mirror of https://github.com/alibaba/MNN.git
81 lines
2.8 KiB
C++
81 lines
2.8 KiB
C++
//
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// ReLU6GradTest.cpp
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// MNNTests
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//
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// Created by MNN on 2022/07/12.
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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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#include "../tools/train/source/grad/OpGrad.hpp"
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using namespace MNN;
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using namespace MNN::Express;
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class ReLU6GradTest : public MNNTestCase {
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public:
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char name[20] = "ReLU6";
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virtual ~ReLU6GradTest() = default;
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virtual bool run(int precision) {
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{
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const int len = 4;
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auto input = _Input({len}, NCHW);
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const float inpudata[] = {-1.0, -2.0, 3.0, 6.0};
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auto inputPtr = input->writeMap<float>();
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memcpy(inputPtr, inpudata, len * sizeof(float));
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auto output = _Relu6(input);
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auto opExpr = output->expr().first;
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auto grad = OpGrad::get(opExpr->get()->type());
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float outputDiff[] = {0.1, -0.2, -0.3, 0.4};
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auto inputGrad = grad->onGrad(opExpr, {_Const(outputDiff, {len})});
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const std::vector<float> expectedOutput = {0.0f, 0.0f, -0.3f, 0.0f};
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auto gotOutput = inputGrad[0]->readMap<float>();
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for (int i = 0; i < len; ++i) {
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auto diff = ::fabsf(gotOutput[i] - expectedOutput[i]);
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if (diff > 0.000001) {
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MNN_ERROR("%s grad test failed, expected: %f, but got: %f!\n", name, expectedOutput[i], gotOutput[i]);
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return false;
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}
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}
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}
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{
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float minValue = -3.0f;
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float maxValue = 1.0f;
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const int len = 4;
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auto input = _Input({len}, NCHW);
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const float inpudata[] = {-1.0f, -2.0f, 3.0f, 6.0f};
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auto inputPtr = input->writeMap<float>();
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memcpy(inputPtr, inpudata, len * sizeof(float));
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auto output = _Relu6(input, minValue, maxValue);
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auto opExpr = output->expr().first;
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auto grad = OpGrad::get(opExpr->get()->type());
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float outputDiff[] = {0.1f, -0.2f, -0.3f, 0.4f};
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auto inputGrad = grad->onGrad(opExpr, {_Const(outputDiff, {len})});
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const std::vector<float> expectedOutput = {0.1f, -0.2f, 0.0f, 0.0f};
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auto gotOutput = inputGrad[0]->readMap<float>();
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for (int i = 0; i < len; ++i) {
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auto diff = ::fabsf(gotOutput[i] - expectedOutput[i]);
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if (diff > 0.000001) {
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MNN_ERROR("%f-%f, %s grad test failed, expected: %f, but got: %f!\n", minValue, maxValue, name, expectedOutput[i], gotOutput[i]);
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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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};
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MNNTestSuiteRegister(ReLU6GradTest, "grad/relu6");
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