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.
1 maintainer
Metadata
1 maintainer
Release files for tfra-nightly 0.0.1.dev20210603062916
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| tfra_nightly-0.0.1.dev20210603062916-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-0.0.1.dev20210603062916-cp38-cp38-macosx_10_13_x86_64.whl | CPython 3.8 | CPython 3.8 | macOS 10.13+ x86-64 | Details |
| tfra_nightly-0.0.1.dev20210603062916-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-0.0.1.dev20210603062916-cp37-cp37m-macosx_10_13_x86_64.whl | CPython 3.7 | CPython 3.7 pymalloc | macOS 10.13+ x86-64 | Details |
| tfra_nightly-0.0.1.dev20210603062916-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-0.0.1.dev20210603062916-cp36-cp36m-macosx_10_13_x86_64.whl | CPython 3.6 | CPython 3.6 pymalloc | macOS 10.13+ x86-64 | Details |
Total release size: 13.3 MB
Release files / tfra_nightly-0.0.1.dev20210603062916-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
| Download URL | tfra_nightly-0.0.1.dev20210603062916-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 |
e37bdc7338884388112087437767ce0eefd16178d52a183ac8651026e1e75cf7
|
|
BLAKE2b-256 checksum How to use checksums |
c7ec1de0778cb84ad8ec3b70e1087b29c68ab4951b48d3e4e7ca385d1341389e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.4.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.7.10
|
Release files / tfra_nightly-0.0.1.dev20210603062916-cp38-cp38-macosx_10_13_x86_64.whl
| Download URL | tfra_nightly-0.0.1.dev20210603062916-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 |
78e03efbbb3e58090fae41498f80d759679f26bf486526a7fec16f069b03b910
|
|
BLAKE2b-256 checksum How to use checksums |
8b4aa477520dda6f9ff57596374e80edfa25afb89e890d801205d0539050526b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.4.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.7.10
|
Release files / tfra_nightly-0.0.1.dev20210603062916-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
| Download URL | tfra_nightly-0.0.1.dev20210603062916-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 |
5c3b27acb121fcdd716220ca38175c3fe15fba54c8525ccbd1d4110730072ad3
|
|
BLAKE2b-256 checksum How to use checksums |
4688b74c8deaf402ea59cbbadde1ac787d5c61045616d787fdd2f22f9bd45e10
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.4.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.7.10
|
Release files / tfra_nightly-0.0.1.dev20210603062916-cp37-cp37m-macosx_10_13_x86_64.whl
| Download URL | tfra_nightly-0.0.1.dev20210603062916-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 |
f44dc1c557846beea70a22ab6978525558140961142a6ab093e95a19aabf3534
|
|
BLAKE2b-256 checksum How to use checksums |
ba7f42fef75a4b13e8dade9bb3c20502e822b9ac8a2d5da661cf779e8a5cb6f2
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.4.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.7.10
|
Release files / tfra_nightly-0.0.1.dev20210603062916-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
| Download URL | tfra_nightly-0.0.1.dev20210603062916-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl |
|---|---|
| Size | 2.7 MB |
| Tags | CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.12+ x86-64 |
|
SHA-256 checksum How to use checksums |
bdd9d4b822905f92813938a6feaf4c16bdb569317259b350dc0da78b0d362239
|
|
BLAKE2b-256 checksum How to use checksums |
7c890e13d237ca20d4b01fcccd761746e973575b5de9df46f660d776a6253328
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.4.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.7.10
|
Release files / tfra_nightly-0.0.1.dev20210603062916-cp36-cp36m-macosx_10_13_x86_64.whl
| Download URL | tfra_nightly-0.0.1.dev20210603062916-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 |
fffe3e193400aa8d880f83b7a52fe646df94dbb4b8a09b89e46a309b223d4e43
|
|
BLAKE2b-256 checksum How to use checksums |
cd8d64420b725e6baae3238dcb83e8e450e6ee4740eac26c8c3b57f5fcb918a2
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.4.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.7.10
|
Security for tfra-nightly 0.0.1.dev20210603062916
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.
