TensorFlow

TensorFlow C++ Session API reference documentation

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++:

  1. Build the computation graph using the Python API.
  2. Use tf.train.write_graph() to write the graph to a file.
  3. 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();
}
  1. Run the graph with a call to session->Run()

Env

Session

Status

Tensor

Thread