tensorflow

https://github.com/kaleid-liner/tensorflow

Science Score: 49.0%

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CITATION.cff file
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Found 3 DOI reference(s) in README
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Scientific vocabulary similarity
Low similarity (14.3%) to scientific vocabulary

Last synced: 7 months ago · JSON representation

Repository

Basic Info

Host: GitHub
Owner: kaleid-liner
License: apache-2.0
Language: C++
Default Branch: sync-cpu-no-copy
Size: 826 MB

Statistics

Stars: 2
Watchers: 2
Forks: 0
Open Issues: 0
Releases: 0

Created over 3 years ago · Last pushed almost 3 years ago

Metadata Files

Readme Contributing License Code of conduct Citation Codeowners Security Authors Zenodo

README.md

Documentation | ------------------- | |

TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.

TensorFlow was originally developed by researchers and engineers working on the Google Brain team within Google's Machine Intelligence Research organization to conduct machine learning and deep neural networks research. The system is general enough to be applicable in a wide variety of other domains, as well.

TensorFlow provides stable Python and C++ APIs, as well as non-guaranteed backward compatible API for other languages.

Keep up-to-date with release announcements and security updates by subscribing to announce@tensorflow.org. See all the mailing lists.

Install

See the TensorFlow install guide for the pip package, to enable GPU support, use a Docker container, and build from source.

To install the current release, which includes support for CUDA-enabled GPU cards (Ubuntu and Windows):

$ pip install tensorflow

A smaller CPU-only package is also available:

$ pip install tensorflow-cpu

To update TensorFlow to the latest version, add --upgrade flag to the above commands.

Nightly binaries are available for testing using the tf-nightly and tf-nightly-cpu packages on PyPi.

Try your first TensorFlow program

shell $ python

```python

import tensorflow as tf tf.add(1, 2).numpy() 3 hello = tf.constant('Hello, TensorFlow!') hello.numpy() b'Hello, TensorFlow!' ```

For more examples, see the TensorFlow tutorials.

Contribution guidelines

If you want to contribute to TensorFlow, be sure to review the contribution guidelines. This project adheres to TensorFlow's code of conduct. By participating, you are expected to uphold this code.

We use GitHub issues for tracking requests and bugs, please see TensorFlow Discuss for general questions and discussion, and please direct specific questions to Stack Overflow.

The TensorFlow project strives to abide by generally accepted best practices in open-source software development:

Continuous build status

You can find more community-supported platforms and configurations in the TensorFlow SIG Build community builds table.

Official Builds

Build Type | Status | Artifacts ----------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- Linux CPU | | PyPI Linux GPU | | PyPI Linux XLA | | TBA macOS | | PyPI Windows CPU | | PyPI Windows GPU | | PyPI Android | | Download Raspberry Pi 0 and 1 | | Py3 Raspberry Pi 2 and 3 | | Py3 Libtensorflow MacOS CPU | Status Temporarily Unavailable | Nightly Binary Official GCS Libtensorflow Linux CPU | Status Temporarily Unavailable | Nightly Binary Official GCS Libtensorflow Linux GPU | Status Temporarily Unavailable | Nightly Binary Official GCS Libtensorflow Windows CPU | Status Temporarily Unavailable | Nightly Binary Official GCS Libtensorflow Windows GPU | Status Temporarily Unavailable | Nightly Binary Official GCS