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-0.12.0.dev20200918223509-cp38-cp38-win_amd64.whl (925.6 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.12.0.dev20200918223509-cp38-cp38-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64

tfa_nightly-0.12.0.dev20200918223509-cp38-cp38-macosx_10_13_x86_64.whl (628.2 kB view details)

Uploaded CPython 3.8macOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20200918223509-cp37-cp37m-win_amd64.whl (925.6 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.12.0.dev20200918223509-cp37-cp37m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.12.0.dev20200918223509-cp37-cp37m-macosx_10_13_x86_64.whl (628.3 kB view details)

Uploaded CPython 3.7mmacOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20200918223509-cp36-cp36m-win_amd64.whl (925.6 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.12.0.dev20200918223509-cp36-cp36m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.12.0.dev20200918223509-cp36-cp36m-macosx_10_13_x86_64.whl (628.3 kB view details)

Uploaded CPython 3.6mmacOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20200918223509-cp35-cp35m-win_amd64.whl (925.6 kB view details)

Uploaded CPython 3.5mWindows x86-64

tfa_nightly-0.12.0.dev20200918223509-cp35-cp35m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.5mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.12.0.dev20200918223509-cp35-cp35m-macosx_10_13_x86_64.whl (628.3 kB view details)

Uploaded CPython 3.5mmacOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.12.0.dev20200918223509-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200918223509-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 925.6 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/50.3.0 requests-toolbelt/0.9.1 tqdm/4.49.0 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200918223509-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 b9f59f3a12086b11a6351097e1bf7ad1da2cf612928b8383b876711476046e66
MD5 3925e0ae9c80577e0b34ba7c3f5506bb
BLAKE2b-256 8398e960df0671a7fdd6e72b9541cb3a45678b43c211c166c252b533b1ebe297

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200918223509-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200918223509-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 8c3d9227b538bff619a1f4d19879ce3e72485440cce97d5c246fa57c593de590
MD5 b14ed04c2b4279681f7638a24e941c8a
BLAKE2b-256 1f9e04938c56711bb0c3d1d67085ae9c9836f19fb0588582a74ada8cfdf85041

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200918223509-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200918223509-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 441c9e01f521744fb57671cf4013129bce7255ce160e99bdd78b799ee890ef69
MD5 ecacde1e11d61ace63d23701ff484cc9
BLAKE2b-256 4d0ee24c9a3aadaf2af4e46088bdf55d2e776e952e8917b10a7fc5cfac89f4e7

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200918223509-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200918223509-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 925.6 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/50.3.0 requests-toolbelt/0.9.1 tqdm/4.49.0 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200918223509-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 6c00c7bef77f5d41a6e9f657cd3f50b4c55a63b7d7bf6131c06a0a9568699786
MD5 069cfd4e58f57e8445fa698929c36b12
BLAKE2b-256 01aaefda71f92dcfe61583090a67965dff648d36cd6e6a646ee9c94b2b321afb

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200918223509-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200918223509-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 91e6312360e8a5e26424dfe03efe55bf57abf9f2440aa3dc66a1764e75d8fb0e
MD5 eebdb48f446f7aef593b2927f836ff61
BLAKE2b-256 250e813f98d4282f7c345fb98ab0187faab0a54a58fbfbdc98bba51f9d332054

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200918223509-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200918223509-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 bbaca82000010bc85e52ee43e2558db47a7bb34d961c345259aa9db7986fc041
MD5 fe6cfb1d72bf8053d5d0710c60152a26
BLAKE2b-256 29bbb3395c0a55685e0036a52675e396da66357718f86c84f2bca6a2b379140d

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200918223509-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200918223509-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 925.6 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/50.3.0 requests-toolbelt/0.9.1 tqdm/4.49.0 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200918223509-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 f84cecd97f4eaaa7176f120269e2bb3153ec06e544dec474e797b9d5e97da5c7
MD5 35b4b2b5ef51b585a98dfeffef952a57
BLAKE2b-256 87223d47e1fffafaea3f0499f6b443f96fd8b6b9818910f97336c7f6ca14f7da

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200918223509-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200918223509-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 67e888a573762944ad87c94d7aef5a43b551a9abf95b1232c32ad5ca37cc182d
MD5 67418874c2e341b224a5cf90fa4bf87c
BLAKE2b-256 643af4f6a1ee16f9b251d27be399bd83eb41fd767b6a9a68f304364e8e509f26

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200918223509-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200918223509-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 f70bededb2062ab82e472b3b30f345fbc259134bbb93e17bc71b8de8f99cdec7
MD5 ee675f2438787c1af5e1548abcb9a48a
BLAKE2b-256 908d600165b1eefa2070e0593ebf5e6942b173fa2e2984a5b2a82c393c38f591

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200918223509-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200918223509-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 925.6 kB
  • Tags: CPython 3.5m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/50.3.0 requests-toolbelt/0.9.1 tqdm/4.49.0 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200918223509-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 a11d0f4bb7e27d0e5aeb93ccd37383c9b8e2977ace904b99a2e2e644d0880cac
MD5 afef6d1e8b806e915a9ec6b1aee09fc7
BLAKE2b-256 41b5a45f21d732ba221bb81dea4219f1fbe8f75413c56d2d57c50e2fc5e708c9

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200918223509-cp35-cp35m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200918223509-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 1f939f04862a5ed86ea7cb35bf6c94d463564d4138440e74390e3c4b5d37c1c8
MD5 5087f3dec95a2d7f54e82f174b89da10
BLAKE2b-256 5bb581926d4e725a0115ace74bf444f4fbafbd3254cb4cfb41ae737b695c2de2

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200918223509-cp35-cp35m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200918223509-cp35-cp35m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 a575611272b1bac1cc676c2002f61283bbd4f8f13354649c80d280aa0887420f
MD5 15ea748998198e15e5a75abf665e7bcc
BLAKE2b-256 bfa34278516866c0f679eafb006f6a876fbc7fdc5e0261af353cb6bea4ff4dd1

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