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.dev20200801002138-cp38-cp38-win_amd64.whl (915.8 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.11.0.dev20200801002138-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.dev20200801002138-cp38-cp38-macosx_10_13_x86_64.whl (614.3 kB view details)

Uploaded CPython 3.8macOS 10.13+ x86-64

tfa_nightly-0.11.0.dev20200801002138-cp37-cp37m-win_amd64.whl (915.8 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.11.0.dev20200801002138-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.dev20200801002138-cp37-cp37m-macosx_10_13_x86_64.whl (614.3 kB view details)

Uploaded CPython 3.7mmacOS 10.13+ x86-64

tfa_nightly-0.11.0.dev20200801002138-cp36-cp36m-win_amd64.whl (915.8 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.11.0.dev20200801002138-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.dev20200801002138-cp36-cp36m-macosx_10_13_x86_64.whl (614.3 kB view details)

Uploaded CPython 3.6mmacOS 10.13+ x86-64

tfa_nightly-0.11.0.dev20200801002138-cp35-cp35m-win_amd64.whl (915.8 kB view details)

Uploaded CPython 3.5mWindows x86-64

tfa_nightly-0.11.0.dev20200801002138-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.dev20200801002138-cp35-cp35m-macosx_10_13_x86_64.whl (614.3 kB view details)

Uploaded CPython 3.5mmacOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.11.0.dev20200801002138-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200801002138-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 915.8 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/49.2.0 requests-toolbelt/0.9.1 tqdm/4.48.0 CPython/3.7.8

File hashes

Hashes for tfa_nightly-0.11.0.dev20200801002138-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 3047205ad2b1007afea26f7d706683ed95e73b515192db700d859487985996bf
MD5 b2c61420cd1c6ae50663b351fa7fe8a9
BLAKE2b-256 a744e9dbbcd70cbd0928d19c5c272342ef624f40a559fb73c7c38e5ade886cb0

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200801002138-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200801002138-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 dd23d023fe9237ad07d3e714bb569277b140341b86b978ed5f34572b4ded4c74
MD5 8a1d3cb3824c618f834c94bef24ee672
BLAKE2b-256 e3b3286c236f319e59c7582413b99b5d3e6664e95b46d520a284a0d946964740

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200801002138-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200801002138-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 8bd7307981eb69653b0bd1b533070ddfa67794dbee67223c21a8c5e316f4072a
MD5 1c10d77868e13e6a093e842e376861cd
BLAKE2b-256 02b16c414f983477c29322d81010927dbaba635843c18a51e1eca1a9374e3a43

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200801002138-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200801002138-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 915.8 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/49.2.0 requests-toolbelt/0.9.1 tqdm/4.48.0 CPython/3.7.8

File hashes

Hashes for tfa_nightly-0.11.0.dev20200801002138-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 9215955a9c87f167c80b8b9de59b7e6dc3b10ad0461fb4ab57aa2007b899bb12
MD5 8a02c7c200c987adf9bf3971529e0240
BLAKE2b-256 d4d1082fecc0a13c75db8f6845a2349fbb80029cf32a2e600c51d97b0ab1459a

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200801002138-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200801002138-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 6624c777796eee6afc36066d6c68dab6e004a4dd07536609a5704ff30e21cf31
MD5 6ffd39d161b97df3d3e5e5c7ea511b01
BLAKE2b-256 fd1435460b906d3f3de8860ab1ae52bef3413319e4253d4e4a413c143acc6b5e

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200801002138-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200801002138-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 ef6af1c9f4cb48fe0a67d5f5b94ed11c9dfcfac5346290b3a05b2d7f84618e88
MD5 80ccfbeab1f85b274f848202e2a13a81
BLAKE2b-256 ed66ea8275cf7cbb9e0953615a7db07638bc1241a6aea24b18e5dffeafad12fa

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200801002138-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200801002138-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 915.8 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/49.2.0 requests-toolbelt/0.9.1 tqdm/4.48.0 CPython/3.7.8

File hashes

Hashes for tfa_nightly-0.11.0.dev20200801002138-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 44d07d960b9fcef6249ff8a00a6cf5b7ae773dd02b1f4d7c06ec45e8eac2ac5f
MD5 7081a538bd52335a881d6feca089d5f2
BLAKE2b-256 332811bde4fe9b05404483b943432531a89cf18748bd6535c27af007f8a6131c

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200801002138-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200801002138-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 44483be2d5d48927a48372fa4d276fab428ce42fd416210bb1aa86ee70ac562f
MD5 4f229e86010a74f7b0bb0816d402ecaf
BLAKE2b-256 27f646f982a2fdf2d80bec07c70bcbf5e9dd75dd567d0788f51ce7da1fa71c06

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200801002138-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200801002138-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 3ec2275b2e8c69dd96f5f506fe6bc9edf946be5d03a56ad3c8a647f8d147c353
MD5 2a3e89f8676fba4f45f19c78682a695e
BLAKE2b-256 bafb84316c894b129ed4fbd3b47c09c38820f08bf8f3623e8cf374feac38ff9b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200801002138-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200801002138-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 915.8 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/49.2.0 requests-toolbelt/0.9.1 tqdm/4.48.0 CPython/3.7.8

File hashes

Hashes for tfa_nightly-0.11.0.dev20200801002138-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 5f98b65ff10c83c95d8421c582d875807c7e1091265e4088462b73517328dd07
MD5 4f7684b7cb821c8ab00821664be92bb6
BLAKE2b-256 fe78a5bb1e0db6ce75cb6039f58e215268b874fccc7721a749ae03f7d898803b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200801002138-cp35-cp35m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200801002138-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 ce26d872aa359fc4d2b9a9576a83be0326ca9070a9575d955077e8d7280b4017
MD5 a2742751f006ecff72a0553190c465c1
BLAKE2b-256 2a7b3f8e3e06b5aea23f7a9507764d18bbe9f9b085228cbdfa55996380878e1a

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200801002138-cp35-cp35m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200801002138-cp35-cp35m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 56d44d59aaec797a6be1966ceb4701c84f40a29beb3d599c2944f54a8e3756ea
MD5 37428dbd16de0e38ffb521324d05ec97
BLAKE2b-256 91722b8b6fa16dc62f80ab9201c46d633763575c4b2f35464bfd3a3d32bb2eda

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