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-0.11.0.dev20200522152948-cp38-cp38-win_amd64.whl (895.7 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.11.0.dev20200522152948-cp38-cp38-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200522152948-cp38-cp38-macosx_10_13_x86_64.whl (590.5 kB view details)

Uploaded CPython 3.8macOS 10.13+ x86-64

tfa_nightly-0.11.0.dev20200522152948-cp37-cp37m-win_amd64.whl (895.7 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.11.0.dev20200522152948-cp37-cp37m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200522152948-cp37-cp37m-macosx_10_13_x86_64.whl (590.5 kB view details)

Uploaded CPython 3.7mmacOS 10.13+ x86-64

tfa_nightly-0.11.0.dev20200522152948-cp36-cp36m-win_amd64.whl (895.7 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.11.0.dev20200522152948-cp36-cp36m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200522152948-cp36-cp36m-macosx_10_13_x86_64.whl (590.5 kB view details)

Uploaded CPython 3.6mmacOS 10.13+ x86-64

tfa_nightly-0.11.0.dev20200522152948-cp35-cp35m-win_amd64.whl (895.7 kB view details)

Uploaded CPython 3.5mWindows x86-64

tfa_nightly-0.11.0.dev20200522152948-cp35-cp35m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.5mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200522152948-cp35-cp35m-macosx_10_13_x86_64.whl (590.5 kB view details)

Uploaded CPython 3.5mmacOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.11.0.dev20200522152948-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200522152948-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 895.7 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.4.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200522152948-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 da199860d39718661806a4787c7c90247351ab0e1e62c774172bb9bae8f6af3c
MD5 26d4c95916dc7445a526feb85dce4303
BLAKE2b-256 92b4aa1eeab387ba1ec72bd8eb17e497464dbcd0b1966e07e4e27bc57e948183

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200522152948-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200522152948-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 007aaa98a4855301d27b9b74a45c9df0625381dd7fed406b080ec66e491ea358
MD5 e4eb6ec7c545f637f7668c9a1bfd7be4
BLAKE2b-256 d26d0b53c90e0f0313431394cd2cc766507ceee8a785527e16030f5135c4de0b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200522152948-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200522152948-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 2f3bb3dead3b9434a472860226886173dc079e5bbdf7095020269bd0ce19a22b
MD5 233ec9ed2661ff66cb21d2e27db5da46
BLAKE2b-256 73ff06886f46851bf19c075ba63773354a4064bd583063f83f0f24108cf623b4

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200522152948-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200522152948-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 895.7 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.4.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200522152948-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 e869b7dfc0c35c39a99aad260b119fed8849b77ea9ed2ab56a259ca49968412d
MD5 878f2dfce02cb2d95d86df39c0c9389b
BLAKE2b-256 9e363f998358a8cc8e26d578fb0bc597c146857339534fdf37ffe5a456813eab

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200522152948-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200522152948-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 e2553e6079da57325fcd1345cb2b536a6668c29c1e15b3190a72ebca1faffece
MD5 a86677bb314e6731087a8cd3665eaf18
BLAKE2b-256 4f81b667b52caaf1e973528274312b377d8c2b70bc92461278d54f245be250e7

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200522152948-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200522152948-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 ed5c8e5994967366ba1f3569402134a1e53bf7bd77a104acd00efb0a446c1402
MD5 3edf60de283d07162e9b19e9d90d7997
BLAKE2b-256 dea6a90c733eeb143471851b09c4db3343c1e24e1c92358e12db7de2f642606d

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200522152948-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200522152948-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 895.7 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.4.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200522152948-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 b6bbabac370da7180eb08f4c2d1af39d35c3657527bb8f79fa285d3c4f8ec957
MD5 8be1caec9504ad4e48c4e88c438bbbdf
BLAKE2b-256 d7d969029506b90ada5cb8b8cfce5298eac873547ca95bab5a15a05a62f90ef3

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200522152948-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200522152948-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 b13939e02544c92982df54a0bd0979ebb006102d3db86e4e446475c12ab64f5f
MD5 8367a1f8bc48e9493acf6c87e63bb00d
BLAKE2b-256 ff0a34c2b01d55172d509f043ce6769ce3ef218e404fe54bfe7c88bf9b45fe16

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200522152948-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200522152948-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 36a664b5e37cf15b862b82f2d3823bcda83d969ab014412f6c98e4af9c111123
MD5 ecdc473ef8260dc3741cc94fb9b2e1db
BLAKE2b-256 073fa3edf54f76b449f11477682126899963f8dd3bc2d6e0c03c389168e666a1

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200522152948-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200522152948-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 895.7 kB
  • Tags: CPython 3.5m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.4.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200522152948-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 29ca5dea4d22d7b9f29ae944002bb7a49b2ebd4b0ea4d8cb66c346f70acd37e0
MD5 6a2ec6d7c6c11170d1df197b2e587112
BLAKE2b-256 344e17da9d8d785b817eb8143cd25ad98b7056d24cf45b79b9bef408aee98601

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200522152948-cp35-cp35m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200522152948-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 bd96c13f8b16908af2da9ed32929ef0e025a170ae785c570684cc6d0e0ae2b08
MD5 fb97c6aacc86ec874bfea29d25d6dcff
BLAKE2b-256 40fdf8f8e347f1520d51a8da1a0a5aaf3e288d3fda62ca08261814535cd621b1

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200522152948-cp35-cp35m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200522152948-cp35-cp35m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 e57be94c4fd6683905d0512d4fe01e75f87d82880c577ef07bd40c48ff194b27
MD5 b54e1a6cd6e815bad0b35ad3523942d4
BLAKE2b-256 8d717dbf41c8d3960809879fef6be18b6082e4c3ce7b55cca0a0750fde94082c

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