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.dev20200514002713-cp38-cp38-win_amd64.whl (893.2 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.10.0.dev20200514002713-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.dev20200514002713-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.dev20200514002713-cp37-cp37m-win_amd64.whl (893.2 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.10.0.dev20200514002713-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.dev20200514002713-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.dev20200514002713-cp36-cp36m-win_amd64.whl (893.2 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.10.0.dev20200514002713-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.dev20200514002713-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.dev20200514002713-cp35-cp35m-win_amd64.whl (893.2 kB view details)

Uploaded CPython 3.5mWindows x86-64

tfa_nightly-0.10.0.dev20200514002713-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.dev20200514002713-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.dev20200514002713-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.10.0.dev20200514002713-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 893.2 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.dev20200514002713-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 37546856be24f69c8a03ff5fb1ced0d45758f293861b106bade181ed3f9af0dd
MD5 eed3da6564c4b7930028b77114762d76
BLAKE2b-256 bf5041a61714a54550611535ea74123fc58f5fda430cbc2cc883b37d976edefd

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002713-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002713-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 f5af61c7e7d8841147515b2e4917f38e350a8b98648b85d07074e431d79fb6f4
MD5 ee6d5e74258af9924b5cd8653f5e44c2
BLAKE2b-256 d558c6661ea42f0f90e49584271b38000654e044f550a3690daf0e793ef0c517

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002713-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002713-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 b039f2dfab872f08750c2d60b6c107c3e77ed9d2fe46c9c316ffabb85d48f9e0
MD5 1c8f5911790620be21ea60548d02570c
BLAKE2b-256 ca76d973d164a899fb5ba2555af58f1e3507e46f861ea1c9a17dca9153999d11

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002713-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.10.0.dev20200514002713-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 893.2 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.dev20200514002713-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 1aff2ac5a73427aa2842e8aca11dc48b1784fbdb142050d30ed382b8aa783353
MD5 b5d8d4d38578e65c4ac2350d1b6c03ae
BLAKE2b-256 810c0e93dc1028f862104fb5fc3beb54e74d9f81d1a08f5a6917cb7a59e3196c

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002713-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002713-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 1d16c208c6874fb29186f6f216850cb4ea6f0c85591fa6a1ab6678298fc4a248
MD5 4674bf7e701c8100fbf019db4f102dfd
BLAKE2b-256 0a9b05ba84bc4ac010d62ce9140ead81320299ea65b6ab8336c082e73da35267

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002713-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002713-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 9995c4dd2288e143d93808fd338b297d1795328c2ea1474afd4efdca0f77efd2
MD5 014addb399cd38fa00920d10f1e265f4
BLAKE2b-256 1433f9e9220f0022ea5ac4a3754af1a18d89a7d17f82f653b26477ea502589e4

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002713-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.10.0.dev20200514002713-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 893.2 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.dev20200514002713-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 313bde78c447f9046f73980f532f1ae88becd57f8129a647c549219084e10ee4
MD5 85e77c71b13c46b460e0640e9e1e318b
BLAKE2b-256 fda12be358c00156adaed2258f25de87cdb6574179dcd3b3f852cb82f4a023aa

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002713-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002713-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 783529351a7aab1982938a965dff9d3e9847d83cf7dff089974c1ad42e274d27
MD5 1fe80e322179d6fafcae3d9c68f5e7b9
BLAKE2b-256 867f5266dae31ec76af88ef8807bc9290a6f798203d84e6e723c36cc4b43b05d

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002713-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002713-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 9c0d989aee8dc67f6338d0a8091e6f53f6615152bff38653292c8bbcb61b240d
MD5 7fa4bcab15638cef49a4786e54b43687
BLAKE2b-256 d01aeb1eec0a5a15ce3b4f46fef9f6100624e70b9d3efd4b2a78be72ff62af8f

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002713-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.10.0.dev20200514002713-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 893.2 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.dev20200514002713-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 49fbbcd409b8f6650cce26730629bdc5d8c011424b9a4c0a7397401c8ce5abe2
MD5 fe96675f51185183fdff6a7a02b2faf9
BLAKE2b-256 b273b9d88d98dc4b8400def257b245d58ee2b52e3f10a635fecc9e9cb37952de

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002713-cp35-cp35m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002713-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 222dd82ca30d8f06f5590ba9b21e3a6de60235195ec6b554c759b85e5f64d19f
MD5 e448b3f516f15e2ee18e052d9ce7c977
BLAKE2b-256 0924c9fde4d20385912a6911844e494ae4ff8e13b77d2892f30dbe9c1353fd68

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.10.0.dev20200514002713-cp35-cp35m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.10.0.dev20200514002713-cp35-cp35m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 e40ac7e50b309e639b5baeb6a045811c904624ff330bc90cdcbe7cd82e91710b
MD5 403f550971fbb0ffa1410317d422cef9
BLAKE2b-256 a030dd44f78fd831aa2a424f160bde9ae97f1fba86f927d03bf0f51dc3ab68a8

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