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.dev20230923

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.dev20230923
File Actions
tfq_nightly-0.7.3.dev20230923-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.dev20230923-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
tfq_nightly-0.7.3.dev20230923-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.dev20230923-cp39-cp39-macosx_12_1_x86_64.whl
tfq_nightly-0.7.3.dev20230923-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.dev20230923-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
tfq_nightly-0.7.3.dev20230923-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.dev20230923-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Total release size: 40.9 MB

Release files / tfq_nightly-0.7.3.dev20230923-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230923-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
a1c10601c627648c87e8805a98d1dc8e514bf27b63539a82b9336083b7fb0d55
BLAKE2b-256 checksum
How to use checksums
f42604b19e9c5b42102f815b44c7eebdbac3da3c0411e5260d2f0ec6946370c7
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.dev20230923-cp39-cp39-macosx_12_1_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230923-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
7f3b349f6d85079249c9f44b87edf50846a73a751ea56e4808c0fbf108cc055b
BLAKE2b-256 checksum
How to use checksums
d2775618543f204f7921b933e95b2ffca1887ea805b5f339068799d6525dd316
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.dev20230923-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230923-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
335a14a195519fe7d2c332b264479d980c215ecd9eb89c7622441683f851f97a
BLAKE2b-256 checksum
How to use checksums
bde1a9372739406e5199bd7b63a15f5c7cd06ac9a31d01a06a6d8aaf040f7a88
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.dev20230923-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230923-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
4b2d0979b3e4e2aa0fd57aba0e685ae5469d8603980122747edbdd8e6ca30ab5
BLAKE2b-256 checksum
How to use checksums
8f93fe26162c873b7b7d309abde7cefc39f1486a2d57d50263b699dec2f1ed78
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.dev20230923

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