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.dev20200825014936-cp38-cp38-win_amd64.whl (920.8 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.12.0.dev20200825014936-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.dev20200825014936-cp38-cp38-macosx_10_13_x86_64.whl (619.2 kB view details)

Uploaded CPython 3.8macOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20200825014936-cp37-cp37m-win_amd64.whl (920.8 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.12.0.dev20200825014936-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.dev20200825014936-cp37-cp37m-macosx_10_13_x86_64.whl (619.2 kB view details)

Uploaded CPython 3.7mmacOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20200825014936-cp36-cp36m-win_amd64.whl (920.8 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.12.0.dev20200825014936-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.dev20200825014936-cp36-cp36m-macosx_10_13_x86_64.whl (619.2 kB view details)

Uploaded CPython 3.6mmacOS 10.13+ x86-64

tfa_nightly-0.12.0.dev20200825014936-cp35-cp35m-win_amd64.whl (920.8 kB view details)

Uploaded CPython 3.5mWindows x86-64

tfa_nightly-0.12.0.dev20200825014936-cp35-cp35m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.5mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.12.0.dev20200825014936-cp35-cp35m-macosx_10_13_x86_64.whl (619.2 kB view details)

Uploaded CPython 3.5mmacOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.12.0.dev20200825014936-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200825014936-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 920.8 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.6.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200825014936-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 4940db8d82ced803d0e617c0f174306c5d9a9172e0ff93984511523738fadbd6
MD5 a45054c208ade13a8e3b2740bc28ddb4
BLAKE2b-256 90c05278a73ac90d7d4e45d2f1db4ca89389bc08a8091395215bd7b39a4847c7

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200825014936-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200825014936-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 9f8d24ba96e735749c7f3a9227dc987a03d8a442384eaeeda3ee45d552afb0cb
MD5 c563819540d3783bab9000aecab4f0ac
BLAKE2b-256 5604ebbf5119d6ba15e564ce23803e5fb71692f4b06700240d5593a862d223ce

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200825014936-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200825014936-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 a428fdd300534de6541831e6a0a8da8f8e698f3badf3617fcfa5b06304e0bb7d
MD5 42e9143ea80feb835d1a78259269cf47
BLAKE2b-256 13d9fd045e9cbe971e72ed3429b37b19293fc85518d889adc2d23440349c744d

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200825014936-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200825014936-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 920.8 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.6.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200825014936-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 366c6ff93a85ada80859d49edbd2f775d1fdb4cd35af44ba6c1ea6375a502d19
MD5 2761564e2715911c2f43d238bbc7e460
BLAKE2b-256 1872f47b8da395d5780236307177f41d8fc13f97ee6b7c99a6d3862146b8b28b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200825014936-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200825014936-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 c93f4b263680e231576102b32ef6a138c1fabdb4af778242e80ce52d5ebdd2ac
MD5 a18ee179fb7af970afb535a34d28e385
BLAKE2b-256 07327fd2357a9c32a82c3c28c05b25778bd2acf594b5b242d1778a2cd4903ffe

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200825014936-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200825014936-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 1259e6027bbcf8fdaf582c449aae81cfdf3aad23ffd88171b261f2564947db59
MD5 4a2e775df334d7b27929805fc1091ae2
BLAKE2b-256 da26572f3fc6b1fe3f922529e0fbe6c59edfeb4970251d84321e11bc728403b4

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200825014936-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200825014936-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 920.8 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.6.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200825014936-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 cbdc482a2c3c037db23fa22d42049046ea63c26c05acac2d210f090880a52802
MD5 4735d1037c43d5fcf81d7cf9d20aca26
BLAKE2b-256 50f4e109ce27ce1ed6ce4a16cc6a294dc60e0942258ecafc5dd3fa652c151458

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200825014936-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200825014936-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 40b70fbee0b9d598cabc2b94d40de8222e0d0ed968aedaab1a0ee7d79e0140b8
MD5 bbcc155d16b3c769338683bbc4f83994
BLAKE2b-256 a64be87d90b90b67505b363fb2ae65cd4d07e50529f777dc859aa192709cfd93

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200825014936-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200825014936-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 67a5d2372fbbac4bb9e36507eead295ebc1223faf2e80bc2b3bd33b7ee010e84
MD5 3d98ddc46f395fcc9af8a96aeb874a5d
BLAKE2b-256 b1544501ef705e218d88cdfcb5116b3e0e08dde7d42be89ef682a4f106a970c0

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200825014936-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.12.0.dev20200825014936-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 920.8 kB
  • Tags: CPython 3.5m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.6.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.9

File hashes

Hashes for tfa_nightly-0.12.0.dev20200825014936-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 60b55cf5c00ba7150c2002c4f3a75016425da68eb2f71a17eaa01a6b9c051c82
MD5 c0fd4ea39e82bebd2e115f62e96b94e2
BLAKE2b-256 6a4de49e792ac8a2e5105d99c12c5f91fa9e08eb2aac84d25c7a28fe6d97b759

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200825014936-cp35-cp35m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200825014936-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 54fc2b865f62d33d6dfcb77125918d3803cdaaf2c2a1cd75f1f5156c85b04bc8
MD5 c1b4bb687f781c8d4f16dabe753428bd
BLAKE2b-256 d1d33f17ffa3370cfe7c1fbea807a3d94add626099e389352803ffccd781a466

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.12.0.dev20200825014936-cp35-cp35m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.12.0.dev20200825014936-cp35-cp35m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 582a412b77962461d7faf3364dc97f5ffb6f7c6ee95d7b64ec64dab75eaa9c32
MD5 782e1dce5c30ffccb2b355d7325aa85b
BLAKE2b-256 fe4435ea30c6a45ae8ac8d1c0aae4dc31bb50c4b119dfee5f6b69b8166118353

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