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-0.15.0.dev20210918121830-cp39-cp39-win_amd64.whl (753.3 kB view details)

Uploaded CPython 3.9 Windows x86-64

tfa_nightly-0.15.0.dev20210918121830-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-0.15.0.dev20210918121830-cp39-cp39-macosx_11_0_arm64.whl (551.5 kB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

tfa_nightly-0.15.0.dev20210918121830-cp39-cp39-macosx_10_13_x86_64.whl (583.0 kB view details)

Uploaded CPython 3.9 macOS 10.13+ x86-64

tfa_nightly-0.15.0.dev20210918121830-cp38-cp38-win_amd64.whl (753.3 kB view details)

Uploaded CPython 3.8 Windows x86-64

tfa_nightly-0.15.0.dev20210918121830-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-0.15.0.dev20210918121830-cp38-cp38-macosx_11_0_arm64.whl (551.5 kB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

tfa_nightly-0.15.0.dev20210918121830-cp38-cp38-macosx_10_13_x86_64.whl (583.0 kB view details)

Uploaded CPython 3.8 macOS 10.13+ x86-64

tfa_nightly-0.15.0.dev20210918121830-cp37-cp37m-win_amd64.whl (753.3 kB view details)

Uploaded CPython 3.7m Windows x86-64

tfa_nightly-0.15.0.dev20210918121830-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-0.15.0.dev20210918121830-cp37-cp37m-macosx_10_13_x86_64.whl (583.0 kB view details)

Uploaded CPython 3.7m macOS 10.13+ x86-64

tfa_nightly-0.15.0.dev20210918121830-cp36-cp36m-win_amd64.whl (753.3 kB view details)

Uploaded CPython 3.6m Windows x86-64

tfa_nightly-0.15.0.dev20210918121830-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-0.15.0.dev20210918121830-cp36-cp36m-macosx_10_13_x86_64.whl (583.0 kB view details)

Uploaded CPython 3.6m macOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.15.0.dev20210918121830-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.15.0.dev20210918121830-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 753.3 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.15.0.dev20210918121830-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 dffab87789ff7734bc197c9484cec54bee89424f5f98f105a2d29882f046046d
MD5 3dc505d6153d214a433eda48ff672fff
BLAKE2b-256 d54998f0dead0bfd45a711e36864be0f190c2b36720cc7d0c90763ed122c418b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210918121830-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210918121830-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 88104d058e3e49e78a168de9e126e6e0e41acae93d17243c24ccb0ed2f3932bf
MD5 053737079d79e9d1f07f353daec96301
BLAKE2b-256 a58a8874af23f5b96eb9109ff3e5174e32bb3d4dc7e4829aee9bd478a227c30f

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210918121830-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210918121830-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 ecd17dfe7be5fad22313c0b022e858de6c0edd6e86f4208d26a0da16d6fb6796
MD5 adf981753dd712efd38454a1cccae503
BLAKE2b-256 59ba1a817f9092de1f3c12163c41894a45039455daebbbcd9bf11abc89c561b7

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210918121830-cp39-cp39-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210918121830-cp39-cp39-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 3c3fff5e9d853a1b172f0d6cfe708671e808c3b680fed38c537e22c31e4a8a89
MD5 f6efadf47fad628e4c2338279a882a43
BLAKE2b-256 6a2b9532c7f3152235e674150fdc78bfd09efd32d75e27e0e59722daa18521c7

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210918121830-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.15.0.dev20210918121830-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 753.3 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.15.0.dev20210918121830-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 976d76f5d2660cdf46295c3dbf4b63438c21840e918da7d448455339490afe0b
MD5 ee860b15de4ac56b4812bf51d5ae9ade
BLAKE2b-256 130468dee25a000d6d4ea84104914e371664f50c4170d198491a3f5d2eaa8689

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210918121830-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210918121830-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 3127a6dda88c9a334f8994dab0351f2e8947ffc8af357c38a5d49ae1c897eacc
MD5 7969c07530949ae3ba83fe17351e92fd
BLAKE2b-256 009110d077e7c160c26e31d917c9b17ca4349b27f2050e9da1e2243a77f2541f

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210918121830-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210918121830-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 409ae552d4a6bc26a84ba4bb9e92bf287087528092a029cac64dc854020bea2e
MD5 d0cd030405c062c7e5d57a5994598b5f
BLAKE2b-256 a6d1568d2380e07d566eaf53075a94013d16cd3750c145cba098a5af2fbb1d12

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210918121830-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210918121830-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 f5c8b89350cef528fa555b2d7784e22108a8479ce3033582875ceea5b7589329
MD5 017aa96cacdef8fd152cc7e45a343f72
BLAKE2b-256 e92fbd897693e3e23139f938bf9c835dae4d9989f2faa17cd0912e7a92f772c2

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210918121830-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.15.0.dev20210918121830-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 753.3 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.15.0.dev20210918121830-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 3cd89a0b5ddec9696fa5bd5b13ffc1c660ca06066924aed0bd39e117f4d6ddcf
MD5 46f309f93891dae868046c585769399c
BLAKE2b-256 ef4e417241267cbfd13de1d1f481bb546fcc73ea664562ff62a90f4a5bd92e2d

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210918121830-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210918121830-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 ffdac450b2b634eb973feb95fc0e76f1edc656e9f5372d2d8dae457d347ce8ab
MD5 bef9b5e3d6ddb456b4ea653f29a73a11
BLAKE2b-256 b4954ced52107e1b5a5d83466e76ae3ffd6f0eef2abcee49206b920af139179b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210918121830-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210918121830-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 5c863a5583bd8143778c6f47db8b24fe1db26367d87924661d8d7305039c51df
MD5 e9e022bf353f1f1be85753e5b03c044e
BLAKE2b-256 a645cd985c75027972d09ea16f5588a0e59a747753c5a63c0fb5d17bc836152b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210918121830-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.15.0.dev20210918121830-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 753.3 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.15.0.dev20210918121830-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 d750a25f6b9ae62f2280f7dda65fd69d94c248689d944baf30ee2b8ffd49dbfb
MD5 802a9e8512e7a588b4b15147f82aa8a1
BLAKE2b-256 0028b6340632dd93f978085b0c85413e9837883ed1761962c7bec914fd022c3a

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210918121830-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210918121830-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 823704ed9daf6b8c072eee1672e755b26d1142528ffdb9e934b4c95334b322e7
MD5 a0020e11da1b0de36a47711eb2873dd7
BLAKE2b-256 99f3970eef11723d017a1f7a3ddc6296f4127e7dd1b61d0048f812484b854555

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210918121830-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210918121830-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 1d97cda13b363fd4f16db2b48adcfab5ccfe59521ef2ad8a050791db189fa43f
MD5 f68e014acf73c00f6323edcb9efbced4
BLAKE2b-256 45ec3e852d33a668041d911188debb61cf9cb65f7e284cc9568ab2c7c827efaa

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