mirror of https://github.com/alibaba/MNN.git
77 lines
3.5 KiB
C++
77 lines
3.5 KiB
C++
//
|
|
// BatchToSpaceNDTest.cpp
|
|
// MNNTests
|
|
//
|
|
// Created by MNN on 2019/01/15.
|
|
// Copyright © 2018, Alibaba Group Holding Limited
|
|
//
|
|
|
|
#include <MNN/expr/Expr.hpp>
|
|
#include <MNN/expr/ExprCreator.hpp>
|
|
#include "MNNTestSuite.h"
|
|
#include "TestUtils.h"
|
|
|
|
using namespace MNN::Express;
|
|
class BatchToSpaceNDTest : public MNNTestCase {
|
|
public:
|
|
virtual ~BatchToSpaceNDTest() = default;
|
|
virtual bool run(int precision) {
|
|
auto input = _Input({4, 1, 1, 3}, NHWC);
|
|
input->setName("input_tensor");
|
|
// set input data
|
|
const float inpudata[] = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0};
|
|
auto inputPtr = input->writeMap<float>();
|
|
memcpy(inputPtr, inpudata, 12 * sizeof(float));
|
|
input->unMap();
|
|
const int blockshapedata[] = {2, 2};
|
|
const int cropsdata[] = {0, 0, 0, 0};
|
|
auto block_shape = _Const(blockshapedata,
|
|
{
|
|
2,
|
|
},
|
|
NCHW, halide_type_of<int>());
|
|
auto crops = _Const(cropsdata, {2, 2}, NCHW, halide_type_of<int>());
|
|
input = _Convert(input, NC4HW4);
|
|
if (false) {
|
|
auto inputPtr2 = input->readMap<float>();
|
|
const std::vector<float> expectedOutput = {1.0f, 2.0f, 3.0f, 0.0f, 4.0f, 5.0f, 6.0f, 0.0f,
|
|
7.0f, 8.0f, 9.0f, 0.0f, 10.0f, 11.0f, 12.0f, 0.0f};
|
|
if (!checkVector<float>(inputPtr2, expectedOutput.data(), expectedOutput.size(), 0.01)) {
|
|
MNN_ERROR("BatchToSpaceNDTest test failed!\n");
|
|
for (int i = 0; i < expectedOutput.size(); ++i) {
|
|
MNN_PRINT("Correct: %f - Compute: %f\n", expectedOutput[i], inputPtr2[i]);
|
|
}
|
|
return false;
|
|
}
|
|
}
|
|
// 1 input and 2 params
|
|
auto tmp = _BatchToSpaceND(input, block_shape, crops);
|
|
auto output = _Convert(tmp, NHWC);
|
|
// 3 inputs and 1 param
|
|
std::unique_ptr<MNN::OpT> op(new MNN::OpT);
|
|
op->type = MNN::OpType_BatchToSpaceND;
|
|
auto _tmp = Variable::create(Expr::create(std::move(op), {input, block_shape, crops}));
|
|
auto _output = _Convert(tmp, NHWC);
|
|
auto checkOutput = [](VARP output) {
|
|
const std::vector<float> expectedOutput = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0};
|
|
auto gotOutput = output->readMap<float>();
|
|
if (!checkVector<float>(gotOutput, expectedOutput.data(), 12, 0.01)) {
|
|
MNN_ERROR("BatchToSpaceNDTest test failed!\n");
|
|
for (int i = 0; i < 12; ++i) {
|
|
MNN_PRINT("Correct: %f - Compute: %f\n", expectedOutput[i], gotOutput[i]);
|
|
}
|
|
return false;
|
|
}
|
|
const std::vector<int> expectedDims = {1, 2, 2, 3};
|
|
auto gotDims = output->getInfo()->dim;
|
|
if (!checkVector<int>(gotDims.data(), expectedDims.data(), 4, 0)) {
|
|
MNN_ERROR("BatchToSpaceNDTest test failed!\n");
|
|
return false;
|
|
}
|
|
return true;
|
|
};
|
|
return checkOutput(output) && checkOutput(_output);
|
|
}
|
|
};
|
|
MNNTestSuiteRegister(BatchToSpaceNDTest, "op/batch_to_space_nd");
|