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-0.16.0.dev20211214105053-cp39-cp39-win_amd64.whl (758.6 kB view details)

Uploaded CPython 3.9Windows x86-64

tfa_nightly-0.16.0.dev20211214105053-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-0.16.0.dev20211214105053-cp39-cp39-macosx_11_0_arm64.whl (548.7 kB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

tfa_nightly-0.16.0.dev20211214105053-cp39-cp39-macosx_10_13_x86_64.whl (581.4 kB view details)

Uploaded CPython 3.9macOS 10.13+ x86-64

tfa_nightly-0.16.0.dev20211214105053-cp38-cp38-win_amd64.whl (758.6 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.16.0.dev20211214105053-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-0.16.0.dev20211214105053-cp38-cp38-macosx_11_0_arm64.whl (548.7 kB view details)

Uploaded CPython 3.8macOS 11.0+ ARM64

tfa_nightly-0.16.0.dev20211214105053-cp38-cp38-macosx_10_13_x86_64.whl (581.3 kB view details)

Uploaded CPython 3.8macOS 10.13+ x86-64

tfa_nightly-0.16.0.dev20211214105053-cp37-cp37m-win_amd64.whl (758.6 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.16.0.dev20211214105053-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-0.16.0.dev20211214105053-cp37-cp37m-macosx_10_13_x86_64.whl (581.3 kB view details)

Uploaded CPython 3.7mmacOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.16.0.dev20211214105053-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.16.0.dev20211214105053-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 758.6 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.16.0.dev20211214105053-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 97be06da979b34520a09e0f0289ad47e887adfc6349e373632bd9f617996ebfb
MD5 a210d24f225778a65245823370c5dabf
BLAKE2b-256 ba1374b53c51add803225ab4e5f5fbcbc7aad95c2b025836000cabe35e956c12

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211214105053-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211214105053-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 66fc11ef9052f0af2d0912ff94a79a7b350e199cda1bcd23c1cf99e0fc9dc215
MD5 7e9472d2bfb5b9e651d4a63f66bc6090
BLAKE2b-256 231ed2095257b457c45adf1eb40780fc735ff6a17814302a08c0d4ef3a4bfd52

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211214105053-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211214105053-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 fe3dea773f2b37c9fe701e8db6b4255f6ed29a95cb3656b842308545b6018082
MD5 c31593c2b33c6a0ec157161977cd06a4
BLAKE2b-256 ae6acb2074dcf9801e6754df1062612949c637211b33ff9debdc4c1719bbd7b9

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211214105053-cp39-cp39-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211214105053-cp39-cp39-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 96efb8f0134f652d56ed42d4571a59bedfbd7f08a43d428d07b5a3b512e4729c
MD5 d3552b894c1df04947513b3f6aed748d
BLAKE2b-256 b9a8d837d26cdd42e90f05eae719818521a6e2eab611f722af634249059ca5f1

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211214105053-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.16.0.dev20211214105053-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 758.6 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.16.0.dev20211214105053-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 a7fdb5317b16423ce5f2541145b7bcc5d8bf8e83e8ccf07b164044ea6e742c6b
MD5 1e82031d73846ee57ca478064edff73b
BLAKE2b-256 c7ad110e78e4a7e8e80e41169093ef20ed1d14c2e235bd9158013041fc4a7f61

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211214105053-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211214105053-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 207c3767bc6c15e86f9889d223d0da433bd555481d09105433743e87bf11cbe7
MD5 5d6dffa103195b571e8a2d82732e09b9
BLAKE2b-256 8491721ed11bb2b9e894b45f5f81c3d0e5a7d504eec357a5bf5d0f22ec2f09a9

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211214105053-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211214105053-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 e46e65890421d257cf44f7213e1d33f32065d5a9bfb62d4a262f482f0695fe3d
MD5 de27543596068a6470895d4ec99c5087
BLAKE2b-256 10ca5635200a22dc2d3cebd9427128af69556630b71a6bd5b6c1907ebb1b1b1f

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211214105053-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211214105053-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 f95e0aac82bea97f67ef1bc6b6995610a9ac1fd1c9cac49e3bda5709d0f8c80f
MD5 55a8bc57f102516b18a8bf716dea3197
BLAKE2b-256 169e38c0b0d8bcc2019818f577ed400d5a2dcc0ac03fbce95d4a0a50570192f9

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211214105053-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.16.0.dev20211214105053-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 758.6 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.7.12

File hashes

Hashes for tfa_nightly-0.16.0.dev20211214105053-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 6889614eab250a8c756f2dcd0e75d492f79c3a7cce539c5d0ad3faa0d727362d
MD5 45e13ad7c6bbe832a5e7e7aa373c1e44
BLAKE2b-256 d0f06cb06981b39faff07e3b9b3cbde5ec0b54ca5b0658926cb923655aba7f67

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211214105053-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211214105053-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 754290339d42147bc461b8a3b2b024c0a78006767f1c2efc74d73d11155c7c3f
MD5 ea5592329ab37e9b306f243ddf1a4dff
BLAKE2b-256 1599b867c8c9bc9f776bdbe8476c2a1f34508a5fc6611fa810e4568dd0912ada

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211214105053-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211214105053-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 e420c935d5866e8eac5cee785eefb2ac0ee1994bd5bc5dcbe12b212ea08e3492
MD5 997936077bc0c067adc76634e23ce610
BLAKE2b-256 b9d37f998695e56db28fad660ebd650466fc16af74aff19c6003c73d39d233bf

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