Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2017 Arm Ltd. All rights reserved. |
| 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #include <armnn/ArmNN.hpp> |
| 7 | #include <armnn/INetwork.hpp> |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 8 | |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 9 | #include "../Serializer.hpp" |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 10 | |
Derek Lamberti | 0028d1b | 2019-02-20 13:57:42 +0000 | [diff] [blame] | 11 | #include <armnnDeserializer/IDeserializer.hpp> |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 12 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 13 | #include <random> |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 14 | #include <sstream> |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 15 | #include <vector> |
| 16 | |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 17 | #include <boost/test/unit_test.hpp> |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 18 | #include <flatbuffers/idl.h> |
| 19 | |
Derek Lamberti | 0028d1b | 2019-02-20 13:57:42 +0000 | [diff] [blame] | 20 | using armnnDeserializer::IDeserializer; |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 21 | |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 22 | namespace |
| 23 | { |
| 24 | |
| 25 | armnn::INetworkPtr DeserializeNetwork(const std::string& serializerString) |
| 26 | { |
| 27 | std::vector<std::uint8_t> const serializerVector{serializerString.begin(), serializerString.end()}; |
Derek Lamberti | 0028d1b | 2019-02-20 13:57:42 +0000 | [diff] [blame] | 28 | return IDeserializer::Create()->CreateNetworkFromBinary(serializerVector); |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 29 | } |
| 30 | |
| 31 | std::string SerializeNetwork(const armnn::INetwork& network) |
| 32 | { |
| 33 | armnnSerializer::Serializer serializer; |
| 34 | serializer.Serialize(network); |
| 35 | |
| 36 | std::stringstream stream; |
| 37 | serializer.SaveSerializedToStream(stream); |
| 38 | |
| 39 | std::string serializerString{stream.str()}; |
| 40 | return serializerString; |
| 41 | } |
| 42 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 43 | template<typename DataType> |
| 44 | static std::vector<DataType> GenerateRandomData(size_t size) |
| 45 | { |
| 46 | constexpr bool isIntegerType = std::is_integral<DataType>::value; |
| 47 | using Distribution = |
| 48 | typename std::conditional<isIntegerType, |
| 49 | std::uniform_int_distribution<DataType>, |
| 50 | std::uniform_real_distribution<DataType>>::type; |
| 51 | |
| 52 | static constexpr DataType lowerLimit = std::numeric_limits<DataType>::min(); |
| 53 | static constexpr DataType upperLimit = std::numeric_limits<DataType>::max(); |
| 54 | |
| 55 | static Distribution distribution(lowerLimit, upperLimit); |
| 56 | static std::default_random_engine generator; |
| 57 | |
| 58 | std::vector<DataType> randomData(size); |
| 59 | std::generate(randomData.begin(), randomData.end(), []() { return distribution(generator); }); |
| 60 | |
| 61 | return randomData; |
| 62 | } |
| 63 | |
| 64 | void CheckDeserializedNetworkAgainstOriginal(const armnn::INetwork& deserializedNetwork, |
| 65 | const armnn::INetwork& originalNetwork, |
| 66 | const armnn::TensorShape& inputShape, |
| 67 | const armnn::TensorShape& outputShape, |
| 68 | armnn::LayerBindingId inputBindingId = 0, |
| 69 | armnn::LayerBindingId outputBindingId = 0) |
| 70 | { |
| 71 | armnn::IRuntime::CreationOptions options; |
| 72 | armnn::IRuntimePtr runtime = armnn::IRuntime::Create(options); |
| 73 | |
| 74 | std::vector<armnn::BackendId> preferredBackends = { armnn::BackendId("CpuRef") }; |
| 75 | |
| 76 | // Optimize original network |
| 77 | armnn::IOptimizedNetworkPtr optimizedOriginalNetwork = |
| 78 | armnn::Optimize(originalNetwork, preferredBackends, runtime->GetDeviceSpec()); |
| 79 | BOOST_CHECK(optimizedOriginalNetwork); |
| 80 | |
| 81 | // Optimize deserialized network |
| 82 | armnn::IOptimizedNetworkPtr optimizedDeserializedNetwork = |
| 83 | armnn::Optimize(deserializedNetwork, preferredBackends, runtime->GetDeviceSpec()); |
| 84 | BOOST_CHECK(optimizedDeserializedNetwork); |
| 85 | |
| 86 | armnn::NetworkId networkId1; |
| 87 | armnn::NetworkId networkId2; |
| 88 | |
| 89 | // Load original and deserialized network |
| 90 | armnn::Status status1 = runtime->LoadNetwork(networkId1, std::move(optimizedOriginalNetwork)); |
| 91 | BOOST_CHECK(status1 == armnn::Status::Success); |
| 92 | |
| 93 | armnn::Status status2 = runtime->LoadNetwork(networkId2, std::move(optimizedDeserializedNetwork)); |
| 94 | BOOST_CHECK(status2 == armnn::Status::Success); |
| 95 | |
| 96 | // Generate some input data |
| 97 | std::vector<float> inputData = GenerateRandomData<float>(inputShape.GetNumElements()); |
| 98 | |
| 99 | armnn::InputTensors inputTensors1 |
| 100 | { |
| 101 | { 0, armnn::ConstTensor(runtime->GetInputTensorInfo(networkId1, inputBindingId), inputData.data()) } |
| 102 | }; |
| 103 | |
| 104 | armnn::InputTensors inputTensors2 |
| 105 | { |
| 106 | { 0, armnn::ConstTensor(runtime->GetInputTensorInfo(networkId2, inputBindingId), inputData.data()) } |
| 107 | }; |
| 108 | |
| 109 | std::vector<float> outputData1(outputShape.GetNumElements()); |
| 110 | std::vector<float> outputData2(outputShape.GetNumElements()); |
| 111 | |
| 112 | armnn::OutputTensors outputTensors1 |
| 113 | { |
| 114 | { 0, armnn::Tensor(runtime->GetOutputTensorInfo(networkId1, outputBindingId), outputData1.data()) } |
| 115 | }; |
| 116 | |
| 117 | armnn::OutputTensors outputTensors2 |
| 118 | { |
| 119 | { 0, armnn::Tensor(runtime->GetOutputTensorInfo(networkId2, outputBindingId), outputData2.data()) } |
| 120 | }; |
| 121 | |
| 122 | // Run original and deserialized network |
| 123 | runtime->EnqueueWorkload(networkId1, inputTensors1, outputTensors1); |
| 124 | runtime->EnqueueWorkload(networkId2, inputTensors2, outputTensors2); |
| 125 | |
| 126 | // Compare output data |
| 127 | BOOST_CHECK_EQUAL_COLLECTIONS(outputData1.begin(), outputData1.end(), |
| 128 | outputData2.begin(), outputData2.end()); |
| 129 | } |
| 130 | |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 131 | } // anonymous namespace |
| 132 | |
| 133 | BOOST_AUTO_TEST_SUITE(SerializerTests) |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 134 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 135 | BOOST_AUTO_TEST_CASE(SerializeAddition) |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 136 | { |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 137 | class VerifyAdditionName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy> |
| 138 | { |
| 139 | public: |
| 140 | void VisitAdditionLayer(const armnn::IConnectableLayer*, const char* name) override |
| 141 | { |
| 142 | BOOST_TEST(name == "addition"); |
| 143 | } |
| 144 | }; |
| 145 | |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 146 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 147 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 148 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 149 | |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 150 | armnn::IConnectableLayer* const additionLayer = network->AddAdditionLayer("addition"); |
| 151 | inputLayer0->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(0)); |
| 152 | inputLayer1->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(1)); |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 153 | |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 154 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 155 | additionLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 156 | |
Jim Flynn | 3091b06 | 2019-02-15 14:45:04 +0000 | [diff] [blame] | 157 | armnn::TensorShape shape{1U}; |
| 158 | armnn::TensorInfo info(shape, armnn::DataType::Float32); |
| 159 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 160 | inputLayer1->GetOutputSlot(0).SetTensorInfo(info); |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 161 | additionLayer->GetOutputSlot(0).SetTensorInfo(info); |
Jim Flynn | 3091b06 | 2019-02-15 14:45:04 +0000 | [diff] [blame] | 162 | |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 163 | armnnSerializer::Serializer serializer; |
| 164 | serializer.Serialize(*network); |
| 165 | |
| 166 | std::stringstream stream; |
| 167 | serializer.SaveSerializedToStream(stream); |
| 168 | BOOST_TEST(stream.str().length() > 0); |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 169 | |
| 170 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(stream.str()); |
| 171 | BOOST_CHECK(deserializedNetwork); |
| 172 | |
| 173 | VerifyAdditionName nameChecker; |
| 174 | deserializedNetwork->Accept(nameChecker); |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 175 | } |
| 176 | |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 177 | BOOST_AUTO_TEST_CASE(SerializeConstant) |
| 178 | { |
| 179 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 180 | |
| 181 | armnn::ConstTensor inputTensor; |
| 182 | |
| 183 | armnn::IConnectableLayer* const inputLayer0 = network->AddConstantLayer(inputTensor, "constant"); |
| 184 | armnn::IConnectableLayer* const outputLayer0 = network->AddOutputLayer(0); |
| 185 | |
| 186 | inputLayer0->GetOutputSlot(0).Connect(outputLayer0->GetInputSlot(0)); |
| 187 | |
| 188 | armnnSerializer::Serializer serializer; |
| 189 | serializer.Serialize(*network); |
| 190 | |
| 191 | std::stringstream stream; |
| 192 | serializer.SaveSerializedToStream(stream); |
| 193 | BOOST_TEST(stream.str().length() > 0); |
| 194 | BOOST_TEST(stream.str().find("constant") != stream.str().npos); |
| 195 | } |
| 196 | |
| 197 | BOOST_AUTO_TEST_CASE(SerializeDeserializeConstant) |
| 198 | { |
| 199 | class VerifyConstantName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy> |
| 200 | { |
| 201 | public: |
| 202 | void VisitConstantLayer(const armnn::IConnectableLayer*, const armnn::ConstTensor&, const char* name) override |
| 203 | { |
| 204 | BOOST_TEST(name == "constant"); |
| 205 | } |
| 206 | }; |
| 207 | |
| 208 | armnn::TensorInfo commonTensorInfo({ 2, 3 }, armnn::DataType::Float32); |
| 209 | |
| 210 | std::vector<float> constantData = GenerateRandomData<float>(commonTensorInfo.GetNumElements()); |
| 211 | armnn::ConstTensor constTensor(commonTensorInfo, constantData); |
| 212 | |
| 213 | // Builds up the structure of the network. |
| 214 | armnn::INetworkPtr net(armnn::INetwork::Create()); |
| 215 | |
| 216 | armnn::IConnectableLayer* input = net->AddInputLayer(0); |
| 217 | armnn::IConnectableLayer* constant = net->AddConstantLayer(constTensor, "constant"); |
| 218 | armnn::IConnectableLayer* add = net->AddAdditionLayer(); |
| 219 | armnn::IConnectableLayer* output = net->AddOutputLayer(0); |
| 220 | |
| 221 | input->GetOutputSlot(0).Connect(add->GetInputSlot(0)); |
| 222 | constant->GetOutputSlot(0).Connect(add->GetInputSlot(1)); |
| 223 | add->GetOutputSlot(0).Connect(output->GetInputSlot(0)); |
| 224 | |
| 225 | // Sets the tensors in the network. |
| 226 | input->GetOutputSlot(0).SetTensorInfo(commonTensorInfo); |
| 227 | constant->GetOutputSlot(0).SetTensorInfo(commonTensorInfo); |
| 228 | add->GetOutputSlot(0).SetTensorInfo(commonTensorInfo); |
| 229 | |
| 230 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*net)); |
| 231 | BOOST_CHECK(deserializedNetwork); |
| 232 | |
| 233 | VerifyConstantName nameChecker; |
| 234 | deserializedNetwork->Accept(nameChecker); |
| 235 | |
| 236 | CheckDeserializedNetworkAgainstOriginal(*net, |
| 237 | *deserializedNetwork, |
| 238 | commonTensorInfo.GetShape(), |
| 239 | commonTensorInfo.GetShape()); |
| 240 | } |
| 241 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 242 | BOOST_AUTO_TEST_CASE(SerializeMultiplication) |
Sadik Armagan | 5f45027 | 2019-02-12 14:31:45 +0000 | [diff] [blame] | 243 | { |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 244 | class VerifyMultiplicationName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy> |
| 245 | { |
| 246 | public: |
| 247 | void VisitMultiplicationLayer(const armnn::IConnectableLayer*, const char* name) override |
| 248 | { |
| 249 | BOOST_TEST(name == "multiplication"); |
| 250 | } |
| 251 | }; |
| 252 | |
Sadik Armagan | 5f45027 | 2019-02-12 14:31:45 +0000 | [diff] [blame] | 253 | const armnn::TensorInfo info({ 1, 5, 2, 3 }, armnn::DataType::Float32); |
| 254 | |
| 255 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 256 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 257 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 258 | |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 259 | const char* multLayerName = "multiplication"; |
Sadik Armagan | 5f45027 | 2019-02-12 14:31:45 +0000 | [diff] [blame] | 260 | |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 261 | armnn::IConnectableLayer* const multiplicationLayer = network->AddMultiplicationLayer(multLayerName); |
| 262 | inputLayer0->GetOutputSlot(0).Connect(multiplicationLayer->GetInputSlot(0)); |
| 263 | inputLayer1->GetOutputSlot(0).Connect(multiplicationLayer->GetInputSlot(1)); |
Sadik Armagan | 5f45027 | 2019-02-12 14:31:45 +0000 | [diff] [blame] | 264 | |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 265 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 266 | multiplicationLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
Sadik Armagan | 5f45027 | 2019-02-12 14:31:45 +0000 | [diff] [blame] | 267 | |
Jim Flynn | 3091b06 | 2019-02-15 14:45:04 +0000 | [diff] [blame] | 268 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 269 | inputLayer1->GetOutputSlot(0).SetTensorInfo(info); |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 270 | multiplicationLayer->GetOutputSlot(0).SetTensorInfo(info); |
Jim Flynn | 3091b06 | 2019-02-15 14:45:04 +0000 | [diff] [blame] | 271 | |
Sadik Armagan | 5f45027 | 2019-02-12 14:31:45 +0000 | [diff] [blame] | 272 | armnnSerializer::Serializer serializer; |
| 273 | serializer.Serialize(*network); |
| 274 | |
| 275 | std::stringstream stream; |
| 276 | serializer.SaveSerializedToStream(stream); |
| 277 | BOOST_TEST(stream.str().length() > 0); |
| 278 | BOOST_TEST(stream.str().find(multLayerName) != stream.str().npos); |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 279 | |
| 280 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(stream.str()); |
| 281 | BOOST_CHECK(deserializedNetwork); |
| 282 | |
| 283 | VerifyMultiplicationName nameChecker; |
| 284 | deserializedNetwork->Accept(nameChecker); |
Sadik Armagan | 5f45027 | 2019-02-12 14:31:45 +0000 | [diff] [blame] | 285 | } |
| 286 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 287 | BOOST_AUTO_TEST_CASE(SerializeDeserializeConvolution2d) |
Saoirse Stewart | 263829c | 2019-02-19 15:54:14 +0000 | [diff] [blame] | 288 | { |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 289 | |
| 290 | class VerifyConvolution2dName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy> |
| 291 | { |
| 292 | public: |
| 293 | void VisitConvolution2dLayer(const armnn::IConnectableLayer*, |
| 294 | const armnn::Convolution2dDescriptor&, |
| 295 | const armnn::ConstTensor&, |
| 296 | const armnn::Optional<armnn::ConstTensor>&, |
| 297 | const char* name) override |
| 298 | { |
| 299 | BOOST_TEST(name == "convolution"); |
| 300 | } |
| 301 | }; |
| 302 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 303 | armnn::TensorInfo inputInfo ({ 1, 5, 5, 1 }, armnn::DataType::Float32); |
| 304 | armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32); |
Saoirse Stewart | 263829c | 2019-02-19 15:54:14 +0000 | [diff] [blame] | 305 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 306 | armnn::TensorInfo weightsInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32); |
| 307 | armnn::TensorInfo biasesInfo ({ 1 }, armnn::DataType::Float32); |
| 308 | |
| 309 | // Construct network |
| 310 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 311 | |
| 312 | armnn::Convolution2dDescriptor descriptor; |
| 313 | descriptor.m_PadLeft = 1; |
| 314 | descriptor.m_PadRight = 1; |
| 315 | descriptor.m_PadTop = 1; |
| 316 | descriptor.m_PadBottom = 1; |
| 317 | descriptor.m_StrideX = 2; |
| 318 | descriptor.m_StrideY = 2; |
| 319 | descriptor.m_BiasEnabled = true; |
| 320 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 321 | |
| 322 | std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements()); |
| 323 | armnn::ConstTensor weights(weightsInfo, weightsData); |
| 324 | |
| 325 | std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements()); |
| 326 | armnn::ConstTensor biases(biasesInfo, biasesData); |
| 327 | |
| 328 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0, "input"); |
| 329 | armnn::IConnectableLayer* const convLayer = |
| 330 | network->AddConvolution2dLayer(descriptor, weights, biases, "convolution"); |
| 331 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0, "output"); |
| 332 | |
| 333 | inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0)); |
| 334 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 335 | |
| 336 | convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 337 | convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 338 | |
| 339 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 340 | BOOST_CHECK(deserializedNetwork); |
| 341 | |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 342 | VerifyConvolution2dName nameChecker; |
| 343 | deserializedNetwork->Accept(nameChecker); |
| 344 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 345 | CheckDeserializedNetworkAgainstOriginal(*network, |
| 346 | *deserializedNetwork, |
| 347 | inputInfo.GetShape(), |
| 348 | outputInfo.GetShape()); |
| 349 | } |
| 350 | |
| 351 | BOOST_AUTO_TEST_CASE(SerializeDeserializeReshape) |
| 352 | { |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 353 | class VerifyReshapeName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy> |
| 354 | { |
| 355 | public: |
| 356 | void VisitReshapeLayer(const armnn::IConnectableLayer*, const armnn::ReshapeDescriptor&, const char* name) |
| 357 | { |
| 358 | BOOST_TEST(name == "reshape"); |
| 359 | } |
| 360 | }; |
| 361 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 362 | unsigned int inputShape[] = { 1, 9 }; |
| 363 | unsigned int outputShape[] = { 3, 3 }; |
Saoirse Stewart | 263829c | 2019-02-19 15:54:14 +0000 | [diff] [blame] | 364 | |
| 365 | auto inputTensorInfo = armnn::TensorInfo(2, inputShape, armnn::DataType::Float32); |
| 366 | auto outputTensorInfo = armnn::TensorInfo(2, outputShape, armnn::DataType::Float32); |
| 367 | auto reshapeOutputTensorInfo = armnn::TensorInfo(2, outputShape, armnn::DataType::Float32); |
| 368 | |
| 369 | armnn::ReshapeDescriptor reshapeDescriptor; |
| 370 | reshapeDescriptor.m_TargetShape = reshapeOutputTensorInfo.GetShape(); |
| 371 | |
| 372 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 373 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 374 | armnn::IConnectableLayer* const reshapeLayer = network->AddReshapeLayer(reshapeDescriptor, "reshape"); |
| 375 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
Saoirse Stewart | 263829c | 2019-02-19 15:54:14 +0000 | [diff] [blame] | 376 | |
| 377 | inputLayer->GetOutputSlot(0).Connect(reshapeLayer->GetInputSlot(0)); |
| 378 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 379 | reshapeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 380 | reshapeLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| 381 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 382 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 383 | BOOST_CHECK(deserializedNetwork); |
Saoirse Stewart | 263829c | 2019-02-19 15:54:14 +0000 | [diff] [blame] | 384 | |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 385 | VerifyReshapeName nameChecker; |
| 386 | deserializedNetwork->Accept(nameChecker); |
| 387 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 388 | CheckDeserializedNetworkAgainstOriginal(*network, |
| 389 | *deserializedNetwork, |
| 390 | inputTensorInfo.GetShape(), |
| 391 | outputTensorInfo.GetShape()); |
Saoirse Stewart | 263829c | 2019-02-19 15:54:14 +0000 | [diff] [blame] | 392 | } |
| 393 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 394 | BOOST_AUTO_TEST_CASE(SerializeDeserializeDepthwiseConvolution2d) |
| 395 | { |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 396 | class VerifyDepthwiseConvolution2dName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy> |
| 397 | { |
| 398 | public: |
| 399 | void VisitDepthwiseConvolution2dLayer(const armnn::IConnectableLayer*, |
| 400 | const armnn::DepthwiseConvolution2dDescriptor&, |
| 401 | const armnn::ConstTensor&, |
| 402 | const armnn::Optional<armnn::ConstTensor>&, |
| 403 | const char* name) override |
| 404 | { |
| 405 | BOOST_TEST(name == "depthwise_convolution"); |
| 406 | } |
| 407 | }; |
| 408 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 409 | armnn::TensorInfo inputInfo ({ 1, 5, 5, 3 }, armnn::DataType::Float32); |
| 410 | armnn::TensorInfo outputInfo({ 1, 3, 3, 3 }, armnn::DataType::Float32); |
| 411 | |
| 412 | armnn::TensorInfo weightsInfo({ 1, 3, 3, 3 }, armnn::DataType::Float32); |
| 413 | armnn::TensorInfo biasesInfo ({ 3 }, armnn::DataType::Float32); |
| 414 | |
| 415 | armnn::DepthwiseConvolution2dDescriptor descriptor; |
| 416 | descriptor.m_StrideX = 1; |
| 417 | descriptor.m_StrideY = 1; |
| 418 | descriptor.m_BiasEnabled = true; |
| 419 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 420 | |
| 421 | std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements()); |
| 422 | armnn::ConstTensor weights(weightsInfo, weightsData); |
| 423 | |
| 424 | std::vector<int32_t> biasesData = GenerateRandomData<int32_t>(biasesInfo.GetNumElements()); |
| 425 | armnn::ConstTensor biases(biasesInfo, biasesData); |
| 426 | |
| 427 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 428 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 429 | armnn::IConnectableLayer* const depthwiseConvLayer = |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 430 | network->AddDepthwiseConvolution2dLayer(descriptor, weights, biases, "depthwise_convolution"); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 431 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 432 | |
| 433 | inputLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(0)); |
| 434 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 435 | depthwiseConvLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 436 | depthwiseConvLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 437 | |
| 438 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 439 | BOOST_CHECK(deserializedNetwork); |
| 440 | |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 441 | VerifyDepthwiseConvolution2dName nameChecker; |
| 442 | deserializedNetwork->Accept(nameChecker); |
| 443 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 444 | CheckDeserializedNetworkAgainstOriginal(*network, |
| 445 | *deserializedNetwork, |
| 446 | inputInfo.GetShape(), |
| 447 | outputInfo.GetShape()); |
| 448 | } |
| 449 | |
| 450 | BOOST_AUTO_TEST_CASE(SerializeDeserializeSoftmax) |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 451 | { |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 452 | class VerifySoftmaxName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy> |
| 453 | { |
| 454 | public: |
| 455 | void VisitSoftmaxLayer(const armnn::IConnectableLayer*, const armnn::SoftmaxDescriptor&, const char* name) |
| 456 | { |
| 457 | BOOST_TEST(name == "softmax"); |
| 458 | } |
| 459 | }; |
| 460 | |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 461 | armnn::TensorInfo tensorInfo({1, 10}, armnn::DataType::Float32); |
| 462 | |
| 463 | armnn::SoftmaxDescriptor descriptor; |
| 464 | descriptor.m_Beta = 1.0f; |
| 465 | |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 466 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 467 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 468 | armnn::IConnectableLayer* const softmaxLayer = network->AddSoftmaxLayer(descriptor, "softmax"); |
| 469 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 470 | |
| 471 | inputLayer->GetOutputSlot(0).Connect(softmaxLayer->GetInputSlot(0)); |
| 472 | inputLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo); |
| 473 | softmaxLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 474 | softmaxLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo); |
| 475 | |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 476 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 477 | BOOST_CHECK(deserializedNetwork); |
| 478 | |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 479 | VerifySoftmaxName nameChecker; |
| 480 | deserializedNetwork->Accept(nameChecker); |
| 481 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 482 | CheckDeserializedNetworkAgainstOriginal(*network, |
| 483 | *deserializedNetwork, |
| 484 | tensorInfo.GetShape(), |
| 485 | tensorInfo.GetShape()); |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 486 | } |
| 487 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 488 | BOOST_AUTO_TEST_CASE(SerializeDeserializePooling2d) |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 489 | { |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 490 | class VerifyPooling2dName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy> |
| 491 | { |
| 492 | void VisitPooling2dLayer(const armnn::IConnectableLayer*, const armnn::Pooling2dDescriptor&, const char* name) |
| 493 | { |
| 494 | BOOST_TEST(name == "pooling2d"); |
| 495 | } |
| 496 | }; |
| 497 | |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 498 | unsigned int inputShape[] = {1, 2, 2, 1}; |
| 499 | unsigned int outputShape[] = {1, 1, 1, 1}; |
| 500 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 501 | auto inputInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32); |
| 502 | auto outputInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32); |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 503 | |
| 504 | armnn::Pooling2dDescriptor desc; |
| 505 | desc.m_DataLayout = armnn::DataLayout::NHWC; |
| 506 | desc.m_PadTop = 0; |
| 507 | desc.m_PadBottom = 0; |
| 508 | desc.m_PadLeft = 0; |
| 509 | desc.m_PadRight = 0; |
| 510 | desc.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 511 | desc.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 512 | desc.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 513 | desc.m_PoolHeight = 2; |
| 514 | desc.m_PoolWidth = 2; |
| 515 | desc.m_StrideX = 2; |
| 516 | desc.m_StrideY = 2; |
| 517 | |
| 518 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 519 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 520 | armnn::IConnectableLayer* const pooling2dLayer = network->AddPooling2dLayer(desc, "pooling2d"); |
| 521 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 522 | |
| 523 | inputLayer->GetOutputSlot(0).Connect(pooling2dLayer->GetInputSlot(0)); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 524 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 525 | pooling2dLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 526 | pooling2dLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 527 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 528 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 529 | BOOST_CHECK(deserializedNetwork); |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 530 | |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 531 | VerifyPooling2dName nameChecker; |
| 532 | deserializedNetwork->Accept(nameChecker); |
| 533 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 534 | CheckDeserializedNetworkAgainstOriginal(*network, |
| 535 | *deserializedNetwork, |
| 536 | inputInfo.GetShape(), |
| 537 | outputInfo.GetShape()); |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 538 | } |
| 539 | |
Nattapat Chaimanowong | 30b0020 | 2019-02-20 17:31:34 +0000 | [diff] [blame] | 540 | BOOST_AUTO_TEST_CASE(SerializeDeserializePermute) |
| 541 | { |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 542 | class VerifyPermuteName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy> |
| 543 | { |
| 544 | public: |
| 545 | void VisitPermuteLayer(const armnn::IConnectableLayer*, const armnn::PermuteDescriptor&, const char* name) |
| 546 | { |
| 547 | BOOST_TEST(name == "permute"); |
| 548 | } |
| 549 | }; |
| 550 | |
Nattapat Chaimanowong | 30b0020 | 2019-02-20 17:31:34 +0000 | [diff] [blame] | 551 | unsigned int inputShape[] = { 4, 3, 2, 1 }; |
| 552 | unsigned int outputShape[] = { 1, 2, 3, 4 }; |
| 553 | unsigned int dimsMapping[] = { 3, 2, 1, 0 }; |
| 554 | |
| 555 | auto inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32); |
| 556 | auto outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32); |
| 557 | |
| 558 | armnn::PermuteDescriptor permuteDescriptor(armnn::PermutationVector(dimsMapping, 4)); |
| 559 | |
| 560 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 561 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 562 | armnn::IConnectableLayer* const permuteLayer = network->AddPermuteLayer(permuteDescriptor, "permute"); |
| 563 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
Nattapat Chaimanowong | 30b0020 | 2019-02-20 17:31:34 +0000 | [diff] [blame] | 564 | |
| 565 | inputLayer->GetOutputSlot(0).Connect(permuteLayer->GetInputSlot(0)); |
| 566 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 567 | permuteLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 568 | permuteLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| 569 | |
| 570 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 571 | BOOST_CHECK(deserializedNetwork); |
| 572 | |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 573 | VerifyPermuteName nameChecker; |
| 574 | deserializedNetwork->Accept(nameChecker); |
| 575 | |
Nattapat Chaimanowong | 30b0020 | 2019-02-20 17:31:34 +0000 | [diff] [blame] | 576 | CheckDeserializedNetworkAgainstOriginal(*network, |
| 577 | *deserializedNetwork, |
| 578 | inputTensorInfo.GetShape(), |
| 579 | outputTensorInfo.GetShape()); |
| 580 | } |
| 581 | |
Sadik Armagan | dbb0c0c | 2019-02-21 09:01:41 +0000 | [diff] [blame] | 582 | BOOST_AUTO_TEST_CASE(SerializeDeserializeFullyConnected) |
| 583 | { |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 584 | class VerifyFullyConnectedName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy> |
| 585 | { |
| 586 | public: |
| 587 | void VisitFullyConnectedLayer(const armnn::IConnectableLayer*, |
| 588 | const armnn::FullyConnectedDescriptor&, |
| 589 | const armnn::ConstTensor&, |
| 590 | const armnn::Optional<armnn::ConstTensor>&, |
| 591 | const char* name) override |
| 592 | { |
| 593 | BOOST_TEST(name == "fully_connected"); |
| 594 | } |
| 595 | }; |
| 596 | |
Sadik Armagan | dbb0c0c | 2019-02-21 09:01:41 +0000 | [diff] [blame] | 597 | armnn::TensorInfo inputInfo ({ 2, 5, 1, 1 }, armnn::DataType::Float32); |
| 598 | armnn::TensorInfo outputInfo({ 2, 3 }, armnn::DataType::Float32); |
| 599 | |
| 600 | armnn::TensorInfo weightsInfo({ 5, 3 }, armnn::DataType::Float32); |
| 601 | armnn::TensorInfo biasesInfo ({ 3 }, armnn::DataType::Float32); |
| 602 | |
| 603 | armnn::FullyConnectedDescriptor descriptor; |
| 604 | descriptor.m_BiasEnabled = true; |
| 605 | descriptor.m_TransposeWeightMatrix = false; |
| 606 | |
| 607 | std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements()); |
| 608 | std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements()); |
| 609 | |
| 610 | armnn::ConstTensor weights(weightsInfo, weightsData); |
| 611 | armnn::ConstTensor biases(biasesInfo, biasesData); |
| 612 | |
| 613 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 614 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0, "input"); |
| 615 | armnn::IConnectableLayer* const fullyConnectedLayer = network->AddFullyConnectedLayer(descriptor, |
| 616 | weights, |
| 617 | biases, |
| 618 | "fully_connected"); |
| 619 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0, "output"); |
| 620 | |
| 621 | inputLayer->GetOutputSlot(0).Connect(fullyConnectedLayer->GetInputSlot(0)); |
| 622 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 623 | |
| 624 | fullyConnectedLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 625 | fullyConnectedLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 626 | |
| 627 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 628 | BOOST_CHECK(deserializedNetwork); |
| 629 | |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 630 | VerifyFullyConnectedName nameChecker; |
| 631 | deserializedNetwork->Accept(nameChecker); |
| 632 | |
Sadik Armagan | dbb0c0c | 2019-02-21 09:01:41 +0000 | [diff] [blame] | 633 | CheckDeserializedNetworkAgainstOriginal(*network, |
| 634 | *deserializedNetwork, |
| 635 | inputInfo.GetShape(), |
| 636 | outputInfo.GetShape()); |
| 637 | } |
| 638 | |
Nattapat Chaimanowong | 4528699 | 2019-02-26 15:53:02 +0000 | [diff] [blame] | 639 | BOOST_AUTO_TEST_CASE(SerializeDeserializeSpaceToBatchNd) |
| 640 | { |
| 641 | class VerifySpaceToBatchNdName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy> |
| 642 | { |
| 643 | public: |
| 644 | void VisitSpaceToBatchNdLayer(const armnn::IConnectableLayer*, |
| 645 | const armnn::SpaceToBatchNdDescriptor& spaceToBatchNdDescriptor, |
| 646 | const char* name) override |
| 647 | { |
| 648 | BOOST_TEST(name == "SpaceToBatchNdLayer"); |
| 649 | } |
| 650 | }; |
| 651 | |
| 652 | unsigned int inputShape[] = {2, 1, 2, 4}; |
| 653 | unsigned int outputShape[] = {8, 1, 1, 3}; |
| 654 | |
| 655 | armnn::SpaceToBatchNdDescriptor desc; |
| 656 | desc.m_DataLayout = armnn::DataLayout::NCHW; |
| 657 | desc.m_BlockShape = {2, 2}; |
| 658 | desc.m_PadList = {{0, 0}, {2, 0}}; |
| 659 | |
| 660 | auto inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32); |
| 661 | auto outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32); |
| 662 | |
| 663 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 664 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 665 | armnn::IConnectableLayer* const spaceToBatchNdLayer = network->AddSpaceToBatchNdLayer(desc, "SpaceToBatchNdLayer"); |
| 666 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 667 | |
| 668 | inputLayer->GetOutputSlot(0).Connect(spaceToBatchNdLayer->GetInputSlot(0)); |
| 669 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 670 | spaceToBatchNdLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 671 | spaceToBatchNdLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| 672 | |
| 673 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 674 | BOOST_CHECK(deserializedNetwork); |
| 675 | |
| 676 | VerifySpaceToBatchNdName nameChecker; |
| 677 | deserializedNetwork->Accept(nameChecker); |
| 678 | |
| 679 | CheckDeserializedNetworkAgainstOriginal(*network, |
| 680 | *deserializedNetwork, |
| 681 | inputTensorInfo.GetShape(), |
| 682 | outputTensorInfo.GetShape()); |
| 683 | } |
| 684 | |
Nattapat Chaimanowong | 30b0020 | 2019-02-20 17:31:34 +0000 | [diff] [blame] | 685 | BOOST_AUTO_TEST_SUITE_END() |