Optimize if-statements with if-constexpr (#4022) #5950
facebook-github-botfbgemm_gpu_ci_genai.yml
on: push
Matrix: build_artifact
Matrix: test_and_publish_artifact
Annotations
8 errors
|
build_artifact (x86, linux.24xlarge, 3.10, 12.8.0, clang)
The self-hosted runner lost communication with the server. Verify the machine is running and has a healthy network connection. Anything in your workflow that terminates the runner process, starves it for CPU/Memory, or blocks its network access can cause this error.
|
|
build_artifact (x86, linux.24xlarge, 3.13, 12.8.0, clang)
The self-hosted runner lost communication with the server. Verify the machine is running and has a healthy network connection. Anything in your workflow that terminates the runner process, starves it for CPU/Memory, or blocks its network access can cause this error.
|
|
build_artifact (x86, linux.24xlarge, 3.11, 12.8.0, gcc)
The self-hosted runner lost communication with the server. Verify the machine is running and has a healthy network connection. Anything in your workflow that terminates the runner process, starves it for CPU/Memory, or blocks its network access can cause this error.
|
|
build_artifact (x86, linux.24xlarge, 3.9, 12.8.0, gcc)
The self-hosted runner lost communication with the server. Verify the machine is running and has a healthy network connection. Anything in your workflow that terminates the runner process, starves it for CPU/Memory, or blocks its network access can cause this error.
|
|
test_and_publish_artifact (x86, linux.g5.4xlarge.nvidia.gpu, 3.11, 12.8.0, 12.6.3, gcc)
Unable to download artifact(s): Artifact not found for name: fbgemm_gpu_nightly_genai_x86_gcc_py3.11_cu12.8.0.whl
Please ensure that your artifact is not expired and the artifact was uploaded using a compatible version of toolkit/upload-artifact.
For more information, visit the GitHub Artifacts FAQ: https://github.com/actions/toolkit/blob/main/packages/artifact/docs/faq.md
|
|
test_and_publish_artifact (x86, linux.g5.4xlarge.nvidia.gpu, 3.13, 12.8.0, 12.6.3, clang)
Unable to download artifact(s): Artifact not found for name: fbgemm_gpu_nightly_genai_x86_clang_py3.13_cu12.8.0.whl
Please ensure that your artifact is not expired and the artifact was uploaded using a compatible version of toolkit/upload-artifact.
For more information, visit the GitHub Artifacts FAQ: https://github.com/actions/toolkit/blob/main/packages/artifact/docs/faq.md
|
|
test_and_publish_artifact (x86, linux.g5.4xlarge.nvidia.gpu, 3.9, 12.8.0, 12.6.3, gcc)
Unable to download artifact(s): Artifact not found for name: fbgemm_gpu_nightly_genai_x86_gcc_py3.9_cu12.8.0.whl
Please ensure that your artifact is not expired and the artifact was uploaded using a compatible version of toolkit/upload-artifact.
For more information, visit the GitHub Artifacts FAQ: https://github.com/actions/toolkit/blob/main/packages/artifact/docs/faq.md
|
|
test_and_publish_artifact (x86, linux.g5.4xlarge.nvidia.gpu, 3.10, 12.8.0, 12.6.3, clang)
Unable to download artifact(s): Artifact not found for name: fbgemm_gpu_nightly_genai_x86_clang_py3.10_cu12.8.0.whl
Please ensure that your artifact is not expired and the artifact was uploaded using a compatible version of toolkit/upload-artifact.
For more information, visit the GitHub Artifacts FAQ: https://github.com/actions/toolkit/blob/main/packages/artifact/docs/faq.md
|
Artifacts
Produced during runtime
| Name | Size | Digest | |
|---|---|---|---|
|
fbgemm_gpu_nightly_genai_x86_clang_py3.10_cu11.8.0.whl
|
5.25 MB |
sha256:04f25abc45aaad9a671da35e37de349666d58d51f633bda71aabe2e720d74f84
|
|
|
fbgemm_gpu_nightly_genai_x86_clang_py3.10_cu12.6.3.whl
|
11.9 MB |
sha256:8a403b079179a9018adb24a8e0d7ed98e32d109d68412c9e32f090a92f8d0463
|
|
|
fbgemm_gpu_nightly_genai_x86_clang_py3.11_cu11.8.0.whl
|
5.25 MB |
sha256:e38c02ec131e0e5075d615c5c8a04bfeb8b184fb457f646a8b07c3ec885157e8
|
|
|
fbgemm_gpu_nightly_genai_x86_clang_py3.11_cu12.6.3.whl
|
11.9 MB |
sha256:7305738db85486d6ee84ba781c06fc43a7bfd0bae10b420a78027439eadeef12
|
|
|
fbgemm_gpu_nightly_genai_x86_clang_py3.11_cu12.8.0.whl
|
17.5 MB |
sha256:61b872dcb15a177a136484cd0b25696e93b28c0293bd3ebed1a1d6ee28a388a8
|
|
|
fbgemm_gpu_nightly_genai_x86_clang_py3.12_cu11.8.0.whl
|
5.25 MB |
sha256:bbdaf160ce0f1eff70f0a291f6c5c14f5354ce1ba510fbda6e6b15e29eaa8d57
|
|
|
fbgemm_gpu_nightly_genai_x86_clang_py3.12_cu12.6.3.whl
|
11.9 MB |
sha256:06196a841564d39e0bea526bb74f2cd2bbd1d0b8ece3e63898c4ba41ef3b6bca
|
|
|
fbgemm_gpu_nightly_genai_x86_clang_py3.12_cu12.8.0.whl
|
17.5 MB |
sha256:1db30b8aca237ebfbbd07e9fc49c182ad01c8c648a5c220d0fa127d8481e7b3c
|
|
|
fbgemm_gpu_nightly_genai_x86_clang_py3.13_cu11.8.0.whl
|
5.25 MB |
sha256:480bc2d491c38c5ea2611d9483c7e65ed5c65cc65eba0b399cce59b11e94e1a1
|
|
|
fbgemm_gpu_nightly_genai_x86_clang_py3.13_cu12.6.3.whl
|
11.9 MB |
sha256:4d6dee662b7fbfbc33d71d0301dc25c63ec30aafa99ccdd808b71ad2020268cc
|
|
|
fbgemm_gpu_nightly_genai_x86_clang_py3.9_cu11.8.0.whl
|
5.25 MB |
sha256:fbe7d6e032fac6563c4b74762a018518ceed676fa44c645edd127682c449f7d3
|
|
|
fbgemm_gpu_nightly_genai_x86_clang_py3.9_cu12.6.3.whl
|
11.9 MB |
sha256:4686bc564a90d681084c38667f0f471cee17bf6feeec753cc5a6c0c62dae4270
|
|
|
fbgemm_gpu_nightly_genai_x86_clang_py3.9_cu12.8.0.whl
|
17.5 MB |
sha256:01d4fa71dc247180e2b74dc28b1969a02f807fbd33365a66d4224845db5de391
|
|
|
fbgemm_gpu_nightly_genai_x86_gcc_py3.10_cu11.8.0.whl
|
5.15 MB |
sha256:4e2ceb43cb6f8844b71fe21cf509a7a0e76ddf7a7c7b3b2c1f57fc28c4c7d75e
|
|
|
fbgemm_gpu_nightly_genai_x86_gcc_py3.10_cu12.6.3.whl
|
11.8 MB |
sha256:e76893170ae327fe5beeb2fcd8e0e6ea3ddb4398b76b2229cd04534e7a49d5b5
|
|
|
fbgemm_gpu_nightly_genai_x86_gcc_py3.10_cu12.8.0.whl
|
17.5 MB |
sha256:4fdf81d9789c6d8f50daca1563b420894483caa62f97a5e29bdc18fa1d90e941
|
|
|
fbgemm_gpu_nightly_genai_x86_gcc_py3.11_cu11.8.0.whl
|
5.15 MB |
sha256:5af928e3687d3ddb874033437d04c4a9dfc40c7f47b48b37ca5a6c3c51d444cb
|
|
|
fbgemm_gpu_nightly_genai_x86_gcc_py3.11_cu12.6.3.whl
|
11.8 MB |
sha256:148a3461c8250dfcf20d3e7f1a04fa57214c1c5511cfb83aa6cfab8a4d70500d
|
|
|
fbgemm_gpu_nightly_genai_x86_gcc_py3.12_cu11.8.0.whl
|
5.15 MB |
sha256:cfc2d16dda7a2d11d6583cf2d4a59a90c1e8143de057a33b0f28a2045d7c1865
|
|
|
fbgemm_gpu_nightly_genai_x86_gcc_py3.12_cu12.6.3.whl
|
11.8 MB |
sha256:71c92eb72f7e3c00a77c1a11dc549ab4b5183afe81de3d5d3d33e978f5c850ff
|
|
|
fbgemm_gpu_nightly_genai_x86_gcc_py3.12_cu12.8.0.whl
|
17.5 MB |
sha256:6483f3b8d0b5b6698ed294baf19566c2373a209b935f767e2bbecabc34313962
|
|
|
fbgemm_gpu_nightly_genai_x86_gcc_py3.13_cu11.8.0.whl
|
5.15 MB |
sha256:4aa04b30d6a45969a5915f8fe8a3874f975b99fb5adec9d90fe3a91f0a69efe5
|
|
|
fbgemm_gpu_nightly_genai_x86_gcc_py3.13_cu12.6.3.whl
|
11.8 MB |
sha256:57c4d45b0b2a4f1f02fb35a43fb461d42cea319f6a862335de24a14ed5ef2373
|
|
|
fbgemm_gpu_nightly_genai_x86_gcc_py3.13_cu12.8.0.whl
|
17.5 MB |
sha256:0a317e396a03c3a617581da3200e5672f0436507daa0609c465040f14b76ecf1
|
|
|
fbgemm_gpu_nightly_genai_x86_gcc_py3.9_cu11.8.0.whl
|
5.15 MB |
sha256:08b555a395c96fd963656b6abbb349d13a5d7cb8c881b934b9a6eeac369a793a
|
|
|
fbgemm_gpu_nightly_genai_x86_gcc_py3.9_cu12.6.3.whl
|
11.8 MB |
sha256:24ab602745fd12290bc03a6937be13b87909d7ae2d4ea18dd674f2e70a6739de
|
|