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-0.10.0.dev20200514002023-cp38-cp38-win_amd64.whl (893.3 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.10.0.dev20200514002023-cp38-cp38-manylinux2010_x86_64.whl (1.0 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64

tfa_nightly-0.10.0.dev20200514002023-cp38-cp38-macosx_10_13_x86_64.whl (588.1 kB view details)

Uploaded CPython 3.8macOS 10.13+ x86-64

tfa_nightly-0.10.0.dev20200514002023-cp37-cp37m-win_amd64.whl (893.3 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.10.0.dev20200514002023-cp37-cp37m-manylinux2010_x86_64.whl (1.0 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.10.0.dev20200514002023-cp37-cp37m-macosx_10_13_x86_64.whl (588.1 kB view details)

Uploaded CPython 3.7mmacOS 10.13+ x86-64

tfa_nightly-0.10.0.dev20200514002023-cp36-cp36m-win_amd64.whl (893.3 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.10.0.dev20200514002023-cp36-cp36m-manylinux2010_x86_64.whl (1.0 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.10.0.dev20200514002023-cp36-cp36m-macosx_10_13_x86_64.whl (588.1 kB view details)

Uploaded CPython 3.6mmacOS 10.13+ x86-64

tfa_nightly-0.10.0.dev20200514002023-cp35-cp35m-win_amd64.whl (893.3 kB view details)

Uploaded CPython 3.5mWindows x86-64

tfa_nightly-0.10.0.dev20200514002023-cp35-cp35m-manylinux2010_x86_64.whl (1.0 MB view details)

Uploaded CPython 3.5mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.10.0.dev20200514002023-cp35-cp35m-macosx_10_13_x86_64.whl (588.1 kB view details)

Uploaded CPython 3.5mmacOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.10.0.dev20200514002023-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.10.0.dev20200514002023-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 893.3 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002023-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 405556933c0e380dcc77b80def1b67baccc0729500cb23687f8e202fe8fd7aab
MD5 3eac3ccdf7306e7405c34311edc3d9b9
BLAKE2b-256 aca679baa7ddab2f4f6058b3adb7713b3db37a6b6b4310068d42cda0d3bcbdd5

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002023-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002023-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 28c646c2f6b8ecc27d61cad612341908275a4e3b7d4b8e8dd54bc86a6a666d5b
MD5 24f117718a5788c6119f2d3518ae9c6c
BLAKE2b-256 77caa1936fc6318c8ec7ca4a875c598a31c9e98f89c7531fb92c70edc74d5d5b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002023-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002023-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 81d970a879533289925dfd48d30fe6f2e0ca846ed811c6e1cddf08e35d267c20
MD5 3a58d826b00c7830cd1160c90220000f
BLAKE2b-256 ecbb779d170bb8841eb144a4f811759454006be07ca935c9f459936606a26cb0

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002023-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.10.0.dev20200514002023-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 893.3 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002023-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 e3f45ea550717f0500a5cbedce408ee2ff56365b45ab412131f732dc93acfac0
MD5 4f025e166738d6bafd116879a091a3a2
BLAKE2b-256 f6b9718bc25cd20c0418a1f8c1bc6347eb84d085f7e65fe6918de9971c8154ca

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002023-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002023-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 541754064b93050aefc23f1e65e787013c138f1b8ea7e4c306064490a573dd3f
MD5 48ca1670404948930adddfea91a0292c
BLAKE2b-256 94ff42004525b6088ba5953ad8f7967a18bea486c40c408265d692ee46d49b3e

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002023-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002023-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 fe6b5ceb5b58d13520fcc47756777847c09e8d20976e92bf67a72b4f05ddbfda
MD5 ac23d185cc1daf59c6240127b252b761
BLAKE2b-256 dc259bdd09b701f7e620f90e12ac9affadb3b65b4482057fe1713ecfe5007894

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002023-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.10.0.dev20200514002023-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 893.3 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002023-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 dff100bf81fb3dc4d9a0af50ed005d6ea44fd6676aa10e62c507519730825844
MD5 0cbad5e6018eee751de95852f2570eb7
BLAKE2b-256 7d3bdf9f6c2bca9d61c7d67273adfbe93dd6a56871429031d6556a6c13bf8f4a

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002023-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002023-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 5490eea19889cfc8ac6f0e2b5ff1b2b91865805b722418cc22a3138a7f1bd4b1
MD5 540361f2968668be6335ec462451e583
BLAKE2b-256 1de5c4660c16e70d06ea3756b6ae1984f77bb9215e53c2af764ad89d65222a8e

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002023-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002023-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 11a010e1f2b6098549ef92d4fb86a61d97f9af07af0f32a69965154996d71cc2
MD5 447ebc82087216e584f8428ba81a3ff7
BLAKE2b-256 27d50fa83a0205f538ab9ac24629720666e0241e26aae9007ece2d4929de2c4e

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002023-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.10.0.dev20200514002023-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 893.3 kB
  • Tags: CPython 3.5m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002023-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 809297af6462a7b65b3fe8997136f2a1a502952721dcf74583a09af609589d77
MD5 3d230c1fd106b9f7ebbc2e65c23d7551
BLAKE2b-256 d3ffc00461668e5c5e9916aa528d1cd22d945161e0c19cb1bf615b2347d03842

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002023-cp35-cp35m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002023-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 cc7a842655267db6a44481e194b59c444fda4391c2c32fa034ca2b4659bda593
MD5 e67f8d1b33df747b7034a7a31a3c75ad
BLAKE2b-256 a478f03da1dc98c6871b90bd77397937cf4c4e355f2758c2e94bb9feabb0ec5c

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002023-cp35-cp35m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002023-cp35-cp35m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 5adc8c2fbafd65083c9b0adb3bcaa64d40c82fae0e40f8741831bc132684b15e
MD5 7350ede3c6b6d3e681983fe195f0540c
BLAKE2b-256 460896ae96a41ee26003971734188df0c0f569ccbbb34732c0c719a229059cab

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