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-0.17.0.dev20220215214707-cp310-cp310-win_amd64.whl (759.0 kB view details)

Uploaded CPython 3.10Windows x86-64

tfa_nightly-0.17.0.dev20220215214707-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.12+ x86-64

tfa_nightly-0.17.0.dev20220215214707-cp310-cp310-macosx_10_15_x86_64.whl (591.5 kB view details)

Uploaded CPython 3.10macOS 10.15+ x86-64

tfa_nightly-0.17.0.dev20220215214707-cp39-cp39-win_amd64.whl (759.0 kB view details)

Uploaded CPython 3.9Windows x86-64

tfa_nightly-0.17.0.dev20220215214707-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.12+ x86-64

tfa_nightly-0.17.0.dev20220215214707-cp39-cp39-macosx_11_0_arm64.whl (548.4 kB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

tfa_nightly-0.17.0.dev20220215214707-cp39-cp39-macosx_10_15_x86_64.whl (591.5 kB view details)

Uploaded CPython 3.9macOS 10.15+ x86-64

tfa_nightly-0.17.0.dev20220215214707-cp38-cp38-win_amd64.whl (759.0 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.17.0.dev20220215214707-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64

tfa_nightly-0.17.0.dev20220215214707-cp38-cp38-macosx_11_0_arm64.whl (548.3 kB view details)

Uploaded CPython 3.8macOS 11.0+ ARM64

tfa_nightly-0.17.0.dev20220215214707-cp38-cp38-macosx_10_15_x86_64.whl (591.4 kB view details)

Uploaded CPython 3.8macOS 10.15+ x86-64

tfa_nightly-0.17.0.dev20220215214707-cp37-cp37m-win_amd64.whl (759.0 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.17.0.dev20220215214707-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.17.0.dev20220215214707-cp37-cp37m-macosx_10_15_x86_64.whl (591.4 kB view details)

Uploaded CPython 3.7mmacOS 10.15+ x86-64

File details

Details for the file tfa_nightly-0.17.0.dev20220215214707-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.17.0.dev20220215214707-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 759.0 kB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.17.0.dev20220215214707-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 c7fc2aeac4ea429e35a7ee7e31de9a555bd15fb046c8547695953814f290394e
MD5 23381411b54f04965eb4dee5ccfa57c6
BLAKE2b-256 518bc5c237db612bc9df2f13f60882858627d5163888dfdc6d741e679a64be2c

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220215214707-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220215214707-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 36b4647a4c6734caf5935528f78f7872e017a9e15ec07fe5f93870a7b549f70f
MD5 a4ad624a581d60518b58623421e5e7ed
BLAKE2b-256 0be0e557dc54f8a0934021b92ef894f8d5dd5c273af9d8c2b1b635dffb6629a6

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220215214707-cp310-cp310-macosx_10_15_x86_64.whl.

File metadata

  • Download URL: tfa_nightly-0.17.0.dev20220215214707-cp310-cp310-macosx_10_15_x86_64.whl
  • Upload date:
  • Size: 591.5 kB
  • Tags: CPython 3.10, macOS 10.15+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.17.0.dev20220215214707-cp310-cp310-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 7d1fcb589c16057fa6b407e902ddfc5ab8b460006ed30ccf11ffc61f0c36a481
MD5 bfd0d2a490cd6a62a94b7cb9e10f4993
BLAKE2b-256 a1f574a029efc8a170f5cb04d83b27947915bab6704005b098d86d7935327bbf

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220215214707-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.17.0.dev20220215214707-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 759.0 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.17.0.dev20220215214707-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 7d80509f6b22a5c5dfce4113f0a3d95d979603c619519048b9ca55d763decae5
MD5 2f93751b42810331fccd8c0297311e6c
BLAKE2b-256 f0d40d1e7b9576481e7295396081c92459ee03ce2672fd14e2cd01d4e9094562

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220215214707-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220215214707-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 bd6a4f96b8429937b19cbe983780d0d0e5db66719bae531eb0562cc60fd6fa37
MD5 acea9216c3df1d70c0661c7470501ffd
BLAKE2b-256 cad504547c7f0ea1ebd9e2fd5771f024b63498bd16baa8ad419adfbb8512fa4a

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220215214707-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

  • Download URL: tfa_nightly-0.17.0.dev20220215214707-cp39-cp39-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 548.4 kB
  • Tags: CPython 3.9, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.17.0.dev20220215214707-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7659269b70913c07f1322b9b412a6852258d63dd2601a93a01aa554ad57cedb5
MD5 6b1ae3f8fc132640cf307a58a18c390b
BLAKE2b-256 bf99feef7416a00662f4a2109dc333a1839e70a79e542cc7e5e12fc1d18aade8

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220215214707-cp39-cp39-macosx_10_15_x86_64.whl.

File metadata

  • Download URL: tfa_nightly-0.17.0.dev20220215214707-cp39-cp39-macosx_10_15_x86_64.whl
  • Upload date:
  • Size: 591.5 kB
  • Tags: CPython 3.9, macOS 10.15+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.17.0.dev20220215214707-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 0bd17703ce892a86e6bbf0c6ce0aaea5d1a73211220658f55994c4dbeaff1541
MD5 8b0ac5cacd79ad8f741263ee42f70ef1
BLAKE2b-256 df8a487fbfd359b1e201d907b588f201ee63a9b0d18a4a473b4c2aaa3722bff6

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220215214707-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.17.0.dev20220215214707-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 759.0 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.17.0.dev20220215214707-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 2cb65845ef2b2335e0692e76e95c77817cf1a8c984e5fb4f9a87cbbab11f6631
MD5 1ed3b2bed680be377ece728a1560f10e
BLAKE2b-256 379f2e8aef5c487f606c61ac68342bf0574da1915fd704f5648c0387e156823d

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220215214707-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220215214707-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 d4de2a46c15d5cb0bbc9096fe5f781b161f3c77c3aa79ba09c796e7c1c018e77
MD5 64b73bf168ca85c751fc01761e9e8b11
BLAKE2b-256 2fa564995f479a2b4922f3f93716eee35ed7e4c01dec25633337091efc6cb4c1

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220215214707-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

  • Download URL: tfa_nightly-0.17.0.dev20220215214707-cp38-cp38-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 548.3 kB
  • Tags: CPython 3.8, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.17.0.dev20220215214707-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 6e7714758b2862a22a8749719886c44b50e8b4b9ba8d71cf94278a09c70feda2
MD5 aa58cf55ec01aa2f5e34da9eb49ad380
BLAKE2b-256 2ac8a544944e1cdc29f5693f6d989db7fcd4aa353079afeef743c03cdceefdbb

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220215214707-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

  • Download URL: tfa_nightly-0.17.0.dev20220215214707-cp38-cp38-macosx_10_15_x86_64.whl
  • Upload date:
  • Size: 591.4 kB
  • Tags: CPython 3.8, macOS 10.15+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.17.0.dev20220215214707-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 f8163560426e1336f414052a4ea71a2d8ade8b7179ebc74bd5759ef95c5c014b
MD5 57644b954fa38c536bda4f10b1db9caa
BLAKE2b-256 775f2e41512bafc59596c27fd1449bafffe58476778c3bd508fd7a7b78004278

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220215214707-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.17.0.dev20220215214707-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 759.0 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.17.0.dev20220215214707-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 9127f86a9e2f9d2d1f571a9d534388d2bab045ee26b1b41e36b7499b837fbf2c
MD5 39a470a6e1e4295c848cbdc24e41f564
BLAKE2b-256 4513889eebeaddea5a7be133d3276a7abe3d0a0ef040b50336ec1cc70e583927

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220215214707-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.17.0.dev20220215214707-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 4fb217d57f034ae8104547eb2c2cfee4e63d16e8d83c9b1ed5e7cf0ed93e3446
MD5 ae45e0a451f09acbf10b6962c8f2a64a
BLAKE2b-256 8df34cf68db3c5e951de407c399feee602c1efdc665e562f563db4fb671d27de

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.17.0.dev20220215214707-cp37-cp37m-macosx_10_15_x86_64.whl.

File metadata

  • Download URL: tfa_nightly-0.17.0.dev20220215214707-cp37-cp37m-macosx_10_15_x86_64.whl
  • Upload date:
  • Size: 591.4 kB
  • Tags: CPython 3.7m, macOS 10.15+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.17.0.dev20220215214707-cp37-cp37m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 b6fa8012e54622f0273d6d867dfb2e58f569b695d298d37b51aeef320fe197ab
MD5 70dc3cf95bb3561e929d160459c07974
BLAKE2b-256 13c8c02a3f5a995a2e38fe89aa9c56175daba760ff4645792bf7e772a6cd4f04

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