// // SpaceToBatchNDTest.cpp // MNNTests // // Created by MNN on 2019/01/15. // Copyright © 2018, Alibaba Group Holding Limited // #include #include #include "MNNTestSuite.h" #include "TestUtils.h" using namespace MNN::Express; class SpaceToBatchNDTest : public MNNTestCase { public: virtual ~SpaceToBatchNDTest() = default; virtual bool run(int precision) { auto input = _Input({3, 1, 2, 2}, NCHW); 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(); memcpy(inputPtr, inpudata, 12 * sizeof(float)); input->unMap(); const int blockshapedata[] = {2, 2}; const int paddingdata[] = {0, 0, 0, 0}; auto block_shape = _Const(blockshapedata, { 2, }, NCHW, halide_type_of()); auto paddings = _Const(paddingdata, {2, 2}, NCHW, halide_type_of()); input = _Convert(input, NC4HW4); // 1 input and 2 params auto tmp = _SpaceToBatchND(input, block_shape, paddings); auto output = _Convert(tmp, NCHW); // 3 inputs and 0 param std::unique_ptr op(new MNN::OpT); op->type = MNN::OpType_SpaceToBatchND; auto _tmp = Variable::create(Expr::create(std::move(op), {input, block_shape, paddings})); auto _output = _Convert(_tmp, NCHW); auto checkOutput = [](VARP output) { const std::vector expectedOutput = {1.0, 5.0, 9.0, 2.0, 6.0, 10.0, 3.0, 7.0, 11.0, 4.0, 8.0, 12.0}; auto gotOutput = output->readMap(); if (!checkVector(gotOutput, expectedOutput.data(), 12, 0.01)) { MNN_ERROR("SpaceToBatchNDTest test failed!\n"); return false; } const std::vector expectedDims = {12, 1, 1, 1}; auto gotDims = output->getInfo()->dim; if (!checkVector(gotDims.data(), expectedDims.data(), 4, 0)) { MNN_ERROR("SpaceToBatchNDTest test failed!\n"); return false; } return true; }; return checkOutput(output) && checkOutput(_output); } }; MNNTestSuiteRegister(SpaceToBatchNDTest, "op/space_to_batch_nd");