/* // Copyright (c) 2017 Intel Corporation // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. */ #include <../api/CPP/cldnn_defs.h> #include <../api/CPP/engine.hpp> #include <../api/CPP/input_layout.hpp> #include <../api/CPP/memory.hpp> #include <../api/CPP/data.hpp> #include <../api/CPP/topology.hpp> #include <../api/CPP/network.hpp> #include <iostream> #include "helper_functions.h" /*! @page c3 Network and execution. * @section intro Introduction * In this chapter we will explain how to create and execute network. * * @include chapter_3.cpp * */ using namespace cldnn; void chapter_3(engine& engine, topology& topology) { std::cout << std::endl << "-- Chapter 3 --" << std::endl; // Since we have topology and engine, we are ready to create network. Network is compiled graph/topology. During network creation // all kernels are compiled and memory is allocated. network network(engine, topology); // We are almost ready to go. Need to create and set input for network: memory input_mem = memory::allocate(engine, { data_types::f32, format::bfyx,{ 1, 1, 3, 1 } }); set_values(input_mem, { -3.0f, -2.0f, 2.5f }); // Set input network.set_input_data("input", input_mem); // Ready to go: auto outputs = network.execute(); for (auto it : outputs) { // Print primtive info for all outputs. std::cout << network.get_primitive_info(it.first) << std::endl; // OUTPUT: // id: fc, type : fully connected // input : softmax, count : 3, size : [b:1, f : 1, x : 3, y : 1] // weights id : fc_weights, count : 9, bias id : fc_bias, count : 3 // with activation : false // output padding lower size : [b:0, f : 0, x : 0, y : 0] // output padding upper size : [b:0, f : 0, x : 0, y : 0] // output : count : 3, size : [b:1, f : 1, x : 3, y : 1] auto mem_pointer = it.second.get_memory().pointer<float>(); for (auto i : mem_pointer) { std::cout << i << " "; } std::cout << std::endl; // As you probably noticed network output is a result of the last one primitive "fc". By the last one we mean, the one that // is not input to any other primitive. } // What if someone may want to look into intermediate results (hidden layers). This will be described in next chapter (4). }