TensorFlow is an open source software library for numerical computation usingdata flow graphs. The graph nodes represent mathematical operations, whilethe graph edges represent the multidimensional data arrays (tensors) that flowbetween them. This flexible architecture enables you to deploy computation to oneor more CPUs or GPUs in a desktop, server, or mobile device without rewritingcode. TensorFlow also includes TensorBoard, a data visualization toolkit.
TensorFlow was originally developed by researchers and engineersworking on the Google Brain team within Google's Machine Intelligence Researchorganization for the purposes of conducting machine learning and deep neuralnetworks research. The system is general enough to be applicable in a widevariety of other domains, as well.
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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 packagesunder the tf-nightly andtf-nightly-gpu project on pypi.Simply run
pip install tf-nightly or
pip install tf-nightly-gpu in a cleanenvironment to install the nightly TensorFlow build. We support CPU and GPUpackages on Linux, Mac, and Windows.
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() ```
The TensorFlow project strives to abide by generally accepted best practices in open-source software development:
| Build Type | Status | Artifacts || --- | --- | --- || Linux CPU | | pypi || Linux GPU | | pypi || Linux XLA | TBA | TBA || MacOS | | pypi || Windows CPU | | pypi || Windows GPU | | pypi || Android | | demo APK, native libs build history |
Learn more about the TensorFlow community at the community page of tensorflow.org for a few ways to participate.
git clone tensorflow-tensorflow_-_2018-05-15_05-36-46.bundle