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.dev20231002

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.dev20231002
File Actions
tfq_nightly-0.7.3.dev20231002-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.dev20231002-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
tfq_nightly-0.7.3.dev20231002-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.dev20231002-cp39-cp39-macosx_12_1_x86_64.whl
tfq_nightly-0.7.3.dev20231002-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.dev20231002-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
tfq_nightly-0.7.3.dev20231002-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.dev20231002-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Total release size: 40.9 MB

Release files / tfq_nightly-0.7.3.dev20231002-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20231002-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
a91adf0469e015db1153c9d90b8e63474ac411361ef597debb86ae85e0cb591c
BLAKE2b-256 checksum
How to use checksums
49f17a2907b0f799127aa0d269fa1959c449c66f3cf80ec0f792191d47dfc661
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.dev20231002-cp39-cp39-macosx_12_1_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20231002-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
937e9805ff3b98ccfe4d11e8691bc061810371393e148a950ff68514cc39b21d
BLAKE2b-256 checksum
How to use checksums
c79392140c453c6315b8b9eb469a26640613714e958e3c7e5e6542891d32f19f
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.dev20231002-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20231002-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
0b387c0ce0b38d0f8e561835da5c2f1f55f2e42bbd982fce522c3c226415740b
BLAKE2b-256 checksum
How to use checksums
da59d55cd020ceebc827801140995bccd7ff99c43dd9a3e0219ae750adaa69a1
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.dev20231002-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20231002-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
3d9c9f666015fa80d1d348c664f6aad9fe16642611907a8393fded5cfe679575
BLAKE2b-256 checksum
How to use checksums
3167f5daa69d0e798b2eb0d0f8bd257135554909367c0fea19f9f329fec8e48c
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.dev20231002

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