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-0.11.0.dev20200614111138-cp38-cp38-win_amd64.whl (900.1 kB view details)

Uploaded CPython 3.8Windows x86-64

tfa_nightly-0.11.0.dev20200614111138-cp38-cp38-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200614111138-cp38-cp38-macosx_10_13_x86_64.whl (594.7 kB view details)

Uploaded CPython 3.8macOS 10.13+ x86-64

tfa_nightly-0.11.0.dev20200614111138-cp37-cp37m-win_amd64.whl (900.1 kB view details)

Uploaded CPython 3.7mWindows x86-64

tfa_nightly-0.11.0.dev20200614111138-cp37-cp37m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200614111138-cp37-cp37m-macosx_10_13_x86_64.whl (594.7 kB view details)

Uploaded CPython 3.7mmacOS 10.13+ x86-64

tfa_nightly-0.11.0.dev20200614111138-cp36-cp36m-win_amd64.whl (900.1 kB view details)

Uploaded CPython 3.6mWindows x86-64

tfa_nightly-0.11.0.dev20200614111138-cp36-cp36m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200614111138-cp36-cp36m-macosx_10_13_x86_64.whl (594.7 kB view details)

Uploaded CPython 3.6mmacOS 10.13+ x86-64

tfa_nightly-0.11.0.dev20200614111138-cp35-cp35m-win_amd64.whl (900.1 kB view details)

Uploaded CPython 3.5mWindows x86-64

tfa_nightly-0.11.0.dev20200614111138-cp35-cp35m-manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.5mmanylinux: glibc 2.12+ x86-64

tfa_nightly-0.11.0.dev20200614111138-cp35-cp35m-macosx_10_13_x86_64.whl (594.7 kB view details)

Uploaded CPython 3.5mmacOS 10.13+ x86-64

File details

Details for the file tfa_nightly-0.11.0.dev20200614111138-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200614111138-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 900.1 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/47.1.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200614111138-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 ffc1088d8e5fbf3777ff163cf03f28f16f7c6670d513d97f85ae501a7dddb2f2
MD5 5f78594ed4a96a8a89747ba1f5d8d203
BLAKE2b-256 f45544227aa893042424f33174366d6cadf088aa68bcf35967a2d7447d34a484

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200614111138-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200614111138-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 10a607e87205d77f1e9511efb1d1f0f18a140e6f06085e463345069920ff3725
MD5 6883b3b1cbe0a7a85da4fcd89dac906a
BLAKE2b-256 8feaf2834bcc30f71bbf9c44bf2fd6ebe43254ab963d5fd30fe71ed4d2d8c0c0

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200614111138-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200614111138-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 397ce4ca56f3a8558d1365caa642eb485a7e08bef41536e07c4c90e5f6c93fbe
MD5 ef2069a6c5922f2013108833b7012a4f
BLAKE2b-256 7bff4a3f5ab1aeae79d61227b512ea5219690cbb8fe38647f2c7571d44dbdc30

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200614111138-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200614111138-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 900.1 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/47.1.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200614111138-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 9bf103d731bb03f6f77980310053b4de14920fa9453d78db336cc8ad3181ae78
MD5 768dd06ee2b0620b17fe12b4133eea79
BLAKE2b-256 6a8143e0bc93dcd1b7798afc2b8fad59af28d186ef744a3c844d0d76d22c734b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200614111138-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200614111138-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 dba14225dd55497a640a02e6e972d68a530a3253d62ae106d2de7add898be566
MD5 4f4af710dea80db9a7d8e20c8057c0a9
BLAKE2b-256 da1660dcf4931786f318855ebb1a20bd1cc659f32998225955c25380c01647da

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200614111138-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200614111138-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 e2d1a0ba6bdbf2f041526d583e219ec1e4131e4da66e24119504f7f771341e7e
MD5 a333823ee2f21c839c0203e4ae95af7d
BLAKE2b-256 6b71d441305c3d839046e72fb9dfa63b01e297f3e32737e71ceb130c8ed5ef8b

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200614111138-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200614111138-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 900.1 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/47.1.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200614111138-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 f4f686d48578613a8e2715fd171ffa4d2a721175dcc4106533987a0f17ea1661
MD5 1dbb944938c823485f13aa6b5d09025e
BLAKE2b-256 8d634518b7c6377ec72c884b178b7b977d7d802b9d9f9aafd969d0fefa148f84

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200614111138-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200614111138-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 736b3b181eed34ba9a747bb928b39a425fcf8c1e61d9c0d062b2394e7bae9a45
MD5 62cdf8070d4da656d09dc8d960e4d29a
BLAKE2b-256 51cf1e9cfa16f363c1be5dd64fa0b9d211860ad842a64a2e6e102eff5a982ed4

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200614111138-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200614111138-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 167267129c40e22a6de58e849d1c6670c59564f8f2182056dcf8f37c242f4941
MD5 acc5aadfc286f5448c4b7da0202e31ed
BLAKE2b-256 0541ae25e1c577fdee5f8edfa346cd1b891023a15a322d7828f91cbbbae86528

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200614111138-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: tfa_nightly-0.11.0.dev20200614111138-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 900.1 kB
  • Tags: CPython 3.5m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/47.1.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.7.7

File hashes

Hashes for tfa_nightly-0.11.0.dev20200614111138-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 f18e52df412cbbacf30819ecc3cfd47b2929d69e282e59fb9078d002f2eb88aa
MD5 e623621bf268956b4f683ff0609b782c
BLAKE2b-256 2e0b53196c3cd1e07a86da1e1cb3e1fa142308a78ef21358df97eea4c633ed9a

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200614111138-cp35-cp35m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200614111138-cp35-cp35m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 48548b41693b45947518395ae26bb7b5de3a340616c4ef25ee950d9564cab608
MD5 667bb9c38e002510fb16532433a30fbb
BLAKE2b-256 3804626f17fdc107ef34c4c5b73e41813fb07c47fcf565b894364739598326db

See more details on using hashes here.

File details

Details for the file tfa_nightly-0.11.0.dev20200614111138-cp35-cp35m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfa_nightly-0.11.0.dev20200614111138-cp35-cp35m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 96e4df11f58bb57075018e097225c9ad1ca8c115679c39031fdae6cb9c14868a
MD5 28e2ae5f3066c4cad007b1d79f42e999
BLAKE2b-256 7bbde6f458ec393e1037669334810141362a3e69ac6274dd9c47dbdd755bfa3f

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