99
|
|
|
cuml_conda_python_cuda12_py310_aarch64
|
3.29 MB |
sha256:57259f35d37f504b6d1e0b9cda78b36a1d1366645fa890bb0e8626caf7eb7714
|
|
|
cuml_conda_python_cuda12_py310_x86_64
|
3.54 MB |
sha256:7722019ed5761718caeda043d021abab5d3f06ef479bb09afea0f6ee31baba43
|
|
|
cuml_conda_python_cuda12_py311_aarch64
|
3.51 MB |
sha256:77e18d4a735d6aed3b807a603dd0404c7d1290b766f139365a96aaf503a6069b
|
|
|
cuml_conda_python_cuda12_py311_x86_64
|
3.78 MB |
sha256:85fb4af862ec56d570ab9956c9d5fd5a04a15fdb82d00c988f286e9852c8ced1
|
|
|
cuml_conda_python_cuda12_py312_aarch64
|
3.35 MB |
sha256:1f3be52cfff1cc7d0c712d32ae007662be4cd38a9b970ae1a54d0386b3717a74
|
|
|
cuml_conda_python_cuda12_py312_x86_64
|
3.63 MB |
sha256:83f04edc9d023b288ac4aa6282494df577238a5117c9895799fc336f53645b4c
|
|
|
cuml_conda_python_cuda12_py313_aarch64
|
3.38 MB |
sha256:6affe6ea32df7a9b030458320aa5d479defa8c7b0823ddac3ade72372a71811e
|
|
|
cuml_conda_python_cuda12_py313_x86_64
|
3.65 MB |
sha256:915f3df912a64b71d860a91054a823ff2eedab14ba316d48bfa711c151b08912
|
|
|
cuml_conda_python_cuda13_py310_aarch64
|
3.29 MB |
sha256:b5f4236619dbbb94f285f217043f4fd38f891a278d1d5b74447d4b48a4e29491
|
|
|
cuml_conda_python_cuda13_py310_x86_64
|
3.54 MB |
sha256:78979c153a92418a1a741563f30cae9da5ecdac53e1382e3f30fc283c228fac5
|
|
|
cuml_conda_python_cuda13_py311_aarch64
|
3.51 MB |
sha256:7b18c17241d963ca4bcfaebd65e01de5d389fc39015cc06d59e7a40a8e3b235f
|
|
|
cuml_conda_python_cuda13_py311_x86_64
|
3.78 MB |
sha256:9c6a4ea9659f07db18f255624948ff504c65259540705547c80270bc8364a9c4
|
|
|
cuml_conda_python_cuda13_py312_aarch64
|
3.35 MB |
sha256:fde45bfa5cd33c91f0c9befc1a246af5eff57c13d748597dbf3c80944e6ce6ed
|
|
|
cuml_conda_python_cuda13_py312_x86_64
|
3.63 MB |
sha256:8d0b91dadfdcdb9b09e159b5d325e1fd80c0bb291acb06a814cea9132721e84f
|
|
|
cuml_conda_python_cuda13_py313_aarch64
|
3.38 MB |
sha256:1c9841e6c7d39643dd2e15fa44fc79ebacbdda7fa74d5c8adb5373ecbbd39d6f
|
|
|
cuml_conda_python_cuda13_py313_x86_64
|
3.65 MB |
sha256:56d8fa131a29de4e079947066c1c3e0a0ed7d4a9149c6ab6ef1931e73df2b384
|
|
|
cuml_wheel_cpp_libcuml_cu12_aarch64
|
450 MB |
sha256:ee65db5958a92432c4c1321e398333afd3dd5b6867d7b83a1ccef0c343830307
|
|
|
cuml_wheel_cpp_libcuml_cu12_x86_64
|
451 MB |
sha256:4a4975dd456a3ec8d7c8efbcb1e00b743eed46cc33b7073959d89910d90b731d
|
|
|
cuml_wheel_cpp_libcuml_cu13_aarch64
|
233 MB |
sha256:0c321a8633047d912163a3e01f0e363bd862f4741539af66a87773d582d5a8e7
|
|
|
cuml_wheel_cpp_libcuml_cu13_x86_64
|
234 MB |
sha256:0817ac8278455843c7a5cdfa6ea75163365fe88ad5ab97e520657edb7925897e
|
|
|
cuml_wheel_python_cuml_cu12_py310_aarch64
|
5.92 MB |
sha256:16f219b3437d308790d499595d03b18f3d001fea8172035848518231e1dbd9f9
|
|
|
cuml_wheel_python_cuml_cu12_py310_x86_64
|
6.33 MB |
sha256:16118d7a854bb1e5eb614f7cbebf82e68fac3c34cceea0f4f1eb2d38cd079e31
|
|
|
cuml_wheel_python_cuml_cu12_py311_aarch64
|
5.97 MB |
sha256:604390e9b16013195272962c3ab80d8e0f459f9c6823863207834412ca66059d
|
|
|
cuml_wheel_python_cuml_cu12_py311_x86_64
|
6.37 MB |
sha256:d9136d7be357444772ba1d2292e66a422787cbfbc875a0cfd112f5f5c67a42da
|
|
|
cuml_wheel_python_cuml_cu12_py312_aarch64
|
5.82 MB |
sha256:cee65cec6b4e121dcec6512992c100dcb772ec4ad6bfd46ee6c5494f18086a8d
|
|
|
cuml_wheel_python_cuml_cu12_py312_x86_64
|
6.24 MB |
sha256:9f5b3c15755492d77b5e18083c5c3c917731626dcca35e5cc0d35f6f01ae6d9a
|
|
|
cuml_wheel_python_cuml_cu12_py313_aarch64
|
5.8 MB |
sha256:b2512dbf15868ebb6182211d66d3a1eb188d43cc772a0b125f104a937f0da380
|
|
|
cuml_wheel_python_cuml_cu12_py313_x86_64
|
6.22 MB |
sha256:8cd1978a046680b18898617022d43da5915ff9fb9191a93164463632a8d2959c
|
|
|
cuml_wheel_python_cuml_cu13_py310_aarch64
|
5.86 MB |
sha256:2dc8215a13d05f4d2165a839611c6edf914a9967bfbdd101416ab264025b8111
|
|
|
cuml_wheel_python_cuml_cu13_py310_x86_64
|
6.28 MB |
sha256:c1b7d6c58f209a69b645037b5ba0ffa420e1df5970088915be2502d537972e5c
|
|
|
cuml_wheel_python_cuml_cu13_py311_aarch64
|
5.91 MB |
sha256:44be317d17464facbcdc95dd02f13bef42ad4ac2cc9c2027070138e372bcb6fd
|
|
|
cuml_wheel_python_cuml_cu13_py311_x86_64
|
6.32 MB |
sha256:3e9725f046855e388f507c7efa3f244afffd7f738333c3c4b7dbeebf22773dae
|
|
|
cuml_wheel_python_cuml_cu13_py312_aarch64
|
5.76 MB |
sha256:4f8c66b4b1697ebff7948124200132bd515153f80a8fc7005ddecb4a8ae0923d
|
|
|
cuml_wheel_python_cuml_cu13_py312_x86_64
|
6.19 MB |
sha256:c3db6fdd832e8fe36b2ca3c336aee79f2e47c3b0b2b4a4547bab8a2887ce769c
|
|
|
cuml_wheel_python_cuml_cu13_py313_aarch64
|
5.74 MB |
sha256:b74bb451ae175fba0c6beb02529eac1df3c6b2bedffc546fd28f74fc8d3480bc
|
|
|
cuml_wheel_python_cuml_cu13_py313_x86_64
|
6.17 MB |
sha256:88440ceb206643933d0bfe9ee7d8286c671f6a83796345088f85528690ea3ab6
|
|
|
sccache-client-logs-cuda13.0-conda-amd64-19978254121-1-22544
|
47.2 KB |
sha256:c5cb424289ccd52feb8169b905c59d735f193990dafb1879c52811a3385c0563
|
|
|
sccache-client-logs-cuda13.0-conda-arm64-19978254121-1-12987
|
47.3 KB |
sha256:55fed50d602f1f1679d690cef921ca9d1b9cb41f3abf15fb7fda430ba30710c3
|
|
|
sccache-client-logs-cuda13.0-pip-amd64-19978254121-1-23719
|
124 KB |
sha256:c82c277dc27e96683f8e749d22bf2bf1ccb66e9463466b27ec20b49ca8301de2
|
|
|
sccache-client-logs-cuda13.0-pip-arm64-19978254121-1-11027
|
124 KB |
sha256:92899ac83604088663e36e55101d2a0d2549e224a13dd95e7535a54b6cf22474
|
|