Function CreateGraphDef

tensorflow/cc/tutorials/example_trainer.cc:50–84

A = [3 2; -1 0]; x = rand(2, 1); We want to compute the largest eigenvalue for A. repeat x = y / y.norm(); y = A * x; end

// We want to compute the largest eigenvalue for A.
// repeat x = y / y.norm(); y = A * x; end
GraphDef CreateGraphDef() {
  // TODO(jeff,opensource): This should really be a more interesting
  // computation.  Maybe turn this into an mnist model instead?
  Scope root = Scope::NewRootScope();
  using namespace ::tensorflow::ops;  // NOLINT(build/namespaces)

  // A = [3 2; -1 0].  Using Const<float> means the result will be a
  // float tensor even though the initializer has integers.
  auto a = Const<float>(root, {{3, 2}, {-1, 0}});

  // x = [1.0; 1.0]
  auto x = Const(root.WithOpName("x"), {{1.f}, {1.f}});

  // y = A * x
  auto y = MatMul(root.WithOpName("y"), a, x);

  // y2 = y.^2
  auto y2 = Square(root, y);

  // y2_sum = sum(y2).  Note that you can pass constants directly as
  // inputs.  Sum() will automatically create a Const node to hold the
  // 0 value.
  auto y2_sum = Sum(root, y2, 0);

  // y_norm = sqrt(y2_sum)
  auto y_norm = Sqrt(root, y2_sum);

  // y_normalized = y ./ y_norm
  Div(root.WithOpName("y_normalized"), y, y_norm);

  GraphDef def;
  TF_CHECK_OK(root.ToGraphDef(&def));

  return def;
}

string DebugString(const Tensor& x, const Tensor& y) {
  CHECK_EQ(x.NumElements(), 2);