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-0.13.0.dev20210215215050-cp38-cp38-win_amd64.whl (610.5 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.13.0.dev20210215215050-cp38-cp38-manylinux2010_x86_64.whl (640.7 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64

tfa_nightly-0.13.0.dev20210215215050-cp38-cp38-macosx_10_13_x86_64.whl (491.8 kB view details)

Uploaded CPython 3.8macOS 10.13+ x86-64

tfa_nightly-0.13.0.dev20210215215050-cp37-cp37m-win_amd64.whl (610.5 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.13.0.dev20210215215050-cp37-cp37m-manylinux2010_x86_64.whl (640.7 kB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.13.0.dev20210215215050-cp37-cp37m-macosx_10_13_x86_64.whl (491.8 kB view details)

Uploaded CPython 3.7mmacOS 10.13+ x86-64

tfa_nightly-0.13.0.dev20210215215050-cp36-cp36m-win_amd64.whl (610.5 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.13.0.dev20210215215050-cp36-cp36m-manylinux2010_x86_64.whl (640.7 kB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.13.0.dev20210215215050-cp36-cp36m-macosx_10_13_x86_64.whl (491.8 kB view details)

Uploaded CPython 3.6mmacOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.13.0.dev20210215215050-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.13.0.dev20210215215050-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 610.5 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.56.2 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.13.0.dev20210215215050-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 ec44d6a57c3c3b438d7a3c1f89d76df5f1ae206e252baec153c35fd6fe74a5a6
MD5 7c467cca713359e71ae932e93377bc98
BLAKE2b-256 14a372c9207162949dd3fe8cf8fa8dfdee3faab009d700880e6172c39fa6815b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.13.0.dev20210215215050-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.13.0.dev20210215215050-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 41a0a1203620ca17192effd7e5e136d0868d6b1182c8e7427e5f80ae13a80c91
MD5 899e418aa391453649ae672c8ed7d416
BLAKE2b-256 7a0d7f0520d1f3a863e067f11c8ffd94115f7ed14b888d90a31fa20941fe5173

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.13.0.dev20210215215050-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.13.0.dev20210215215050-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 24c000f957fe54b3900e069821b6b09a03c66074703631e09ceb3354d3b8cc32
MD5 6aa197fdda210ae30e1f1aa6a078ebfd
BLAKE2b-256 c7b02090f534ee37f7593f1a1443b6560be33468d53e6442ea9e796fb90f55b8

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.13.0.dev20210215215050-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.13.0.dev20210215215050-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 610.5 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.56.2 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.13.0.dev20210215215050-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 df95d442bee2bdc32dcad3e70a3e58ab97c31e4085a6d29a9a020534a4a9de18
MD5 7f7af70bf1db33c874dd8270afffa887
BLAKE2b-256 2b38a795b00863a43170e57d1d2f0f854191789220ec5a633730d14363794983

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.13.0.dev20210215215050-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.13.0.dev20210215215050-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 349a59774c0c454f9254462806a1f3125e0a029ab765ca245de2d7099d91c3c4
MD5 6cdf67227273eba92b9322e11855156c
BLAKE2b-256 87bcb1b4a953f8f99192c1d56a8ebbbff4ec0739bd2d4e6028d240b4622c8eca

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.13.0.dev20210215215050-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.13.0.dev20210215215050-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 b11efcf82884155e13aa57c1d433f749e4d3a1f062b11e0596f2bb394247d388
MD5 00e9659bf5976162e21acb7203fffd23
BLAKE2b-256 ec1b41f549b0666857c7468e77c676739d3a2b2373e5f15c7a71543dfaf7d9c2

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.13.0.dev20210215215050-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.13.0.dev20210215215050-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 610.5 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.56.2 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.13.0.dev20210215215050-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 f855a6fa55f8406857644f230823356f42eb193187dcbc9f120bc719e6517b11
MD5 84b82ec9a644914d62130839118bab51
BLAKE2b-256 d07b7b659f53856cb73a2d9ff4da121401a00636088256780ab0b2d26cf3ca6d

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.13.0.dev20210215215050-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.13.0.dev20210215215050-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 a9eaca68c4d9fde1bd6f7641ca2ee089ec0df986df8fd396ca1dd77e7005375b
MD5 e8ec659e56528e4ecb815ce21cd1f8b0
BLAKE2b-256 08a67d6d39581571eba858f99f729b15b71d6dd3aeba506e9e7e6b7f76530051

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.13.0.dev20210215215050-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.13.0.dev20210215215050-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 9eb6e2033ca997e9686176bfbbfbc09c7df1ee77e95db31eb74f510994b749ca
MD5 a6b75e20dfef3de9e42a9a4df69ad1a7
BLAKE2b-256 5c96c742823d1be29852e1f99a09177b6bdb4c271eda3eaabb3d13fceed2ceee

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