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TensorFlow is an open source software library for numerical computation using
data flow graphs. The graph nodes represent mathematical operations, while
the graph edges represent the multidimensional data arrays (tensors) that flow
between them. This flexible architecture lets you deploy computation to one
or more CPUs or GPUs in a desktop, server, or mobile device without rewriting
code. TensorFlow also includes TensorBoard, a data visualization toolkit.

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

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. So please see
TensorFlow Discuss for general questions
and discussion, and please direct specific questions to Stack Overflow.

Installation

See Installing TensorFlow for instructions on how to install our release binaries or how to build from source.

People who are a little more adventurous can also try our nightly binaries:

Nightly pip packages

  • We are pleased to announce that TensorFlow now offers nightly pip packages
    under the tf-nightly and
    tf-nightly-gpu project on pypi.
    Simply run pip install tf-nightly or pip install tf-nightly-gpu in a clean
    environment to install the nightly TensorFlow build. We support CPU and GPU
    packages on Linux, Mac, and Windows.

Individual whl files

Try your first TensorFlow program

$ python
>>> import tensorflow as tf
>>> hello = tf.constant('Hello, TensorFlow!')
>>> sess = tf.Session()
>>> sess.run(hello)
'Hello, TensorFlow!'
>>> a = tf.constant(10)
>>> b = tf.constant(32)
>>> sess.run(a + b)
42
>>> sess.close()

For more information

Learn more about the TensorFlow community at the community page of tensorflow.org for a few ways to participate.

License

Apache License 2.0

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