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.dev20200914173936-cp38-cp38-win_amd64.whl (920.3 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.12.0.dev20200914173936-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.dev20200914173936-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.dev20200914173936-cp37-cp37m-win_amd64.whl (920.3 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.12.0.dev20200914173936-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.dev20200914173936-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.dev20200914173936-cp36-cp36m-win_amd64.whl (920.3 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.12.0.dev20200914173936-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.dev20200914173936-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.dev20200914173936-cp35-cp35m-win_amd64.whl (920.3 kB view details)

Uploaded CPython 3.5mWindows x86-64

tfa_nightly-0.12.0.dev20200914173936-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.dev20200914173936-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.dev20200914173936-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200914173936-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.dev20200914173936-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 3e536a9cdf7fe62816ac02903a1a7fd9184068fed9ea9e04325bb00b20750999
MD5 5b9a89bbb1980435e77a2ebfd0547b0f
BLAKE2b-256 de85029fe95991cb1fbe7bc6e67cee1c9727357e3724f3ebc5f642076bdcdaa4

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914173936-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914173936-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 30abc65766d2647c5a259faf31e63667c4d6d470463145989933b4eed001e8fe
MD5 ace6d90bddba7318ab3867f34a4d5b41
BLAKE2b-256 4411569e45d353a37eb35badb0edb8f70b8251662dfbfd00adc1646d5746ce06

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914173936-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914173936-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 250dc771dad38b5394ca9cf87eb4eb38a23645d6ea0cc782fdcb1b5e250efcad
MD5 096e4a7a254a15f39ed498e6364b53a2
BLAKE2b-256 f6e126beaca9f832337d65ae3743c30dbfd4065e2db088e466b5e9f4850562c1

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914173936-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200914173936-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.dev20200914173936-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 836d6af7d0c6ef98cde001b8f08c62ef29d5a057838c870cd124f048e30e5585
MD5 7592aa35d3ed3a6cbb692066778fe12e
BLAKE2b-256 6b539c7f6fe3024c892b69c3a7bce461d2482b12944b4c15aca662201646d7f3

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914173936-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914173936-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 fda69082f0013ad1adb1d98a65a7d39885433618cad09cba4c7bef12074319c5
MD5 65f9d3ab3483761e99da4bed8e9dad32
BLAKE2b-256 6505f9199a66338896a7a4b027fedcd04fda1e4b960919d7201ca8dab8104902

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914173936-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914173936-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 4ba718c31d5da27c022ff83e31dfa3ff4565129b0ce5e355226728b82e284c40
MD5 bced820821bc6134107d8bea38e4d3cc
BLAKE2b-256 4a5c466c91e4e37713fb90f2b518c627ddc5de8452a77261975a02703b2f04bd

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914173936-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200914173936-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.dev20200914173936-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 c92288c0fac0590c2c759179df0d83b117a14c57594cfdfb3240adcedac8e3f4
MD5 065df62d244a1b47e4a0ad72206f6f2d
BLAKE2b-256 a202c3d05bc79f1d8c5d5fa24c9bc8aaa9b03e5c106f22382d04d3f5055c568c

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914173936-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914173936-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 bebfd848ae7f9e642aeae5875b129397ff85657b47ee909a61abb13c21e0a70f
MD5 856aed318670fbaa126f7f63b15bb042
BLAKE2b-256 b79d6572b88e63ae1f472c0c10cdfca5ff86cb08aafcaca72ad9574c65a56a23

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914173936-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914173936-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 f63dc66fabbd47de1fe7c96011eb5c48280cbbe7129210f79bccb3d142976a0d
MD5 87cf3f8750b0697a9662fe22bef03bd4
BLAKE2b-256 2b2c63b90ae0476a1ffcd46cd5c48a6c1ca403b208d7638c686d0334d1a47ff8

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914173936-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200914173936-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.dev20200914173936-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 8b1bbd615a087c8882e36ed4a60ee8bcab90115a76646f7fb15d697ff7318c5b
MD5 072b38f2f2eac27e952b7b6af7d9c962
BLAKE2b-256 845f92652ec637f00a1806ceeed3f44133fdf1996fbd13414e5d907bb1937569

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914173936-cp35-cp35m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914173936-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 f25e91aca2a276066696f7f9ec540d85f410b8867d23ea072c09827a723bdca6
MD5 0d1ba581ec411580fda77c49d7cb7161
BLAKE2b-256 bf28ca503576b30b4ccaa871325ce137eb1a431fcf8975af32e0663e00d8d90e

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200914173936-cp35-cp35m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200914173936-cp35-cp35m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 ee6e159aa3bb1c8da8c32652b55b8c0d380543e62f57e4641f382718685bf837
MD5 bc8c275994120aac48b1367dfbf54029
BLAKE2b-256 34358ae68223ae02b9371171c6abd1aa0d1a204769609908b839bf4c1a54fb9a

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