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.dev20210607114358

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.dev20210607114358
File
tfra_nightly-0.2.0.dev20210607114358-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.dev20210607114358-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.dev20210607114358-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.dev20210607114358-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.dev20210607114358-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.dev20210607114358-cp36-cp36m-macosx_10_13_x86_64.whl CPython 3.6 CPython 3.6 pymalloc macOS 10.13+ x86-64 Details

Total release size: 73.4 MB

Release files / tfra_nightly-0.2.0.dev20210607114358-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl

Download URL tfra_nightly-0.2.0.dev20210607114358-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Size 2.7 MB
Tags CPython 3.8 Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
810e84838e81fde7c531bb50c06a2e82ef6f10d86906619aee67cec3e504aa7e
BLAKE2b-256 checksum
How to use checksums
cdf6fe85288e7dcc780353d838ce0ef10a319e6a751b0a9da36260ae90b19d49
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.7.10

Release files / tfra_nightly-0.2.0.dev20210607114358-cp38-cp38-macosx_10_13_x86_64.whl

Download URL tfra_nightly-0.2.0.dev20210607114358-cp38-cp38-macosx_10_13_x86_64.whl
Size 1.8 MB
Tags CPython 3.8 macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
bf03d849dc1a0d610b0c174af11a92e243114341fa738f89d3e2716f15688f45
BLAKE2b-256 checksum
How to use checksums
5ce760996fcea3453e95925c162cceacce46a64890de48ca186963b42cc998a4
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.7.10

Release files / tfra_nightly-0.2.0.dev20210607114358-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl

Download URL tfra_nightly-0.2.0.dev20210607114358-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Size 2.7 MB
Tags CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
1d4f12540fec8165c5beceb1397e8a1a99f36dba5181319d5dc4fc6ec8d70e9e
BLAKE2b-256 checksum
How to use checksums
624fbeada9be8a8742249b28e4f13adbfe43a5a143770bc32d63b5c21dc85d6d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.7.10

Release files / tfra_nightly-0.2.0.dev20210607114358-cp37-cp37m-macosx_10_13_x86_64.whl

Download URL tfra_nightly-0.2.0.dev20210607114358-cp37-cp37m-macosx_10_13_x86_64.whl
Size 1.8 MB
Tags CPython 3.7 CPython 3.7 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
5d2d319d6895e8a483555197d2e7f90af47ae47becabe48ae49e54b8ef7a7d65
BLAKE2b-256 checksum
How to use checksums
7376bc3416ddd13f5b25e6629c768de5a49597751c62ebd0ee916fa09b9792a5
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.7.10

Release files / tfra_nightly-0.2.0.dev20210607114358-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl

Download URL tfra_nightly-0.2.0.dev20210607114358-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Size 62.7 MB
Tags CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
e9fb3dbda06b406f6d1c778ed3091471d07f7ad20a8db7913d44c25a10798b45
BLAKE2b-256 checksum
How to use checksums
703652dab9513e7660117f5f9253b0aef42e5a391a1ffb929e2f013a88d50671
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.7.10

Release files / tfra_nightly-0.2.0.dev20210607114358-cp36-cp36m-macosx_10_13_x86_64.whl

Download URL tfra_nightly-0.2.0.dev20210607114358-cp36-cp36m-macosx_10_13_x86_64.whl
Size 1.8 MB
Tags CPython 3.6 CPython 3.6 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
e1387b6ed50daca432f46b7b7ec373eb3cf783ea030169de2569e6bd2946a2bf
BLAKE2b-256 checksum
How to use checksums
0e9136adfbab52a36cc1ec6a6914fceefa3c968d0140c58f246c817a95387d24
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.7.10

Security for tfra-nightly 0.2.0.dev20210607114358

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