mirror of https://github.com/alibaba/MNN.git
63 lines
2.1 KiB
C++
63 lines
2.1 KiB
C++
//
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// ScaleTest.cpp
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// MNNTests
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//
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// Created by MNN on 2021/10/22.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include <MNN/expr/Expr.hpp>
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#include <MNN/expr/ExprCreator.hpp>
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#include "MNNTestSuite.h"
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#include "TestUtils.h"
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using namespace MNN::Express;
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class ScaleTest : public MNNTestCase {
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public:
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virtual ~ScaleTest() = default;
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virtual bool run(int precision) {
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auto input = _Input({1, 2, 2, 1}, NCHW);
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// set input data
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const float inpudata[] = {-1.0, -2.0, 3.0, 4.0};
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auto inputPtr = input->writeMap<float>();
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memcpy(inputPtr, inpudata, 4 * sizeof(float));
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input = _Convert(input, NC4HW4);
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auto output = _Scale(input, 2, {2.0, 1.0}, {3.0, 4.0});
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output = _Convert(output, NCHW);
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const std::vector<float> expectedOutput = {1, -1, 7, 8};
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auto gotOutput = output->readMap<float>();
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if (!checkVector<float>(gotOutput, expectedOutput.data(), 4, 1e-5)) {
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MNN_ERROR("ScaleTest test failed!\n");
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return false;
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}
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return true;
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}
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};
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class ScaleInt8Test : public MNNTestCase {
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public:
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virtual ~ScaleInt8Test() = default;
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virtual bool run(int precision) {
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auto input = _Input({1, 2, 2, 1}, NCHW);
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input->writeScaleMap(0.0313725, 1.f);
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// set input data
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const float inpudata[] = {-1.0, -2.0, 3.0, 4.0};
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auto inputPtr = input->writeMap<float>();
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memcpy(inputPtr, inpudata, 4 * sizeof(float));
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input = _Convert(input, NC4HW4);
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auto output = _Scale(input, 2, {2.0, 1.0}, {3.0, 4.0});
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output = _Convert(output, NCHW);
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output->writeScaleMap(0.0628, 1.f);
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const std::vector<float> expectedOutput = {1, -1, 7, 8};
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auto gotOutput = output->readMap<float>();
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if (!checkVector<float>(gotOutput, expectedOutput.data(), 4, 1e-1)) {
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MNN_ERROR("ScaleTestInt8 test failed!\n");
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return false;
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}
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return true;
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}
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};
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MNNTestSuiteRegister(ScaleTest, "op/scale");
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MNNTestSuiteRegister(ScaleInt8Test, "op/scaleInt8");
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