chore: import upstream snapshot with attribution
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//
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// TransposeSpeed.cpp
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// MNNTests
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//
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// Created by MNN on 2020/09/27.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include <math.h>
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#include <MNN/expr/Expr.hpp>
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#include <MNN/expr/ExprCreator.hpp>
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#include <random>
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#define MNN_OPEN_TIME_TRACE
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#include <MNN/AutoTime.hpp>
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#include "MNNTestSuite.h"
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using namespace MNN::Express;
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#define WIDTH 501
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#define HEIGHT 243
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#define TIME 100
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class TransposeSpeed : public MNNTestCase {
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public:
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void SpeedTest() {
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auto x = _Input({1, 1, HEIGHT, WIDTH}, NCHW, halide_type_of<float>());
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auto output = _Transpose(x, {0, 3, 2, 1});
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{
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AUTOTIME;
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for (int i = 0; i < TIME; ++i) {
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x->writeMap<float>();
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output->readMap<float>();
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}
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}
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}
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bool CorrectTest() {
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auto x = _Input({1, 1, HEIGHT, WIDTH}, NCHW, halide_type_of<int>());
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std::vector<int> input(WIDTH * HEIGHT);
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for (int u=0; u<HEIGHT; ++u) {
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for (int v=0; v<WIDTH; ++v) {
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input[u * WIDTH + v] = u * u - v * 2;
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}
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}
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auto xPtr = x->writeMap<int>();
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::memcpy(xPtr, input.data(), HEIGHT * WIDTH * sizeof(int));
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auto output = _Transpose(x, {0, 3, 2, 1});
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auto yPtr = output->readMap<int>();
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auto outputInfo = output->getInfo();
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MNN_PRINT("Output: %d, %d, %d, %d\n", outputInfo->dim[0], outputInfo->dim[1], outputInfo->dim[2], outputInfo->dim[3]);
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for (int u=0; u<HEIGHT; ++u) {
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for (int v=0; v<WIDTH; ++v) {
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auto correct = input[u * WIDTH + v];
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auto result = yPtr[u + v * HEIGHT];
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if (correct != result) {
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MNN_ERROR("Error for %d - %d, correct: %d, error: %d\n", u, v, correct, result);
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return false;
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}
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}
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}
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return true;
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}
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virtual bool run(int precision) {
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MNN_PRINT("Test Convert for %d, %d, x %d\n", WIDTH, HEIGHT, TIME);
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SpeedTest();
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return CorrectTest();
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}
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};
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MNNTestSuiteRegister(TransposeSpeed, "speed/Transpose");
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