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

tfa_nightly-0.16.0.dev20211116104445-cp39-cp39-win_amd64.whl (758.4 kB view details)

Uploaded CPython 3.9 Windows x86-64

tfa_nightly-0.16.0.dev20211116104445-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.12+ x86-64

tfa_nightly-0.16.0.dev20211116104445-cp39-cp39-macosx_11_0_arm64.whl (557.3 kB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

tfa_nightly-0.16.0.dev20211116104445-cp39-cp39-macosx_10_13_x86_64.whl (587.0 kB view details)

Uploaded CPython 3.9 macOS 10.13+ x86-64

tfa_nightly-0.16.0.dev20211116104445-cp38-cp38-win_amd64.whl (758.4 kB view details)

Uploaded CPython 3.8 Windows x86-64

tfa_nightly-0.16.0.dev20211116104445-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.12+ x86-64

tfa_nightly-0.16.0.dev20211116104445-cp38-cp38-macosx_11_0_arm64.whl (557.2 kB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

tfa_nightly-0.16.0.dev20211116104445-cp38-cp38-macosx_10_13_x86_64.whl (586.9 kB view details)

Uploaded CPython 3.8 macOS 10.13+ x86-64

tfa_nightly-0.16.0.dev20211116104445-cp37-cp37m-win_amd64.whl (758.4 kB view details)

Uploaded CPython 3.7m Windows x86-64

tfa_nightly-0.16.0.dev20211116104445-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.12+ x86-64

tfa_nightly-0.16.0.dev20211116104445-cp37-cp37m-macosx_10_13_x86_64.whl (586.9 kB view details)

Uploaded CPython 3.7m macOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.16.0.dev20211116104445-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.16.0.dev20211116104445-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 758.4 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.7.1 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.dev20211116104445-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 73456d1b4812b61bc1c26d6d72b3aebbcd19aad860b9666ddfd56e1a6ea916e6
MD5 b7505937c30c12d1538f5fa74b24e868
BLAKE2b-256 1d861303be25ecd522e106cc05596a288cf210a766c9d45842ce49dc8313f790

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211116104445-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211116104445-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 9fb2cf63654f005ecc61e471a173186b69656799cd33032e4230e8f43e4fc795
MD5 d49b13076520b4ae25cbf73bfb84f6df
BLAKE2b-256 0e287b0510622f3b5823d4f2d9bef513c62f2651ab0e4eca2a0311545b82a3a0

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211116104445-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211116104445-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a0858a8a92a3a25a4ebef1a817258da60b85783c31094242f5123442cb054854
MD5 cee002c9beccb156732aa83a46ed3af6
BLAKE2b-256 4114dbb399be6fc2f3a6248b9db22e760837da8223241c2414f86c89d8de7f9f

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211116104445-cp39-cp39-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211116104445-cp39-cp39-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 0b55db1e4f019a62ec7164c44408d0c579080011fdd40940d5c8ac9f14f32da2
MD5 a411614015b23e8fa2e4dcac25cba7d6
BLAKE2b-256 ef608e99cb6f84c73cfa310512f4665579cde5fb99bcb0c940dc0e34388b500f

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211116104445-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.16.0.dev20211116104445-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 758.4 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.7.1 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.dev20211116104445-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 e9cbb24115586cb9b361229ebecf9f64bcc40d62695662dc4081ee40601a02a9
MD5 255ed725f2b1944844cc31437388b72d
BLAKE2b-256 08fe6e1e492f817d8a81d030b0726acba6bcbf69d3cc22abd0227d1a3b9a6bd2

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211116104445-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211116104445-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 eb7cfab6ff8285db3aa7dc2c02de6c9a619363e488a1e29feca28672a9009a19
MD5 5b71c4d5a0344e7fe892a14e52c5b9ae
BLAKE2b-256 821631ca5286535e02ecc355f51820fe231e8aea0c8ea8bcca22954cc4eb0fd0

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211116104445-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211116104445-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 6b8ca3f70e7a8cd9596f3929fe2336e4c066699a55515350a1586dd55104719f
MD5 45d6fb3b4083b93dd757f050b6a87aef
BLAKE2b-256 6d64aa053bf021a34ccde41b09a0b35979780aa4fbdafdcabd25fe560ed4f00d

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211116104445-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211116104445-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 4f016143b06bf926cc4c9744384c89da0d94543631fd3ff2fa763e608b5a633b
MD5 7225ef14421f16101c555ce044cbaa8e
BLAKE2b-256 a09b81b2e16410cbca3fb92691d98e8e611995b880351fa46fee5ba057554ab8

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211116104445-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.16.0.dev20211116104445-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 758.4 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.7.1 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.dev20211116104445-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 3dfe40b558bfc238a2b6ef6777354f76a199d2cf26d168a7855623a01fe5a227
MD5 6ae03a048877b0b710dc07a7027dd125
BLAKE2b-256 c5703c5ea7587aa6bc302d29dfa71f80b017ebc4c89c75c096f97e4da1a1f2dd

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211116104445-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211116104445-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 3add155ccd3535251ea004911fc12bd4991064a46bbeb09c8cdcfd5b24002bdc
MD5 08b34d9d2796d4638b644c41b41328f0
BLAKE2b-256 36e591f6e30c675c464be9e531ffb15af8a510c37c141704f4b8f83fc814d777

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.16.0.dev20211116104445-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.16.0.dev20211116104445-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 dfc3f709d20e771a506fb538f54d134207fbabe57300614a864a58083b60ff4a
MD5 63608980372dae2a0f80d1f2d31bb684
BLAKE2b-256 6b38c2611077564a0aa235fbb4bf2cbfeb81d3f03991f86ffb0cb63f4460428b

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page