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-0.7.0.dev20191113-cp37-cp37m-manylinux2010_x86_64.whl (1.9 MB view details)

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

tfa_nightly-0.7.0.dev20191113-cp37-cp37m-macosx_10_13_x86_64.whl (491.5 kB view details)

Uploaded CPython 3.7m macOS 10.13+ x86-64

tfa_nightly-0.7.0.dev20191113-cp36-cp36m-manylinux2010_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.12+ x86-64

tfa_nightly-0.7.0.dev20191113-cp36-cp36m-macosx_10_13_x86_64.whl (491.5 kB view details)

Uploaded CPython 3.6m macOS 10.13+ x86-64

tfa_nightly-0.7.0.dev20191113-cp35-cp35m-manylinux2010_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.5m manylinux: glibc 2.12+ x86-64

tfa_nightly-0.7.0.dev20191113-cp35-cp35m-macosx_10_13_x86_64.whl (491.5 kB view details)

Uploaded CPython 3.5m macOS 10.13+ x86-64

tfa_nightly-0.7.0.dev20191113-cp27-cp27mu-manylinux2010_x86_64.whl (1.9 MB view details)

Uploaded CPython 2.7mu manylinux: glibc 2.12+ x86-64

tfa_nightly-0.7.0.dev20191113-cp27-cp27m-macosx_10_13_x86_64.whl (491.5 kB view details)

Uploaded CPython 2.7m macOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.7.0.dev20191113-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

  • Download URL: tfa_nightly-0.7.0.dev20191113-cp37-cp37m-manylinux2010_x86_64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.7m, manylinux: glibc 2.12+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0 requests-toolbelt/0.9.1 tqdm/4.38.0 CPython/2.7.12

File hashes

Hashes for tfa_nightly-0.7.0.dev20191113-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 54a844fb7e744a8deaa291f97cbaa78d52494f134087f830051b76947cca80f0
MD5 9ebec7b9a69e426c6e1eff76df07f742
BLAKE2b-256 78660ac81e10dcd14ed28c13694069eb104146ec0954df7ed23dd38104745305

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.7.0.dev20191113-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.7.0.dev20191113-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 5e3999e20ba6847334deae722da3432a8a28884034f18fdfe38fc9b470e96f2a
MD5 9e0cee01b30e848ff69b990284006439
BLAKE2b-256 b259b21036b771cfeb8b357ce299fd8aa3307e3055e43ce2e1cecb62f1d9dea4

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.7.0.dev20191113-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

  • Download URL: tfa_nightly-0.7.0.dev20191113-cp36-cp36m-manylinux2010_x86_64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.6m, manylinux: glibc 2.12+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0 requests-toolbelt/0.9.1 tqdm/4.38.0 CPython/2.7.12

File hashes

Hashes for tfa_nightly-0.7.0.dev20191113-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 e32db9a04f6443a0f2a99697d892746aabda902de33cc3bd94125854fe14cc79
MD5 21c5e8929c6274da37493a8a78c31847
BLAKE2b-256 d327fac29349e04407f12a446bc92ec22e70c476ffefa9fd576a6f98db237b70

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.7.0.dev20191113-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.7.0.dev20191113-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 7bf86f9b28e9814d5c9b4a0a5af01499adf2ef00376c819bb8b77bd6c5a4ea62
MD5 700b816ae7e2f14419163f821d9974df
BLAKE2b-256 b307752ae336fdf0314722a8a8f3c09e4abcfa046c1e443f73c7d9f3e8efc80a

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.7.0.dev20191113-cp35-cp35m-manylinux2010_x86_64.whl.

File metadata

  • Download URL: tfa_nightly-0.7.0.dev20191113-cp35-cp35m-manylinux2010_x86_64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.5m, manylinux: glibc 2.12+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0 requests-toolbelt/0.9.1 tqdm/4.38.0 CPython/2.7.12

File hashes

Hashes for tfa_nightly-0.7.0.dev20191113-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 d42fb8e24da2b1c56e219fe633127d63a07852e2252645922d4afa5013f7af51
MD5 f9b19cbdd773cc46aad98b1cd56b88e2
BLAKE2b-256 6325201cfffad65614b7a1d3f1dad0774c512b13fa28407bb97fb8f81b672a83

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.7.0.dev20191113-cp35-cp35m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.7.0.dev20191113-cp35-cp35m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 68d3b45971504a166d9ddbecfb39bbf9c99dcc1e79052e9b1bd1118833e2a1f9
MD5 9322dc4f79b321d391adb88a3fb46692
BLAKE2b-256 0c18e3c9e672a81db15b0f6b6d43c406da0ef44681fbab93eead562aed2c7dd2

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.7.0.dev20191113-cp27-cp27mu-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.7.0.dev20191113-cp27-cp27mu-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 d56c9a1d254b5f0c0541a23aaeca218e56e977f2c745e77ecdcbb523df0ff6f1
MD5 f79cf289113d809a97ab52671b9581ea
BLAKE2b-256 3b2310cffa771601e5ac726b05ab2b45b9d124ef882e7e9316cfc124d564fbfc

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.7.0.dev20191113-cp27-cp27m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.7.0.dev20191113-cp27-cp27m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 c16d7e081f57a8d1a0402756f58b02a54088d824494916e19d690f751e01ed76
MD5 e7bea7190fa3d61a0fcac7d5293f74ac
BLAKE2b-256 be0eaff49c76b32184856e0b4e288462306b8de21dff1b9e76497ff19c6fae18

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