Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

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).

Metadata

Release files for tfa-nightly 0.7.0.dev20191216

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distributions (wheels)

Table of built distributions (wheels) for tfa-nightly 0.7.0.dev20191216
File Actions
tfa_nightly-0.7.0.dev20191216-cp37-cp37m-manylinux2010_x86_64.whl CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.12+ x86-64 Details for tfa_nightly-0.7.0.dev20191216-cp37-cp37m-manylinux2010_x86_64.whl
tfa_nightly-0.7.0.dev20191216-cp37-cp37m-macosx_10_13_x86_64.whl CPython 3.7 CPython 3.7 pymalloc macOS 10.13+ x86-64 Details for tfa_nightly-0.7.0.dev20191216-cp37-cp37m-macosx_10_13_x86_64.whl
tfa_nightly-0.7.0.dev20191216-cp36-cp36m-manylinux2010_x86_64.whl CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.12+ x86-64 Details for tfa_nightly-0.7.0.dev20191216-cp36-cp36m-manylinux2010_x86_64.whl
tfa_nightly-0.7.0.dev20191216-cp36-cp36m-macosx_10_13_x86_64.whl CPython 3.6 CPython 3.6 pymalloc macOS 10.13+ x86-64 Details for tfa_nightly-0.7.0.dev20191216-cp36-cp36m-macosx_10_13_x86_64.whl
tfa_nightly-0.7.0.dev20191216-cp35-cp35m-manylinux2010_x86_64.whl CPython 3.5 CPython 3.5 pymalloc Linux glibc 2.12+ x86-64 Details for tfa_nightly-0.7.0.dev20191216-cp35-cp35m-manylinux2010_x86_64.whl
tfa_nightly-0.7.0.dev20191216-cp35-cp35m-macosx_10_13_x86_64.whl CPython 3.5 CPython 3.5 pymalloc macOS 10.13+ x86-64 Details for tfa_nightly-0.7.0.dev20191216-cp35-cp35m-macosx_10_13_x86_64.whl
tfa_nightly-0.7.0.dev20191216-cp27-cp27mu-manylinux2010_x86_64.whl CPython 2.7 CPython 2.7 pymalloc wide-unicode Linux glibc 2.12+ x86-64 Details for tfa_nightly-0.7.0.dev20191216-cp27-cp27mu-manylinux2010_x86_64.whl
tfa_nightly-0.7.0.dev20191216-cp27-cp27m-macosx_10_13_x86_64.whl CPython 2.7 CPython 2.7 pymalloc macOS 10.13+ x86-64 Details for tfa_nightly-0.7.0.dev20191216-cp27-cp27m-macosx_10_13_x86_64.whl

Total release size: 6.3 MB

Release files / tfa_nightly-0.7.0.dev20191216-cp37-cp37m-manylinux2010_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191216-cp37-cp37m-manylinux2010_x86_64.whl
Size 1.0 MB
Tags CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
c01ad190b145e5b38ef7696f45f553253d60817283b216281d546cc3f8f77e57
BLAKE2b-256 checksum
How to use checksums
32531fbe378b473b4906c29ac6de87ff698d4631e172fb8c0c935233371e2ede
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/2.7.12

Release files / tfa_nightly-0.7.0.dev20191216-cp37-cp37m-macosx_10_13_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191216-cp37-cp37m-macosx_10_13_x86_64.whl
Size 536.5 kB
Tags CPython 3.7 CPython 3.7 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
d00663bb4f2c54608e054e8bec6f996b0edddcddca368c1240f4e27737d1babf
BLAKE2b-256 checksum
How to use checksums
847c915288e4b889040ee7ab90434e5db4efba7853c3da553ca57c01fec50426
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/2.7.17

Release files / tfa_nightly-0.7.0.dev20191216-cp36-cp36m-manylinux2010_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191216-cp36-cp36m-manylinux2010_x86_64.whl
Size 1.0 MB
Tags CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
9ed60eb066e89e78bb6ea0416fc862622eece3abeaad43055768143e60a962ab
BLAKE2b-256 checksum
How to use checksums
f2666fa31aa864cd7fda1b05bc9f29eb8c834f172640a2896aa102d8adbf173b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/2.7.12

Release files / tfa_nightly-0.7.0.dev20191216-cp36-cp36m-macosx_10_13_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191216-cp36-cp36m-macosx_10_13_x86_64.whl
Size 536.5 kB
Tags CPython 3.6 CPython 3.6 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
331bf72aa3a49f190917a3727dc7e507b7f25928bfdca7bcb1c9c08903dc0f03
BLAKE2b-256 checksum
How to use checksums
a2a02909a110e73d1635258f185dfb6627672a2e230e7a0969f4158a78f433cb
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/2.7.17

Release files / tfa_nightly-0.7.0.dev20191216-cp35-cp35m-manylinux2010_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191216-cp35-cp35m-manylinux2010_x86_64.whl
Size 1.0 MB
Tags CPython 3.5 CPython 3.5 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
4fd02d010adc221293b333cbd80db6a1ac499363bb2daa26662fa0819f88c1ed
BLAKE2b-256 checksum
How to use checksums
c1ebc66bfcfa53dfe58497389adabe1dce59e1e88594dfdbdbcdb7d973dc9d3f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/2.7.12

Release files / tfa_nightly-0.7.0.dev20191216-cp35-cp35m-macosx_10_13_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191216-cp35-cp35m-macosx_10_13_x86_64.whl
Size 536.5 kB
Tags CPython 3.5 CPython 3.5 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
5776eb7a4ae76406fc63453bec65f6cc4d792098172df11fe600222c49e3374c
BLAKE2b-256 checksum
How to use checksums
8c14c6888cb2fc1cf22e416b045d1dd116f530aa6500e57e5594561ef04bffb7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/2.7.17

Release files / tfa_nightly-0.7.0.dev20191216-cp27-cp27mu-manylinux2010_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191216-cp27-cp27mu-manylinux2010_x86_64.whl
Size 1.0 MB
Tags CPython 2.7 CPython 2.7 pymalloc wide-unicode Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
b85958ce10da4f9f312642ab818280a4034de5cef828d7e406b659768284c430
BLAKE2b-256 checksum
How to use checksums
25036d0a8d3164130d2385c6aa4768459c91ec367934ac32cd49678d66fe76d4
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/2.7.12

Release files / tfa_nightly-0.7.0.dev20191216-cp27-cp27m-macosx_10_13_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191216-cp27-cp27m-macosx_10_13_x86_64.whl
Size 536.5 kB
Tags CPython 2.7 CPython 2.7 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
69a75748a4655e772d9a0aff2d60edde27924f2f6c9c055721b2fe607e62bb94
BLAKE2b-256 checksum
How to use checksums
7ebba08743b080568c20c8858b4ed0244ad35b1b98da55d2e5e0112b1049e6fa
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/2.7.17

Security for tfa-nightly 0.7.0.dev20191216

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page