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.dev20191219

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.dev20191219
File Actions
tfa_nightly-0.7.0.dev20191219-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.dev20191219-cp37-cp37m-manylinux2010_x86_64.whl
tfa_nightly-0.7.0.dev20191219-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.dev20191219-cp37-cp37m-macosx_10_13_x86_64.whl
tfa_nightly-0.7.0.dev20191219-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.dev20191219-cp36-cp36m-manylinux2010_x86_64.whl
tfa_nightly-0.7.0.dev20191219-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.dev20191219-cp36-cp36m-macosx_10_13_x86_64.whl
tfa_nightly-0.7.0.dev20191219-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.dev20191219-cp35-cp35m-manylinux2010_x86_64.whl
tfa_nightly-0.7.0.dev20191219-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.dev20191219-cp35-cp35m-macosx_10_13_x86_64.whl
tfa_nightly-0.7.0.dev20191219-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.dev20191219-cp27-cp27mu-manylinux2010_x86_64.whl
tfa_nightly-0.7.0.dev20191219-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.dev20191219-cp27-cp27m-macosx_10_13_x86_64.whl

Total release size: 6.3 MB

Release files / tfa_nightly-0.7.0.dev20191219-cp37-cp37m-manylinux2010_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191219-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
f8e792477848b76242fcc7f41ece0bc98493f850bc3d2175d4fd5d3df0902fed
BLAKE2b-256 checksum
How to use checksums
2eaaa8a3d112e06b126d400b03f9cb2ec2c3124837cef484c51e952650905d45
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.dev20191219-cp37-cp37m-macosx_10_13_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191219-cp37-cp37m-macosx_10_13_x86_64.whl
Size 537.4 kB
Tags CPython 3.7 CPython 3.7 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
4ec6ca4b2db5de7cabb14fc02a0e4190a074666477a41ba0be2211116fbdaa55
BLAKE2b-256 checksum
How to use checksums
f57430b58163dab293dae8f4afb7ed7469d4cdf5b7e981af1bfecf0bf32157a7
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.dev20191219-cp36-cp36m-manylinux2010_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191219-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
7f137b0dca4b098c305361020a3d267257140ba6c0bdb3fb552d26a9f5d2efb1
BLAKE2b-256 checksum
How to use checksums
ece21014da44858e0234f69104045bc0a770be07afe16049d91dc92c32565d5b
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.dev20191219-cp36-cp36m-macosx_10_13_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191219-cp36-cp36m-macosx_10_13_x86_64.whl
Size 537.4 kB
Tags CPython 3.6 CPython 3.6 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
73bd7152d5a0831c93f9fd10847e1e97f69ccefbd8e48da2d5cfd52d1e13b8d0
BLAKE2b-256 checksum
How to use checksums
f702663c7e5cdc74823efb38e1f08a40836a13e14d519ccb6b7695e7e53dd8c3
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.dev20191219-cp35-cp35m-manylinux2010_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191219-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
4c29e7f5af110b514cb4c36256cbbb9ea9333abe6e7e7903ef98014fb7084691
BLAKE2b-256 checksum
How to use checksums
be1b0cfdf4ad601a6ad674fec7f022720116d5b2666bb5f96b7ecd0491a87d69
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.dev20191219-cp35-cp35m-macosx_10_13_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191219-cp35-cp35m-macosx_10_13_x86_64.whl
Size 537.4 kB
Tags CPython 3.5 CPython 3.5 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
b0264bb6c5ee53f1106fca48fb954e6ee3fbd02e9760fdf897806c12a29bb089
BLAKE2b-256 checksum
How to use checksums
a044067e5735eaa9e0e7026d60eb4256af4bc6c75488a2d89313b5f9df90b54d
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.dev20191219-cp27-cp27mu-manylinux2010_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191219-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
d86387e5404cba2d75a8854c1886ad2cd758b127dcae301f7a4f2c2c52699b9c
BLAKE2b-256 checksum
How to use checksums
95f60eab6941089ad2e21ea02df2585a00a155897cdec81a07abe9f82adb8e7d
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.dev20191219-cp27-cp27m-macosx_10_13_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191219-cp27-cp27m-macosx_10_13_x86_64.whl
Size 537.4 kB
Tags CPython 2.7 CPython 2.7 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
ca9f132caca87d2f41d601a21e3285d1d2f62ba5ee8004596ac66e798330c34b
BLAKE2b-256 checksum
How to use checksums
b66228538977312b1874e3f61fa510748c570600a01ef6b7df077d520f20f74f
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.dev20191219

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