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chore: import upstream snapshot with attribution

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wehub-resource-sync
2026-07-13 13:33:03 +08:00
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benchmark/exprModels/SqueezeNetExpr.cpp
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//
// SqueezeNetExpr.cpp
// MNN
// Reference paper: https://arxiv.org/pdf/1602.07360.pdf
//
// Created by MNN on 2019/06/25.
// Copyright © 2018, Alibaba Group Holding Limited
//
#include "SqueezeNetExpr.hpp"
#include <MNN/expr/ExprCreator.hpp>
using namespace MNN::Express;
// fire module in squeezeNet model
static VARP fireMoudle(VARP x, int inputChannel, int squeeze_1x1,
int expand_1x1, int expand_3x3) {
x = _Conv(0.0f, 0.0f, x, {inputChannel, squeeze_1x1}, {1, 1}, VALID, {1, 1}, {1, 1}, 1);
auto y1 = _Conv(0.0f, 0.0f, x, {squeeze_1x1, expand_1x1}, {1, 1}, VALID, {1, 1}, {1, 1}, 1);
auto y2 = _Conv(0.0f, 0.0f, x, {squeeze_1x1, expand_3x3}, {3, 3}, SAME, {1, 1}, {1, 1}, 1);
return _Concat({y1, y2}, 1); // concat on channel axis (NCHW)
}
VARP squeezeNetExpr(int numClass) {
auto x = _Input({1, 3, 224, 224}, NC4HW4);
x = _Conv(0.0f, 0.0f, x, {3, 96}, {7, 7}, SAME, {2, 2}, {1, 1}, 1);
x = _MaxPool(x, {3, 3}, {2, 2}, SAME);
x = fireMoudle(x, 96, 16, 64, 64);
x = fireMoudle(x, 128, 16, 64, 64);
x = fireMoudle(x, 128, 32, 128, 128);
x = _MaxPool(x, {3, 3}, {2, 2}, SAME);
x = fireMoudle(x, 256, 32, 128, 128);
x = fireMoudle(x, 256, 48, 192, 192);
x = fireMoudle(x, 384, 48, 192, 192);
x = fireMoudle(x, 384, 64, 256, 256);
x = _MaxPool(x, {3, 3}, {2, 2}, SAME);
x = fireMoudle(x, 512, 64, 256, 256);
x = _Conv(0.0f, 0.0f, x, {512, numClass}, {1, 1}, VALID, {1, 1}, {1, 1}, 1);
x = _AvePool(x, {14, 14}, {1, 1}, VALID);
return x;
}