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.dev20230707

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.dev20230707
File Actions
tfq_nightly-0.7.3.dev20230707-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.dev20230707-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
tfq_nightly-0.7.3.dev20230707-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.dev20230707-cp39-cp39-macosx_12_1_x86_64.whl
tfq_nightly-0.7.3.dev20230707-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.dev20230707-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
tfq_nightly-0.7.3.dev20230707-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.dev20230707-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Total release size: 40.9 MB

Release files / tfq_nightly-0.7.3.dev20230707-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230707-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
b4de21cde8e10640bd1c9b904f5180016e72c8233384b25f64b3b11caf6211be
BLAKE2b-256 checksum
How to use checksums
13791b78944a854e569df8179c1fece726985bd0881692fb77a802cf187e6031
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.9.15

Release files / tfq_nightly-0.7.3.dev20230707-cp39-cp39-macosx_12_1_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230707-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
6f0c20a5cc4b7041758c9c8367bbc63a7b371c142e84778bbfe0cdee2c6858ae
BLAKE2b-256 checksum
How to use checksums
ffb780c2d92eec8c80489a6c3d71d92af8c28b53ee84b3eec25c7a83deca6452
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.dev20230707-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230707-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
e8657997be384ebfcee6bdc77bba6db4d200c9d0eea8596b61bf4f394b5470e5
BLAKE2b-256 checksum
How to use checksums
2430eb4a67b88d4918be931d06afd7149f3a33ba2a34d993daf31037fd31ddce
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.dev20230707-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230707-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
5bf825ab4d7b0a81483d12908981171ebbd8850012610f5b09bc8fb5d0687fcc
BLAKE2b-256 checksum
How to use checksums
34a5e56b4efbeeaca46c1fae47b862fc2c117f99a245c85eb281de51adc6f0bd
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.7.15

Security for tfq-nightly 0.7.3.dev20230707

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