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.dev20200914191129-cp38-cp38-win_amd64.whl (920.3 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.12.0.dev20200914191129-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.dev20200914191129-cp38-cp38-macosx_10_13_x86_64.whl (622.9 kB view details)

Uploaded CPython 3.8macOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20200914191129-cp37-cp37m-win_amd64.whl (920.3 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.12.0.dev20200914191129-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.dev20200914191129-cp37-cp37m-macosx_10_13_x86_64.whl (622.9 kB view details)

Uploaded CPython 3.7mmacOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20200914191129-cp36-cp36m-win_amd64.whl (920.3 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.12.0.dev20200914191129-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.dev20200914191129-cp36-cp36m-macosx_10_13_x86_64.whl (622.9 kB view details)

Uploaded CPython 3.6mmacOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20200914191129-cp35-cp35m-win_amd64.whl (920.3 kB view details)

Uploaded CPython 3.5mWindows x86-64

tfa_nightly-0.12.0.dev20200914191129-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.dev20200914191129-cp35-cp35m-macosx_10_13_x86_64.whl (622.9 kB view details)

Uploaded CPython 3.5mmacOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.12.0.dev20200914191129-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200914191129-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 920.3 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.dev20200914191129-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 11140373b3a261e2b8c9971f417e23ef516fd67407eab92534851d2ad1e1806d
MD5 64a7d519b56b4c784fce46320e41baf4
BLAKE2b-256 e1d5014e495e5d8cb3f4efbc2ecaa9d42506fe100a62ee1d770a1ccc6fb4f1e8

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914191129-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914191129-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 9543080de618e398399bc32798afb3433b0b693b1629c1f7c97387cb26ee7eeb
MD5 6837995321294253f9b3d6639f87beda
BLAKE2b-256 5644a350d828c69acbdd4acac0090723cc8c3dcf50ce03ed22e6f75d76563b08

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914191129-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914191129-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 052e7f7c93302144a83c0e777b3b6f9cee3fa337df68d798133b2efdec9e6d8c
MD5 d128eba20c992f7debd918a1dd69d9be
BLAKE2b-256 e1c5526c57c1bbae009d3eb3a855fe0f76a834d401f6ff68aef7eac911c9694c

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914191129-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200914191129-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 920.3 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.dev20200914191129-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 56f488549d4b728d0dc0997f31b134b3f0d0a804d3c9a94636de7e2ab7538d95
MD5 139e9c1d1225efbd91b5bc75b295edd9
BLAKE2b-256 a8b744abca5930ff8fe6e128dfdf92f7e9c048902ee781b1e354ab5866f1eb17

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914191129-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914191129-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 0708279650504722758cf120156c0b8e9b50f98b8547d70cc5410c58eb6ef33c
MD5 fda6620b357fd6140b5f296035d3cb90
BLAKE2b-256 a620d49e2cbf839e1dc149f751698d0dc8f56696fed08323ee6db811a36871dd

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914191129-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914191129-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 3a18c3aae9a404385ee7ad6e53e2a292b3985947201ba2f5615c6294b9f2db29
MD5 8803e80a60bcecbe66570a65bd051be1
BLAKE2b-256 8eec575df80c4d3496589c42363ddeb398b2069c19bb27cc1022cf929a0b4dac

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914191129-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200914191129-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 920.3 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.dev20200914191129-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 9d7ee18f4cc626ce6cc256930f3ba7672ae62294f07edf4f42cbb7896d1c68ce
MD5 2e3ffb9b3aabd08916a9f668ca8dc639
BLAKE2b-256 d0cb265e2de094395ab985ed99ca2ab2c78d9228acba054a107b379cb4b3d0de

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914191129-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914191129-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 3996431c3b4599c38bb8377e8c02be9066c8f7184a75f4a30ffc3f34029796b5
MD5 4e880012eddb8b622ad1344a08293f9d
BLAKE2b-256 898ed9bac97fbabbf3b046cbd630d0a37942e880726e6c1991554be375421ccc

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914191129-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914191129-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 35b36d6215d93194a50cc05417b99bc567188c5160fe2ba8f86ea775a0af95e0
MD5 bf875d93b34b7f4499510fae22096a08
BLAKE2b-256 eaead3cb20fccfb7cc6b192f6d632f5b2f5f9927baae96e3c6ba2c92f946e7cf

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914191129-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200914191129-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 920.3 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.dev20200914191129-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 ec13c67815209485fedc9ec5ff94f53035519694f105e1b03e219985944c961a
MD5 2a1e547e9930f70edb08b51bba5cf8fb
BLAKE2b-256 62c830a2fe5423150ed91cb6e6e4b504c5ce82e7a2e5e59378fd886f36d89783

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914191129-cp35-cp35m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914191129-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 0a0b8c4bd23627b95d45f2e58f0857cb024f073175841f3d65b57b8ab8f07831
MD5 509be7846b4b6accce621f7ab0da774b
BLAKE2b-256 83c1c5b7066d67eba0df3a9309b296526e7bafaecf049879f09b860bb17b6854

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914191129-cp35-cp35m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914191129-cp35-cp35m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 1f50a3386250b100fb22ef13f7b6e3c16971b05c412bae70902d2a016cc91370
MD5 67d066e3aa33212e669a6ad928fdfc5f
BLAKE2b-256 fb0431ad77c227d93dfacd60014112b2fd86e6f471f500fd46c83ae65b64a106

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