| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // See LICENSE file in the project root for full license information. |
| // |
| #include "DriverTestHelpers.hpp" |
| #include <boost/test/unit_test.hpp> |
| #include <log/log.h> |
| |
| #include "OperationsUtils.h" |
| |
| BOOST_AUTO_TEST_SUITE(Convolution2DTests) |
| |
| using ArmnnDriver = armnn_driver::ArmnnDriver; |
| using DriverOptions = armnn_driver::DriverOptions; |
| using namespace driverTestHelpers; |
| |
| namespace |
| { |
| |
| void PaddingTestImpl(android::nn::PaddingScheme paddingScheme) |
| { |
| auto driver = std::make_unique<ArmnnDriver>(DriverOptions(armnn::Compute::CpuRef)); |
| Model model = {}; |
| |
| uint32_t outSize = paddingScheme == android::nn::kPaddingSame ? 2 : 1; |
| |
| // add operands |
| float weightValue[] = {1, -1, 0, 1}; |
| float biasValue[] = {0}; |
| |
| AddInputOperand(model, hidl_vec<uint32_t>{1, 2, 3, 1}); |
| AddTensorOperand(model, hidl_vec<uint32_t>{1, 2, 2, 1}, weightValue); |
| AddTensorOperand(model, hidl_vec<uint32_t>{1}, biasValue); |
| AddIntOperand(model, (int32_t)paddingScheme); // padding |
| AddIntOperand(model, 2); // stride x |
| AddIntOperand(model, 2); // stride y |
| AddIntOperand(model, 0); // no activation |
| AddOutputOperand(model, hidl_vec<uint32_t>{1, 1, outSize, 1}); |
| |
| // make the convolution operation |
| model.operations.resize(1); |
| model.operations[0].type = OperationType::CONV_2D; |
| model.operations[0].inputs = hidl_vec<uint32_t>{0, 1, 2, 3, 4, 5, 6}; |
| model.operations[0].outputs = hidl_vec<uint32_t>{7}; |
| |
| // make the prepared model |
| android::sp<IPreparedModel> preparedModel = PrepareModel(model, *driver); |
| |
| // construct the request |
| DataLocation inloc = {}; |
| inloc.poolIndex = 0; |
| inloc.offset = 0; |
| inloc.length = 6 * sizeof(float); |
| RequestArgument input = {}; |
| input.location = inloc; |
| input.dimensions = hidl_vec<uint32_t>{}; |
| |
| DataLocation outloc = {}; |
| outloc.poolIndex = 1; |
| outloc.offset = 0; |
| outloc.length = outSize * sizeof(float); |
| RequestArgument output = {}; |
| output.location = outloc; |
| output.dimensions = hidl_vec<uint32_t>{}; |
| |
| Request request = {}; |
| request.inputs = hidl_vec<RequestArgument>{input}; |
| request.outputs = hidl_vec<RequestArgument>{output}; |
| |
| |
| // set the input data (matching source test) |
| float indata[] = {4, 1, 0, 3, -1, 2}; |
| AddPoolAndSetData(6, request, indata); |
| |
| // add memory for the output |
| android::sp<IMemory> outMemory = AddPoolAndGetData(outSize, request); |
| float* outdata = static_cast<float*>(static_cast<void*>(outMemory->getPointer())); |
| |
| // run the execution |
| Execute(preparedModel, request); |
| |
| // check the result |
| if (paddingScheme == android::nn::kPaddingValid) |
| { |
| BOOST_TEST(outdata[0] == 2); |
| } |
| else if (paddingScheme == android::nn::kPaddingSame) |
| { |
| BOOST_TEST(outdata[0] == 2); |
| BOOST_TEST(outdata[1] == 0); |
| } |
| else |
| { |
| BOOST_TEST(false); |
| } |
| } |
| |
| } // namespace <anonymous> |
| |
| BOOST_AUTO_TEST_CASE(ConvValidPadding) |
| { |
| PaddingTestImpl(android::nn::kPaddingValid); |
| } |
| |
| BOOST_AUTO_TEST_CASE(ConvSamePadding) |
| { |
| PaddingTestImpl(android::nn::kPaddingSame); |
| } |
| |
| BOOST_AUTO_TEST_SUITE_END() |