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-1.8.0-cp314-cp314-manylinux_2_28_x86_64.whl (495.2 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.28+ x86-64

fbgemm_gpu-1.8.0-cp313-cp313-manylinux_2_28_x86_64.whl (495.2 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ x86-64

fbgemm_gpu-1.8.0-cp312-cp312-manylinux_2_28_x86_64.whl (495.2 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ x86-64

fbgemm_gpu-1.8.0-cp311-cp311-manylinux_2_28_x86_64.whl (493.1 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ x86-64

fbgemm_gpu-1.8.0-cp310-cp310-manylinux_2_28_x86_64.whl (495.2 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ x86-64

File details

Details for the file fbgemm_gpu-1.8.0-cp314-cp314-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu-1.8.0-cp314-cp314-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 2c3b52a5cdcaef86859815762504e756ec368c0e24ae51576a2b4dd32b049007
MD5 d601d027854bab36ed7c6d80a8e25917
BLAKE2b-256 f98029b038454e4e59b71b34df207ca8730c4f6670608f939d679aa345c79d5f

See more details on using hashes here.

File details

Details for the file fbgemm_gpu-1.8.0-cp313-cp313-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu-1.8.0-cp313-cp313-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 acc22d0d0e35159bea42b3f295dcffef036c490d3cf58dde95fc368d35a8958a
MD5 ef5c5b90c9a69cbcca4696a59224bc20
BLAKE2b-256 5e3f00793a47b89b999b94f6daa74a086bfe7979b5a7ba3b89380ea88333f9ee

See more details on using hashes here.

File details

Details for the file fbgemm_gpu-1.8.0-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu-1.8.0-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 4e630a834586a0af4a07de4c444c8055f673679bcd26ef05441109489168f375
MD5 8113c3aae2cc3c883afc91451059cf61
BLAKE2b-256 46ba2474fdd7896d0881ec5ec282fc6bc92819ced607881ecb4c301b838f6fb9

See more details on using hashes here.

File details

Details for the file fbgemm_gpu-1.8.0-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu-1.8.0-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 6cd8ab6c201eac3a61f0b5a499c5936571fb9311b31410068339babc4f2eac3b
MD5 2784c4e495fa768eba5e502afc002366
BLAKE2b-256 1f5079f523b5d536e9ec3e7f7c7d938c51b08e8756aff019297abca5abe2663e

See more details on using hashes here.

File details

Details for the file fbgemm_gpu-1.8.0-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu-1.8.0-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 c3eb8f37278a430dc82d1cc4316fc497552c6ca1b3780c46bdb3a0fcc9d90e33
MD5 7855cdb1a82b60b7d0ef6f587831c507
BLAKE2b-256 3e0804b29f4273a0aa91424a6c106215c09ac515218b88374b73f13fe5a8b00c

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