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

tfa_nightly-0.14.0.dev20210803212520-cp39-cp39-win_amd64.whl (747.3 kB view details)

Uploaded CPython 3.9 Windows x86-64

tfa_nightly-0.14.0.dev20210803212520-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.12+ x86-64

tfa_nightly-0.14.0.dev20210803212520-cp39-cp39-macosx_10_13_x86_64.whl (579.1 kB view details)

Uploaded CPython 3.9 macOS 10.13+ x86-64

tfa_nightly-0.14.0.dev20210803212520-cp38-cp38-win_amd64.whl (747.3 kB view details)

Uploaded CPython 3.8 Windows x86-64

tfa_nightly-0.14.0.dev20210803212520-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.12+ x86-64

tfa_nightly-0.14.0.dev20210803212520-cp38-cp38-macosx_10_13_x86_64.whl (579.1 kB view details)

Uploaded CPython 3.8 macOS 10.13+ x86-64

tfa_nightly-0.14.0.dev20210803212520-cp37-cp37m-win_amd64.whl (747.3 kB view details)

Uploaded CPython 3.7m Windows x86-64

tfa_nightly-0.14.0.dev20210803212520-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.12+ x86-64

tfa_nightly-0.14.0.dev20210803212520-cp37-cp37m-macosx_10_13_x86_64.whl (579.1 kB view details)

Uploaded CPython 3.7m macOS 10.13+ x86-64

tfa_nightly-0.14.0.dev20210803212520-cp36-cp36m-win_amd64.whl (747.3 kB view details)

Uploaded CPython 3.6m Windows x86-64

tfa_nightly-0.14.0.dev20210803212520-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.12+ x86-64

tfa_nightly-0.14.0.dev20210803212520-cp36-cp36m-macosx_10_13_x86_64.whl (579.2 kB view details)

Uploaded CPython 3.6m macOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.14.0.dev20210803212520-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.14.0.dev20210803212520-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 747.3 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.7.11

File hashes

Hashes for tfa_nightly-0.14.0.dev20210803212520-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 44ffe79f88251cfa2690e15e7165bd6d084237f1f7be1e58fc050f30a1c10833
MD5 76d9602d224406e663899df96b5e008d
BLAKE2b-256 3290d93da631c93d84747f1d003a8b5a1dc5b5af7b358d6046f4252b55080c70

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.14.0.dev20210803212520-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.14.0.dev20210803212520-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 463d9688c61c86faaf72cb6564ea2bb1857dfd2f78a0f8e3060bf4d627e3e366
MD5 a18ba549a138be5f6c8f2fca34c1df85
BLAKE2b-256 b3001fc63cc3d3ebac9c2a0422c60fa5aa23b8c75cd513c9cdf91ec3485d1c42

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.14.0.dev20210803212520-cp39-cp39-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.14.0.dev20210803212520-cp39-cp39-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 5a06bc63270d08bf5fdf6c762e9b9d9b17f92a636092bcf3d8afa26218715346
MD5 fb5562028eb1182d436c57680eb1072e
BLAKE2b-256 ea2574e345ad673455fae49d1453a40b69af2afd7422b578c6c94bea79340993

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.14.0.dev20210803212520-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.14.0.dev20210803212520-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 747.3 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.7.11

File hashes

Hashes for tfa_nightly-0.14.0.dev20210803212520-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 8f38e633a54567520f56f5fbc879334622494167b99a5ce1b021d9efcb620807
MD5 8f246720f50dab5ac07b4b207111e259
BLAKE2b-256 11066db1c50766166b840d2e140b9b93bfd817dcd333118835015c3eaed3e2ea

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.14.0.dev20210803212520-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.14.0.dev20210803212520-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 6dea95332d2bd17fa201d6ca000bc70f1273f1f85c37857e954075a125d4c29b
MD5 24650edb9ec720784de111300a95f8c6
BLAKE2b-256 2569e49a218d8ee859dffff5c070cbdb9b626c7373d85ee88a32fa360a07f903

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.14.0.dev20210803212520-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.14.0.dev20210803212520-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 18641d042135e3550aea2a3f52bddc75f80bf24e9736103d5a2aa364f41124b4
MD5 10bd382d9de726770b5ac0c8e0a02f03
BLAKE2b-256 923908eea4d983b2b927b0d63a30bc1f5ebc9d8a976cae335246714cf8324318

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.14.0.dev20210803212520-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.14.0.dev20210803212520-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 747.3 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.7.11

File hashes

Hashes for tfa_nightly-0.14.0.dev20210803212520-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 31d4d3569358d4c6c8fcce4c95066d19d92c66d1c954c42f12f8a1ec4992201e
MD5 65860da5d0b83fa823f6ac9ee97b4d89
BLAKE2b-256 e13869f03d9d6f0c2760ad5af63919ced575ee32e99005128e6a707f071cd6fb

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.14.0.dev20210803212520-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.14.0.dev20210803212520-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 e72be1f740847e2bb0a464b8465b3992dcded39ad27ce0670008e96479f5a503
MD5 b70e524cf0630e1ad5f74b53de844ef7
BLAKE2b-256 5acff974e51617c54eca80432bbddd0845d8b99d4d4980e784e6e7399b7189c1

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.14.0.dev20210803212520-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.14.0.dev20210803212520-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 7521f74d7328a8ddd1a89c24f6dd21636c8dc6f7a808d292277f14ba040b2a2e
MD5 e3261ce26df5ba1386586b6470ca9dfa
BLAKE2b-256 23b81c5ea233af7a6ad3e504bfb4e8e32a8021bb5d88b6c6ebe5d622404e6ca2

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.14.0.dev20210803212520-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.14.0.dev20210803212520-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 747.3 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.7.11

File hashes

Hashes for tfa_nightly-0.14.0.dev20210803212520-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 53bbd64c13f6b13ee70d53c5a06ee2359570d996af879a737a35934fb8048043
MD5 74b40808b74da5a705d2d6add42ebad5
BLAKE2b-256 235c6d5cb7838e3cfdd48ab327e81f71664751d630d2bfd4bf07bc3b8e681c0c

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.14.0.dev20210803212520-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.14.0.dev20210803212520-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 67f3bad7d1b1382105c047abc26c1d97a37c4a6dbe1760bfed5077633d66edd4
MD5 afdf9815cf8d7681ef73770b47157ee3
BLAKE2b-256 4101021bbae1e8db81f2c3b4ba216345fb81113f21feb789c76f9b3c38f9c0fb

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.14.0.dev20210803212520-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.14.0.dev20210803212520-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 5ed07cd4af4b0ed4afb8369c0ee36953cd45c5fc45cc014e02e13b5ed1a37766
MD5 75331d9b787a96fe9017012a3a9e9318
BLAKE2b-256 d676d8a3baec67d18800672633c166df23bbda154ca78a328580275bd16ef75f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page