Skip to main content

TensorFlow Addons.

Project description

TensorFlow Addons is a repository of contributions that conform to well- established API patterns, but implement new functionality not available in core TensorFlow. TensorFlow natively supports a large number of operators, layers, metrics, losses, and optimizers. However, in a fast moving field like ML, there are many interesting new developments that cannot be integrated into core TensorFlow (because their broad applicability is not yet clear, or it is mostly used by a smaller subset of the community).

Project details


Release history Release notifications | RSS feed

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.

tfa_nightly-0.17.0.dev20220520212236-cp310-cp310-win_amd64.whl (761.4 kB view details)

Uploaded CPython 3.10Windows x86-64

tfa_nightly-0.17.0.dev20220520212236-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

tfa_nightly-0.17.0.dev20220520212236-cp310-cp310-macosx_10_15_x86_64.whl (591.7 kB view details)

Uploaded CPython 3.10macOS 10.15+ x86-64

tfa_nightly-0.17.0.dev20220520212236-cp39-cp39-win_amd64.whl (761.4 kB view details)

Uploaded CPython 3.9Windows x86-64

tfa_nightly-0.17.0.dev20220520212236-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

tfa_nightly-0.17.0.dev20220520212236-cp39-cp39-macosx_11_0_arm64.whl (548.6 kB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

tfa_nightly-0.17.0.dev20220520212236-cp39-cp39-macosx_10_15_x86_64.whl (591.7 kB view details)

Uploaded CPython 3.9macOS 10.15+ x86-64

tfa_nightly-0.17.0.dev20220520212236-cp38-cp38-win_amd64.whl (761.4 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.17.0.dev20220520212236-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ x86-64

tfa_nightly-0.17.0.dev20220520212236-cp38-cp38-macosx_11_0_arm64.whl (548.6 kB view details)

Uploaded CPython 3.8macOS 11.0+ ARM64

tfa_nightly-0.17.0.dev20220520212236-cp38-cp38-macosx_10_15_x86_64.whl (591.6 kB view details)

Uploaded CPython 3.8macOS 10.15+ x86-64

tfa_nightly-0.17.0.dev20220520212236-cp37-cp37m-win_amd64.whl (761.4 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.17.0.dev20220520212236-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.17+ x86-64

tfa_nightly-0.17.0.dev20220520212236-cp37-cp37m-macosx_10_15_x86_64.whl (591.6 kB view details)

Uploaded CPython 3.7mmacOS 10.15+ x86-64

File details

Details for the file tfa_nightly-0.17.0.dev20220520212236-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220520212236-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 bb10fb5cb262cc3a377baf0ceb9ae88eca51ae491ab2f02f56a37ecf84a23176
MD5 a674e186e99a624fd0c3facd4c005e0a
BLAKE2b-256 e779d511aa928ecb8f7d0b5dd4c16d69f7af672491fd327e318681f36507d728

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220520212236-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220520212236-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ebe82b5229b33662efbba118a1045092601ebc3fe68176f47591c2213b9fdc2f
MD5 a7c3086a89350831cdf1b239db9fecea
BLAKE2b-256 aaabba94de685e9b3f5bd84af59d8cff8e0cffd471917fd6aaa494ceedacccc7

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220520212236-cp310-cp310-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220520212236-cp310-cp310-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 c5d0e37f129a4a1767d059eccdea7bed8893e70d357d5731911120b2c28c3695
MD5 e7fd2d04ab355e0db397ec002870f162
BLAKE2b-256 fc69502f9792d333abb39b909f8b2d17ae0d29c0da0e92f888bcc46431e8e52c

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220520212236-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220520212236-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 42fff47fba6fafebc416cb710ebdecdd88e0a6d033ab7137c32d32971613e938
MD5 0d42b1ec91307f19cf2dde9109638c0e
BLAKE2b-256 de6def0cd574b30e692a05192d0cc3091b93a2811c3170065f9ca652a14519eb

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220520212236-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220520212236-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 968455843392fd85babe8aee34b0d7644c7b61284916f5f04a096aa6bf0f9741
MD5 dcee2720767d313f1bad9691dca8374f
BLAKE2b-256 4ffaf3ed8224a2e08304be552dc718fcca3c6554b2d962b75d594bf5b604ff7e

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220520212236-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220520212236-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 5318eec709b82893903d24d570b3a21faa37c4376ad798ad8fa3f418649786b0
MD5 8ed1024c81e6ed136bda301a89953c5d
BLAKE2b-256 8675188ab39c1036874df2566d31d571eb1fea96415df151a2345b35257be1ac

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220520212236-cp39-cp39-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220520212236-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 7143e9a6d14370a7e4a1addfa239542ea384d3ad3401c146b10635e2eb7e4b0a
MD5 f25cebdfd255dda5975b874407e9ae2c
BLAKE2b-256 d3c9675f3b515ad30b0b2492cf3296cabd78302a504719b09eb4294cb7faae98

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220520212236-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220520212236-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 471e750dbbf0152f2bbb9cd69903fc84405fc9bc8f90bae2e520f0f35c71cb97
MD5 03f8ba1793f3fd7520fc18a638c8b2cf
BLAKE2b-256 b83c7348df324e62d6d437110dd2f532b5aebe1df30cc7c322cc2a5ad0c0c872

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220520212236-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220520212236-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 9eb12be44fea72dac1f5382e473a7ca6553a7ea8d2f6aee030d79d7eeab9444a
MD5 5eb352708450fceb25c71a2bdd15ab49
BLAKE2b-256 fd6ef6c931c3730b7a3567dcf46b8c6fa35019b17aa23f90f807625718e0989b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220520212236-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220520212236-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a832e856be5a5694283236e0b1ee5a61c1507dc5884463b56f96ce55cf66e56b
MD5 06c4c8198fe260a49c0d762b5193200f
BLAKE2b-256 734880a4a56bbc4da436ecb23e9c968fa20c10a98109ebbe1f504390ce493f88

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220520212236-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220520212236-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 7f7fb333cbb7c694c0c734aea8d796389354aa8d61561bdd65156b96686bbcd8
MD5 bb602b6649f63710b1c6f5b0979608bd
BLAKE2b-256 cb540569397fcc9d3be32711ad301c43fc7ee29b60f6b46250717a578b2d05ec

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220520212236-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220520212236-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 e06179b5516944063632f074322d6104750398bfb705d8e078d2121efdefa3d6
MD5 dac28216247df6e57b1b9c2db00042a2
BLAKE2b-256 38042f613a2bd39113e4a90a16015bdd095ca9790626db516236ab97a3164384

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220520212236-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220520212236-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 7165c0b1f7d4309e753b065e1f855eb1e0cdfdb95bb37d543a8684f58799c48d
MD5 b2deda1928e6d1efbc84ccddac3f012a
BLAKE2b-256 ec2bdea328847064b7ab835e236f10c544903e5d603fed5bda6d2a493247b327

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220520212236-cp37-cp37m-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220520212236-cp37-cp37m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 18ee54e0db7d28a6fed442ddd25320c13259f5bd4e7e0bc61077fcf86eeda0fb
MD5 50971e3c48b1eeeacc382dfce5f41b49
BLAKE2b-256 ec467caca817472aa3c8aec60364c3ca12c726c97bb2b58b71bd6130b3f63d57

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