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-0.11.0.dev20200525175543-cp38-cp38-win_amd64.whl (895.0 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.11.0.dev20200525175543-cp38-cp38-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200525175543-cp38-cp38-macosx_10_13_x86_64.whl (589.8 kB view details)

Uploaded CPython 3.8macOS 10.13+ x86-64

tfa_nightly-0.11.0.dev20200525175543-cp37-cp37m-win_amd64.whl (895.0 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.11.0.dev20200525175543-cp37-cp37m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200525175543-cp37-cp37m-macosx_10_13_x86_64.whl (589.8 kB view details)

Uploaded CPython 3.7mmacOS 10.13+ x86-64

tfa_nightly-0.11.0.dev20200525175543-cp36-cp36m-win_amd64.whl (895.0 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.11.0.dev20200525175543-cp36-cp36m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200525175543-cp36-cp36m-macosx_10_13_x86_64.whl (589.8 kB view details)

Uploaded CPython 3.6mmacOS 10.13+ x86-64

tfa_nightly-0.11.0.dev20200525175543-cp35-cp35m-win_amd64.whl (895.0 kB view details)

Uploaded CPython 3.5mWindows x86-64

tfa_nightly-0.11.0.dev20200525175543-cp35-cp35m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.5mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200525175543-cp35-cp35m-macosx_10_13_x86_64.whl (589.8 kB view details)

Uploaded CPython 3.5mmacOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.11.0.dev20200525175543-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200525175543-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 895.0 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/46.4.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200525175543-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 f3d6be2c555be0aa254d8e92d317410f4bc13eaf88449170533ff14cc5fb9015
MD5 44eb39466e4f75b283ce3ce4474ebc9a
BLAKE2b-256 5f62776c17bcdd93ed580e7ffdd4c50946d10dac58ce2eaf814a87052886a899

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200525175543-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200525175543-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 cf560ffadbb1bf4c02e3f70f3f93222b702bec6241402e7143c31564f01d5298
MD5 b48636edd64f7629351121c16043b14c
BLAKE2b-256 209e60a504006b5bfa4607843ab2925c86caa4180dfe9f3e148dc761cb90c6c2

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200525175543-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200525175543-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 6c257e6d9ee32940953c286753ad9f5bd9852365abc391c9067e4e28f2f62f74
MD5 e7352f951ee3af836e9a5bf22696c2bd
BLAKE2b-256 201f353b35cf8e2b2eef63d067207560b3251c691fd80f728cd7d75cf639612a

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200525175543-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200525175543-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 895.0 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/46.4.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200525175543-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 05443424c80b136bef6416b89e0b3cfc27ad5451cc19374f4e8714c5a8440de9
MD5 8fe5adb59d8153bd3984a7755c8f127f
BLAKE2b-256 c4a908b1412ded8f8629293b8622977e21642fc67cc04bc7e31f5d774e105c38

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200525175543-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200525175543-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 e1a3060bbf669fedcb3bc9fc981cea892581b37aad5e9622d5a264cf68553f56
MD5 0a4039849ab6115e1a60015da5f44a55
BLAKE2b-256 882a3ba0092be5223b311a1ef49a1331fb71058e8c9c8c5091cf7185d8a8aade

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200525175543-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200525175543-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 cb4cc5949ec76475c717362b172db5e7e9912747601ffc2dd0dfe850dfc6097b
MD5 d29704249cf3ff5a07278b8b942ae188
BLAKE2b-256 3c723e5de5000a136bab0e341ee86c37572184a2912adc18efd21a644bb5b211

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200525175543-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200525175543-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 895.0 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/46.4.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200525175543-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 d3ffd6d23c03dce0093343c16f7e4b1d5561f32461b33083129c68ca275c46cb
MD5 be4bf8b4d72a4e5f0cfa18a309f1327f
BLAKE2b-256 b2b40eb6364a3068c1460e1773f3821be146e3e217cf65afdf807c168bc1c2b2

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200525175543-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200525175543-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 35952c7ac529eaf562f0fd2fb9672ca8c6423078a4d30e97d742ca8174234d12
MD5 0edcdb19412e6dd61b29baf5e021febe
BLAKE2b-256 a5a1b45caa2fcb8572603df5df0b6841afbb9653ac854e4dfb157672ad561cfd

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200525175543-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200525175543-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 e9c4e3164d96200850601681cb3996aa003b00f0c53b3bd631e2d30c1f0a09c6
MD5 199bb2ea23d7cf997306996ca104426b
BLAKE2b-256 bd54f174adad217232283adbb42f85eda3bf379fe083722b1a43ef2ed31b36f2

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200525175543-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200525175543-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 895.0 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/46.4.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200525175543-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 89c64c7a19cf1c6f9e41192fcfadad82f487e6d7c36e503f6a36a922d1425bfe
MD5 a55e9126af188733ca5bb897d2948ea7
BLAKE2b-256 9039a8db3ed83e5ec3d2a7e4cbcf90f218b2c72c0ff1c61813259b486a8bd574

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200525175543-cp35-cp35m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200525175543-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 2e8cf0585a489369f6e5a64bc9fcd93d782628f268e907df7fd839b54b68b7a0
MD5 2d729ef44c1338a3caea4a0504708c24
BLAKE2b-256 989461e3585323a52e4492d17e177a0e593f12c2a50876e6f967767a130e6549

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200525175543-cp35-cp35m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200525175543-cp35-cp35m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 b7951b70bd60ec5b1c131b90557ae8a6a2d862a679e2d3c75ef1f465f1aada7f
MD5 b6c0ed3632eb059855e6708e43220b93
BLAKE2b-256 7e09697ec8f15a5691c54d56ef98f73ea614093a3cd7fa1a7cfca9d23a030029

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