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.dev20200911002148-cp38-cp38-win_amd64.whl (917.6 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.12.0.dev20200911002148-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.dev20200911002148-cp38-cp38-macosx_10_13_x86_64.whl (620.3 kB view details)

Uploaded CPython 3.8macOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20200911002148-cp37-cp37m-win_amd64.whl (917.7 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.12.0.dev20200911002148-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.dev20200911002148-cp37-cp37m-macosx_10_13_x86_64.whl (620.3 kB view details)

Uploaded CPython 3.7mmacOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20200911002148-cp36-cp36m-win_amd64.whl (917.7 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.12.0.dev20200911002148-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.dev20200911002148-cp36-cp36m-macosx_10_13_x86_64.whl (620.3 kB view details)

Uploaded CPython 3.6mmacOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20200911002148-cp35-cp35m-win_amd64.whl (917.6 kB view details)

Uploaded CPython 3.5mWindows x86-64

tfa_nightly-0.12.0.dev20200911002148-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.dev20200911002148-cp35-cp35m-macosx_10_13_x86_64.whl (620.3 kB view details)

Uploaded CPython 3.5mmacOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.12.0.dev20200911002148-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200911002148-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 917.6 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/4.48.2 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200911002148-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 ad6786f00eaf6fb3f65c450f95c534f454adbcde3093a48cfb022719af3da667
MD5 b5b74926c132076a9a4d16df20ce9e0c
BLAKE2b-256 c5bab5a0e2c146b09f4a9b1ee40d6363fdba707f36e6d36b88721c47719dbd5d

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200911002148-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200911002148-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 c6f411353fbfcdc56f47dba2d64cac30566f96acd6c1f30d54d79a432aeb8683
MD5 d71a4e41e8e3974e8bacb0cc547c087e
BLAKE2b-256 8e28513c9c82eddb9abf0816aaca7e3b285ee3096a11376b68bfe50dcbb38de7

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200911002148-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200911002148-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 37dee5db499a23cf1e0a761aa2d0addf7fc33c9d1c427aa6670454e9bea95ab8
MD5 6db9f107e638811f4e1645bf8934c318
BLAKE2b-256 7edcd4c7716ad104dc60ca01b41a160592a0815ae245af2bf0cb8f7218568000

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200911002148-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200911002148-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 917.7 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/4.48.2 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200911002148-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 5ede3f02543bda7f9be3322fb035ab6b40f3fa064959ce12f5462018815fa2a3
MD5 73f434da3654b6615206c3dc1b0d493f
BLAKE2b-256 c0cd2ac3a148faaaf505d76bca305960fa1614ea14c669428d27e8fbfd4361d5

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200911002148-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200911002148-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 2d475dbb6989ae01d7f45bd6d4867f2fc39d6fc16541dd13e3929249709dd998
MD5 d20b196df79fb72a4a5e91505f2a9d3f
BLAKE2b-256 71af457b24990ff58a38e4d7f21799780a7c7da133557d5844b96d999b1868ea

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200911002148-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200911002148-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 a212e5b050462226e2dd6a91a077f95f8ba69f9abb9fc6f639c8ea60a73b529f
MD5 e8a346edfee01c52ad11d05f8e89ae74
BLAKE2b-256 09b47c0ad6ba4e20d8c964b5b01dddbb4ccc33f54b3064caf98c817aff220a3c

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200911002148-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200911002148-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 917.7 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/4.48.2 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200911002148-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 5b927c4f32589042db99b07d6e4cec9bafa6bf4080d103e5f2a4495935cb77ea
MD5 c04992e969c8997a32cdfe51e7ac15ac
BLAKE2b-256 b908e991860df1ea94c437bbf69fe68288cad3dd4bce957becea40ad5a81deae

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200911002148-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200911002148-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 d5eeb9854f4323417dc684ffd977cefe22b8237655d111ca04d18d6c4ae091b6
MD5 6861b1bc2f4fdf7e8bd663d01e94f047
BLAKE2b-256 6a4f396ccaef27b4c967094fe2caa8668eb15ccc0a65119f9774d1655fa5742d

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200911002148-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200911002148-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 d855f967920c0b2b39ee8f9f83f9d10bf354733f1acfcf5a139ddcd0d90f04c5
MD5 309e2dd8fbd9d1bf64dce5c80b16b995
BLAKE2b-256 c78bea0575bc5211648e5819b4ec94888945a1c8b9f236c14400920c730d439f

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200911002148-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200911002148-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 917.6 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/4.48.2 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200911002148-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 2f1eb729a3ac5cc7485cb284f07630cac1b6f00913b653728d161517dd4b59ff
MD5 1da558fbe39929fdb67c2d39c7e27f54
BLAKE2b-256 dba88104d52d1e65695b0661add2ae46860ad38c91745a77872e9549c513d30b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200911002148-cp35-cp35m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200911002148-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 4133b8e4c9d6a1c0efe30310e129e931c69354ded7e63ce65562043c203077b3
MD5 19aa006a05c60d47dade54d34a4a7be1
BLAKE2b-256 70daf57e1252f314b12b87d2d823b38fa8ba78625c6c4232e20df8db6351f6f3

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200911002148-cp35-cp35m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200911002148-cp35-cp35m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 dd9024bff8165d6fc908c5262512996bcf8b3850973fffa79f7943c98c0fcef7
MD5 b7470d391abcdcf4c6ae8f55ae9ec346
BLAKE2b-256 0be6243c4f5ebd4007d50e447270707bcbe4fe54bb97f993fddf3da12717cd48

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