wehub-resource-sync
120 lines
5.1 KiB
C++
120 lines
5.1 KiB
C++
//
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// mobileNetExpr.cpp
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// MNN
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// Reference paper: https://arxiv.org/pdf/1704.04861.pdf https://arxiv.org/pdf/1801.04381.pdf
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//
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// Created by MNN on 2019/06/25.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include <map>
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#include "MobileNetExpr.hpp"
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#include <MNN/expr/ExprCreator.hpp>
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using namespace MNN::Express;
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// When we use MNNConverter to convert other mobilenet model to MNN model,
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// {Conv3x3Depthwise + BN + Relu + Conv1x1 + BN + Relu} will be converted
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// and optimized to {Conv3x3Depthwise + Conv1x1}
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static VARP convBlock(VARP x, INTS channels, int stride) {
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int inputChannel = channels[0], outputChannel = channels[1];
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int group = inputChannel;
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x = _Conv(0.0f, 0.0f, x, {inputChannel, inputChannel}, {3, 3}, SAME, {stride, stride}, {1, 1}, group);
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x = _Conv(0.0f, 0.0f, x, {inputChannel, outputChannel}, {1, 1}, SAME, {1, 1}, {1, 1}, 1);
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return x;
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}
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VARP mobileNetV1Expr(MobileNetWidthType alpha, MobileNetResolutionType beta, int numClass) {
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int inputSize, poolSize; // MobileNet_224, MobileNet_192, MobileNet_160, MobileNet_128
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{
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auto inputSizeMap = std::map<MobileNetResolutionType, int>({
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{MobileNet_224, 224},
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{MobileNet_192, 192},
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{MobileNet_160, 160},
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{MobileNet_128, 128}
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});
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if (inputSizeMap.find(beta) == inputSizeMap.end()) {
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MNN_ERROR("MobileNetResolutionType (%d) not support, only support [MobileNet_224, MobileNet_192, MobileNet_160, MobileNet_128]\n", beta);
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return VARP(nullptr);
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}
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inputSize = inputSizeMap[beta];
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poolSize = inputSize / 32;
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}
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int channels[6]; // MobileNet_100, MobileNet_075, MobileNet_050, MobileNet_025
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{
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auto channelsMap = std::map<MobileNetWidthType, int>({
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{MobileNet_100, 32},
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{MobileNet_075, 24},
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{MobileNet_050, 16},
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{MobileNet_025, 8}
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});
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if (channelsMap.find(alpha) == channelsMap.end()) {
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MNN_ERROR("MobileNetWidthType (%d) not support, only support [MobileNet_100, MobileNet_075, MobileNet_050, MobileNet_025]\n", alpha);
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return VARP(nullptr);
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}
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channels[0] = channelsMap[alpha];
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}
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for (int i = 1; i < 6; ++i) {
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channels[i] = channels[0] * (1 << i);
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}
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auto x = _Input({1, 3, inputSize, inputSize}, NC4HW4);
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x = _Conv(0.0f, 0.0f, x, {3, channels[0]}, {3, 3}, SAME, {2, 2}, {1, 1}, 1);
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x = convBlock(x, {channels[0], channels[1]}, 1);
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x = convBlock(x, {channels[1], channels[2]}, 2);
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x = convBlock(x, {channels[2], channels[2]}, 1);
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x = convBlock(x, {channels[2], channels[3]}, 2);
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x = convBlock(x, {channels[3], channels[3]}, 1);
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x = convBlock(x, {channels[3], channels[4]}, 2);
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x = convBlock(x, {channels[4], channels[4]}, 1);
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x = convBlock(x, {channels[4], channels[4]}, 1);
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x = convBlock(x, {channels[4], channels[4]}, 1);
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x = convBlock(x, {channels[4], channels[4]}, 1);
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x = convBlock(x, {channels[4], channels[4]}, 1);
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x = convBlock(x, {channels[4], channels[5]}, 2);
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x = convBlock(x, {channels[5], channels[5]}, 1);
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x = _AvePool(x, {poolSize, poolSize}, {1, 1}, VALID);
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x = _Conv(0.0f, 0.0f, x, {channels[5], numClass}, {1, 1}, VALID, {1, 1}, {1, 1}, 1); // reshape FC with Conv1x1
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x = _Softmax(x, -1);
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return x;
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}
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static VARP bottleNeck(VARP x, INTS channels, int stride, int expansionRatio) {
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int inputChannel = channels[0], outputChannel = channels[1];
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int expansionChannel = inputChannel * expansionRatio, group = expansionChannel;
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auto y = _Conv(0.0f, 0.0f, x, {inputChannel, expansionChannel}, {1, 1}, VALID, {1, 1}, {1, 1}, 1);
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y = _Conv(0.0f, 0.0f, y, {expansionChannel, expansionChannel}, {3, 3}, SAME, {stride, stride}, {1, 1}, group);
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y = _Conv(0.0f, 0.0f, y, {expansionChannel, outputChannel}, {1, 1}, VALID, {1, 1}, {1, 1}, 1);
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if (inputChannel != outputChannel || stride != 1) {
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x = _Conv(0.0f, 0.0f, x, {inputChannel, outputChannel}, {1, 1}, SAME, {stride, stride}, {1, 1}, 1);
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}
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y = _Add(x, y);
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return y;
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}
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static VARP bottleNeckBlock(VARP x, INTS channels, int stride, int expansionRatio, int number) {
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x = bottleNeck(x, {channels[0], channels[1]}, stride, expansionRatio);
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for (int i = 1; i < number; ++i) {
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x = bottleNeck(x, {channels[1], channels[1]}, 1, expansionRatio);
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}
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return x;
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}
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VARP mobileNetV2Expr(int numClass) {
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auto x = _Input({1, 3, 224, 224}, NC4HW4);
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x = _Conv(0.0f, 0.0f, x, {3, 32}, {3, 3}, SAME, {2, 2}, {1, 1}, 1);
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x = bottleNeckBlock(x, {32, 16}, 1, 1, 1);
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x = bottleNeckBlock(x, {16, 24}, 2, 6, 2);
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x = bottleNeckBlock(x, {24, 32}, 2, 6, 3);
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x = bottleNeckBlock(x, {32, 64}, 2, 6, 4);
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x = bottleNeckBlock(x, {64, 96}, 1, 6, 3);
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x = bottleNeckBlock(x, {96, 160}, 2, 6, 3);
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x = bottleNeckBlock(x, {160, 320}, 1, 6, 1);
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x = _Conv(0.0f, 0.0f, x, {320, 1280}, {1, 1}, VALID, {1, 1}, {1, 1}, 1);
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x = _AvePool(x, {7, 7}, {1, 1}, VALID);
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x = _Conv(0.0f, 0.0f, x, {1280, numClass}, {1, 1}, VALID, {1, 1}, {1, 1}, 1); // reshape FC with Conv1x1
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return x;
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}
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