Skip to main content
Pre-release

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

TensorFlow Quantum is an open source library for high performance batch quantum computation on quantum simulators and quantum computers. The goal of TensorFlow Quantum is to help researchers develop a deeper understanding of quantum data and quantum systems via hybrid models.

TensorFlow Quantum was created in an ongoing collaboration between the University of Waterloo and the Quantum AI team at Google along with help from many other contributors within Google.

Metadata

Release files for tfq-nightly 0.7.3.dev20230716

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 tfq-nightly 0.7.3.dev20230716
File Actions
tfq_nightly-0.7.3.dev20230716-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.9 CPython 3.9 Linux glibc 2.17+ x86-64 Details for tfq_nightly-0.7.3.dev20230716-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
tfq_nightly-0.7.3.dev20230716-cp39-cp39-macosx_12_1_x86_64.whl CPython 3.9 CPython 3.9 macosx 12 1 x86 64 Details for tfq_nightly-0.7.3.dev20230716-cp39-cp39-macosx_12_1_x86_64.whl
tfq_nightly-0.7.3.dev20230716-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.8 CPython 3.8 Linux glibc 2.17+ x86-64 Details for tfq_nightly-0.7.3.dev20230716-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
tfq_nightly-0.7.3.dev20230716-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.17+ x86-64 Details for tfq_nightly-0.7.3.dev20230716-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Total release size: 40.9 MB

Release files / tfq_nightly-0.7.3.dev20230716-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230716-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Size 10.8 MB
Tags CPython 3.9 Linux glibc 2.17+ x86-64
SHA-256 checksum
How to use checksums
459df888029cffddb92079e27e6ddadf88242c90e31c266e0ba067d8bfb5497d
BLAKE2b-256 checksum
How to use checksums
30487d7defdea49e69ad12744e5639c356b68397ade26d9a9e83045982ab6108
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.9.17

Release files / tfq_nightly-0.7.3.dev20230716-cp39-cp39-macosx_12_1_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230716-cp39-cp39-macosx_12_1_x86_64.whl
Size 8.5 MB
Tags CPython 3.9 macosx 12 1 x86 64
SHA-256 checksum
How to use checksums
f9caece6e019b0a59b4198b171825b98e6e85a8a2e00bcf41273e0f96b1e73b3
BLAKE2b-256 checksum
How to use checksums
fd014465fab5fa37ad1eff2de42ffa478d60661ca4a42be323a2fca314cac763
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.9.6

Release files / tfq_nightly-0.7.3.dev20230716-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230716-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Size 10.8 MB
Tags CPython 3.8 Linux glibc 2.17+ x86-64
SHA-256 checksum
How to use checksums
6f2a79866e52e8a8cdeb26a20a54bf17c1117a8825665a1b35cae160082090fe
BLAKE2b-256 checksum
How to use checksums
433ff2562621cfc00df2e00271f5976046e2a06decdc0846c2776f3d3746b9b0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.8.10

Release files / tfq_nightly-0.7.3.dev20230716-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230716-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Size 10.8 MB
Tags CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.17+ x86-64
SHA-256 checksum
How to use checksums
620781f2c7cdee27f00f83ba5b11b18e17085031cd6a210e2b31f90389891fbe
BLAKE2b-256 checksum
How to use checksums
171334e40ecf408ad138d544674e60fe2f1fce82bdb2db192ac47a9cded0c622
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.7.17

Security for tfq-nightly 0.7.3.dev20230716

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