Update to use Python 3.9 syntax (#4909) #6065
build_wheels_genai_linux_x86.yml
on: push
generate-matrix
/
generate
6s
Matrix: pytorch/FBGEMM / build
Matrix: pytorch/FBGEMM / upload / upload
Annotations
1 warning
filter-matrix
The `python-version` input is not set. The version of Python currently in `PATH` will be used.
|
Artifacts
Produced during runtime
Name | Size | Digest | |
---|---|---|---|
pytorch_FBGEMM__3.10_cu126_x86_64
|
15.2 MB |
sha256:a28c65082e245c14d1f9005b0566536b20291e7017977b5eacd160da737a6ce6
|
|
pytorch_FBGEMM__3.10_cu128_x86_64
|
43.5 MB |
sha256:f1dc009d755b7b6358f405e4256378bf02b17253567b8636eb25c8c3b9d09880
|
|
pytorch_FBGEMM__3.10_cu130_x86_64
|
41.4 MB |
sha256:e241bd410f5b0517ac5cf82e22b8f2ec67cfb5f1fd28d27207764f8dce00a4a1
|
|
pytorch_FBGEMM__3.10_rocm6.3_x86_64
|
11.1 MB |
sha256:6815065d626ab8a7b57bcc950ac6e4443a881f3d3c74356efc616383479c7ab4
|
|
pytorch_FBGEMM__3.10_rocm6.4_x86_64
|
11.2 MB |
sha256:8843438213d9937dad179dfd020b0fdb469b6ae69e8560f16d9a1cd3a2be2db6
|
|
pytorch_FBGEMM__3.11_cu126_x86_64
|
15.2 MB |
sha256:88ec8d939405dcf19eb6597612b40ff0373b540ee511a73822a91cb481090933
|
|
pytorch_FBGEMM__3.11_cu128_x86_64
|
43.5 MB |
sha256:8e621214a774c7e9df43e32a6c2b07961aafffe5118655016ce47b548f4a0a89
|
|
pytorch_FBGEMM__3.11_cu130_x86_64
|
41.4 MB |
sha256:d58c7f02a16da4514f2c31fdf940409a1d450bb043d24d6aae7b7602e697bf94
|
|
pytorch_FBGEMM__3.11_rocm6.3_x86_64
|
11.2 MB |
sha256:cf0dbc14bab694af54c5ce1519f055948f080d87b517600ab895ec7363e006eb
|
|
pytorch_FBGEMM__3.11_rocm6.4_x86_64
|
11.2 MB |
sha256:c7aa59639cda65b72476ecb58093dd1dd3e682300ecae703caf5f0d0fc5acd8c
|
|
pytorch_FBGEMM__3.12_cu126_x86_64
|
15.2 MB |
sha256:c62de4245d55ec4a2758ce0618f77da85a3e615bd3fbf7cd9d251ddb16aebeb9
|
|
pytorch_FBGEMM__3.12_cu128_x86_64
|
43.5 MB |
sha256:e67aa48de0ab6d8b9225876dcd4b74349d49c47532a86a43f60be5dc764db982
|
|
pytorch_FBGEMM__3.12_cu130_x86_64
|
41.4 MB |
sha256:0e2b545b0845204e77a002e26d820b2fa0d686b9eae3f3de2ad6fb9354ba33e4
|
|
pytorch_FBGEMM__3.12_rocm6.3_x86_64
|
11.1 MB |
sha256:9c7f520460501c05574815474225d3a9e4ac451bc0a412d9124a13b7e039c052
|
|
pytorch_FBGEMM__3.12_rocm6.4_x86_64
|
11.2 MB |
sha256:a09e9f040ce5b3f0219626d8ceb15a77f8236812ba2c08cae634f9e9b5abe5ed
|
|
pytorch_FBGEMM__3.13_cu126_x86_64
|
15.2 MB |
sha256:98dddf283311ebb2bb16fad43f854df35ae8ae7c909526c9d60676a8fde77535
|
|
pytorch_FBGEMM__3.13_cu128_x86_64
|
43.5 MB |
sha256:a67c2b3657e716c39e71d1c640a2fa2f51e614c46fd8157d51780f1a7008fc6f
|
|
pytorch_FBGEMM__3.13_cu130_x86_64
|
41.4 MB |
sha256:6b2145b3864f4118a72a1e524378de6d7cab4c0f4bbdb99537199c3ee7151e13
|
|
pytorch_FBGEMM__3.13_rocm6.3_x86_64
|
11.1 MB |
sha256:e3557ffa1e9aeda112840d57bcd46101a3b750748fa2d35ad46717fb4559363e
|
|
pytorch_FBGEMM__3.13_rocm6.4_x86_64
|
11.2 MB |
sha256:3fbb455e48cb63033d86e6daf612603523464f136710e1ec79bb87d397e57e6f
|
|
pytorch_FBGEMM__3.13t_cu126_x86_64
|
15.2 MB |
sha256:4cbd3177cbc15120f040cddd947331e6396b727ddddbee7be700aebe1d9db259
|
|
pytorch_FBGEMM__3.13t_cu128_x86_64
|
43.5 MB |
sha256:b2b58c79e0839eaffcc14d043dcb24b3495dba7fa07083a97e9c5ee10060dd40
|
|
pytorch_FBGEMM__3.13t_cu130_x86_64
|
41.4 MB |
sha256:850e7fff2ed5984f5998582d9c910ea02cdef24baa8e53d1b5d28d4256a892e0
|
|
pytorch_FBGEMM__3.14_cu126_x86_64
|
15.2 MB |
sha256:1b1e90b91ce421ef18b475762001f1c26efec52c996986e5863eecb07fc922c7
|
|
pytorch_FBGEMM__3.14_cu128_x86_64
|
43.5 MB |
sha256:56b495b17a7836bb133aaf21ff22d8bc3e21abeb3c2d4bac5d9baae90953628e
|
|
pytorch_FBGEMM__3.14_cu130_x86_64
|
41.4 MB |
sha256:579d8da3cf0beba5c01fa917629fd2525bd0b3832ddb9a1bd6fc2b12a3955f7f
|
|
pytorch_FBGEMM__3.14_rocm6.3_x86_64
|
11.1 MB |
sha256:0fe6ff89191b9e308b30c850799ba1dbd12d98fd59fb0af21ca8765d726c316e
|
|
pytorch_FBGEMM__3.14_rocm6.4_x86_64
|
11.2 MB |
sha256:62dd43b05083df921009e96b245bfb7589b65600c11f2c0220ef555a94307989
|
|
pytorch_FBGEMM__3.14t_cu126_x86_64
|
15.2 MB |
sha256:420efb2e264cf660a5c6b78b07c48b9e94219f5627ec86f6cead924f7b3d4da5
|
|
pytorch_FBGEMM__3.14t_cu128_x86_64
|
43.5 MB |
sha256:4aa9e789b5b3a6277c8620197fb4034ba2e23e256082009f11dad55009d708e0
|
|
pytorch_FBGEMM__3.14t_cu130_x86_64
|
41.4 MB |
sha256:722fc15b1e19f7d58e2e575bb4e3bbb1811e7ee852af6835c5b6f289daa60d32
|
|
pytorch_FBGEMM__3.14t_rocm6.3_x86_64
|
11.1 MB |
sha256:f8b41d97bb2d2e967490e648e0dcd14c278abbd02d852673d5ced64ddb00d571
|
|
pytorch_FBGEMM__3.14t_rocm6.4_x86_64
|
11.2 MB |
sha256:397524d77db92567a79a7b5a18501417a554823710c8ee9e951525561c9a3319
|
|