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-0.12.0.dev20201102193147-cp38-cp38-win_amd64.whl (927.9 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.12.0.dev20201102193147-cp38-cp38-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64

tfa_nightly-0.12.0.dev20201102193147-cp38-cp38-macosx_10_13_x86_64.whl (634.5 kB view details)

Uploaded CPython 3.8macOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20201102193147-cp37-cp37m-win_amd64.whl (927.9 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.12.0.dev20201102193147-cp37-cp37m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.12.0.dev20201102193147-cp37-cp37m-macosx_10_13_x86_64.whl (634.5 kB view details)

Uploaded CPython 3.7mmacOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20201102193147-cp36-cp36m-win_amd64.whl (927.9 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.12.0.dev20201102193147-cp36-cp36m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.12.0.dev20201102193147-cp36-cp36m-macosx_10_13_x86_64.whl (634.5 kB view details)

Uploaded CPython 3.6mmacOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.12.0.dev20201102193147-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20201102193147-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 927.9 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20201102193147-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 9c5e2309661e4d34c256f672e34272d609436aaf5d09884e74c7978905f4c311
MD5 182b9ebda3a94e4a28899f68e61592c1
BLAKE2b-256 161e0e61ef8e08023a020e32b395071206d40514a401136134168dc0f73b79f7

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20201102193147-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20201102193147-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 21b44ba7d1ea0ec87ac61ea032f597ad516718e52fce19c046078adbe706a2b9
MD5 16781b0c970272879316d93445c96790
BLAKE2b-256 976a0f5dd293c108990b8caecb613150cbaf5ab0a85f5d7bbc0b4603d2d40437

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20201102193147-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20201102193147-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 17c1f3e3f4568819a8e305617a7cf2986afe0753cffae2ce2ea3613345445eef
MD5 9444355e3b1cd5989b41c9dd1df170d6
BLAKE2b-256 c1c8de738ad46813a1ff51f155b451dc0133dad464778479a4e2a0e69beba183

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20201102193147-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20201102193147-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 927.9 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20201102193147-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 5be5cc6d7be59aaf6cdcb86cdeddfcdd6765f57a7bb625fa53414d358c7ae9d0
MD5 2428ce7688beff29ae2a3d8f53d7d240
BLAKE2b-256 d5fe8b0552f3c988ef2a94004b601ff21887769d9b01aa64a6eabf2205a6d02f

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20201102193147-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20201102193147-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 ef19b06fad4f668f7b77bf6050eac6f88533d5322bf6bcb2c5cc020423e07c4c
MD5 a592e0e65702d7d02950ffb969fd7330
BLAKE2b-256 fcf572181a733e43c6fdf282ddfbbd876b070a3338e9bd9157979c429caef5fd

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20201102193147-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20201102193147-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 69dff15ddba11113d066d7b27ba5627eb0712878dbaaa7d5613597fb245e0a4c
MD5 41d758cae39085e1bd02baa819aedfbe
BLAKE2b-256 7d908f4b85274c3236b9419446eb4ee9c7503aa6c17214e29c5c46233961a4cd

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20201102193147-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20201102193147-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 927.9 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20201102193147-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 44c74890e7aad294a4be8c8e0ed8775a46791466ec1fb916f01789d31f89c460
MD5 1bb5990de9a268385366d30a8f35c251
BLAKE2b-256 d092eeaacede2df9f5b64686563b9967dd3f0da4f59e36e9b98040e9099d1744

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20201102193147-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20201102193147-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 3be470c5927938e2b224b14d682414f887ebb89fe4cf8c9442d4f014d8a56d65
MD5 343786a0a6d624877344102ab75bbacf
BLAKE2b-256 8be9c272748488fdd751bdb37e7a2666244e09ec8c4e3f2f40ded5310552cc95

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20201102193147-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20201102193147-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 0dee4238e6e26dee021c932d518df032b717f819b6b1df7db5d6095a8ab71d6d
MD5 f3adad2b953e307dbfbbbdc4c0cfc595
BLAKE2b-256 369ccd0a836097f856d9e5711c3642deff7b89498ae6412f0c9b73c8b343ccb8

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