| 28 | } |
| 29 | |
| 30 | VARP _mobileNetV1Expr() { |
| 31 | int inputSize = 224, poolSize; // MobileNet_224, MobileNet_192, MobileNet_160, MobileNet_128 |
| 32 | { |
| 33 | inputSize = 224; |
| 34 | poolSize = inputSize / 32; |
| 35 | } |
| 36 | |
| 37 | int channels[6]; // MobileNet_100, MobileNet_075, MobileNet_050, MobileNet_025 |
| 38 | { channels[0] = 32; } |
| 39 | |
| 40 | for (int i = 1; i < 6; ++i) { |
| 41 | channels[i] = channels[0] * (1 << i); |
| 42 | } |
| 43 | |
| 44 | auto x = _Input({1, 3, inputSize, inputSize}, NC4HW4); |
| 45 | x = _Conv(0.0f, 0.0f, x, {3, channels[0]}, {3, 3}, SAME, {2, 2}, {1, 1}, 1); |
| 46 | x = convBlock(x, {channels[0], channels[1]}, 1); |
| 47 | x = convBlock(x, {channels[1], channels[2]}, 2); |
| 48 | x = convBlock(x, {channels[2], channels[2]}, 1); |
| 49 | x = convBlock(x, {channels[2], channels[3]}, 2); |
| 50 | x = convBlock(x, {channels[3], channels[3]}, 1); |
| 51 | x = convBlock(x, {channels[3], channels[4]}, 2); |
| 52 | x = convBlock(x, {channels[4], channels[4]}, 1); |
| 53 | x = convBlock(x, {channels[4], channels[4]}, 1); |
| 54 | x = convBlock(x, {channels[4], channels[4]}, 1); |
| 55 | x = convBlock(x, {channels[4], channels[4]}, 1); |
| 56 | x = convBlock(x, {channels[4], channels[4]}, 1); |
| 57 | x = convBlock(x, {channels[4], channels[5]}, 2); |
| 58 | x = convBlock(x, {channels[5], channels[5]}, 1); |
| 59 | x = _AvePool(x, {poolSize, poolSize}, {1, 1}, VALID); |
| 60 | x = _Conv(0.0f, 0.0f, x, {channels[5], 1001}, {1, 1}, VALID, {1, 1}, {1, 1}, 1); // reshape FC with Conv1x1 |
| 61 | x = _Softmax(x, -1); |
| 62 | return x; |
| 63 | } |
| 64 | class MemoryIncreaseMobileNetV1Test : public MNNTestCase { |
| 65 | public: |
| 66 | virtual bool run(int precision) { |