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.dev20200902121308-cp38-cp38-win_amd64.whl (916.8 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.12.0.dev20200902121308-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.dev20200902121308-cp38-cp38-macosx_10_13_x86_64.whl (619.5 kB view details)

Uploaded CPython 3.8macOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20200902121308-cp37-cp37m-win_amd64.whl (916.8 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.12.0.dev20200902121308-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.dev20200902121308-cp37-cp37m-macosx_10_13_x86_64.whl (619.5 kB view details)

Uploaded CPython 3.7mmacOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20200902121308-cp36-cp36m-win_amd64.whl (916.8 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.12.0.dev20200902121308-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.dev20200902121308-cp36-cp36m-macosx_10_13_x86_64.whl (619.5 kB view details)

Uploaded CPython 3.6mmacOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20200902121308-cp35-cp35m-win_amd64.whl (916.8 kB view details)

Uploaded CPython 3.5mWindows x86-64

tfa_nightly-0.12.0.dev20200902121308-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.dev20200902121308-cp35-cp35m-macosx_10_13_x86_64.whl (619.5 kB view details)

Uploaded CPython 3.5mmacOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.12.0.dev20200902121308-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200902121308-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 916.8 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/49.6.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200902121308-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 79294167798641f4881331338f64741210e7caf6ccf3ca1f27ae8198a4ac7152
MD5 7fc96d029a25ceaf7861ded7c380b4a3
BLAKE2b-256 66ebd063bd9e91e1a20511d6a5cb8c981ffcde8d8b40f213c04ccc90bce2c561

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200902121308-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200902121308-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 fa0d98ef078059680ebddacd737f6b5eb05117b541642a6a0a6a81ad376c62f4
MD5 ee4a715c6800356b123162791ecf7803
BLAKE2b-256 601f54595a77990745811cd5b6783415318b124183d16a3cfad47af3b1015597

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200902121308-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200902121308-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 e49eed36abc8acd305e890497551609137987e71ed646908748d940697b70e41
MD5 952884c906cbf4af3fbf8176ec0075c5
BLAKE2b-256 c0c3832587eec99c6c86f0b950854bb823824bf42966c7651a3a2e1a35d3f46a

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200902121308-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200902121308-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 916.8 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/49.6.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200902121308-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 83e79721716dfbb650ab3086f0b3187352fbb2895b75aa376bbd5d62f133e838
MD5 e861c7d62cf938ad7bc26c37ce5a7d8e
BLAKE2b-256 6adf119ea3f6d2a3080c4dfba00f063db410997a89ec228f67f91c74a3f2a14e

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200902121308-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200902121308-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 41b9f8618ec7939be9d7543ab7fcab138b7faf63e604dfbae3bdb4eaa2f2cc43
MD5 9390b0ea6adb706d92d7819d7dd9e1a7
BLAKE2b-256 979aa1cffc99b505e31ba0de9fd83771d36890a3c2378682a999af7a2c025154

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200902121308-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200902121308-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 18737d931dcf3ac5acfc1b4fcc7252179c2e88dff5ec0f738e748d06d82fb1a6
MD5 0418cb00a506c4f9adfa243a9987c2b0
BLAKE2b-256 8ce42080b23ae7e788b6cbcfd993a68c01e54ffa3feddff6db31c192c03bebde

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200902121308-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200902121308-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 916.8 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/49.6.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200902121308-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 d6dda5b456d5e53a7b43c0283a4bdff828608deff56a250ff295becf3d4aef2f
MD5 299a4db9fcf7515288fcbc41ad348c57
BLAKE2b-256 c352d82a59c0060d8ef62bbd785cc1007d8b643e7bc46ba01119fc49f5bf798b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200902121308-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200902121308-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 a5dfb053c0fbba4523439058080dd421869b40ed7334a3384ecef87e22cbeb89
MD5 7dee3c7973d80f792a8e849638864baf
BLAKE2b-256 c3dfea1f2f41ab7b37b216b21184d5b044fb426a2e88b9ed05a01b4cec721a77

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200902121308-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200902121308-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 2c13d2dca1f76ee608ac594b555592992cacdbc486c0bdffc862da1861be44de
MD5 146454fa1060779081d7302d8df38acf
BLAKE2b-256 c431554844bba4c16b886396b4d8807fda2ed550a2c20bb5105e5d12976997ac

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200902121308-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200902121308-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 916.8 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/49.6.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200902121308-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 ab12ce529245a5ddba5de6cef5b1718dda58f0dfdf2ba55876277b74d86a0432
MD5 85e9e2bdd9bf7cb30f6ccb3cba2bf4a6
BLAKE2b-256 54835835cabdfbb916774574849aa22731934d137e64cf7fa22fcea048fe0125

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200902121308-cp35-cp35m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200902121308-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 559c8a20cda46678b3ee91bc97021ab6881a01cd4181b628664895b60e6a7c0d
MD5 3afc5776ac33b2bd0af4958f2537d412
BLAKE2b-256 106d4b8de602d4e4ce499b2d9a4a79a187953272dc4297670d4001573bdcf97b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200902121308-cp35-cp35m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200902121308-cp35-cp35m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 50567456e6a652683bc7413f71f1eb96280c2741a44fc56d2e968194ecbf9df1
MD5 321c80bf27db304d8866fb3dedb0d162
BLAKE2b-256 c44e053d5439b1652733a9198aeb5a81b658761d40be198a14742c97ab93e295

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