OpenVINO Model Pass

ov::pass::ModelPass is used for transformations that take entire ov::Model as an input and process it.

Template for ModelPass transformation class

// template_model_transformation.hpp
class ov::pass::MyModelTransformation : public ov::pass::ModelPass {
public:
    OPENVINO_RTTI("MyModelTransformation", "0");
    bool run_on_model(const std::shared_ptr<ov::Model>& f) override;
};
// template_function_transformation.cpp

bool ov::pass::MyModelTransformation::run_on_model(const std::shared_ptr<ov::Model>& f) {
    RUN_ON_MODEL_SCOPE(MyModelTransformation);
    // Example transformation code
    NodeVector nodes;

    // Traverse nGraph Function in topological order
    for (auto& node : f->get_ordered_ops()) {
        // Check that number of input and output ports are equal to 1
        if (node->inputs().size() == 1 && node->outputs().size() == 1) {
            // Check that input and output shape a fully defined (not dynamic) and number of consumers equal to 1
            Input<Node> input = node->input(0);
            Output<Node> output = node->output(0);
            if (input.get_partial_shape().is_static() && output.get_partial_shape().is_static() &&
                output.get_target_inputs().size() == 1) {
                nodes.push_back(node);
            }
        }
    }

    // Print types and names for collected nodes
    for (auto& node : nodes) {
        std::cout << "Type: " << node->get_type_info().name << std::endl
                  << "Name: " << node->get_friendly_name() << std::endl;
    }

    // Return false because we didn't change nGraph Function
    return false;
}

Using ov::pass::ModelPass, you need to override the run_on_model method where you will write the transformation code. Return value is true if the original model has changed during transformation (new operation was added, or operations replacement was made, or node attributes were changed); otherwise, it is false. Also ov::pass::ModelPass based transformations can be executed via ov::pass::Manager.