MNN/test/op/InnerProductTest.cpp

68 lines
2.9 KiB
C++

//
// InnerProductTest.cpp
// MNNTests
//
// Created by MNN on 2020/07/16.
// Copyright © 2018, Alibaba Group Holding Limited
//
#include <MNN/expr/Expr.hpp>
#include <MNN/expr/ExprCreator.hpp>
#include <string>
#include <vector>
#include "MNNTestSuite.h"
#include "TestUtils.h"
using namespace MNN::Express;
class InnerProductTest : public MNNTestCase {
public:
virtual ~InnerProductTest() = default;
virtual bool run(int precision) {
int batch = 1;
int outputChannel = 2;
auto input = _Input({batch, 4 * 2 * 3}, NCHW, halide_type_of<float>());
std::vector<float> inputData = {// inputChannel 0
1.0, 2.0, 3.0, 4.0, 5.0, 6.0,
// inputChannel 1
1.1, 2.1, 3.1, 4.1, 5.1, 6.1,
// inputChannel 2
1.2, 2.2, 3.2, 4.2, 5.2, 6.2,
// inputChannel 3
1.3, 2.3, 3.3, 4.3, 5.3, 6.3};
std::vector<float> weightData = {/* outputChannel 0*/
// inputChannel 0
1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
// inputChannel 1
1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
// inputChannel 2
1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
// inputChannel 3
1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
/* outputChannel 1*/
// inputChannel 0
4.3, 1.3, 6.3, 0.0, -2.3, 3.3,
// inputChannel 1
-4.0, 5.0, 6.0, 1.0, 2.0, 3.0,
// inputChannel 2
4.1, 5.1, 6.1, 1.1, 2.1, 3.1,
// inputChannel 3
4.2, 5.2, -6.2, 1.2, 2.2, 0.2};
std::vector<float> biasData = {1.0, 0.0};
std::vector<float> outputData = {88.6, 176.86};
INTS outputShape = {batch, outputChannel};
::memcpy(input->writeMap<float>(), inputData.data(), inputData.size() * sizeof(float));
auto output = _InnerProduct(std::move(weightData), std::move(biasData), input, outputShape);
auto outPtr = output->readMap<float>();
if (!checkVectorByRelativeError<float>(outPtr, outputData.data(), outputData.size(), 0.005)) {
MNN_ERROR("InnerProductTest test failed!\n");
return false;
}
return true;
}
};
MNNTestSuiteRegister(InnerProductTest, "op/InnerProduct");