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.dev20230927

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.dev20230927
File Actions
tfq_nightly-0.7.3.dev20230927-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.dev20230927-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
tfq_nightly-0.7.3.dev20230927-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.dev20230927-cp39-cp39-macosx_12_1_x86_64.whl
tfq_nightly-0.7.3.dev20230927-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.dev20230927-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
tfq_nightly-0.7.3.dev20230927-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.dev20230927-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Total release size: 40.9 MB

Release files / tfq_nightly-0.7.3.dev20230927-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230927-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
27ec63d531f2be4a7378d4800026cbbbd04d27781a4d408a1d379565e69e923c
BLAKE2b-256 checksum
How to use checksums
672b0552953387761adb8769e1bdaa62a5148ca347efeb00f04d7da226522259
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.dev20230927-cp39-cp39-macosx_12_1_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230927-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
372dfded9490c741182c15cb73261fb42a1ad8c714afbd84d519ad41fc2956c9
BLAKE2b-256 checksum
How to use checksums
299bfa8e72d445938f26332433846e503f8687b8757410ab979353f84bb65547
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.dev20230927-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230927-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
072c5cd1aabd80abd2692504374984397bc359225bd7cf7b5b0d6be4d628bb8c
BLAKE2b-256 checksum
How to use checksums
d508da886092e238e285e68282ee071c59653479d4e6b57b878e824798c718c4
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.dev20230927-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfq_nightly-0.7.3.dev20230927-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
0261a4e3df1d2268d15a2f75c8a8229803c53a13982a397759e65301acf9cbb2
BLAKE2b-256 checksum
How to use checksums
6f7529c224cc4dc47a7e2c39f8b7c5c10ca5ecb9dea3be80c44e4b470b1413b5
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.dev20230927

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