index.md

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

• tensorflow::Env
• tensorflow::RandomAccessFile
• tensorflow::WritableFile
• tensorflow::EnvWrapper

Session

• tensorflow::Session
• tensorflow::SessionOptions

Status

• tensorflow::Status
• tensorflow::Status::State

Tensor

• tensorflow::Tensor
• tensorflow::TensorShape
• tensorflow::TensorShapeDim
• tensorflow::TensorShapeUtils
• tensorflow::PartialTensorShape
• tensorflow::PartialTensorShapeUtils
• TF_Buffer

Thread

• tensorflow::Thread
• tensorflow::ThreadOptions