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.dev20191010

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.dev20191010
File Actions
tfa_nightly-0.7.0.dev20191010-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.dev20191010-cp37-cp37m-manylinux2010_x86_64.whl
tfa_nightly-0.7.0.dev20191010-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.dev20191010-cp37-cp37m-macosx_10_13_x86_64.whl
tfa_nightly-0.7.0.dev20191010-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.dev20191010-cp36-cp36m-manylinux2010_x86_64.whl
tfa_nightly-0.7.0.dev20191010-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.dev20191010-cp36-cp36m-macosx_10_13_x86_64.whl
tfa_nightly-0.7.0.dev20191010-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.dev20191010-cp35-cp35m-manylinux2010_x86_64.whl
tfa_nightly-0.7.0.dev20191010-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.dev20191010-cp35-cp35m-macosx_10_13_x86_64.whl
tfa_nightly-0.7.0.dev20191010-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.dev20191010-cp27-cp27mu-manylinux2010_x86_64.whl
tfa_nightly-0.7.0.dev20191010-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.dev20191010-cp27-cp27m-macosx_10_13_x86_64.whl

Total release size: 9.3 MB

Release files / tfa_nightly-0.7.0.dev20191010-cp37-cp37m-manylinux2010_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191010-cp37-cp37m-manylinux2010_x86_64.whl
Size 1.9 MB
Tags CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
2efb8ce664862ccae92165f6bcad418124b6658347218d81ead1d434440c8439
BLAKE2b-256 checksum
How to use checksums
e1e2f7ac4d9c5a28656ec45791ad9d113cea362fec408f1dd00820365ea96594
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/41.4.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/2.7.12

Release files / tfa_nightly-0.7.0.dev20191010-cp37-cp37m-macosx_10_13_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191010-cp37-cp37m-macosx_10_13_x86_64.whl
Size 452.8 kB
Tags CPython 3.7 CPython 3.7 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
17fc2dec1fff22ca4775cb7695c91086eb6a7148b0f014cfd9e7f18a899d645e
BLAKE2b-256 checksum
How to use checksums
d9c4d457f13820a245da573fbc38322ad176014bc965f4afc5a7d4fbb7daeb87
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/41.4.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/2.7.15

Release files / tfa_nightly-0.7.0.dev20191010-cp36-cp36m-manylinux2010_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191010-cp36-cp36m-manylinux2010_x86_64.whl
Size 1.9 MB
Tags CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
12355ce74f9f7de8874cc79a4e1573a8db6bc2ad5c0cdab9f6341c35bf1a93e2
BLAKE2b-256 checksum
How to use checksums
1590f3daf79769449b416913f7db3b05935ae9b768a987aad051d194ef366744
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/41.4.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/2.7.12

Release files / tfa_nightly-0.7.0.dev20191010-cp36-cp36m-macosx_10_13_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191010-cp36-cp36m-macosx_10_13_x86_64.whl
Size 452.8 kB
Tags CPython 3.6 CPython 3.6 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
228c9dcda669b2dc41252558f0b5f18fe75ab8bdd9d3e0425c6842f9396563ea
BLAKE2b-256 checksum
How to use checksums
14891c6370842f771f46117264a085fb7ceb99e639d4485d06540f814b91a68c
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/41.4.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/2.7.15

Release files / tfa_nightly-0.7.0.dev20191010-cp35-cp35m-manylinux2010_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191010-cp35-cp35m-manylinux2010_x86_64.whl
Size 1.9 MB
Tags CPython 3.5 CPython 3.5 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
3a7716f5011158d0429d54d6259c2e52fc6818b1f0bd25249626a0e3fe80959f
BLAKE2b-256 checksum
How to use checksums
b612e467b3729884a40de25580f13ce5b8d4bf19f060f2565df40c0262ddcc3b
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/41.4.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/2.7.12

Release files / tfa_nightly-0.7.0.dev20191010-cp35-cp35m-macosx_10_13_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191010-cp35-cp35m-macosx_10_13_x86_64.whl
Size 452.8 kB
Tags CPython 3.5 CPython 3.5 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
625e3729c02d52f88cd4674c1302e552c090b9703564400c942f7b7bee44a0f9
BLAKE2b-256 checksum
How to use checksums
98ab25e92b5b6c8660c6900e6f98a1ca8fac1b6c797c30394602b567a2f15dc0
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/41.4.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/2.7.15

Release files / tfa_nightly-0.7.0.dev20191010-cp27-cp27mu-manylinux2010_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191010-cp27-cp27mu-manylinux2010_x86_64.whl
Size 1.9 MB
Tags CPython 2.7 CPython 2.7 pymalloc wide-unicode Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
5e1a728b92eb97193ff6f296f14127e35adf23d7616e0327d342b7eb95a98c19
BLAKE2b-256 checksum
How to use checksums
80e1a4f24ba94df9cb18bfbf69c5b3fbb438be73db687c1253503f2edec271fd
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/41.4.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/2.7.12

Release files / tfa_nightly-0.7.0.dev20191010-cp27-cp27m-macosx_10_13_x86_64.whl

Download URL tfa_nightly-0.7.0.dev20191010-cp27-cp27m-macosx_10_13_x86_64.whl
Size 452.8 kB
Tags CPython 2.7 CPython 2.7 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
31d93cb23c0c52498e68604b382ea833334266818ecef1c410890669613bb02b
BLAKE2b-256 checksum
How to use checksums
cc18838f677fb6fc6abfe182965444fe25c715acb29d300db4de3b9dd28ef859
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/41.4.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/2.7.15

Security for tfa-nightly 0.7.0.dev20191010

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