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-0.15.0.dev20210819135717-cp39-cp39-win_amd64.whl (748.7 kB view details)

Uploaded CPython 3.9Windows x86-64

tfa_nightly-0.15.0.dev20210819135717-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-0.15.0.dev20210819135717-cp39-cp39-macosx_10_13_x86_64.whl (578.8 kB view details)

Uploaded CPython 3.9macOS 10.13+ x86-64

tfa_nightly-0.15.0.dev20210819135717-cp38-cp38-win_amd64.whl (748.7 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.15.0.dev20210819135717-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-0.15.0.dev20210819135717-cp38-cp38-macosx_10_13_x86_64.whl (578.8 kB view details)

Uploaded CPython 3.8macOS 10.13+ x86-64

tfa_nightly-0.15.0.dev20210819135717-cp37-cp37m-win_amd64.whl (748.7 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.15.0.dev20210819135717-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-0.15.0.dev20210819135717-cp37-cp37m-macosx_10_13_x86_64.whl (578.8 kB view details)

Uploaded CPython 3.7mmacOS 10.13+ x86-64

tfa_nightly-0.15.0.dev20210819135717-cp36-cp36m-win_amd64.whl (748.7 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.15.0.dev20210819135717-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.15.0.dev20210819135717-cp36-cp36m-macosx_10_13_x86_64.whl (578.8 kB view details)

Uploaded CPython 3.6mmacOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.15.0.dev20210819135717-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.15.0.dev20210819135717-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 748.7 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.1 CPython/3.7.11

File hashes

Hashes for tfa_nightly-0.15.0.dev20210819135717-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 c4107cdafdac6f158be9beb3a261018c29f7f8ff766bbe1155d2dcd9569b4f2f
MD5 4221db361140c1768aefb4be37947544
BLAKE2b-256 882cfd8f2a635fb04748506db99fdec56306db082d73e5a214fdcb12aa18fd96

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210819135717-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210819135717-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 3e3af4c5cb0ce5f137e1fc98cb8bf54df681a5d881ca8bf6154400ae8c4ec4d6
MD5 207a5cbf3c1485fb6a472dea165a146b
BLAKE2b-256 aff11820280c1d8564da0182fab103541199c99d16d0bdd67785f11fb1518aeb

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210819135717-cp39-cp39-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210819135717-cp39-cp39-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 b5b6ae3850804a7eac0fb3b03797df04a2d1036f95dec5817aa25973b2a051f6
MD5 4e00f5c82dd73136c1ad5c89d8f532de
BLAKE2b-256 0bf8fb07f0ad3c47c58460d64274fe54323e2dfb662ad5d2a90cff8898cf2a2b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210819135717-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.15.0.dev20210819135717-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 748.7 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.1 CPython/3.7.11

File hashes

Hashes for tfa_nightly-0.15.0.dev20210819135717-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 c87e053d197e71fdac26126149b312bd716dfd9bc27fddeb0d9863fdd2668de3
MD5 44549e6737001944cee53db37b0f0a36
BLAKE2b-256 ef2779c401ec177188d144ba36d6ce4bdc316c00fa2b708e3102fa0351633b52

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210819135717-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210819135717-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 9975f6b0dc26eb667d0f36fe033b8ee444a5d71dddcb425e9551cfcab176ee4f
MD5 25becb576828cadbb7e44b888ab5d0a6
BLAKE2b-256 892c09de84afaa9205c57144fd10bd8c9e13bb0fc06a05912e30925d6bbeaa62

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210819135717-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210819135717-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 3be3f238ce52a74acd8080fbf06b21cfac3f69a347e19683fe4d13a911fa64ba
MD5 7227f304f616337faf4e4d0fb5606c29
BLAKE2b-256 405709136dff7f4505220d934701e1d9ad23d51b625adafe9cfd9a4e9ba1f9d9

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210819135717-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.15.0.dev20210819135717-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 748.7 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.1 CPython/3.7.11

File hashes

Hashes for tfa_nightly-0.15.0.dev20210819135717-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 ff4d577e081b6555991b69fbddb952912a74b6132096068960c7e1d3b0df5b9d
MD5 5b55ee2034f6f1ab6fa767a0d28ac9e5
BLAKE2b-256 080ec867b78e1ab8901b6fa6122ec84f07f9c975fff84cf8fe02c049bc1bde2d

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210819135717-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210819135717-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 dd2563e35f98bcd6f67f3d8ceb9850b357ec8a8c369c8cf33dad415cbd0b6b8d
MD5 58927210bf0e04b908e7db498a51bf02
BLAKE2b-256 334d38bc8897d3908fa22afdc7aefefcb76a4b3b36ebb5da5accee430049f704

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210819135717-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210819135717-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 59ae50214614e8251dba501caf8be31402754d521c62d6db8c767eb3c9cd1ba1
MD5 2f2018d0252567b49173fb2d2ed577c8
BLAKE2b-256 0f959e9a238a1e507f4d4f79839e77133ede0237a3f4be0e521f8114e4200b70

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210819135717-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.15.0.dev20210819135717-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 748.7 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.1 CPython/3.7.11

File hashes

Hashes for tfa_nightly-0.15.0.dev20210819135717-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 55afd78a99c87827ef99e667b054a8bffce9ac4a59ec1b26af59968fd5314307
MD5 6a769e0b870f98686a36b6d0fa32c9a8
BLAKE2b-256 45ea27e5eb17b25f1b16b37eb2064583e05cee421725afd60a8abde6f1f83f74

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210819135717-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210819135717-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 c59f3d2433ca0047ceedbb1a84f55c124d16fd91fc2c76517a6d5732b8afb3c5
MD5 0abf91fc4779e5988f3ebc80c2cf54a6
BLAKE2b-256 6ee3920155bf4743d5e3620a46538a141bed67dcba13173d225dd28bf9d208bd

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.15.0.dev20210819135717-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.15.0.dev20210819135717-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 a6878c1791597ce60853924f33fa5de5084773c7daad4332b85a4eac5f43d4cb
MD5 0e9f0fb0bb01d33b0163f283a7c4592b
BLAKE2b-256 dd9d73d7971531371ba7591f49e310fbed1db3c402151b4b60592b94d7ddaa10

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