TensorFlow's public C++ API includes only the API for executing graphs, as of version 0.5. To control the execution of a graph from C++:
- Build the computation graph using the Python API.
- Use
tf.train.write_graph()
to write the graph to a file. - Load the graph using the C++ Session API. For example:
// Reads a model graph definition from disk, and creates a session object you
// can use to run it.
Status LoadGraph(string graph_file_name, Session** session) {
GraphDef graph_def;
TF_RETURN_IF_ERROR(
ReadBinaryProto(Env::Default(), graph_file_name, &graph_def));
TF_RETURN_IF_ERROR(NewSession(SessionOptions(), session));
TF_RETURN_IF_ERROR((*session)->Create(graph_def));
return Status::OK();
}
- Run the graph with a call to
session->Run()