Skip to main content

No project description provided

Project description

FBGEMM_GPU

FBGEMM_GPU-CPU CI FBGEMM_GPU-CUDA CI FBGEMM_GPU-ROCm CI

FBGEMM_GPU (FBGEMM GPU Kernels Library) is a collection of high-performance PyTorch GPU operator libraries for training and inference. The library provides efficient table batched embedding bag, data layout transformation, and quantization supports.

See the full Documentation for more information on building, installing, and developing with FBGEMM_GPU, as well as the most up-to-date support matrix for this library.

Join the FBGEMM_GPU Community

For questions, support, news updates, or feature requests, please feel free to:

For contributions, please see the CONTRIBUTING file for ways to help out.

License

FBGEMM_GPU is BSD licensed, as found in the LICENSE file.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

fbgemm_gpu-1.7.0-cp314-cp314-manylinux_2_28_x86_64.whl (470.0 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.28+ x86-64

fbgemm_gpu-1.7.0-cp313-cp313-manylinux_2_28_x86_64.whl (468.0 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ x86-64

fbgemm_gpu-1.7.0-cp312-cp312-manylinux_2_28_x86_64.whl (468.0 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ x86-64

fbgemm_gpu-1.7.0-cp311-cp311-manylinux_2_28_x86_64.whl (470.0 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ x86-64

fbgemm_gpu-1.7.0-cp310-cp310-manylinux_2_28_x86_64.whl (468.0 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ x86-64

File details

Details for the file fbgemm_gpu-1.7.0-cp314-cp314-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu-1.7.0-cp314-cp314-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 663d9e3b7dd26b35c4329207d021ed606c0f6e6a2aed88d7b2e3f2bbd913919d
MD5 e9f092e019812172dd77ce31727bcf97
BLAKE2b-256 b184cdd03853c1b0c8a741cebd4b21ceb06cb1cf89b49e54cda6bc74adc93b6f

See more details on using hashes here.

File details

Details for the file fbgemm_gpu-1.7.0-cp313-cp313-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu-1.7.0-cp313-cp313-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 03f004729c0099d694c741e9f4100f6f2ff996318d223e5de84d279c474f4eb0
MD5 bad5b7ca122e6aa632607356ded704bc
BLAKE2b-256 8c34897a2b52145aa75ac4a1606642663b1893d186ad1977a48a08e8d36099c5

See more details on using hashes here.

File details

Details for the file fbgemm_gpu-1.7.0-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu-1.7.0-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 b8d1c33ca1e55ae32b737d084ac6f75fbdbe7a332fde42aea1e4511a11d3f236
MD5 9b0bef3bb24b2e9b7ce8870fd3942f16
BLAKE2b-256 cc4212199c6f0fa029eeb3f09b79a5ad7b52bb786343719d2ca2d9b36019d288

See more details on using hashes here.

File details

Details for the file fbgemm_gpu-1.7.0-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu-1.7.0-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 c2bcdd98ff8d1ca115e53b390de14d6f8c32ee9a74a791a5b23d7f91649cd958
MD5 303f8416cd694728535960e2c99a9701
BLAKE2b-256 af92d82fb5dff30a3924561e4bf703c8d1766b7bf0779d9dbdce323fb277eb33

See more details on using hashes here.

File details

Details for the file fbgemm_gpu-1.7.0-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu-1.7.0-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 9b034443e9a8ace421a5e37c22eb6aacf5c9ab35c886e14c4f98f878cd56736d
MD5 5ac7a2722dda6585f9fc379dc4a21836
BLAKE2b-256 568d98b5a52e5b941aae4ab6cfde72b8b608cee97ab77596378b39d24c12b701

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page