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