This release is a pre-release and may not be stable for production use.
TensorFlow is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices.
Originally developed by researchers and engineers from the Google Brain team within Google's AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains. TensorFlow is licensed under Apache 2.0.
1 maintainer
Metadata
1 maintainer
Release files for tf-nightly-cpu-aws 2.13.0.dev20230426
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
Total release size: 996.2 MB
Release files / tf_nightly_cpu_aws-2.13.0.dev20230426-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
| Download URL | tf_nightly_cpu_aws-2.13.0.dev20230426-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl |
|---|---|
| Size | 249.1 MB |
| Tags | CPython 3.11 Linux glibc 2.17+ ARM64 |
|
SHA-256 checksum How to use checksums |
8cddc6a5718820761027be1f8aa237193b65b0037a8a4dfcad64cb9d4d43f29c
|
|
BLAKE2b-256 checksum How to use checksums |
120b8d8a16baa4c045a46730dca70d76e1d4adc632f42629676f3fd2b5ff9dba
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.10
|
Release files / tf_nightly_cpu_aws-2.13.0.dev20230426-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
| Download URL | tf_nightly_cpu_aws-2.13.0.dev20230426-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl |
|---|---|
| Size | 249.0 MB |
| Tags | CPython 3.10 Linux glibc 2.17+ ARM64 |
|
SHA-256 checksum How to use checksums |
42b6be101e99ae133d916dfa0f8ff5ec69f1ac5c6c8114be9d381fb7b67f74f4
|
|
BLAKE2b-256 checksum How to use checksums |
54e13114800eeca9b6247a750b7b85c1c9b98868649748f1fa75931f29e7c9b7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.10
|
Release files / tf_nightly_cpu_aws-2.13.0.dev20230426-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
| Download URL | tf_nightly_cpu_aws-2.13.0.dev20230426-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl |
|---|---|
| Size | 249.1 MB |
| Tags | CPython 3.9 Linux glibc 2.17+ ARM64 |
|
SHA-256 checksum How to use checksums |
74b0aab82a4e8d73b1a64662d6f280bd181c92e3470a0c2cd9c00eb4d9f8416b
|
|
BLAKE2b-256 checksum How to use checksums |
b4ae090d6dcfcc1f53cbee2e24006fa8b07b79482c91f68aa2ed058b1f53e6dd
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.10
|
Release files / tf_nightly_cpu_aws-2.13.0.dev20230426-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
| Download URL | tf_nightly_cpu_aws-2.13.0.dev20230426-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl |
|---|---|
| Size | 249.0 MB |
| Tags | CPython 3.8 Linux glibc 2.17+ ARM64 |
|
SHA-256 checksum How to use checksums |
b544313176031fae6aa3730ada6066e9a11563feb0a4938db21ab7e1e796f3dd
|
|
BLAKE2b-256 checksum How to use checksums |
a5ba50beb36ea1e1cbdfc851ab833aeaf9672a20ea7965293cc0cc324ed5d2d1
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.10
|
Security for tf-nightly-cpu-aws 2.13.0.dev20230426
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.
