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gerrit-public.fairphone.software / platform / external / tensorflow / ccf9a752f9f10cbee2f4f53b0d46a5951d620922
commitccf9a752f9f10cbee2f4f53b0d46a5951d620922[log] [tgz]
authorJingyue Wu <jingyue@google.com>Tue Feb 28 22:09:13 2017 -0800
committerTensorFlower Gardener <gardener@tensorflow.org>Tue Feb 28 22:28:41 2017 -0800
tree4e9d2760d9505bc527b6587bd1f5879444e8ea0c
parent8777d9a15614b65271d25401f488b70b6b3dca1e [diff]
Add new ops for memory statistics.

This CL adds only the MaxBytesInUse op, which collects the peak memory usage of
a device allocator. Other ops can be added similarly when demanded. For now, we
only enable MaxBytesInUse for GPU because memory statistics are unreliable for
CPU allocators.

This CL essentially merges part of Yaroslav Bulatov's work on
https://github.com/yaroslavvb/memory_probe_ops to TensorFlow.
Change: 148854571
8 files changed
tree: 4e9d2760d9505bc527b6587bd1f5879444e8ea0c
  1. tensorflow/
  2. third_party/
  3. tools/
  4. util/
  5. .gitignore
  6. .gitmodules
  7. ACKNOWLEDGMENTS
  8. ADOPTERS.md
  9. AUTHORS
  10. bower.BUILD
  11. BUILD
  12. configure
  13. CONTRIBUTING.md
  14. ISSUE_TEMPLATE.md
  15. LICENSE
  16. models.BUILD
  17. README.md
  18. RELEASE.md
  19. WORKSPACE
README.md
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TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph 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'd like to contribute to TensorFlow, be sure to review the contribution guidelines.

We use GitHub issues for tracking requests and bugs, but please see Community for general questions and discussion.

Installation

See Download and Setup 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:

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
>>>

##For more information

The TensorFlow community has created amazing things with TensorFlow, please see the resources section of tensorflow.org for an incomplete list.