Skip to main content
Pre-release

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

TensorFlow Recommenders Addons are a collection of projects related to large-scale recommendation systems built upon TensorFlow. They are contributed and maintained by the community. Those contributions will be complementary to TensorFlow Core and TensorFlow Recommenders etc.

Metadata

Release files for tfra-nightly 0.2.0.dev20210916051920

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 tfra-nightly 0.2.0.dev20210916051920
File
tfra_nightly-0.2.0.dev20210916051920-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl CPython 3.8 CPython 3.8 Linux glibc 2.12+ x86-64 Details
tfra_nightly-0.2.0.dev20210916051920-cp38-cp38-macosx_10_13_x86_64.whl CPython 3.8 CPython 3.8 macOS 10.13+ x86-64 Details
tfra_nightly-0.2.0.dev20210916051920-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.12+ x86-64 Details
tfra_nightly-0.2.0.dev20210916051920-cp37-cp37m-macosx_10_13_x86_64.whl CPython 3.7 CPython 3.7 pymalloc macOS 10.13+ x86-64 Details
tfra_nightly-0.2.0.dev20210916051920-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.12+ x86-64 Details
tfra_nightly-0.2.0.dev20210916051920-cp36-cp36m-macosx_10_13_x86_64.whl CPython 3.6 CPython 3.6 pymalloc macOS 10.13+ x86-64 Details

Total release size: 28.2 MB

Release files / tfra_nightly-0.2.0.dev20210916051920-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl

Download URL tfra_nightly-0.2.0.dev20210916051920-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Size 5.8 MB
Tags CPython 3.8 Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
8aa0ee6255dcfb004afc3ade225dbd21e6cac119c77b27b48fee3fcfbcebaa14
BLAKE2b-256 checksum
How to use checksums
a516fae58d2131f7c5ad5c455a6903c8dfbf068fedf57927b859722ef12bba08
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.7.12

Release files / tfra_nightly-0.2.0.dev20210916051920-cp38-cp38-macosx_10_13_x86_64.whl

Download URL tfra_nightly-0.2.0.dev20210916051920-cp38-cp38-macosx_10_13_x86_64.whl
Size 3.6 MB
Tags CPython 3.8 macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
3f4eb2afe8345b3383b110ce1e6f291d448ea7294a2f01c408e60375848f6020
BLAKE2b-256 checksum
How to use checksums
224b5c2956e88ef5e3f356127f8131c32df2c20a522a32e7c6c2e2b5585fbff5
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.7.12

Release files / tfra_nightly-0.2.0.dev20210916051920-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl

Download URL tfra_nightly-0.2.0.dev20210916051920-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Size 5.8 MB
Tags CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
fa300828605c397867c342c990adc06784addf6edc1f79680961a226d6bf1bdc
BLAKE2b-256 checksum
How to use checksums
f4a8d782d20a95c2e3478efd2ce49e6fe38f03f36db4ae5a677d9a284fdad1c8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.7.12

Release files / tfra_nightly-0.2.0.dev20210916051920-cp37-cp37m-macosx_10_13_x86_64.whl

Download URL tfra_nightly-0.2.0.dev20210916051920-cp37-cp37m-macosx_10_13_x86_64.whl
Size 3.6 MB
Tags CPython 3.7 CPython 3.7 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
dd098c91e7155af134d2c27346b11417cbe6ab56b2a2ff88c51ba5442303d0d5
BLAKE2b-256 checksum
How to use checksums
ab157587c764510420a94980a543c3fbde5250ffc896bc4a692f6f586a4e8be6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.7.12

Release files / tfra_nightly-0.2.0.dev20210916051920-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl

Download URL tfra_nightly-0.2.0.dev20210916051920-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Size 5.8 MB
Tags CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
2bfceaa652c6c9d70eed7fc6d900dc80b46bd9c76339fdafce94812e2613a6d2
BLAKE2b-256 checksum
How to use checksums
8c981ea10dbe48e30c4959ea2a5135184a13110f6f9993ee7bb62ed5e7885fc2
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.7.12

Release files / tfra_nightly-0.2.0.dev20210916051920-cp36-cp36m-macosx_10_13_x86_64.whl

Download URL tfra_nightly-0.2.0.dev20210916051920-cp36-cp36m-macosx_10_13_x86_64.whl
Size 3.6 MB
Tags CPython 3.6 CPython 3.6 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
5202b056ee173084a0af101ddde35681d0d7244a890e5b554470ef0312a0bd4c
BLAKE2b-256 checksum
How to use checksums
f1e5b9aeeaf3e094944a5acd1eec5982a80b6a1eff531b5b5087a3eaa6d2024e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.7.12

Security for tfra-nightly 0.2.0.dev20210916051920

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

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