How to build and use Google TensorFlow C++ api

c++ tensorflow
theideasmith picture theideasmith · Nov 10, 2015 · Viewed 127.8k times · Source

I'm really eager to start using Google's new Tensorflow library in C++. The website and docs are just really unclear in terms of how to build the project's C++ API and I don't know where to start.

Can someone with more experience help by discovering and sharing a guide to using tensorflow's C++ API?

Answer

mrry picture mrry · Nov 10, 2015

To get started, you should download the source code from Github, by following the instructions here (you'll need Bazel and a recent version of GCC).

The C++ API (and the backend of the system) is in tensorflow/core. Right now, only the C++ Session interface, and the C API are being supported. You can use either of these to execute TensorFlow graphs that have been built using the Python API and serialized to a GraphDef protocol buffer. There is also an experimental feature for building graphs in C++, but this is currently not quite as full-featured as the Python API (e.g. no support for auto-differentiation at present). You can see an example program that builds a small graph in C++ here.

The second part of the C++ API is the API for adding a new OpKernel, which is the class containing implementations of numerical kernels for CPU and GPU. There are numerous examples of how to build these in tensorflow/core/kernels, as well as a tutorial for adding a new op in C++.

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