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 | |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 6 | #include "../Serializer.hpp" |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 7 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 8 | #include <armnn/ArmNN.hpp> |
| 9 | #include <armnn/INetwork.hpp> |
Derek Lamberti | 0028d1b | 2019-02-20 13:57:42 +0000 | [diff] [blame] | 10 | #include <armnnDeserializer/IDeserializer.hpp> |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 11 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 12 | #include <random> |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 13 | #include <vector> |
| 14 | |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 15 | #include <boost/test/unit_test.hpp> |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 16 | |
Derek Lamberti | 0028d1b | 2019-02-20 13:57:42 +0000 | [diff] [blame] | 17 | using armnnDeserializer::IDeserializer; |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 18 | |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 19 | namespace |
| 20 | { |
| 21 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 22 | struct DefaultLayerVerifierPolicy |
| 23 | { |
Les Bell | e0ca861 | 2019-05-17 16:17:12 +0100 | [diff] [blame] | 24 | static void Apply(const std::string s = "") |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 25 | { |
| 26 | BOOST_TEST_MESSAGE("Unexpected layer found in network"); |
| 27 | BOOST_TEST(false); |
| 28 | } |
| 29 | }; |
| 30 | |
| 31 | class LayerVerifierBase : public armnn::LayerVisitorBase<DefaultLayerVerifierPolicy> |
| 32 | { |
| 33 | public: |
| 34 | LayerVerifierBase(const std::string& layerName, |
| 35 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 36 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 37 | : m_LayerName(layerName) |
| 38 | , m_InputTensorInfos(inputInfos) |
| 39 | , m_OutputTensorInfos(outputInfos) {} |
| 40 | |
| 41 | void VisitInputLayer(const armnn::IConnectableLayer*, armnn::LayerBindingId, const char*) override {} |
| 42 | |
| 43 | void VisitOutputLayer(const armnn::IConnectableLayer*, armnn::LayerBindingId id, const char*) override {} |
| 44 | |
| 45 | protected: |
| 46 | void VerifyNameAndConnections(const armnn::IConnectableLayer* layer, const char* name) |
| 47 | { |
| 48 | BOOST_TEST(name == m_LayerName.c_str()); |
| 49 | |
| 50 | BOOST_TEST(layer->GetNumInputSlots() == m_InputTensorInfos.size()); |
| 51 | BOOST_TEST(layer->GetNumOutputSlots() == m_OutputTensorInfos.size()); |
| 52 | |
| 53 | for (unsigned int i = 0; i < m_InputTensorInfos.size(); i++) |
| 54 | { |
| 55 | const armnn::IOutputSlot* connectedOutput = layer->GetInputSlot(i).GetConnection(); |
| 56 | BOOST_CHECK(connectedOutput); |
| 57 | |
| 58 | const armnn::TensorInfo& connectedInfo = connectedOutput->GetTensorInfo(); |
| 59 | BOOST_TEST(connectedInfo.GetShape() == m_InputTensorInfos[i].GetShape()); |
| 60 | BOOST_TEST( |
| 61 | GetDataTypeName(connectedInfo.GetDataType()) == GetDataTypeName(m_InputTensorInfos[i].GetDataType())); |
Nattapat Chaimanowong | e4294fd | 2019-03-28 09:56:53 +0000 | [diff] [blame] | 62 | |
| 63 | BOOST_TEST(connectedInfo.GetQuantizationScale() == m_InputTensorInfos[i].GetQuantizationScale()); |
| 64 | BOOST_TEST(connectedInfo.GetQuantizationOffset() == m_InputTensorInfos[i].GetQuantizationOffset()); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 65 | } |
| 66 | |
| 67 | for (unsigned int i = 0; i < m_OutputTensorInfos.size(); i++) |
| 68 | { |
| 69 | const armnn::TensorInfo& outputInfo = layer->GetOutputSlot(i).GetTensorInfo(); |
| 70 | BOOST_TEST(outputInfo.GetShape() == m_OutputTensorInfos[i].GetShape()); |
| 71 | BOOST_TEST( |
| 72 | GetDataTypeName(outputInfo.GetDataType()) == GetDataTypeName(m_OutputTensorInfos[i].GetDataType())); |
Nattapat Chaimanowong | e4294fd | 2019-03-28 09:56:53 +0000 | [diff] [blame] | 73 | |
| 74 | BOOST_TEST(outputInfo.GetQuantizationScale() == m_OutputTensorInfos[i].GetQuantizationScale()); |
| 75 | BOOST_TEST(outputInfo.GetQuantizationOffset() == m_OutputTensorInfos[i].GetQuantizationOffset()); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 76 | } |
| 77 | } |
| 78 | |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 79 | void VerifyConstTensors(const std::string& tensorName, |
| 80 | const armnn::ConstTensor* expectedPtr, |
| 81 | const armnn::ConstTensor* actualPtr) |
| 82 | { |
| 83 | if (expectedPtr == nullptr) |
| 84 | { |
| 85 | BOOST_CHECK_MESSAGE(actualPtr == nullptr, tensorName + " should not exist"); |
| 86 | } |
| 87 | else |
| 88 | { |
| 89 | BOOST_CHECK_MESSAGE(actualPtr != nullptr, tensorName + " should have been set"); |
| 90 | if (actualPtr != nullptr) |
| 91 | { |
| 92 | const armnn::TensorInfo& expectedInfo = expectedPtr->GetInfo(); |
| 93 | const armnn::TensorInfo& actualInfo = actualPtr->GetInfo(); |
| 94 | |
| 95 | BOOST_CHECK_MESSAGE(expectedInfo.GetShape() == actualInfo.GetShape(), |
| 96 | tensorName + " shapes don't match"); |
| 97 | BOOST_CHECK_MESSAGE( |
| 98 | GetDataTypeName(expectedInfo.GetDataType()) == GetDataTypeName(actualInfo.GetDataType()), |
| 99 | tensorName + " data types don't match"); |
| 100 | |
| 101 | BOOST_CHECK_MESSAGE(expectedPtr->GetNumBytes() == actualPtr->GetNumBytes(), |
| 102 | tensorName + " (GetNumBytes) data sizes do not match"); |
| 103 | if (expectedPtr->GetNumBytes() == actualPtr->GetNumBytes()) |
| 104 | { |
| 105 | //check the data is identical |
| 106 | const char* expectedData = static_cast<const char*>(expectedPtr->GetMemoryArea()); |
| 107 | const char* actualData = static_cast<const char*>(actualPtr->GetMemoryArea()); |
| 108 | bool same = true; |
| 109 | for (unsigned int i = 0; i < expectedPtr->GetNumBytes(); ++i) |
| 110 | { |
| 111 | same = expectedData[i] == actualData[i]; |
| 112 | if (!same) |
| 113 | { |
| 114 | break; |
| 115 | } |
| 116 | } |
| 117 | BOOST_CHECK_MESSAGE(same, tensorName + " data does not match"); |
| 118 | } |
| 119 | } |
| 120 | } |
| 121 | } |
| 122 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 123 | private: |
| 124 | std::string m_LayerName; |
| 125 | std::vector<armnn::TensorInfo> m_InputTensorInfos; |
| 126 | std::vector<armnn::TensorInfo> m_OutputTensorInfos; |
| 127 | }; |
| 128 | |
| 129 | template<typename T> |
| 130 | void CompareConstTensorData(const void* data1, const void* data2, unsigned int numElements) |
| 131 | { |
| 132 | T typedData1 = static_cast<T>(data1); |
| 133 | T typedData2 = static_cast<T>(data2); |
| 134 | BOOST_CHECK(typedData1); |
| 135 | BOOST_CHECK(typedData2); |
| 136 | |
| 137 | for (unsigned int i = 0; i < numElements; i++) |
| 138 | { |
| 139 | BOOST_TEST(typedData1[i] == typedData2[i]); |
| 140 | } |
| 141 | } |
| 142 | |
| 143 | void CompareConstTensor(const armnn::ConstTensor& tensor1, const armnn::ConstTensor& tensor2) |
| 144 | { |
| 145 | BOOST_TEST(tensor1.GetShape() == tensor2.GetShape()); |
| 146 | BOOST_TEST(GetDataTypeName(tensor1.GetDataType()) == GetDataTypeName(tensor2.GetDataType())); |
| 147 | |
| 148 | switch (tensor1.GetDataType()) |
| 149 | { |
| 150 | case armnn::DataType::Float32: |
| 151 | CompareConstTensorData<const float*>( |
| 152 | tensor1.GetMemoryArea(), tensor2.GetMemoryArea(), tensor1.GetNumElements()); |
| 153 | break; |
| 154 | case armnn::DataType::QuantisedAsymm8: |
| 155 | case armnn::DataType::Boolean: |
| 156 | CompareConstTensorData<const uint8_t*>( |
| 157 | tensor1.GetMemoryArea(), tensor2.GetMemoryArea(), tensor1.GetNumElements()); |
| 158 | break; |
| 159 | case armnn::DataType::Signed32: |
| 160 | CompareConstTensorData<const int32_t*>( |
| 161 | tensor1.GetMemoryArea(), tensor2.GetMemoryArea(), tensor1.GetNumElements()); |
| 162 | break; |
| 163 | default: |
| 164 | // Note that Float16 is not yet implemented |
| 165 | BOOST_TEST_MESSAGE("Unexpected datatype"); |
| 166 | BOOST_TEST(false); |
| 167 | } |
| 168 | } |
| 169 | |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 170 | armnn::INetworkPtr DeserializeNetwork(const std::string& serializerString) |
| 171 | { |
| 172 | std::vector<std::uint8_t> const serializerVector{serializerString.begin(), serializerString.end()}; |
Derek Lamberti | 0028d1b | 2019-02-20 13:57:42 +0000 | [diff] [blame] | 173 | return IDeserializer::Create()->CreateNetworkFromBinary(serializerVector); |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 174 | } |
| 175 | |
| 176 | std::string SerializeNetwork(const armnn::INetwork& network) |
| 177 | { |
| 178 | armnnSerializer::Serializer serializer; |
| 179 | serializer.Serialize(network); |
| 180 | |
| 181 | std::stringstream stream; |
| 182 | serializer.SaveSerializedToStream(stream); |
| 183 | |
| 184 | std::string serializerString{stream.str()}; |
| 185 | return serializerString; |
| 186 | } |
| 187 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 188 | template<typename DataType> |
| 189 | static std::vector<DataType> GenerateRandomData(size_t size) |
| 190 | { |
| 191 | constexpr bool isIntegerType = std::is_integral<DataType>::value; |
| 192 | using Distribution = |
| 193 | typename std::conditional<isIntegerType, |
| 194 | std::uniform_int_distribution<DataType>, |
| 195 | std::uniform_real_distribution<DataType>>::type; |
| 196 | |
| 197 | static constexpr DataType lowerLimit = std::numeric_limits<DataType>::min(); |
| 198 | static constexpr DataType upperLimit = std::numeric_limits<DataType>::max(); |
| 199 | |
| 200 | static Distribution distribution(lowerLimit, upperLimit); |
| 201 | static std::default_random_engine generator; |
| 202 | |
| 203 | std::vector<DataType> randomData(size); |
| 204 | std::generate(randomData.begin(), randomData.end(), []() { return distribution(generator); }); |
| 205 | |
| 206 | return randomData; |
| 207 | } |
| 208 | |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 209 | } // anonymous namespace |
| 210 | |
| 211 | BOOST_AUTO_TEST_SUITE(SerializerTests) |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 212 | |
FinnWilliamsArm | 4ffcc8f | 2019-09-05 14:34:20 +0100 | [diff] [blame] | 213 | BOOST_AUTO_TEST_CASE(SerializeAbs) |
| 214 | { |
| 215 | class AbsLayerVerifier : public LayerVerifierBase |
| 216 | { |
| 217 | public: |
| 218 | AbsLayerVerifier(const std::string& layerName, |
| 219 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 220 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 221 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 222 | |
| 223 | void VisitAbsLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 224 | { |
| 225 | VerifyNameAndConnections(layer, name); |
| 226 | } |
| 227 | }; |
| 228 | |
| 229 | const std::string layerName("abs"); |
| 230 | const armnn::TensorInfo tensorInfo({1, 2, 3}, armnn::DataType::Float32); |
| 231 | |
| 232 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 233 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 234 | |
| 235 | armnn::IConnectableLayer* const absLayer = network->AddAbsLayer(layerName.c_str()); |
| 236 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 237 | |
| 238 | inputLayer->GetOutputSlot(0).Connect(absLayer->GetInputSlot(0)); |
| 239 | absLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 240 | |
| 241 | inputLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo); |
| 242 | absLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo); |
| 243 | |
| 244 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 245 | BOOST_CHECK(deserializedNetwork); |
| 246 | |
| 247 | AbsLayerVerifier verifier(layerName, {tensorInfo}, {tensorInfo}); |
| 248 | deserializedNetwork->Accept(verifier); |
| 249 | } |
| 250 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 251 | BOOST_AUTO_TEST_CASE(SerializeAddition) |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 252 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 253 | class AdditionLayerVerifier : public LayerVerifierBase |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 254 | { |
| 255 | public: |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 256 | AdditionLayerVerifier(const std::string& layerName, |
| 257 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 258 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 259 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 260 | |
| 261 | void VisitAdditionLayer(const armnn::IConnectableLayer* layer, const char* name) override |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 262 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 263 | VerifyNameAndConnections(layer, name); |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 264 | } |
| 265 | }; |
| 266 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 267 | const std::string layerName("addition"); |
| 268 | const armnn::TensorInfo tensorInfo({1, 2, 3}, armnn::DataType::Float32); |
| 269 | |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 270 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 271 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 272 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 273 | armnn::IConnectableLayer* const additionLayer = network->AddAdditionLayer(layerName.c_str()); |
| 274 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 275 | |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 276 | inputLayer0->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(0)); |
| 277 | inputLayer1->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(1)); |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 278 | additionLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 279 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 280 | inputLayer0->GetOutputSlot(0).SetTensorInfo(tensorInfo); |
| 281 | inputLayer1->GetOutputSlot(0).SetTensorInfo(tensorInfo); |
| 282 | additionLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo); |
Jim Flynn | 3091b06 | 2019-02-15 14:45:04 +0000 | [diff] [blame] | 283 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 284 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 285 | BOOST_CHECK(deserializedNetwork); |
| 286 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 287 | AdditionLayerVerifier verifier(layerName, {tensorInfo, tensorInfo}, {tensorInfo}); |
| 288 | deserializedNetwork->Accept(verifier); |
| 289 | } |
Jim Flynn | ac25a1b | 2019-02-28 10:40:49 +0000 | [diff] [blame] | 290 | |
Narumol Prangnawarat | 0cfcf23 | 2019-09-09 17:16:24 +0100 | [diff] [blame] | 291 | BOOST_AUTO_TEST_CASE(SerializeArgMinMax) |
| 292 | { |
| 293 | class ArgMinMaxLayerVerifier : public LayerVerifierBase |
| 294 | { |
| 295 | public: |
| 296 | ArgMinMaxLayerVerifier(const std::string& layerName, |
| 297 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 298 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 299 | const armnn::ArgMinMaxDescriptor& descriptor) |
| 300 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 301 | , m_Descriptor(descriptor) {} |
| 302 | |
| 303 | void VisitArgMinMaxLayer(const armnn::IConnectableLayer* layer, |
| 304 | const armnn::ArgMinMaxDescriptor& descriptor, |
| 305 | const char* name) override |
| 306 | { |
| 307 | VerifyNameAndConnections(layer, name); |
| 308 | VerifyDescriptor(descriptor); |
| 309 | } |
| 310 | |
| 311 | private: |
| 312 | void VerifyDescriptor(const armnn::ArgMinMaxDescriptor& descriptor) |
| 313 | { |
| 314 | BOOST_CHECK(descriptor.m_Function == m_Descriptor.m_Function); |
| 315 | BOOST_CHECK(descriptor.m_Axis == m_Descriptor.m_Axis); |
| 316 | } |
| 317 | |
| 318 | armnn::ArgMinMaxDescriptor m_Descriptor; |
| 319 | }; |
| 320 | |
| 321 | const std::string layerName("argminmax"); |
| 322 | const armnn::TensorInfo inputInfo({1, 2, 3}, armnn::DataType::Float32); |
| 323 | const armnn::TensorInfo outputInfo({1, 3}, armnn::DataType::Signed32); |
| 324 | |
| 325 | armnn::ArgMinMaxDescriptor descriptor; |
| 326 | descriptor.m_Function = armnn::ArgMinMaxFunction::Max; |
| 327 | descriptor.m_Axis = 1; |
| 328 | |
| 329 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 330 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 331 | armnn::IConnectableLayer* const argMinMaxLayer = network->AddArgMinMaxLayer(descriptor, layerName.c_str()); |
| 332 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 333 | |
| 334 | inputLayer->GetOutputSlot(0).Connect(argMinMaxLayer->GetInputSlot(0)); |
| 335 | argMinMaxLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 336 | |
| 337 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 338 | argMinMaxLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 339 | |
| 340 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 341 | BOOST_CHECK(deserializedNetwork); |
| 342 | |
| 343 | ArgMinMaxLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor); |
| 344 | deserializedNetwork->Accept(verifier); |
| 345 | } |
| 346 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 347 | BOOST_AUTO_TEST_CASE(SerializeBatchNormalization) |
| 348 | { |
| 349 | class BatchNormalizationLayerVerifier : public LayerVerifierBase |
| 350 | { |
| 351 | public: |
| 352 | BatchNormalizationLayerVerifier(const std::string& layerName, |
| 353 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 354 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 355 | const armnn::BatchNormalizationDescriptor& descriptor, |
| 356 | const armnn::ConstTensor& mean, |
| 357 | const armnn::ConstTensor& variance, |
| 358 | const armnn::ConstTensor& beta, |
| 359 | const armnn::ConstTensor& gamma) |
| 360 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 361 | , m_Descriptor(descriptor) |
| 362 | , m_Mean(mean) |
| 363 | , m_Variance(variance) |
| 364 | , m_Beta(beta) |
| 365 | , m_Gamma(gamma) {} |
| 366 | |
| 367 | void VisitBatchNormalizationLayer(const armnn::IConnectableLayer* layer, |
| 368 | const armnn::BatchNormalizationDescriptor& descriptor, |
| 369 | const armnn::ConstTensor& mean, |
| 370 | const armnn::ConstTensor& variance, |
| 371 | const armnn::ConstTensor& beta, |
| 372 | const armnn::ConstTensor& gamma, |
| 373 | const char* name) override |
| 374 | { |
| 375 | VerifyNameAndConnections(layer, name); |
| 376 | VerifyDescriptor(descriptor); |
| 377 | |
| 378 | CompareConstTensor(mean, m_Mean); |
| 379 | CompareConstTensor(variance, m_Variance); |
| 380 | CompareConstTensor(beta, m_Beta); |
| 381 | CompareConstTensor(gamma, m_Gamma); |
| 382 | } |
| 383 | |
| 384 | private: |
| 385 | void VerifyDescriptor(const armnn::BatchNormalizationDescriptor& descriptor) |
| 386 | { |
| 387 | BOOST_TEST(descriptor.m_Eps == m_Descriptor.m_Eps); |
| 388 | BOOST_TEST(static_cast<int>(descriptor.m_DataLayout) == static_cast<int>(m_Descriptor.m_DataLayout)); |
| 389 | } |
| 390 | |
| 391 | armnn::BatchNormalizationDescriptor m_Descriptor; |
| 392 | armnn::ConstTensor m_Mean; |
| 393 | armnn::ConstTensor m_Variance; |
| 394 | armnn::ConstTensor m_Beta; |
| 395 | armnn::ConstTensor m_Gamma; |
| 396 | }; |
| 397 | |
| 398 | const std::string layerName("batchNormalization"); |
| 399 | const armnn::TensorInfo inputInfo ({ 1, 3, 3, 1 }, armnn::DataType::Float32); |
| 400 | const armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32); |
| 401 | |
| 402 | const armnn::TensorInfo meanInfo({1}, armnn::DataType::Float32); |
| 403 | const armnn::TensorInfo varianceInfo({1}, armnn::DataType::Float32); |
| 404 | const armnn::TensorInfo betaInfo({1}, armnn::DataType::Float32); |
| 405 | const armnn::TensorInfo gammaInfo({1}, armnn::DataType::Float32); |
| 406 | |
| 407 | armnn::BatchNormalizationDescriptor descriptor; |
| 408 | descriptor.m_Eps = 0.0010000000475f; |
| 409 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 410 | |
| 411 | std::vector<float> meanData({5.0}); |
| 412 | std::vector<float> varianceData({2.0}); |
| 413 | std::vector<float> betaData({1.0}); |
| 414 | std::vector<float> gammaData({0.0}); |
| 415 | |
| 416 | armnn::ConstTensor mean(meanInfo, meanData); |
| 417 | armnn::ConstTensor variance(varianceInfo, varianceData); |
| 418 | armnn::ConstTensor beta(betaInfo, betaData); |
| 419 | armnn::ConstTensor gamma(gammaInfo, gammaData); |
| 420 | |
| 421 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 422 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 423 | armnn::IConnectableLayer* const batchNormalizationLayer = |
| 424 | network->AddBatchNormalizationLayer(descriptor, mean, variance, beta, gamma, layerName.c_str()); |
| 425 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 426 | |
| 427 | inputLayer->GetOutputSlot(0).Connect(batchNormalizationLayer->GetInputSlot(0)); |
| 428 | batchNormalizationLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 429 | |
| 430 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 431 | batchNormalizationLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 432 | |
| 433 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 434 | BOOST_CHECK(deserializedNetwork); |
| 435 | |
| 436 | BatchNormalizationLayerVerifier verifier( |
| 437 | layerName, {inputInfo}, {outputInfo}, descriptor, mean, variance, beta, gamma); |
| 438 | deserializedNetwork->Accept(verifier); |
| 439 | } |
| 440 | |
| 441 | BOOST_AUTO_TEST_CASE(SerializeBatchToSpaceNd) |
| 442 | { |
| 443 | class BatchToSpaceNdLayerVerifier : public LayerVerifierBase |
| 444 | { |
| 445 | public: |
| 446 | BatchToSpaceNdLayerVerifier(const std::string& layerName, |
| 447 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 448 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 449 | const armnn::BatchToSpaceNdDescriptor& descriptor) |
| 450 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 451 | , m_Descriptor(descriptor) {} |
| 452 | |
| 453 | void VisitBatchToSpaceNdLayer(const armnn::IConnectableLayer* layer, |
| 454 | const armnn::BatchToSpaceNdDescriptor& descriptor, |
| 455 | const char* name) override |
| 456 | { |
| 457 | VerifyNameAndConnections(layer, name); |
| 458 | VerifyDescriptor(descriptor); |
| 459 | } |
| 460 | |
| 461 | private: |
| 462 | void VerifyDescriptor(const armnn::BatchToSpaceNdDescriptor& descriptor) |
| 463 | { |
| 464 | BOOST_TEST(descriptor.m_Crops == m_Descriptor.m_Crops); |
| 465 | BOOST_TEST(descriptor.m_BlockShape == m_Descriptor.m_BlockShape); |
| 466 | BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout)); |
| 467 | } |
| 468 | |
| 469 | armnn::BatchToSpaceNdDescriptor m_Descriptor; |
| 470 | }; |
| 471 | |
| 472 | const std::string layerName("spaceToBatchNd"); |
| 473 | const armnn::TensorInfo inputInfo({4, 1, 2, 2}, armnn::DataType::Float32); |
| 474 | const armnn::TensorInfo outputInfo({1, 1, 4, 4}, armnn::DataType::Float32); |
| 475 | |
| 476 | armnn::BatchToSpaceNdDescriptor desc; |
| 477 | desc.m_DataLayout = armnn::DataLayout::NCHW; |
| 478 | desc.m_BlockShape = {2, 2}; |
| 479 | desc.m_Crops = {{0, 0}, {0, 0}}; |
| 480 | |
| 481 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 482 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 483 | armnn::IConnectableLayer* const batchToSpaceNdLayer = network->AddBatchToSpaceNdLayer(desc, layerName.c_str()); |
| 484 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 485 | |
| 486 | inputLayer->GetOutputSlot(0).Connect(batchToSpaceNdLayer->GetInputSlot(0)); |
| 487 | batchToSpaceNdLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 488 | |
| 489 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 490 | batchToSpaceNdLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 491 | |
| 492 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 493 | BOOST_CHECK(deserializedNetwork); |
| 494 | |
| 495 | BatchToSpaceNdLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc); |
| 496 | deserializedNetwork->Accept(verifier); |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 497 | } |
| 498 | |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 499 | BOOST_AUTO_TEST_CASE(SerializeConstant) |
| 500 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 501 | class ConstantLayerVerifier : public LayerVerifierBase |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 502 | { |
| 503 | public: |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 504 | ConstantLayerVerifier(const std::string& layerName, |
| 505 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 506 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 507 | const armnn::ConstTensor& layerInput) |
| 508 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 509 | , m_LayerInput(layerInput) {} |
| 510 | |
| 511 | void VisitConstantLayer(const armnn::IConnectableLayer* layer, |
| 512 | const armnn::ConstTensor& input, |
| 513 | const char* name) override |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 514 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 515 | VerifyNameAndConnections(layer, name); |
| 516 | |
| 517 | CompareConstTensor(input, m_LayerInput); |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 518 | } |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 519 | |
| 520 | void VisitAdditionLayer(const armnn::IConnectableLayer* layer, const char* name = nullptr) override {} |
| 521 | |
| 522 | private: |
| 523 | armnn::ConstTensor m_LayerInput; |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 524 | }; |
| 525 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 526 | const std::string layerName("constant"); |
| 527 | const armnn::TensorInfo info({ 2, 3 }, armnn::DataType::Float32); |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 528 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 529 | std::vector<float> constantData = GenerateRandomData<float>(info.GetNumElements()); |
| 530 | armnn::ConstTensor constTensor(info, constantData); |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 531 | |
Matteo Martincigh | f81edaa | 2019-03-04 14:34:30 +0000 | [diff] [blame] | 532 | armnn::INetworkPtr network(armnn::INetwork::Create()); |
Matteo Martincigh | f81edaa | 2019-03-04 14:34:30 +0000 | [diff] [blame] | 533 | armnn::IConnectableLayer* input = network->AddInputLayer(0); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 534 | armnn::IConnectableLayer* constant = network->AddConstantLayer(constTensor, layerName.c_str()); |
Matteo Martincigh | f81edaa | 2019-03-04 14:34:30 +0000 | [diff] [blame] | 535 | armnn::IConnectableLayer* add = network->AddAdditionLayer(); |
| 536 | armnn::IConnectableLayer* output = network->AddOutputLayer(0); |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 537 | |
| 538 | input->GetOutputSlot(0).Connect(add->GetInputSlot(0)); |
| 539 | constant->GetOutputSlot(0).Connect(add->GetInputSlot(1)); |
| 540 | add->GetOutputSlot(0).Connect(output->GetInputSlot(0)); |
| 541 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 542 | input->GetOutputSlot(0).SetTensorInfo(info); |
| 543 | constant->GetOutputSlot(0).SetTensorInfo(info); |
| 544 | add->GetOutputSlot(0).SetTensorInfo(info); |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 545 | |
Matteo Martincigh | f81edaa | 2019-03-04 14:34:30 +0000 | [diff] [blame] | 546 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 547 | BOOST_CHECK(deserializedNetwork); |
| 548 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 549 | ConstantLayerVerifier verifier(layerName, {}, {info}, constTensor); |
| 550 | deserializedNetwork->Accept(verifier); |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 551 | } |
| 552 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 553 | BOOST_AUTO_TEST_CASE(SerializeConvolution2d) |
Finn Williams | dd2ba7e | 2019-03-01 11:51:52 +0000 | [diff] [blame] | 554 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 555 | class Convolution2dLayerVerifier : public LayerVerifierBase |
Finn Williams | dd2ba7e | 2019-03-01 11:51:52 +0000 | [diff] [blame] | 556 | { |
| 557 | public: |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 558 | Convolution2dLayerVerifier(const std::string& layerName, |
| 559 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 560 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 561 | const armnn::Convolution2dDescriptor& descriptor, |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 562 | const armnn::ConstTensor& weights, |
| 563 | const armnn::Optional<armnn::ConstTensor>& biases) : |
| 564 | LayerVerifierBase(layerName, inputInfos, outputInfos), |
| 565 | m_Descriptor(descriptor), |
| 566 | m_Weights(weights), |
| 567 | m_Biases(biases) |
| 568 | {} |
Finn Williams | dd2ba7e | 2019-03-01 11:51:52 +0000 | [diff] [blame] | 569 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 570 | void VisitConvolution2dLayer(const armnn::IConnectableLayer* layer, |
| 571 | const armnn::Convolution2dDescriptor& descriptor, |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 572 | const armnn::ConstTensor& weights, |
| 573 | const armnn::Optional<armnn::ConstTensor>& biases, |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 574 | const char* name) override |
| 575 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 576 | VerifyNameAndConnections(layer, name); |
| 577 | VerifyDescriptor(descriptor); |
| 578 | |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 579 | // check weights |
| 580 | CompareConstTensor(weights, m_Weights); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 581 | |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 582 | // check biases |
| 583 | BOOST_CHECK(biases.has_value() == descriptor.m_BiasEnabled); |
| 584 | BOOST_CHECK(m_Biases.has_value() == m_Descriptor.m_BiasEnabled); |
| 585 | |
| 586 | BOOST_CHECK(biases.has_value() == m_Biases.has_value()); |
| 587 | |
| 588 | if (biases.has_value() && m_Biases.has_value()) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 589 | { |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 590 | CompareConstTensor(biases.value(), m_Biases.value()); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 591 | } |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 592 | } |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 593 | |
| 594 | private: |
| 595 | void VerifyDescriptor(const armnn::Convolution2dDescriptor& descriptor) |
| 596 | { |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 597 | BOOST_CHECK(descriptor.m_PadLeft == m_Descriptor.m_PadLeft); |
| 598 | BOOST_CHECK(descriptor.m_PadRight == m_Descriptor.m_PadRight); |
| 599 | BOOST_CHECK(descriptor.m_PadTop == m_Descriptor.m_PadTop); |
| 600 | BOOST_CHECK(descriptor.m_PadBottom == m_Descriptor.m_PadBottom); |
| 601 | BOOST_CHECK(descriptor.m_StrideX == m_Descriptor.m_StrideX); |
| 602 | BOOST_CHECK(descriptor.m_StrideY == m_Descriptor.m_StrideY); |
| 603 | BOOST_CHECK(descriptor.m_DilationX == m_Descriptor.m_DilationX); |
| 604 | BOOST_CHECK(descriptor.m_DilationY == m_Descriptor.m_DilationY); |
| 605 | BOOST_CHECK(descriptor.m_BiasEnabled == m_Descriptor.m_BiasEnabled); |
| 606 | BOOST_CHECK(descriptor.m_DataLayout == m_Descriptor.m_DataLayout); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 607 | } |
| 608 | |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 609 | armnn::Convolution2dDescriptor m_Descriptor; |
| 610 | armnn::ConstTensor m_Weights; |
| 611 | armnn::Optional<armnn::ConstTensor> m_Biases; |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 612 | }; |
| 613 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 614 | const std::string layerName("convolution2d"); |
| 615 | const armnn::TensorInfo inputInfo ({ 1, 5, 5, 1 }, armnn::DataType::Float32); |
| 616 | const armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32); |
Saoirse Stewart | 263829c | 2019-02-19 15:54:14 +0000 | [diff] [blame] | 617 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 618 | const armnn::TensorInfo weightsInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32); |
| 619 | const armnn::TensorInfo biasesInfo ({ 1 }, armnn::DataType::Float32); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 620 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 621 | std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements()); |
| 622 | armnn::ConstTensor weights(weightsInfo, weightsData); |
| 623 | |
| 624 | std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements()); |
| 625 | armnn::ConstTensor biases(biasesInfo, biasesData); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 626 | |
| 627 | armnn::Convolution2dDescriptor descriptor; |
| 628 | descriptor.m_PadLeft = 1; |
| 629 | descriptor.m_PadRight = 1; |
| 630 | descriptor.m_PadTop = 1; |
| 631 | descriptor.m_PadBottom = 1; |
| 632 | descriptor.m_StrideX = 2; |
| 633 | descriptor.m_StrideY = 2; |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 634 | descriptor.m_DilationX = 2; |
| 635 | descriptor.m_DilationY = 2; |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 636 | descriptor.m_BiasEnabled = true; |
| 637 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 638 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 639 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 640 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 641 | armnn::IConnectableLayer* const convLayer = |
Matteo Martincigh | fc598e1 | 2019-05-14 10:36:13 +0100 | [diff] [blame] | 642 | network->AddConvolution2dLayer(descriptor, |
| 643 | weights, |
| 644 | armnn::Optional<armnn::ConstTensor>(biases), |
| 645 | layerName.c_str()); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 646 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 647 | |
| 648 | inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0)); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 649 | convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 650 | |
| 651 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 652 | convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 653 | |
| 654 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 655 | BOOST_CHECK(deserializedNetwork); |
| 656 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 657 | Convolution2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases); |
| 658 | deserializedNetwork->Accept(verifier); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 659 | } |
| 660 | |
Aron Virginas-Tar | da9d2d3 | 2019-09-20 10:42:02 +0100 | [diff] [blame] | 661 | BOOST_AUTO_TEST_CASE(SerializeDepthToSpace) |
| 662 | { |
| 663 | class DepthToSpaceLayerVerifier : public LayerVerifierBase |
| 664 | { |
| 665 | public: |
| 666 | DepthToSpaceLayerVerifier(const std::string& layerName, |
| 667 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 668 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 669 | const armnn::DepthToSpaceDescriptor& descriptor) |
| 670 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 671 | , m_Descriptor(descriptor) {} |
| 672 | |
| 673 | void VisitDepthToSpaceLayer(const armnn::IConnectableLayer* layer, |
| 674 | const armnn::DepthToSpaceDescriptor& descriptor, |
| 675 | const char* name) override |
| 676 | { |
| 677 | VerifyNameAndConnections(layer, name); |
| 678 | VerifyDescriptor(descriptor); |
| 679 | } |
| 680 | |
| 681 | private: |
| 682 | void VerifyDescriptor(const armnn::DepthToSpaceDescriptor& descriptor) |
| 683 | { |
| 684 | BOOST_TEST(descriptor.m_BlockSize == m_Descriptor.m_BlockSize); |
| 685 | BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout)); |
| 686 | } |
| 687 | |
| 688 | armnn::DepthToSpaceDescriptor m_Descriptor; |
| 689 | }; |
| 690 | |
| 691 | const std::string layerName("depthToSpace"); |
| 692 | |
| 693 | const armnn::TensorInfo inputInfo ({ 1, 8, 4, 12 }, armnn::DataType::Float32); |
| 694 | const armnn::TensorInfo outputInfo({ 1, 16, 8, 3 }, armnn::DataType::Float32); |
| 695 | |
| 696 | armnn::DepthToSpaceDescriptor desc; |
| 697 | desc.m_BlockSize = 2; |
| 698 | desc.m_DataLayout = armnn::DataLayout::NHWC; |
| 699 | |
| 700 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 701 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 702 | armnn::IConnectableLayer* const depthToSpaceLayer = network->AddDepthToSpaceLayer(desc, layerName.c_str()); |
| 703 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 704 | |
| 705 | inputLayer->GetOutputSlot(0).Connect(depthToSpaceLayer->GetInputSlot(0)); |
| 706 | depthToSpaceLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 707 | |
| 708 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 709 | depthToSpaceLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 710 | |
| 711 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 712 | BOOST_CHECK(deserializedNetwork); |
| 713 | |
| 714 | DepthToSpaceLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc); |
| 715 | deserializedNetwork->Accept(verifier); |
| 716 | } |
| 717 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 718 | BOOST_AUTO_TEST_CASE(SerializeDepthwiseConvolution2d) |
Conor Kennedy | 79ffdf5 | 2019-03-01 14:24:54 +0000 | [diff] [blame] | 719 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 720 | class DepthwiseConvolution2dLayerVerifier : public LayerVerifierBase |
Conor Kennedy | 79ffdf5 | 2019-03-01 14:24:54 +0000 | [diff] [blame] | 721 | { |
| 722 | public: |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 723 | DepthwiseConvolution2dLayerVerifier(const std::string& layerName, |
| 724 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 725 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 726 | const armnn::DepthwiseConvolution2dDescriptor& descriptor, |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 727 | const armnn::ConstTensor& weights, |
| 728 | const armnn::Optional<armnn::ConstTensor>& biases) : |
| 729 | LayerVerifierBase(layerName, inputInfos, outputInfos), |
| 730 | m_Descriptor(descriptor), |
| 731 | m_Weights(weights), |
| 732 | m_Biases(biases) |
| 733 | {} |
Conor Kennedy | 79ffdf5 | 2019-03-01 14:24:54 +0000 | [diff] [blame] | 734 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 735 | void VisitDepthwiseConvolution2dLayer(const armnn::IConnectableLayer* layer, |
| 736 | const armnn::DepthwiseConvolution2dDescriptor& descriptor, |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 737 | const armnn::ConstTensor& weights, |
| 738 | const armnn::Optional<armnn::ConstTensor>& biases, |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 739 | const char* name) override |
| 740 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 741 | VerifyNameAndConnections(layer, name); |
| 742 | VerifyDescriptor(descriptor); |
| 743 | |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 744 | // check weights |
| 745 | CompareConstTensor(weights, m_Weights); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 746 | |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 747 | // check biases |
| 748 | BOOST_CHECK(biases.has_value() == descriptor.m_BiasEnabled); |
| 749 | BOOST_CHECK(m_Biases.has_value() == m_Descriptor.m_BiasEnabled); |
| 750 | |
| 751 | BOOST_CHECK(biases.has_value() == m_Biases.has_value()); |
| 752 | |
| 753 | if (biases.has_value() && m_Biases.has_value()) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 754 | { |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 755 | CompareConstTensor(biases.value(), m_Biases.value()); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 756 | } |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 757 | } |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 758 | |
| 759 | private: |
| 760 | void VerifyDescriptor(const armnn::DepthwiseConvolution2dDescriptor& descriptor) |
| 761 | { |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 762 | BOOST_CHECK(descriptor.m_PadLeft == m_Descriptor.m_PadLeft); |
| 763 | BOOST_CHECK(descriptor.m_PadRight == m_Descriptor.m_PadRight); |
| 764 | BOOST_CHECK(descriptor.m_PadTop == m_Descriptor.m_PadTop); |
| 765 | BOOST_CHECK(descriptor.m_PadBottom == m_Descriptor.m_PadBottom); |
| 766 | BOOST_CHECK(descriptor.m_StrideX == m_Descriptor.m_StrideX); |
| 767 | BOOST_CHECK(descriptor.m_StrideY == m_Descriptor.m_StrideY); |
| 768 | BOOST_CHECK(descriptor.m_DilationX == m_Descriptor.m_DilationX); |
| 769 | BOOST_CHECK(descriptor.m_DilationY == m_Descriptor.m_DilationY); |
| 770 | BOOST_CHECK(descriptor.m_BiasEnabled == m_Descriptor.m_BiasEnabled); |
| 771 | BOOST_CHECK(descriptor.m_DataLayout == m_Descriptor.m_DataLayout); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 772 | } |
| 773 | |
| 774 | armnn::DepthwiseConvolution2dDescriptor m_Descriptor; |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 775 | armnn::ConstTensor m_Weights; |
| 776 | armnn::Optional<armnn::ConstTensor> m_Biases; |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 777 | }; |
| 778 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 779 | const std::string layerName("depwiseConvolution2d"); |
| 780 | const armnn::TensorInfo inputInfo ({ 1, 5, 5, 3 }, armnn::DataType::Float32); |
| 781 | const armnn::TensorInfo outputInfo({ 1, 3, 3, 3 }, armnn::DataType::Float32); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 782 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 783 | const armnn::TensorInfo weightsInfo({ 1, 3, 3, 3 }, armnn::DataType::Float32); |
| 784 | const armnn::TensorInfo biasesInfo ({ 3 }, armnn::DataType::Float32); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 785 | |
| 786 | std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements()); |
| 787 | armnn::ConstTensor weights(weightsInfo, weightsData); |
| 788 | |
| 789 | std::vector<int32_t> biasesData = GenerateRandomData<int32_t>(biasesInfo.GetNumElements()); |
| 790 | armnn::ConstTensor biases(biasesInfo, biasesData); |
| 791 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 792 | armnn::DepthwiseConvolution2dDescriptor descriptor; |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 793 | descriptor.m_PadLeft = 1; |
| 794 | descriptor.m_PadRight = 1; |
| 795 | descriptor.m_PadTop = 1; |
| 796 | descriptor.m_PadBottom = 1; |
| 797 | descriptor.m_StrideX = 2; |
| 798 | descriptor.m_StrideY = 2; |
| 799 | descriptor.m_DilationX = 2; |
| 800 | descriptor.m_DilationY = 2; |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 801 | descriptor.m_BiasEnabled = true; |
| 802 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 803 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 804 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 805 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 806 | armnn::IConnectableLayer* const depthwiseConvLayer = |
Matteo Martincigh | fc598e1 | 2019-05-14 10:36:13 +0100 | [diff] [blame] | 807 | network->AddDepthwiseConvolution2dLayer(descriptor, |
| 808 | weights, |
| 809 | armnn::Optional<armnn::ConstTensor>(biases), |
| 810 | layerName.c_str()); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 811 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 812 | |
| 813 | inputLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(0)); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 814 | depthwiseConvLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 815 | |
| 816 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 817 | depthwiseConvLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 818 | |
| 819 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 820 | BOOST_CHECK(deserializedNetwork); |
| 821 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 822 | DepthwiseConvolution2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases); |
| 823 | deserializedNetwork->Accept(verifier); |
Jim Flynn | 18ce338 | 2019-03-08 11:08:30 +0000 | [diff] [blame] | 824 | } |
| 825 | |
Nattapat Chaimanowong | e4294fd | 2019-03-28 09:56:53 +0000 | [diff] [blame] | 826 | BOOST_AUTO_TEST_CASE(SerializeDequantize) |
| 827 | { |
| 828 | class DequantizeLayerVerifier : public LayerVerifierBase |
| 829 | { |
| 830 | public: |
| 831 | DequantizeLayerVerifier(const std::string& layerName, |
| 832 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 833 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 834 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 835 | |
| 836 | void VisitDequantizeLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 837 | { |
| 838 | VerifyNameAndConnections(layer, name); |
| 839 | } |
| 840 | }; |
| 841 | |
| 842 | const std::string layerName("dequantize"); |
| 843 | const armnn::TensorInfo inputInfo({ 1, 5, 2, 3 }, armnn::DataType::QuantisedAsymm8, 0.5f, 1); |
| 844 | const armnn::TensorInfo outputInfo({ 1, 5, 2, 3 }, armnn::DataType::Float32); |
| 845 | |
| 846 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 847 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 848 | armnn::IConnectableLayer* const dequantizeLayer = network->AddDequantizeLayer(layerName.c_str()); |
| 849 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 850 | |
| 851 | inputLayer->GetOutputSlot(0).Connect(dequantizeLayer->GetInputSlot(0)); |
| 852 | dequantizeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 853 | |
| 854 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 855 | dequantizeLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 856 | |
| 857 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 858 | BOOST_CHECK(deserializedNetwork); |
| 859 | |
| 860 | DequantizeLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}); |
| 861 | deserializedNetwork->Accept(verifier); |
| 862 | } |
| 863 | |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 864 | BOOST_AUTO_TEST_CASE(SerializeDeserializeDetectionPostProcess) |
| 865 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 866 | class DetectionPostProcessLayerVerifier : public LayerVerifierBase |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 867 | { |
| 868 | public: |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 869 | DetectionPostProcessLayerVerifier(const std::string& layerName, |
| 870 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 871 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 872 | const armnn::DetectionPostProcessDescriptor& descriptor, |
| 873 | const armnn::ConstTensor& anchors) |
| 874 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 875 | , m_Descriptor(descriptor) |
| 876 | , m_Anchors(anchors) {} |
| 877 | |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 878 | void VisitDetectionPostProcessLayer(const armnn::IConnectableLayer* layer, |
| 879 | const armnn::DetectionPostProcessDescriptor& descriptor, |
| 880 | const armnn::ConstTensor& anchors, |
| 881 | const char* name) override |
| 882 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 883 | VerifyNameAndConnections(layer, name); |
| 884 | VerifyDescriptor(descriptor); |
| 885 | |
| 886 | CompareConstTensor(anchors, m_Anchors); |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 887 | } |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 888 | |
| 889 | private: |
| 890 | void VerifyDescriptor(const armnn::DetectionPostProcessDescriptor& descriptor) |
| 891 | { |
| 892 | BOOST_TEST(descriptor.m_UseRegularNms == m_Descriptor.m_UseRegularNms); |
| 893 | BOOST_TEST(descriptor.m_MaxDetections == m_Descriptor.m_MaxDetections); |
| 894 | BOOST_TEST(descriptor.m_MaxClassesPerDetection == m_Descriptor.m_MaxClassesPerDetection); |
| 895 | BOOST_TEST(descriptor.m_DetectionsPerClass == m_Descriptor.m_DetectionsPerClass); |
| 896 | BOOST_TEST(descriptor.m_NmsScoreThreshold == m_Descriptor.m_NmsScoreThreshold); |
| 897 | BOOST_TEST(descriptor.m_NmsIouThreshold == m_Descriptor.m_NmsIouThreshold); |
| 898 | BOOST_TEST(descriptor.m_NumClasses == m_Descriptor.m_NumClasses); |
| 899 | BOOST_TEST(descriptor.m_ScaleY == m_Descriptor.m_ScaleY); |
| 900 | BOOST_TEST(descriptor.m_ScaleX == m_Descriptor.m_ScaleX); |
| 901 | BOOST_TEST(descriptor.m_ScaleH == m_Descriptor.m_ScaleH); |
| 902 | BOOST_TEST(descriptor.m_ScaleW == m_Descriptor.m_ScaleW); |
| 903 | } |
| 904 | |
| 905 | armnn::DetectionPostProcessDescriptor m_Descriptor; |
| 906 | armnn::ConstTensor m_Anchors; |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 907 | }; |
| 908 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 909 | const std::string layerName("detectionPostProcess"); |
| 910 | |
| 911 | const std::vector<armnn::TensorInfo> inputInfos({ |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 912 | armnn::TensorInfo({ 1, 6, 4 }, armnn::DataType::Float32), |
| 913 | armnn::TensorInfo({ 1, 6, 3}, armnn::DataType::Float32) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 914 | }); |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 915 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 916 | const std::vector<armnn::TensorInfo> outputInfos({ |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 917 | armnn::TensorInfo({ 1, 3, 4 }, armnn::DataType::Float32), |
| 918 | armnn::TensorInfo({ 1, 3 }, armnn::DataType::Float32), |
| 919 | armnn::TensorInfo({ 1, 3 }, armnn::DataType::Float32), |
| 920 | armnn::TensorInfo({ 1 }, armnn::DataType::Float32) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 921 | }); |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 922 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 923 | armnn::DetectionPostProcessDescriptor descriptor; |
| 924 | descriptor.m_UseRegularNms = true; |
| 925 | descriptor.m_MaxDetections = 3; |
| 926 | descriptor.m_MaxClassesPerDetection = 1; |
| 927 | descriptor.m_DetectionsPerClass =1; |
| 928 | descriptor.m_NmsScoreThreshold = 0.0; |
| 929 | descriptor.m_NmsIouThreshold = 0.5; |
| 930 | descriptor.m_NumClasses = 2; |
| 931 | descriptor.m_ScaleY = 10.0; |
| 932 | descriptor.m_ScaleX = 10.0; |
| 933 | descriptor.m_ScaleH = 5.0; |
| 934 | descriptor.m_ScaleW = 5.0; |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 935 | |
| 936 | const armnn::TensorInfo anchorsInfo({ 6, 4 }, armnn::DataType::Float32); |
| 937 | const std::vector<float> anchorsData({ |
| 938 | 0.5f, 0.5f, 1.0f, 1.0f, |
| 939 | 0.5f, 0.5f, 1.0f, 1.0f, |
| 940 | 0.5f, 0.5f, 1.0f, 1.0f, |
| 941 | 0.5f, 10.5f, 1.0f, 1.0f, |
| 942 | 0.5f, 10.5f, 1.0f, 1.0f, |
| 943 | 0.5f, 100.5f, 1.0f, 1.0f |
| 944 | }); |
| 945 | armnn::ConstTensor anchors(anchorsInfo, anchorsData); |
| 946 | |
| 947 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 948 | armnn::IConnectableLayer* const detectionLayer = |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 949 | network->AddDetectionPostProcessLayer(descriptor, anchors, layerName.c_str()); |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 950 | |
| 951 | for (unsigned int i = 0; i < 2; i++) |
| 952 | { |
| 953 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(static_cast<int>(i)); |
| 954 | inputLayer->GetOutputSlot(0).Connect(detectionLayer->GetInputSlot(i)); |
| 955 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfos[i]); |
| 956 | } |
| 957 | |
| 958 | for (unsigned int i = 0; i < 4; i++) |
| 959 | { |
| 960 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(static_cast<int>(i)); |
| 961 | detectionLayer->GetOutputSlot(i).Connect(outputLayer->GetInputSlot(0)); |
| 962 | detectionLayer->GetOutputSlot(i).SetTensorInfo(outputInfos[i]); |
| 963 | } |
| 964 | |
| 965 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 966 | BOOST_CHECK(deserializedNetwork); |
| 967 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 968 | DetectionPostProcessLayerVerifier verifier(layerName, inputInfos, outputInfos, descriptor, anchors); |
| 969 | deserializedNetwork->Accept(verifier); |
| 970 | } |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 971 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 972 | BOOST_AUTO_TEST_CASE(SerializeDivision) |
| 973 | { |
| 974 | class DivisionLayerVerifier : public LayerVerifierBase |
| 975 | { |
| 976 | public: |
| 977 | DivisionLayerVerifier(const std::string& layerName, |
| 978 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 979 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 980 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 981 | |
| 982 | void VisitDivisionLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 983 | { |
| 984 | VerifyNameAndConnections(layer, name); |
| 985 | } |
| 986 | }; |
| 987 | |
| 988 | const std::string layerName("division"); |
| 989 | const armnn::TensorInfo info({ 1, 5, 2, 3 }, armnn::DataType::Float32); |
| 990 | |
| 991 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 992 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 993 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 994 | armnn::IConnectableLayer* const divisionLayer = network->AddDivisionLayer(layerName.c_str()); |
| 995 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 996 | |
| 997 | inputLayer0->GetOutputSlot(0).Connect(divisionLayer->GetInputSlot(0)); |
| 998 | inputLayer1->GetOutputSlot(0).Connect(divisionLayer->GetInputSlot(1)); |
| 999 | divisionLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1000 | |
| 1001 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 1002 | inputLayer1->GetOutputSlot(0).SetTensorInfo(info); |
| 1003 | divisionLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1004 | |
| 1005 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1006 | BOOST_CHECK(deserializedNetwork); |
| 1007 | |
| 1008 | DivisionLayerVerifier verifier(layerName, {info, info}, {info}); |
| 1009 | deserializedNetwork->Accept(verifier); |
| 1010 | } |
| 1011 | |
| 1012 | BOOST_AUTO_TEST_CASE(SerializeEqual) |
| 1013 | { |
| 1014 | class EqualLayerVerifier : public LayerVerifierBase |
| 1015 | { |
| 1016 | public: |
| 1017 | EqualLayerVerifier(const std::string& layerName, |
| 1018 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1019 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 1020 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 1021 | |
| 1022 | void VisitEqualLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 1023 | { |
| 1024 | VerifyNameAndConnections(layer, name); |
| 1025 | } |
| 1026 | }; |
| 1027 | |
| 1028 | const std::string layerName("equal"); |
| 1029 | const armnn::TensorInfo inputTensorInfo1 = armnn::TensorInfo({2, 1, 2, 4}, armnn::DataType::Float32); |
| 1030 | const armnn::TensorInfo inputTensorInfo2 = armnn::TensorInfo({2, 1, 2, 4}, armnn::DataType::Float32); |
| 1031 | const armnn::TensorInfo outputTensorInfo = armnn::TensorInfo({2, 1, 2, 4}, armnn::DataType::Boolean); |
| 1032 | |
| 1033 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1034 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(0); |
| 1035 | armnn::IConnectableLayer* const inputLayer2 = network->AddInputLayer(1); |
| 1036 | armnn::IConnectableLayer* const equalLayer = network->AddEqualLayer(layerName.c_str()); |
| 1037 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1038 | |
| 1039 | inputLayer1->GetOutputSlot(0).Connect(equalLayer->GetInputSlot(0)); |
| 1040 | inputLayer2->GetOutputSlot(0).Connect(equalLayer->GetInputSlot(1)); |
| 1041 | equalLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1042 | |
| 1043 | inputLayer1->GetOutputSlot(0).SetTensorInfo(inputTensorInfo1); |
| 1044 | inputLayer2->GetOutputSlot(0).SetTensorInfo(inputTensorInfo2); |
| 1045 | equalLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| 1046 | |
| 1047 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1048 | BOOST_CHECK(deserializedNetwork); |
| 1049 | |
| 1050 | EqualLayerVerifier verifier(layerName, {inputTensorInfo1, inputTensorInfo2}, {outputTensorInfo}); |
| 1051 | deserializedNetwork->Accept(verifier); |
| 1052 | } |
| 1053 | |
| 1054 | BOOST_AUTO_TEST_CASE(SerializeFloor) |
| 1055 | { |
| 1056 | class FloorLayerVerifier : public LayerVerifierBase |
| 1057 | { |
| 1058 | public: |
| 1059 | FloorLayerVerifier(const std::string& layerName, |
| 1060 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1061 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 1062 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 1063 | |
| 1064 | void VisitFloorLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 1065 | { |
| 1066 | VerifyNameAndConnections(layer, name); |
| 1067 | } |
| 1068 | }; |
| 1069 | |
| 1070 | const std::string layerName("floor"); |
| 1071 | const armnn::TensorInfo info({4,4}, armnn::DataType::Float32); |
| 1072 | |
| 1073 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1074 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 1075 | armnn::IConnectableLayer* const floorLayer = network->AddFloorLayer(layerName.c_str()); |
| 1076 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1077 | |
| 1078 | inputLayer->GetOutputSlot(0).Connect(floorLayer->GetInputSlot(0)); |
| 1079 | floorLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1080 | |
| 1081 | inputLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1082 | floorLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1083 | |
| 1084 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1085 | BOOST_CHECK(deserializedNetwork); |
| 1086 | |
| 1087 | FloorLayerVerifier verifier(layerName, {info}, {info}); |
| 1088 | deserializedNetwork->Accept(verifier); |
| 1089 | } |
| 1090 | |
| 1091 | BOOST_AUTO_TEST_CASE(SerializeFullyConnected) |
| 1092 | { |
| 1093 | class FullyConnectedLayerVerifier : public LayerVerifierBase |
| 1094 | { |
| 1095 | public: |
| 1096 | FullyConnectedLayerVerifier(const std::string& layerName, |
| 1097 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1098 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 1099 | const armnn::FullyConnectedDescriptor& descriptor, |
| 1100 | const armnn::ConstTensor& weight, |
| 1101 | const armnn::Optional<armnn::ConstTensor>& bias) |
| 1102 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 1103 | , m_Descriptor(descriptor) |
| 1104 | , m_Weight(weight) |
| 1105 | , m_Bias(bias) {} |
| 1106 | |
| 1107 | void VisitFullyConnectedLayer(const armnn::IConnectableLayer* layer, |
| 1108 | const armnn::FullyConnectedDescriptor& descriptor, |
| 1109 | const armnn::ConstTensor& weight, |
| 1110 | const armnn::Optional<armnn::ConstTensor>& bias, |
| 1111 | const char* name) override |
| 1112 | { |
| 1113 | VerifyNameAndConnections(layer, name); |
| 1114 | VerifyDescriptor(descriptor); |
| 1115 | |
| 1116 | CompareConstTensor(weight, m_Weight); |
| 1117 | |
| 1118 | BOOST_TEST(bias.has_value() == m_Bias.has_value()); |
| 1119 | if (bias.has_value() && m_Bias.has_value()) |
| 1120 | { |
| 1121 | CompareConstTensor(bias.value(), m_Bias.value()); |
| 1122 | } |
| 1123 | } |
| 1124 | |
| 1125 | private: |
| 1126 | void VerifyDescriptor(const armnn::FullyConnectedDescriptor& descriptor) |
| 1127 | { |
| 1128 | BOOST_TEST(descriptor.m_BiasEnabled == m_Descriptor.m_BiasEnabled); |
| 1129 | BOOST_TEST(descriptor.m_TransposeWeightMatrix == m_Descriptor.m_TransposeWeightMatrix); |
| 1130 | } |
| 1131 | |
| 1132 | armnn::FullyConnectedDescriptor m_Descriptor; |
| 1133 | armnn::ConstTensor m_Weight; |
| 1134 | armnn::Optional<armnn::ConstTensor> m_Bias; |
| 1135 | }; |
| 1136 | |
| 1137 | const std::string layerName("fullyConnected"); |
| 1138 | const armnn::TensorInfo inputInfo ({ 2, 5, 1, 1 }, armnn::DataType::Float32); |
| 1139 | const armnn::TensorInfo outputInfo({ 2, 3 }, armnn::DataType::Float32); |
| 1140 | |
| 1141 | const armnn::TensorInfo weightsInfo({ 5, 3 }, armnn::DataType::Float32); |
| 1142 | const armnn::TensorInfo biasesInfo ({ 3 }, armnn::DataType::Float32); |
| 1143 | std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements()); |
| 1144 | std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements()); |
| 1145 | armnn::ConstTensor weights(weightsInfo, weightsData); |
| 1146 | armnn::ConstTensor biases(biasesInfo, biasesData); |
| 1147 | |
| 1148 | armnn::FullyConnectedDescriptor descriptor; |
| 1149 | descriptor.m_BiasEnabled = true; |
| 1150 | descriptor.m_TransposeWeightMatrix = false; |
| 1151 | |
| 1152 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1153 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 1154 | armnn::IConnectableLayer* const fullyConnectedLayer = |
Matteo Martincigh | fc598e1 | 2019-05-14 10:36:13 +0100 | [diff] [blame] | 1155 | network->AddFullyConnectedLayer(descriptor, |
| 1156 | weights, |
| 1157 | armnn::Optional<armnn::ConstTensor>(biases), |
| 1158 | layerName.c_str()); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1159 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1160 | |
| 1161 | inputLayer->GetOutputSlot(0).Connect(fullyConnectedLayer->GetInputSlot(0)); |
| 1162 | fullyConnectedLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1163 | |
| 1164 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1165 | fullyConnectedLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 1166 | |
| 1167 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1168 | BOOST_CHECK(deserializedNetwork); |
| 1169 | |
| 1170 | FullyConnectedLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases); |
| 1171 | deserializedNetwork->Accept(verifier); |
| 1172 | } |
| 1173 | |
| 1174 | BOOST_AUTO_TEST_CASE(SerializeGather) |
| 1175 | { |
| 1176 | class GatherLayerVerifier : public LayerVerifierBase |
| 1177 | { |
| 1178 | public: |
| 1179 | GatherLayerVerifier(const std::string& layerName, |
| 1180 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1181 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 1182 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 1183 | |
| 1184 | void VisitGatherLayer(const armnn::IConnectableLayer* layer, const char *name) override |
| 1185 | { |
| 1186 | VerifyNameAndConnections(layer, name); |
| 1187 | } |
| 1188 | |
| 1189 | void VisitConstantLayer(const armnn::IConnectableLayer* layer, |
| 1190 | const armnn::ConstTensor& input, |
| 1191 | const char *name) override {} |
| 1192 | }; |
| 1193 | |
| 1194 | const std::string layerName("gather"); |
| 1195 | armnn::TensorInfo paramsInfo({ 8 }, armnn::DataType::QuantisedAsymm8); |
| 1196 | armnn::TensorInfo outputInfo({ 3 }, armnn::DataType::QuantisedAsymm8); |
| 1197 | const armnn::TensorInfo indicesInfo({ 3 }, armnn::DataType::Signed32); |
| 1198 | |
| 1199 | paramsInfo.SetQuantizationScale(1.0f); |
| 1200 | paramsInfo.SetQuantizationOffset(0); |
| 1201 | outputInfo.SetQuantizationScale(1.0f); |
| 1202 | outputInfo.SetQuantizationOffset(0); |
| 1203 | |
| 1204 | const std::vector<int32_t>& indicesData = {7, 6, 5}; |
| 1205 | |
| 1206 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1207 | armnn::IConnectableLayer *const inputLayer = network->AddInputLayer(0); |
| 1208 | armnn::IConnectableLayer *const constantLayer = |
| 1209 | network->AddConstantLayer(armnn::ConstTensor(indicesInfo, indicesData)); |
| 1210 | armnn::IConnectableLayer *const gatherLayer = network->AddGatherLayer(layerName.c_str()); |
| 1211 | armnn::IConnectableLayer *const outputLayer = network->AddOutputLayer(0); |
| 1212 | |
| 1213 | inputLayer->GetOutputSlot(0).Connect(gatherLayer->GetInputSlot(0)); |
| 1214 | constantLayer->GetOutputSlot(0).Connect(gatherLayer->GetInputSlot(1)); |
| 1215 | gatherLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1216 | |
| 1217 | inputLayer->GetOutputSlot(0).SetTensorInfo(paramsInfo); |
| 1218 | constantLayer->GetOutputSlot(0).SetTensorInfo(indicesInfo); |
| 1219 | gatherLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 1220 | |
| 1221 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1222 | BOOST_CHECK(deserializedNetwork); |
| 1223 | |
| 1224 | GatherLayerVerifier verifier(layerName, {paramsInfo, indicesInfo}, {outputInfo}); |
| 1225 | deserializedNetwork->Accept(verifier); |
| 1226 | } |
| 1227 | |
| 1228 | BOOST_AUTO_TEST_CASE(SerializeGreater) |
| 1229 | { |
| 1230 | class GreaterLayerVerifier : public LayerVerifierBase |
| 1231 | { |
| 1232 | public: |
| 1233 | GreaterLayerVerifier(const std::string& layerName, |
| 1234 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1235 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 1236 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 1237 | |
| 1238 | void VisitGreaterLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 1239 | { |
| 1240 | VerifyNameAndConnections(layer, name); |
| 1241 | } |
| 1242 | }; |
| 1243 | |
| 1244 | const std::string layerName("greater"); |
| 1245 | const armnn::TensorInfo inputTensorInfo1({ 1, 2, 2, 2 }, armnn::DataType::Float32); |
| 1246 | const armnn::TensorInfo inputTensorInfo2({ 1, 2, 2, 2 }, armnn::DataType::Float32); |
| 1247 | const armnn::TensorInfo outputTensorInfo({ 1, 2, 2, 2 }, armnn::DataType::Boolean); |
| 1248 | |
| 1249 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1250 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(0); |
| 1251 | armnn::IConnectableLayer* const inputLayer2 = network->AddInputLayer(1); |
| 1252 | armnn::IConnectableLayer* const greaterLayer = network->AddGreaterLayer(layerName.c_str()); |
| 1253 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1254 | |
| 1255 | inputLayer1->GetOutputSlot(0).Connect(greaterLayer->GetInputSlot(0)); |
| 1256 | inputLayer2->GetOutputSlot(0).Connect(greaterLayer->GetInputSlot(1)); |
| 1257 | greaterLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1258 | |
| 1259 | inputLayer1->GetOutputSlot(0).SetTensorInfo(inputTensorInfo1); |
| 1260 | inputLayer2->GetOutputSlot(0).SetTensorInfo(inputTensorInfo2); |
| 1261 | greaterLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| 1262 | |
| 1263 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1264 | BOOST_CHECK(deserializedNetwork); |
| 1265 | |
| 1266 | GreaterLayerVerifier verifier(layerName, {inputTensorInfo1, inputTensorInfo2}, {outputTensorInfo}); |
| 1267 | deserializedNetwork->Accept(verifier); |
| 1268 | } |
| 1269 | |
Aron Virginas-Tar | 781ced9 | 2019-10-03 11:15:39 +0100 | [diff] [blame^] | 1270 | BOOST_AUTO_TEST_CASE(SerializeInstanceNormalization) |
| 1271 | { |
| 1272 | class InstanceNormalizationLayerVerifier : public LayerVerifierBase |
| 1273 | { |
| 1274 | public: |
| 1275 | InstanceNormalizationLayerVerifier(const std::string& layerName, |
| 1276 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1277 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 1278 | const armnn::InstanceNormalizationDescriptor& descriptor) |
| 1279 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 1280 | , m_Descriptor(descriptor) {} |
| 1281 | |
| 1282 | void VisitInstanceNormalizationLayer(const armnn::IConnectableLayer* layer, |
| 1283 | const armnn::InstanceNormalizationDescriptor& descriptor, |
| 1284 | const char* name) override |
| 1285 | { |
| 1286 | VerifyNameAndConnections(layer, name); |
| 1287 | VerifyDescriptor(descriptor); |
| 1288 | } |
| 1289 | |
| 1290 | private: |
| 1291 | void VerifyDescriptor(const armnn::InstanceNormalizationDescriptor& descriptor) |
| 1292 | { |
| 1293 | BOOST_CHECK(descriptor.m_Gamma == m_Descriptor.m_Gamma); |
| 1294 | BOOST_CHECK(descriptor.m_Beta == m_Descriptor.m_Beta); |
| 1295 | BOOST_CHECK(descriptor.m_Eps == m_Descriptor.m_Eps); |
| 1296 | BOOST_CHECK(descriptor.m_DataLayout == m_Descriptor.m_DataLayout); |
| 1297 | } |
| 1298 | |
| 1299 | armnn::InstanceNormalizationDescriptor m_Descriptor; |
| 1300 | }; |
| 1301 | |
| 1302 | const std::string layerName("instanceNormalization"); |
| 1303 | const armnn::TensorInfo info({ 1, 2, 1, 5 }, armnn::DataType::Float32); |
| 1304 | |
| 1305 | armnn::InstanceNormalizationDescriptor descriptor; |
| 1306 | descriptor.m_Gamma = 1.1f; |
| 1307 | descriptor.m_Beta = 0.1f; |
| 1308 | descriptor.m_Eps = 0.0001f; |
| 1309 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 1310 | |
| 1311 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1312 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 1313 | armnn::IConnectableLayer* const instanceNormLayer = |
| 1314 | network->AddInstanceNormalizationLayer(descriptor, layerName.c_str()); |
| 1315 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1316 | |
| 1317 | inputLayer->GetOutputSlot(0).Connect(instanceNormLayer->GetInputSlot(0)); |
| 1318 | instanceNormLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1319 | |
| 1320 | inputLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1321 | instanceNormLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1322 | |
| 1323 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1324 | BOOST_CHECK(deserializedNetwork); |
| 1325 | |
| 1326 | InstanceNormalizationLayerVerifier verifier(layerName, {info}, {info}, descriptor); |
| 1327 | deserializedNetwork->Accept(verifier); |
| 1328 | } |
| 1329 | |
Ferran Balaguer | 0dcffec | 2019-06-18 16:25:06 +0100 | [diff] [blame] | 1330 | class L2NormalizationLayerVerifier : public LayerVerifierBase |
| 1331 | { |
| 1332 | public: |
| 1333 | L2NormalizationLayerVerifier(const std::string& layerName, |
| 1334 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1335 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 1336 | const armnn::L2NormalizationDescriptor& descriptor) |
| 1337 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 1338 | , m_Descriptor(descriptor) {} |
| 1339 | |
| 1340 | void VisitL2NormalizationLayer(const armnn::IConnectableLayer* layer, |
| 1341 | const armnn::L2NormalizationDescriptor& descriptor, |
| 1342 | const char* name) override |
| 1343 | { |
| 1344 | VerifyNameAndConnections(layer, name); |
| 1345 | VerifyDescriptor(descriptor); |
| 1346 | } |
| 1347 | private: |
| 1348 | void VerifyDescriptor(const armnn::L2NormalizationDescriptor& descriptor) |
| 1349 | { |
| 1350 | BOOST_TEST(descriptor.m_Eps == m_Descriptor.m_Eps); |
| 1351 | BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout)); |
| 1352 | } |
| 1353 | |
| 1354 | armnn::L2NormalizationDescriptor m_Descriptor; |
| 1355 | }; |
| 1356 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1357 | BOOST_AUTO_TEST_CASE(SerializeL2Normalization) |
| 1358 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1359 | const std::string l2NormLayerName("l2Normalization"); |
| 1360 | const armnn::TensorInfo info({1, 2, 1, 5}, armnn::DataType::Float32); |
| 1361 | |
| 1362 | armnn::L2NormalizationDescriptor desc; |
| 1363 | desc.m_DataLayout = armnn::DataLayout::NCHW; |
Ferran Balaguer | 0dcffec | 2019-06-18 16:25:06 +0100 | [diff] [blame] | 1364 | desc.m_Eps = 0.0001f; |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1365 | |
| 1366 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1367 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 1368 | armnn::IConnectableLayer* const l2NormLayer = network->AddL2NormalizationLayer(desc, l2NormLayerName.c_str()); |
| 1369 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1370 | |
| 1371 | inputLayer0->GetOutputSlot(0).Connect(l2NormLayer->GetInputSlot(0)); |
| 1372 | l2NormLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1373 | |
| 1374 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 1375 | l2NormLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1376 | |
| 1377 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1378 | BOOST_CHECK(deserializedNetwork); |
| 1379 | |
| 1380 | L2NormalizationLayerVerifier verifier(l2NormLayerName, {info}, {info}, desc); |
| 1381 | deserializedNetwork->Accept(verifier); |
| 1382 | } |
| 1383 | |
Ferran Balaguer | 0dcffec | 2019-06-18 16:25:06 +0100 | [diff] [blame] | 1384 | BOOST_AUTO_TEST_CASE(EnsureL2NormalizationBackwardCompatibility) |
| 1385 | { |
| 1386 | // The hex array below is a flat buffer containing a simple network with one input |
| 1387 | // a L2Normalization layer and an output layer with dimensions as per the tensor infos below. |
| 1388 | // |
| 1389 | // This test verifies that we can still read back these old style |
| 1390 | // models without the normalization epsilon value. |
| 1391 | unsigned int size = 508; |
| 1392 | const unsigned char l2NormalizationModel[] = { |
| 1393 | 0x10,0x00,0x00,0x00,0x00,0x00,0x0A,0x00,0x10,0x00,0x04,0x00,0x08,0x00,0x0C,0x00,0x0A,0x00,0x00,0x00, |
| 1394 | 0x0C,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x1C,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x3C,0x01,0x00,0x00, |
| 1395 | 0x74,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 1396 | 0x02,0x00,0x00,0x00,0xE8,0xFE,0xFF,0xFF,0x00,0x00,0x00,0x0B,0x04,0x00,0x00,0x00,0xD6,0xFE,0xFF,0xFF, |
| 1397 | 0x0C,0x00,0x00,0x00,0x00,0x00,0x06,0x00,0x08,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00, |
| 1398 | 0x9E,0xFF,0xFF,0xFF,0x02,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x10,0x00,0x00,0x00, |
| 1399 | 0x14,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00, |
| 1400 | 0x00,0x00,0x00,0x00,0x4C,0xFF,0xFF,0xFF,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x44,0xFF,0xFF,0xFF, |
| 1401 | 0x00,0x00,0x00,0x20,0x0C,0x00,0x00,0x00,0x08,0x00,0x0C,0x00,0x04,0x00,0x08,0x00,0x08,0x00,0x00,0x00, |
| 1402 | 0x20,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x04,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x00,0x00,0x0E,0x00, |
| 1403 | 0x18,0x00,0x04,0x00,0x08,0x00,0x0C,0x00,0x10,0x00,0x14,0x00,0x0E,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 1404 | 0x10,0x00,0x00,0x00,0x1F,0x00,0x00,0x00,0x1C,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x0F,0x00,0x00,0x00, |
| 1405 | 0x6C,0x32,0x4E,0x6F,0x72,0x6D,0x61,0x6C,0x69,0x7A,0x61,0x74,0x69,0x6F,0x6E,0x00,0x01,0x00,0x00,0x00, |
| 1406 | 0x48,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0C,0x00,0x00,0x00,0x08,0x00,0x08,0x00,0x00,0x00,0x04,0x00, |
| 1407 | 0x08,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x52,0xFF,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00, |
| 1408 | 0x00,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 1409 | 0x05,0x00,0x00,0x00,0x08,0x00,0x0C,0x00,0x00,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 1410 | 0x00,0x00,0x00,0x00,0x08,0x00,0x0C,0x00,0x07,0x00,0x08,0x00,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x09, |
| 1411 | 0x04,0x00,0x00,0x00,0xF6,0xFF,0xFF,0xFF,0x0C,0x00,0x00,0x00,0x00,0x00,0x06,0x00,0x0A,0x00,0x04,0x00, |
| 1412 | 0x06,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x00,0x00,0x0E,0x00,0x14,0x00,0x00,0x00,0x04,0x00,0x08,0x00, |
| 1413 | 0x0C,0x00,0x10,0x00,0x0E,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x10,0x00,0x00,0x00, |
| 1414 | 0x10,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 1415 | 0x0C,0x00,0x00,0x00,0x08,0x00,0x0A,0x00,0x00,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x10,0x00,0x00,0x00, |
| 1416 | 0x00,0x00,0x0A,0x00,0x10,0x00,0x08,0x00,0x07,0x00,0x0C,0x00,0x0A,0x00,0x00,0x00,0x00,0x00,0x00,0x01, |
| 1417 | 0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00, |
| 1418 | 0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0 }; |
| 1419 | |
| 1420 | std::stringstream ss; |
| 1421 | for (unsigned int i = 0; i < size; ++i) |
| 1422 | { |
| 1423 | ss << l2NormalizationModel[i]; |
| 1424 | } |
| 1425 | std::string l2NormalizationLayerNetwork = ss.str(); |
| 1426 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(l2NormalizationLayerNetwork); |
| 1427 | BOOST_CHECK(deserializedNetwork); |
| 1428 | const std::string layerName("l2Normalization"); |
| 1429 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({1, 2, 1, 5}, armnn::DataType::Float32); |
| 1430 | |
| 1431 | armnn::L2NormalizationDescriptor desc; |
| 1432 | desc.m_DataLayout = armnn::DataLayout::NCHW; |
| 1433 | // Since this variable does not exist in the l2NormalizationModel[] dump, the default value will be loaded. |
| 1434 | desc.m_Eps = 1e-12f; |
| 1435 | |
| 1436 | L2NormalizationLayerVerifier verifier(layerName, {inputInfo}, {inputInfo}, desc); |
| 1437 | deserializedNetwork->Accept(verifier); |
| 1438 | } |
| 1439 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1440 | BOOST_AUTO_TEST_CASE(SerializeMaximum) |
| 1441 | { |
| 1442 | class MaximumLayerVerifier : public LayerVerifierBase |
| 1443 | { |
| 1444 | public: |
| 1445 | MaximumLayerVerifier(const std::string& layerName, |
| 1446 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1447 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 1448 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 1449 | |
| 1450 | void VisitMaximumLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 1451 | { |
| 1452 | VerifyNameAndConnections(layer, name); |
| 1453 | } |
| 1454 | }; |
| 1455 | |
| 1456 | const std::string layerName("maximum"); |
| 1457 | const armnn::TensorInfo info({ 1, 2, 2, 3 }, armnn::DataType::Float32); |
| 1458 | |
| 1459 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1460 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 1461 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 1462 | armnn::IConnectableLayer* const maximumLayer = network->AddMaximumLayer(layerName.c_str()); |
| 1463 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1464 | |
| 1465 | inputLayer0->GetOutputSlot(0).Connect(maximumLayer->GetInputSlot(0)); |
| 1466 | inputLayer1->GetOutputSlot(0).Connect(maximumLayer->GetInputSlot(1)); |
| 1467 | maximumLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1468 | |
| 1469 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 1470 | inputLayer1->GetOutputSlot(0).SetTensorInfo(info); |
| 1471 | maximumLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1472 | |
| 1473 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1474 | BOOST_CHECK(deserializedNetwork); |
| 1475 | |
| 1476 | MaximumLayerVerifier verifier(layerName, {info, info}, {info}); |
| 1477 | deserializedNetwork->Accept(verifier); |
| 1478 | } |
| 1479 | |
| 1480 | BOOST_AUTO_TEST_CASE(SerializeMean) |
| 1481 | { |
| 1482 | class MeanLayerVerifier : public LayerVerifierBase |
| 1483 | { |
| 1484 | public: |
| 1485 | MeanLayerVerifier(const std::string& layerName, |
| 1486 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1487 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 1488 | const armnn::MeanDescriptor& descriptor) |
| 1489 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 1490 | , m_Descriptor(descriptor) {} |
| 1491 | |
| 1492 | void VisitMeanLayer(const armnn::IConnectableLayer* layer, |
| 1493 | const armnn::MeanDescriptor& descriptor, |
| 1494 | const char* name) override |
| 1495 | { |
| 1496 | VerifyNameAndConnections(layer, name); |
| 1497 | VerifyDescriptor(descriptor); |
| 1498 | } |
| 1499 | |
| 1500 | private: |
| 1501 | void VerifyDescriptor(const armnn::MeanDescriptor& descriptor) |
| 1502 | { |
| 1503 | BOOST_TEST(descriptor.m_Axis == m_Descriptor.m_Axis); |
| 1504 | BOOST_TEST(descriptor.m_KeepDims == m_Descriptor.m_KeepDims); |
| 1505 | } |
| 1506 | |
| 1507 | armnn::MeanDescriptor m_Descriptor; |
| 1508 | }; |
| 1509 | |
| 1510 | const std::string layerName("mean"); |
| 1511 | const armnn::TensorInfo inputInfo({1, 1, 3, 2}, armnn::DataType::Float32); |
| 1512 | const armnn::TensorInfo outputInfo({1, 1, 1, 2}, armnn::DataType::Float32); |
| 1513 | |
| 1514 | armnn::MeanDescriptor descriptor; |
| 1515 | descriptor.m_Axis = { 2 }; |
| 1516 | descriptor.m_KeepDims = true; |
| 1517 | |
| 1518 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1519 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 1520 | armnn::IConnectableLayer* const meanLayer = network->AddMeanLayer(descriptor, layerName.c_str()); |
| 1521 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1522 | |
| 1523 | inputLayer->GetOutputSlot(0).Connect(meanLayer->GetInputSlot(0)); |
| 1524 | meanLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1525 | |
| 1526 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1527 | meanLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 1528 | |
| 1529 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1530 | BOOST_CHECK(deserializedNetwork); |
| 1531 | |
| 1532 | MeanLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor); |
| 1533 | deserializedNetwork->Accept(verifier); |
| 1534 | } |
| 1535 | |
Nattapat Chaimanowong | 1f88630 | 2019-04-05 13:37:19 +0100 | [diff] [blame] | 1536 | BOOST_AUTO_TEST_CASE(SerializeMerge) |
| 1537 | { |
| 1538 | class MergeLayerVerifier : public LayerVerifierBase |
| 1539 | { |
| 1540 | public: |
| 1541 | MergeLayerVerifier(const std::string& layerName, |
| 1542 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1543 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 1544 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 1545 | |
| 1546 | void VisitMergeLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 1547 | { |
| 1548 | VerifyNameAndConnections(layer, name); |
| 1549 | } |
| 1550 | }; |
| 1551 | |
| 1552 | const std::string layerName("merge"); |
| 1553 | const armnn::TensorInfo info({ 1, 2, 2, 3 }, armnn::DataType::Float32); |
| 1554 | |
| 1555 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1556 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 1557 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 1558 | armnn::IConnectableLayer* const mergeLayer = network->AddMergeLayer(layerName.c_str()); |
| 1559 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1560 | |
| 1561 | inputLayer0->GetOutputSlot(0).Connect(mergeLayer->GetInputSlot(0)); |
| 1562 | inputLayer1->GetOutputSlot(0).Connect(mergeLayer->GetInputSlot(1)); |
| 1563 | mergeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1564 | |
| 1565 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 1566 | inputLayer1->GetOutputSlot(0).SetTensorInfo(info); |
| 1567 | mergeLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1568 | |
| 1569 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1570 | BOOST_CHECK(deserializedNetwork); |
| 1571 | |
| 1572 | MergeLayerVerifier verifier(layerName, {info, info}, {info}); |
| 1573 | deserializedNetwork->Accept(verifier); |
| 1574 | } |
| 1575 | |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1576 | class MergerLayerVerifier : public LayerVerifierBase |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1577 | { |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1578 | public: |
| 1579 | MergerLayerVerifier(const std::string& layerName, |
| 1580 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1581 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 1582 | const armnn::OriginsDescriptor& descriptor) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1583 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 1584 | , m_Descriptor(descriptor) {} |
| 1585 | |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1586 | void VisitMergerLayer(const armnn::IConnectableLayer* layer, |
| 1587 | const armnn::OriginsDescriptor& descriptor, |
| 1588 | const char* name) override |
| 1589 | { |
Jim Flynn | e242f2d | 2019-05-22 14:24:13 +0100 | [diff] [blame] | 1590 | throw armnn::Exception("MergerLayer should have translated to ConcatLayer"); |
| 1591 | } |
| 1592 | |
| 1593 | void VisitConcatLayer(const armnn::IConnectableLayer* layer, |
| 1594 | const armnn::OriginsDescriptor& descriptor, |
| 1595 | const char* name) override |
| 1596 | { |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1597 | VerifyNameAndConnections(layer, name); |
| 1598 | VerifyDescriptor(descriptor); |
| 1599 | } |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1600 | |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1601 | private: |
| 1602 | void VerifyDescriptor(const armnn::OriginsDescriptor& descriptor) |
| 1603 | { |
| 1604 | BOOST_TEST(descriptor.GetConcatAxis() == m_Descriptor.GetConcatAxis()); |
| 1605 | BOOST_TEST(descriptor.GetNumViews() == m_Descriptor.GetNumViews()); |
| 1606 | BOOST_TEST(descriptor.GetNumDimensions() == m_Descriptor.GetNumDimensions()); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1607 | |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1608 | for (uint32_t i = 0; i < descriptor.GetNumViews(); i++) |
| 1609 | { |
| 1610 | for (uint32_t j = 0; j < descriptor.GetNumDimensions(); j++) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1611 | { |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1612 | BOOST_TEST(descriptor.GetViewOrigin(i)[j] == m_Descriptor.GetViewOrigin(i)[j]); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1613 | } |
| 1614 | } |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1615 | } |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1616 | |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1617 | armnn::OriginsDescriptor m_Descriptor; |
| 1618 | }; |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1619 | |
Jim Flynn | e242f2d | 2019-05-22 14:24:13 +0100 | [diff] [blame] | 1620 | // NOTE: until the deprecated AddMergerLayer disappears this test checks that calling |
| 1621 | // AddMergerLayer places a ConcatLayer into the serialized format and that |
| 1622 | // when this deserialises we have a ConcatLayer |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1623 | BOOST_AUTO_TEST_CASE(SerializeMerger) |
| 1624 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1625 | const std::string layerName("merger"); |
| 1626 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({2, 3, 2, 2}, armnn::DataType::Float32); |
| 1627 | const armnn::TensorInfo outputInfo = armnn::TensorInfo({4, 3, 2, 2}, armnn::DataType::Float32); |
| 1628 | |
| 1629 | const std::vector<armnn::TensorShape> shapes({inputInfo.GetShape(), inputInfo.GetShape()}); |
| 1630 | |
| 1631 | armnn::OriginsDescriptor descriptor = |
Jim Flynn | 825af45 | 2019-05-20 12:49:28 +0100 | [diff] [blame] | 1632 | armnn::CreateDescriptorForConcatenation(shapes.begin(), shapes.end(), 0); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1633 | |
| 1634 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1635 | armnn::IConnectableLayer* const inputLayerOne = network->AddInputLayer(0); |
| 1636 | armnn::IConnectableLayer* const inputLayerTwo = network->AddInputLayer(1); |
Jim Flynn | 906f946 | 2019-05-10 13:55:21 +0100 | [diff] [blame] | 1637 | ARMNN_NO_DEPRECATE_WARN_BEGIN |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1638 | armnn::IConnectableLayer* const mergerLayer = network->AddMergerLayer(descriptor, layerName.c_str()); |
Jim Flynn | 906f946 | 2019-05-10 13:55:21 +0100 | [diff] [blame] | 1639 | ARMNN_NO_DEPRECATE_WARN_END |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1640 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1641 | |
| 1642 | inputLayerOne->GetOutputSlot(0).Connect(mergerLayer->GetInputSlot(0)); |
| 1643 | inputLayerTwo->GetOutputSlot(0).Connect(mergerLayer->GetInputSlot(1)); |
| 1644 | mergerLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1645 | |
| 1646 | inputLayerOne->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1647 | inputLayerTwo->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1648 | mergerLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 1649 | |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1650 | std::string mergerLayerNetwork = SerializeNetwork(*network); |
| 1651 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(mergerLayerNetwork); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1652 | BOOST_CHECK(deserializedNetwork); |
| 1653 | |
| 1654 | MergerLayerVerifier verifier(layerName, {inputInfo, inputInfo}, {outputInfo}, descriptor); |
| 1655 | deserializedNetwork->Accept(verifier); |
| 1656 | } |
| 1657 | |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1658 | BOOST_AUTO_TEST_CASE(EnsureMergerLayerBackwardCompatibility) |
| 1659 | { |
| 1660 | // The hex array below is a flat buffer containing a simple network with two inputs |
Jim Flynn | e242f2d | 2019-05-22 14:24:13 +0100 | [diff] [blame] | 1661 | // a merger layer (now deprecated) and an output layer with dimensions as per the tensor infos below. |
| 1662 | // |
| 1663 | // This test verifies that we can still read back these old style |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1664 | // models replacing the MergerLayers with ConcatLayers with the same parameters. |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1665 | unsigned int size = 760; |
| 1666 | const unsigned char mergerModel[] = { |
| 1667 | 0x10,0x00,0x00,0x00,0x00,0x00,0x0A,0x00,0x10,0x00,0x04,0x00,0x08,0x00,0x0C,0x00,0x0A,0x00,0x00,0x00, |
| 1668 | 0x0C,0x00,0x00,0x00,0x1C,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x38,0x02,0x00,0x00, |
| 1669 | 0x8C,0x01,0x00,0x00,0x70,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 1670 | 0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0xF4,0xFD,0xFF,0xFF,0x00,0x00,0x00,0x0B, |
| 1671 | 0x04,0x00,0x00,0x00,0x92,0xFE,0xFF,0xFF,0x04,0x00,0x00,0x00,0x9A,0xFE,0xFF,0xFF,0x04,0x00,0x00,0x00, |
| 1672 | 0x7E,0xFE,0xFF,0xFF,0x03,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x10,0x00,0x00,0x00, |
| 1673 | 0x14,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00, |
| 1674 | 0x00,0x00,0x00,0x00,0xF8,0xFE,0xFF,0xFF,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0xFE,0xFF,0xFF, |
| 1675 | 0x00,0x00,0x00,0x1F,0x0C,0x00,0x00,0x00,0x08,0x00,0x0C,0x00,0x04,0x00,0x08,0x00,0x08,0x00,0x00,0x00, |
| 1676 | 0x68,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x0C,0x00,0x10,0x00,0x00,0x00,0x04,0x00,0x08,0x00,0x0C,0x00, |
| 1677 | 0x0C,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x02,0x00,0x00,0x00, |
| 1678 | 0x24,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x22,0xFF,0xFF,0xFF,0x04,0x00,0x00,0x00,0x04,0x00,0x00,0x00, |
| 1679 | 0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x3E,0xFF,0xFF,0xFF, |
| 1680 | 0x04,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 1681 | 0x00,0x00,0x00,0x00,0x36,0xFF,0xFF,0xFF,0x02,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x1E,0x00,0x00,0x00, |
| 1682 | 0x14,0x00,0x00,0x00,0x1C,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x6D,0x65,0x72,0x67,0x65,0x72,0x00,0x00, |
| 1683 | 0x02,0x00,0x00,0x00,0x5C,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00, |
| 1684 | 0x34,0xFF,0xFF,0xFF,0x04,0x00,0x00,0x00,0x92,0xFE,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00, |
| 1685 | 0x00,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00, |
| 1686 | 0x02,0x00,0x00,0x00,0x08,0x00,0x10,0x00,0x04,0x00,0x08,0x00,0x08,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 1687 | 0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x08,0x00,0x0C,0x00,0x00,0x00,0x04,0x00,0x08,0x00,0x00,0x00, |
| 1688 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x08,0x00,0x0E,0x00,0x07,0x00,0x08,0x00,0x08,0x00,0x00,0x00, |
| 1689 | 0x00,0x00,0x00,0x09,0x0C,0x00,0x00,0x00,0x00,0x00,0x06,0x00,0x08,0x00,0x04,0x00,0x06,0x00,0x00,0x00, |
| 1690 | 0x0C,0x00,0x00,0x00,0x08,0x00,0x0E,0x00,0x04,0x00,0x08,0x00,0x08,0x00,0x00,0x00,0x18,0x00,0x00,0x00, |
| 1691 | 0x01,0x00,0x00,0x00,0x00,0x00,0x0E,0x00,0x18,0x00,0x04,0x00,0x08,0x00,0x0C,0x00,0x10,0x00,0x14,0x00, |
| 1692 | 0x0E,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x10,0x00,0x00,0x00, |
| 1693 | 0x10,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 1694 | 0x0C,0x00,0x00,0x00,0x08,0x00,0x08,0x00,0x00,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x04,0x00,0x00,0x00, |
| 1695 | 0x66,0xFF,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x04,0x00,0x00,0x00, |
| 1696 | 0x02,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x08,0x00,0x0C,0x00, |
| 1697 | 0x07,0x00,0x08,0x00,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x09,0x04,0x00,0x00,0x00,0xF6,0xFF,0xFF,0xFF, |
| 1698 | 0x0C,0x00,0x00,0x00,0x00,0x00,0x06,0x00,0x0A,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x14,0x00,0x00,0x00, |
| 1699 | 0x00,0x00,0x0E,0x00,0x14,0x00,0x00,0x00,0x04,0x00,0x08,0x00,0x0C,0x00,0x10,0x00,0x0E,0x00,0x00,0x00, |
| 1700 | 0x10,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 1701 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0C,0x00,0x00,0x00,0x08,0x00,0x0A,0x00, |
| 1702 | 0x00,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x00,0x00,0x0A,0x00,0x10,0x00,0x08,0x00, |
| 1703 | 0x07,0x00,0x0C,0x00,0x0A,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 1704 | 0x04,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x02,0x00,0x00,0x00}; |
| 1705 | std::stringstream ss; |
| 1706 | for (unsigned int i = 0; i < size; ++i) |
| 1707 | { |
| 1708 | ss << mergerModel[i]; |
| 1709 | } |
| 1710 | std::string mergerLayerNetwork = ss.str(); |
| 1711 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(mergerLayerNetwork); |
| 1712 | BOOST_CHECK(deserializedNetwork); |
| 1713 | const std::string layerName("merger"); |
| 1714 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({2, 3, 2, 2}, armnn::DataType::Float32); |
| 1715 | const armnn::TensorInfo outputInfo = armnn::TensorInfo({4, 3, 2, 2}, armnn::DataType::Float32); |
| 1716 | |
| 1717 | const std::vector<armnn::TensorShape> shapes({inputInfo.GetShape(), inputInfo.GetShape()}); |
| 1718 | |
| 1719 | armnn::OriginsDescriptor descriptor = |
Jim Flynn | 825af45 | 2019-05-20 12:49:28 +0100 | [diff] [blame] | 1720 | armnn::CreateDescriptorForConcatenation(shapes.begin(), shapes.end(), 0); |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1721 | |
| 1722 | MergerLayerVerifier verifier(layerName, {inputInfo, inputInfo}, {outputInfo}, descriptor); |
| 1723 | deserializedNetwork->Accept(verifier); |
| 1724 | } |
| 1725 | |
Jim Flynn | e242f2d | 2019-05-22 14:24:13 +0100 | [diff] [blame] | 1726 | BOOST_AUTO_TEST_CASE(SerializeConcat) |
| 1727 | { |
| 1728 | const std::string layerName("concat"); |
| 1729 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({2, 3, 2, 2}, armnn::DataType::Float32); |
| 1730 | const armnn::TensorInfo outputInfo = armnn::TensorInfo({4, 3, 2, 2}, armnn::DataType::Float32); |
| 1731 | |
| 1732 | const std::vector<armnn::TensorShape> shapes({inputInfo.GetShape(), inputInfo.GetShape()}); |
| 1733 | |
| 1734 | armnn::OriginsDescriptor descriptor = |
| 1735 | armnn::CreateDescriptorForConcatenation(shapes.begin(), shapes.end(), 0); |
| 1736 | |
| 1737 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1738 | armnn::IConnectableLayer* const inputLayerOne = network->AddInputLayer(0); |
| 1739 | armnn::IConnectableLayer* const inputLayerTwo = network->AddInputLayer(1); |
| 1740 | armnn::IConnectableLayer* const concatLayer = network->AddConcatLayer(descriptor, layerName.c_str()); |
| 1741 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1742 | |
| 1743 | inputLayerOne->GetOutputSlot(0).Connect(concatLayer->GetInputSlot(0)); |
| 1744 | inputLayerTwo->GetOutputSlot(0).Connect(concatLayer->GetInputSlot(1)); |
| 1745 | concatLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1746 | |
| 1747 | inputLayerOne->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1748 | inputLayerTwo->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1749 | concatLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 1750 | |
| 1751 | std::string concatLayerNetwork = SerializeNetwork(*network); |
| 1752 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(concatLayerNetwork); |
| 1753 | BOOST_CHECK(deserializedNetwork); |
| 1754 | |
| 1755 | // NOTE: using the MergerLayerVerifier to ensure that it is a concat layer and not a |
| 1756 | // merger layer that gets placed into the graph. |
| 1757 | MergerLayerVerifier verifier(layerName, {inputInfo, inputInfo}, {outputInfo}, descriptor); |
| 1758 | deserializedNetwork->Accept(verifier); |
| 1759 | } |
| 1760 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1761 | BOOST_AUTO_TEST_CASE(SerializeMinimum) |
| 1762 | { |
| 1763 | class MinimumLayerVerifier : public LayerVerifierBase |
| 1764 | { |
| 1765 | public: |
| 1766 | MinimumLayerVerifier(const std::string& layerName, |
| 1767 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1768 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 1769 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 1770 | |
| 1771 | void VisitMinimumLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 1772 | { |
| 1773 | VerifyNameAndConnections(layer, name); |
| 1774 | } |
| 1775 | }; |
| 1776 | |
| 1777 | const std::string layerName("minimum"); |
| 1778 | const armnn::TensorInfo info({ 1, 2, 2, 3 }, armnn::DataType::Float32); |
| 1779 | |
| 1780 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1781 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 1782 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 1783 | armnn::IConnectableLayer* const minimumLayer = network->AddMinimumLayer(layerName.c_str()); |
| 1784 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1785 | |
| 1786 | inputLayer0->GetOutputSlot(0).Connect(minimumLayer->GetInputSlot(0)); |
| 1787 | inputLayer1->GetOutputSlot(0).Connect(minimumLayer->GetInputSlot(1)); |
| 1788 | minimumLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1789 | |
| 1790 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 1791 | inputLayer1->GetOutputSlot(0).SetTensorInfo(info); |
| 1792 | minimumLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1793 | |
| 1794 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1795 | BOOST_CHECK(deserializedNetwork); |
| 1796 | |
| 1797 | MinimumLayerVerifier verifier(layerName, {info, info}, {info}); |
| 1798 | deserializedNetwork->Accept(verifier); |
| 1799 | } |
| 1800 | |
| 1801 | BOOST_AUTO_TEST_CASE(SerializeMultiplication) |
| 1802 | { |
| 1803 | class MultiplicationLayerVerifier : public LayerVerifierBase |
| 1804 | { |
| 1805 | public: |
| 1806 | MultiplicationLayerVerifier(const std::string& layerName, |
| 1807 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1808 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 1809 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 1810 | |
| 1811 | void VisitMultiplicationLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 1812 | { |
| 1813 | VerifyNameAndConnections(layer, name); |
| 1814 | } |
| 1815 | }; |
| 1816 | |
| 1817 | const std::string layerName("multiplication"); |
| 1818 | const armnn::TensorInfo info({ 1, 5, 2, 3 }, armnn::DataType::Float32); |
| 1819 | |
| 1820 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1821 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 1822 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 1823 | armnn::IConnectableLayer* const multiplicationLayer = network->AddMultiplicationLayer(layerName.c_str()); |
| 1824 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1825 | |
| 1826 | inputLayer0->GetOutputSlot(0).Connect(multiplicationLayer->GetInputSlot(0)); |
| 1827 | inputLayer1->GetOutputSlot(0).Connect(multiplicationLayer->GetInputSlot(1)); |
| 1828 | multiplicationLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1829 | |
| 1830 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 1831 | inputLayer1->GetOutputSlot(0).SetTensorInfo(info); |
| 1832 | multiplicationLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1833 | |
| 1834 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1835 | BOOST_CHECK(deserializedNetwork); |
| 1836 | |
| 1837 | MultiplicationLayerVerifier verifier(layerName, {info, info}, {info}); |
| 1838 | deserializedNetwork->Accept(verifier); |
| 1839 | } |
| 1840 | |
Ellen Norris-Thompson | 5198247 | 2019-06-19 11:46:21 +0100 | [diff] [blame] | 1841 | BOOST_AUTO_TEST_CASE(SerializePrelu) |
| 1842 | { |
| 1843 | class PreluLayerVerifier : public LayerVerifierBase |
| 1844 | { |
| 1845 | public: |
| 1846 | PreluLayerVerifier(const std::string& layerName, |
| 1847 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1848 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 1849 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 1850 | |
| 1851 | void VisitPreluLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 1852 | { |
| 1853 | VerifyNameAndConnections(layer, name); |
| 1854 | } |
| 1855 | }; |
| 1856 | |
| 1857 | const std::string layerName("prelu"); |
| 1858 | |
| 1859 | armnn::TensorInfo inputTensorInfo ({ 4, 1, 2 }, armnn::DataType::Float32); |
| 1860 | armnn::TensorInfo alphaTensorInfo ({ 5, 4, 3, 1 }, armnn::DataType::Float32); |
| 1861 | armnn::TensorInfo outputTensorInfo({ 5, 4, 3, 2 }, armnn::DataType::Float32); |
| 1862 | |
| 1863 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1864 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 1865 | armnn::IConnectableLayer* const alphaLayer = network->AddInputLayer(1); |
| 1866 | armnn::IConnectableLayer* const preluLayer = network->AddPreluLayer(layerName.c_str()); |
| 1867 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1868 | |
| 1869 | inputLayer->GetOutputSlot(0).Connect(preluLayer->GetInputSlot(0)); |
| 1870 | alphaLayer->GetOutputSlot(0).Connect(preluLayer->GetInputSlot(1)); |
| 1871 | preluLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1872 | |
| 1873 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 1874 | alphaLayer->GetOutputSlot(0).SetTensorInfo(alphaTensorInfo); |
| 1875 | preluLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| 1876 | |
| 1877 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1878 | BOOST_CHECK(deserializedNetwork); |
| 1879 | |
| 1880 | PreluLayerVerifier verifier(layerName, {inputTensorInfo, alphaTensorInfo}, {outputTensorInfo}); |
| 1881 | deserializedNetwork->Accept(verifier); |
| 1882 | } |
| 1883 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1884 | BOOST_AUTO_TEST_CASE(SerializeNormalization) |
| 1885 | { |
| 1886 | class NormalizationLayerVerifier : public LayerVerifierBase |
| 1887 | { |
| 1888 | public: |
| 1889 | NormalizationLayerVerifier(const std::string& layerName, |
| 1890 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1891 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 1892 | const armnn::NormalizationDescriptor& descriptor) |
| 1893 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 1894 | , m_Descriptor(descriptor) {} |
| 1895 | |
| 1896 | void VisitNormalizationLayer(const armnn::IConnectableLayer* layer, |
| 1897 | const armnn::NormalizationDescriptor& descriptor, |
| 1898 | const char* name) override |
| 1899 | { |
| 1900 | VerifyNameAndConnections(layer, name); |
| 1901 | VerifyDescriptor(descriptor); |
| 1902 | } |
| 1903 | |
| 1904 | private: |
| 1905 | void VerifyDescriptor(const armnn::NormalizationDescriptor& descriptor) |
| 1906 | { |
| 1907 | BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout)); |
| 1908 | BOOST_TEST(descriptor.m_NormSize == m_Descriptor.m_NormSize); |
| 1909 | BOOST_TEST(descriptor.m_Alpha == m_Descriptor.m_Alpha); |
| 1910 | BOOST_TEST(descriptor.m_Beta == m_Descriptor.m_Beta); |
| 1911 | BOOST_TEST(descriptor.m_K == m_Descriptor.m_K); |
| 1912 | BOOST_TEST( |
| 1913 | static_cast<int>(descriptor.m_NormChannelType) == static_cast<int>(m_Descriptor.m_NormChannelType)); |
| 1914 | BOOST_TEST( |
| 1915 | static_cast<int>(descriptor.m_NormMethodType) == static_cast<int>(m_Descriptor.m_NormMethodType)); |
| 1916 | } |
| 1917 | |
| 1918 | armnn::NormalizationDescriptor m_Descriptor; |
| 1919 | }; |
| 1920 | |
| 1921 | const std::string layerName("normalization"); |
| 1922 | const armnn::TensorInfo info({2, 1, 2, 2}, armnn::DataType::Float32); |
| 1923 | |
| 1924 | armnn::NormalizationDescriptor desc; |
| 1925 | desc.m_DataLayout = armnn::DataLayout::NCHW; |
| 1926 | desc.m_NormSize = 3; |
| 1927 | desc.m_Alpha = 1; |
| 1928 | desc.m_Beta = 1; |
| 1929 | desc.m_K = 1; |
| 1930 | |
| 1931 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1932 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 1933 | armnn::IConnectableLayer* const normalizationLayer = network->AddNormalizationLayer(desc, layerName.c_str()); |
| 1934 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1935 | |
| 1936 | inputLayer->GetOutputSlot(0).Connect(normalizationLayer->GetInputSlot(0)); |
| 1937 | normalizationLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1938 | |
| 1939 | inputLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1940 | normalizationLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1941 | |
| 1942 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1943 | BOOST_CHECK(deserializedNetwork); |
| 1944 | |
| 1945 | NormalizationLayerVerifier verifier(layerName, {info}, {info}, desc); |
| 1946 | deserializedNetwork->Accept(verifier); |
| 1947 | } |
| 1948 | |
Jim Flynn | 965c7c6 | 2019-06-24 14:32:41 +0100 | [diff] [blame] | 1949 | class PadLayerVerifier : public LayerVerifierBase |
| 1950 | { |
| 1951 | public: |
| 1952 | PadLayerVerifier(const std::string& layerName, |
| 1953 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1954 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 1955 | const armnn::PadDescriptor& descriptor) |
| 1956 | : LayerVerifierBase(layerName, inputInfos, outputInfos), m_Descriptor(descriptor) {} |
| 1957 | |
| 1958 | void VisitPadLayer(const armnn::IConnectableLayer* layer, |
| 1959 | const armnn::PadDescriptor& descriptor, |
| 1960 | const char* name) override |
| 1961 | { |
| 1962 | VerifyNameAndConnections(layer, name); |
| 1963 | VerifyDescriptor(descriptor); |
| 1964 | } |
| 1965 | |
| 1966 | private: |
| 1967 | void VerifyDescriptor(const armnn::PadDescriptor& descriptor) |
| 1968 | { |
| 1969 | BOOST_TEST(descriptor.m_PadList == m_Descriptor.m_PadList); |
Aron Virginas-Tar | f356905 | 2019-07-05 16:01:08 +0100 | [diff] [blame] | 1970 | BOOST_TEST(descriptor.m_PadValue == m_Descriptor.m_PadValue); |
Jim Flynn | 965c7c6 | 2019-06-24 14:32:41 +0100 | [diff] [blame] | 1971 | } |
| 1972 | |
| 1973 | armnn::PadDescriptor m_Descriptor; |
| 1974 | }; |
| 1975 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1976 | BOOST_AUTO_TEST_CASE(SerializePad) |
| 1977 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1978 | |
| 1979 | const std::string layerName("pad"); |
| 1980 | const armnn::TensorInfo inputTensorInfo = armnn::TensorInfo({1, 2, 3, 4}, armnn::DataType::Float32); |
| 1981 | const armnn::TensorInfo outputTensorInfo = armnn::TensorInfo({1, 3, 5, 7}, armnn::DataType::Float32); |
| 1982 | |
| 1983 | armnn::PadDescriptor desc({{0, 0}, {1, 0}, {1, 1}, {1, 2}}); |
| 1984 | |
| 1985 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1986 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 1987 | armnn::IConnectableLayer* const padLayer = network->AddPadLayer(desc, layerName.c_str()); |
| 1988 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1989 | |
| 1990 | inputLayer->GetOutputSlot(0).Connect(padLayer->GetInputSlot(0)); |
| 1991 | padLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1992 | |
| 1993 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 1994 | padLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| 1995 | |
| 1996 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1997 | BOOST_CHECK(deserializedNetwork); |
| 1998 | |
| 1999 | PadLayerVerifier verifier(layerName, {inputTensorInfo}, {outputTensorInfo}, desc); |
| 2000 | deserializedNetwork->Accept(verifier); |
| 2001 | } |
| 2002 | |
Jim Flynn | 965c7c6 | 2019-06-24 14:32:41 +0100 | [diff] [blame] | 2003 | BOOST_AUTO_TEST_CASE(CheckSerializePadBackwardCompatibility) |
| 2004 | { |
| 2005 | // The PadDescriptor is being extended with a float PadValue (so a value other than 0 |
| 2006 | // can be used to pad the tensor. |
| 2007 | // |
| 2008 | // This test contains a binary representation of a simple input->pad->output network |
| 2009 | // prior to this change to test that the descriptor has been updated in a backward |
| 2010 | // compatible way with respect to Deserialization of older binary dumps |
| 2011 | unsigned int size = 532; |
| 2012 | const unsigned char padModel[] = { |
| 2013 | 0x10,0x00,0x00,0x00,0x00,0x00,0x0A,0x00,0x10,0x00,0x04,0x00,0x08,0x00,0x0C,0x00,0x0A,0x00,0x00,0x00, |
| 2014 | 0x0C,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x1C,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x54,0x01,0x00,0x00, |
| 2015 | 0x6C,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 2016 | 0x02,0x00,0x00,0x00,0xD0,0xFE,0xFF,0xFF,0x00,0x00,0x00,0x0B,0x04,0x00,0x00,0x00,0x96,0xFF,0xFF,0xFF, |
| 2017 | 0x04,0x00,0x00,0x00,0x9E,0xFF,0xFF,0xFF,0x04,0x00,0x00,0x00,0x72,0xFF,0xFF,0xFF,0x02,0x00,0x00,0x00, |
| 2018 | 0x10,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 2019 | 0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x2C,0xFF,0xFF,0xFF, |
| 2020 | 0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x24,0xFF,0xFF,0xFF,0x00,0x00,0x00,0x16,0x0C,0x00,0x00,0x00, |
| 2021 | 0x08,0x00,0x0E,0x00,0x04,0x00,0x08,0x00,0x08,0x00,0x00,0x00,0x4C,0x00,0x00,0x00,0x0C,0x00,0x00,0x00, |
| 2022 | 0x00,0x00,0x06,0x00,0x08,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x08,0x00,0x00,0x00, |
| 2023 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 2024 | 0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x00,0x00,0x0E,0x00,0x18,0x00,0x04,0x00, |
| 2025 | 0x08,0x00,0x0C,0x00,0x10,0x00,0x14,0x00,0x0E,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x10,0x00,0x00,0x00, |
| 2026 | 0x14,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x70,0x61,0x64,0x00, |
| 2027 | 0x01,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0C,0x00,0x00,0x00,0x08,0x00,0x08,0x00, |
| 2028 | 0x00,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x52,0xFF,0xFF,0xFF,0x00,0x00,0x00,0x01, |
| 2029 | 0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00, |
| 2030 | 0x05,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x08,0x00,0x0C,0x00,0x00,0x00,0x04,0x00,0x08,0x00,0x00,0x00, |
| 2031 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x08,0x00,0x0C,0x00,0x07,0x00,0x08,0x00,0x08,0x00,0x00,0x00, |
| 2032 | 0x00,0x00,0x00,0x09,0x04,0x00,0x00,0x00,0xF6,0xFF,0xFF,0xFF,0x0C,0x00,0x00,0x00,0x00,0x00,0x06,0x00, |
| 2033 | 0x0A,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x00,0x00,0x0E,0x00,0x14,0x00,0x00,0x00, |
| 2034 | 0x04,0x00,0x08,0x00,0x0C,0x00,0x10,0x00,0x0E,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 2035 | 0x10,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 2036 | 0x01,0x00,0x00,0x00,0x0C,0x00,0x00,0x00,0x08,0x00,0x0A,0x00,0x00,0x00,0x04,0x00,0x08,0x00,0x00,0x00, |
| 2037 | 0x10,0x00,0x00,0x00,0x00,0x00,0x0A,0x00,0x10,0x00,0x08,0x00,0x07,0x00,0x0C,0x00,0x0A,0x00,0x00,0x00, |
| 2038 | 0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 2039 | 0x02,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0 }; |
| 2040 | |
| 2041 | std::stringstream ss; |
| 2042 | for (unsigned int i = 0; i < size; ++i) |
| 2043 | { |
| 2044 | ss << padModel[i]; |
| 2045 | } |
| 2046 | std::string padNetwork = ss.str(); |
| 2047 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(padNetwork); |
| 2048 | BOOST_CHECK(deserializedNetwork); |
| 2049 | |
| 2050 | const std::string layerName("pad"); |
| 2051 | const armnn::TensorInfo inputTensorInfo = armnn::TensorInfo({1, 2, 3, 4}, armnn::DataType::Float32); |
| 2052 | const armnn::TensorInfo outputTensorInfo = armnn::TensorInfo({1, 3, 5, 7}, armnn::DataType::Float32); |
| 2053 | |
| 2054 | armnn::PadDescriptor desc({{0, 0}, {1, 0}, {1, 1}, {1, 2}}); |
| 2055 | |
| 2056 | PadLayerVerifier verifier(layerName, {inputTensorInfo}, {outputTensorInfo}, desc); |
| 2057 | deserializedNetwork->Accept(verifier); |
| 2058 | } |
| 2059 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2060 | BOOST_AUTO_TEST_CASE(SerializePermute) |
| 2061 | { |
| 2062 | class PermuteLayerVerifier : public LayerVerifierBase |
| 2063 | { |
| 2064 | public: |
| 2065 | PermuteLayerVerifier(const std::string& layerName, |
| 2066 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2067 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 2068 | const armnn::PermuteDescriptor& descriptor) |
| 2069 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 2070 | , m_Descriptor(descriptor) {} |
| 2071 | |
| 2072 | void VisitPermuteLayer(const armnn::IConnectableLayer* layer, |
| 2073 | const armnn::PermuteDescriptor& descriptor, |
| 2074 | const char* name) override |
| 2075 | { |
| 2076 | VerifyNameAndConnections(layer, name); |
| 2077 | VerifyDescriptor(descriptor); |
| 2078 | } |
| 2079 | |
| 2080 | private: |
| 2081 | void VerifyDescriptor(const armnn::PermuteDescriptor& descriptor) |
| 2082 | { |
| 2083 | BOOST_TEST(descriptor.m_DimMappings.IsEqual(m_Descriptor.m_DimMappings)); |
| 2084 | } |
| 2085 | |
| 2086 | armnn::PermuteDescriptor m_Descriptor; |
| 2087 | }; |
| 2088 | |
| 2089 | const std::string layerName("permute"); |
| 2090 | const armnn::TensorInfo inputTensorInfo({4, 3, 2, 1}, armnn::DataType::Float32); |
| 2091 | const armnn::TensorInfo outputTensorInfo({1, 2, 3, 4}, armnn::DataType::Float32); |
| 2092 | |
| 2093 | armnn::PermuteDescriptor descriptor(armnn::PermutationVector({3, 2, 1, 0})); |
| 2094 | |
| 2095 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2096 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2097 | armnn::IConnectableLayer* const permuteLayer = network->AddPermuteLayer(descriptor, layerName.c_str()); |
| 2098 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2099 | |
| 2100 | inputLayer->GetOutputSlot(0).Connect(permuteLayer->GetInputSlot(0)); |
| 2101 | permuteLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2102 | |
| 2103 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 2104 | permuteLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| 2105 | |
| 2106 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2107 | BOOST_CHECK(deserializedNetwork); |
| 2108 | |
| 2109 | PermuteLayerVerifier verifier(layerName, {inputTensorInfo}, {outputTensorInfo}, descriptor); |
| 2110 | deserializedNetwork->Accept(verifier); |
| 2111 | } |
| 2112 | |
| 2113 | BOOST_AUTO_TEST_CASE(SerializePooling2d) |
| 2114 | { |
| 2115 | class Pooling2dLayerVerifier : public LayerVerifierBase |
| 2116 | { |
| 2117 | public: |
| 2118 | Pooling2dLayerVerifier(const std::string& layerName, |
| 2119 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2120 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 2121 | const armnn::Pooling2dDescriptor& descriptor) |
| 2122 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 2123 | , m_Descriptor(descriptor) {} |
| 2124 | |
| 2125 | void VisitPooling2dLayer(const armnn::IConnectableLayer* layer, |
| 2126 | const armnn::Pooling2dDescriptor& descriptor, |
| 2127 | const char* name) override |
| 2128 | { |
| 2129 | VerifyNameAndConnections(layer, name); |
| 2130 | VerifyDescriptor(descriptor); |
| 2131 | } |
| 2132 | |
| 2133 | private: |
| 2134 | void VerifyDescriptor(const armnn::Pooling2dDescriptor& descriptor) |
| 2135 | { |
| 2136 | BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout)); |
| 2137 | BOOST_TEST(descriptor.m_PadLeft == m_Descriptor.m_PadLeft); |
| 2138 | BOOST_TEST(descriptor.m_PadRight == m_Descriptor.m_PadRight); |
| 2139 | BOOST_TEST(descriptor.m_PadTop == m_Descriptor.m_PadTop); |
| 2140 | BOOST_TEST(descriptor.m_PadBottom == m_Descriptor.m_PadBottom); |
| 2141 | BOOST_TEST(descriptor.m_PoolWidth == m_Descriptor.m_PoolWidth); |
| 2142 | BOOST_TEST(descriptor.m_PoolHeight == m_Descriptor.m_PoolHeight); |
| 2143 | BOOST_TEST(descriptor.m_StrideX == m_Descriptor.m_StrideX); |
| 2144 | BOOST_TEST(descriptor.m_StrideY == m_Descriptor.m_StrideY); |
| 2145 | |
| 2146 | BOOST_TEST( |
| 2147 | static_cast<int>(descriptor.m_PaddingMethod) == static_cast<int>(m_Descriptor.m_PaddingMethod)); |
| 2148 | BOOST_TEST( |
| 2149 | static_cast<int>(descriptor.m_PoolType) == static_cast<int>(m_Descriptor.m_PoolType)); |
| 2150 | BOOST_TEST( |
| 2151 | static_cast<int>(descriptor.m_OutputShapeRounding) == |
| 2152 | static_cast<int>(m_Descriptor.m_OutputShapeRounding)); |
| 2153 | } |
| 2154 | |
| 2155 | armnn::Pooling2dDescriptor m_Descriptor; |
| 2156 | }; |
| 2157 | |
| 2158 | const std::string layerName("pooling2d"); |
| 2159 | const armnn::TensorInfo inputInfo({1, 2, 2, 1}, armnn::DataType::Float32); |
| 2160 | const armnn::TensorInfo outputInfo({1, 1, 1, 1}, armnn::DataType::Float32); |
| 2161 | |
| 2162 | armnn::Pooling2dDescriptor desc; |
| 2163 | desc.m_DataLayout = armnn::DataLayout::NHWC; |
| 2164 | desc.m_PadTop = 0; |
| 2165 | desc.m_PadBottom = 0; |
| 2166 | desc.m_PadLeft = 0; |
| 2167 | desc.m_PadRight = 0; |
| 2168 | desc.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 2169 | desc.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 2170 | desc.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 2171 | desc.m_PoolHeight = 2; |
| 2172 | desc.m_PoolWidth = 2; |
| 2173 | desc.m_StrideX = 2; |
| 2174 | desc.m_StrideY = 2; |
| 2175 | |
| 2176 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2177 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2178 | armnn::IConnectableLayer* const pooling2dLayer = network->AddPooling2dLayer(desc, layerName.c_str()); |
| 2179 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2180 | |
| 2181 | inputLayer->GetOutputSlot(0).Connect(pooling2dLayer->GetInputSlot(0)); |
| 2182 | pooling2dLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2183 | |
| 2184 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2185 | pooling2dLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2186 | |
| 2187 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2188 | BOOST_CHECK(deserializedNetwork); |
| 2189 | |
| 2190 | Pooling2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc); |
| 2191 | deserializedNetwork->Accept(verifier); |
| 2192 | } |
| 2193 | |
Derek Lamberti | 87acb27 | 2019-03-27 16:51:31 +0000 | [diff] [blame] | 2194 | BOOST_AUTO_TEST_CASE(SerializeQuantize) |
| 2195 | { |
| 2196 | class QuantizeLayerVerifier : public LayerVerifierBase |
| 2197 | { |
| 2198 | public: |
| 2199 | QuantizeLayerVerifier(const std::string& layerName, |
| 2200 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2201 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 2202 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 2203 | |
| 2204 | void VisitQuantizeLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 2205 | { |
| 2206 | VerifyNameAndConnections(layer, name); |
| 2207 | } |
| 2208 | }; |
| 2209 | |
| 2210 | const std::string layerName("quantize"); |
| 2211 | const armnn::TensorInfo info({ 1, 2, 2, 3 }, armnn::DataType::Float32); |
| 2212 | |
| 2213 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2214 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2215 | armnn::IConnectableLayer* const quantizeLayer = network->AddQuantizeLayer(layerName.c_str()); |
| 2216 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2217 | |
| 2218 | inputLayer->GetOutputSlot(0).Connect(quantizeLayer->GetInputSlot(0)); |
| 2219 | quantizeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2220 | |
| 2221 | inputLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2222 | quantizeLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2223 | |
| 2224 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2225 | BOOST_CHECK(deserializedNetwork); |
| 2226 | |
| 2227 | QuantizeLayerVerifier verifier(layerName, {info}, {info}); |
| 2228 | deserializedNetwork->Accept(verifier); |
| 2229 | } |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2230 | BOOST_AUTO_TEST_CASE(SerializeReshape) |
| 2231 | { |
| 2232 | class ReshapeLayerVerifier : public LayerVerifierBase |
| 2233 | { |
| 2234 | public: |
| 2235 | ReshapeLayerVerifier(const std::string& layerName, |
| 2236 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2237 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 2238 | const armnn::ReshapeDescriptor& descriptor) |
| 2239 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 2240 | , m_Descriptor(descriptor) {} |
| 2241 | |
| 2242 | void VisitReshapeLayer(const armnn::IConnectableLayer* layer, |
| 2243 | const armnn::ReshapeDescriptor& descriptor, |
| 2244 | const char* name) override |
| 2245 | { |
| 2246 | VerifyNameAndConnections(layer, name); |
| 2247 | VerifyDescriptor(descriptor); |
| 2248 | } |
| 2249 | |
| 2250 | private: |
| 2251 | void VerifyDescriptor(const armnn::ReshapeDescriptor& descriptor) |
| 2252 | { |
| 2253 | BOOST_TEST(descriptor.m_TargetShape == m_Descriptor.m_TargetShape); |
| 2254 | } |
| 2255 | |
| 2256 | armnn::ReshapeDescriptor m_Descriptor; |
| 2257 | }; |
| 2258 | |
| 2259 | const std::string layerName("reshape"); |
| 2260 | const armnn::TensorInfo inputInfo({1, 9}, armnn::DataType::Float32); |
| 2261 | const armnn::TensorInfo outputInfo({3, 3}, armnn::DataType::Float32); |
| 2262 | |
| 2263 | armnn::ReshapeDescriptor descriptor({3, 3}); |
| 2264 | |
| 2265 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2266 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2267 | armnn::IConnectableLayer* const reshapeLayer = network->AddReshapeLayer(descriptor, layerName.c_str()); |
| 2268 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2269 | |
| 2270 | inputLayer->GetOutputSlot(0).Connect(reshapeLayer->GetInputSlot(0)); |
| 2271 | reshapeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2272 | |
| 2273 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2274 | reshapeLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2275 | |
| 2276 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2277 | BOOST_CHECK(deserializedNetwork); |
| 2278 | |
| 2279 | ReshapeLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor); |
| 2280 | deserializedNetwork->Accept(verifier); |
| 2281 | } |
| 2282 | |
FinnWilliamsArm | 6fb339a | 2019-06-28 15:07:10 +0100 | [diff] [blame] | 2283 | BOOST_AUTO_TEST_CASE(SerializeResize) |
| 2284 | { |
| 2285 | class ResizeLayerVerifier : public LayerVerifierBase |
| 2286 | { |
| 2287 | public: |
| 2288 | ResizeLayerVerifier(const std::string& layerName, |
| 2289 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2290 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 2291 | const armnn::ResizeDescriptor& descriptor) |
| 2292 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 2293 | , m_Descriptor(descriptor) {} |
| 2294 | |
| 2295 | void VisitResizeLayer(const armnn::IConnectableLayer* layer, |
| 2296 | const armnn::ResizeDescriptor& descriptor, |
| 2297 | const char* name) override |
| 2298 | { |
| 2299 | VerifyNameAndConnections(layer, name); |
| 2300 | VerifyDescriptor(descriptor); |
| 2301 | } |
| 2302 | |
| 2303 | private: |
| 2304 | void VerifyDescriptor(const armnn::ResizeDescriptor& descriptor) |
| 2305 | { |
Aron Virginas-Tar | 169d2f1 | 2019-07-01 19:01:44 +0100 | [diff] [blame] | 2306 | BOOST_CHECK(descriptor.m_DataLayout == m_Descriptor.m_DataLayout); |
| 2307 | BOOST_CHECK(descriptor.m_TargetWidth == m_Descriptor.m_TargetWidth); |
FinnWilliamsArm | 6fb339a | 2019-06-28 15:07:10 +0100 | [diff] [blame] | 2308 | BOOST_CHECK(descriptor.m_TargetHeight == m_Descriptor.m_TargetHeight); |
Aron Virginas-Tar | 169d2f1 | 2019-07-01 19:01:44 +0100 | [diff] [blame] | 2309 | BOOST_CHECK(descriptor.m_Method == m_Descriptor.m_Method); |
FinnWilliamsArm | 6fb339a | 2019-06-28 15:07:10 +0100 | [diff] [blame] | 2310 | } |
| 2311 | |
| 2312 | armnn::ResizeDescriptor m_Descriptor; |
| 2313 | }; |
| 2314 | |
| 2315 | const std::string layerName("resize"); |
| 2316 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({1, 3, 5, 5}, armnn::DataType::Float32); |
| 2317 | const armnn::TensorInfo outputInfo = armnn::TensorInfo({1, 3, 2, 4}, armnn::DataType::Float32); |
| 2318 | |
| 2319 | armnn::ResizeDescriptor desc; |
Aron Virginas-Tar | 169d2f1 | 2019-07-01 19:01:44 +0100 | [diff] [blame] | 2320 | desc.m_TargetWidth = 4; |
FinnWilliamsArm | 6fb339a | 2019-06-28 15:07:10 +0100 | [diff] [blame] | 2321 | desc.m_TargetHeight = 2; |
Aron Virginas-Tar | 169d2f1 | 2019-07-01 19:01:44 +0100 | [diff] [blame] | 2322 | desc.m_Method = armnn::ResizeMethod::NearestNeighbor; |
FinnWilliamsArm | 6fb339a | 2019-06-28 15:07:10 +0100 | [diff] [blame] | 2323 | |
| 2324 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2325 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2326 | armnn::IConnectableLayer* const resizeLayer = network->AddResizeLayer(desc, layerName.c_str()); |
| 2327 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2328 | |
| 2329 | inputLayer->GetOutputSlot(0).Connect(resizeLayer->GetInputSlot(0)); |
| 2330 | resizeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2331 | |
| 2332 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2333 | resizeLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2334 | |
| 2335 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2336 | BOOST_CHECK(deserializedNetwork); |
| 2337 | |
| 2338 | ResizeLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc); |
| 2339 | deserializedNetwork->Accept(verifier); |
| 2340 | } |
| 2341 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2342 | BOOST_AUTO_TEST_CASE(SerializeRsqrt) |
| 2343 | { |
| 2344 | class RsqrtLayerVerifier : public LayerVerifierBase |
| 2345 | { |
| 2346 | public: |
| 2347 | RsqrtLayerVerifier(const std::string& layerName, |
| 2348 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2349 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 2350 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 2351 | |
| 2352 | void VisitRsqrtLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 2353 | { |
| 2354 | VerifyNameAndConnections(layer, name); |
| 2355 | } |
| 2356 | }; |
| 2357 | |
| 2358 | const std::string layerName("rsqrt"); |
| 2359 | const armnn::TensorInfo tensorInfo({ 3, 1, 2 }, armnn::DataType::Float32); |
| 2360 | |
| 2361 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2362 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2363 | armnn::IConnectableLayer* const rsqrtLayer = network->AddRsqrtLayer(layerName.c_str()); |
| 2364 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2365 | |
| 2366 | inputLayer->GetOutputSlot(0).Connect(rsqrtLayer->GetInputSlot(0)); |
| 2367 | rsqrtLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2368 | |
| 2369 | inputLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo); |
| 2370 | rsqrtLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo); |
| 2371 | |
| 2372 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2373 | BOOST_CHECK(deserializedNetwork); |
| 2374 | |
| 2375 | RsqrtLayerVerifier verifier(layerName, {tensorInfo}, {tensorInfo}); |
| 2376 | deserializedNetwork->Accept(verifier); |
| 2377 | } |
| 2378 | |
Aron Virginas-Tar | 2fda80b | 2019-09-18 13:36:52 +0100 | [diff] [blame] | 2379 | BOOST_AUTO_TEST_CASE(SerializeSlice) |
| 2380 | { |
| 2381 | class SliceLayerVerifier : public LayerVerifierBase |
| 2382 | { |
| 2383 | public: |
| 2384 | SliceLayerVerifier(const std::string& layerName, |
| 2385 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2386 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 2387 | const armnn::SliceDescriptor& descriptor) |
| 2388 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 2389 | , m_Descriptor(descriptor) {} |
| 2390 | |
| 2391 | void VisitSliceLayer(const armnn::IConnectableLayer* layer, |
| 2392 | const armnn::SliceDescriptor& descriptor, |
| 2393 | const char* name) override |
| 2394 | { |
| 2395 | VerifyNameAndConnections(layer, name); |
| 2396 | VerifyDescriptor(descriptor); |
| 2397 | } |
| 2398 | |
| 2399 | private: |
| 2400 | void VerifyDescriptor(const armnn::SliceDescriptor& descriptor) |
| 2401 | { |
| 2402 | BOOST_CHECK_EQUAL_COLLECTIONS(descriptor.m_Begin.begin(), descriptor.m_Begin.end(), |
| 2403 | m_Descriptor.m_Begin.begin(), m_Descriptor.m_Begin.end()); |
| 2404 | |
| 2405 | BOOST_CHECK_EQUAL_COLLECTIONS(descriptor.m_Size.begin(), descriptor.m_Size.end(), |
| 2406 | m_Descriptor.m_Size.begin(), m_Descriptor.m_Size.end()); |
| 2407 | } |
| 2408 | |
| 2409 | armnn::SliceDescriptor m_Descriptor; |
| 2410 | }; |
| 2411 | |
| 2412 | const std::string layerName{"slice"}; |
| 2413 | |
| 2414 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({3, 2, 3, 1}, armnn::DataType::Float32); |
| 2415 | const armnn::TensorInfo outputInfo = armnn::TensorInfo({2, 2, 2, 1}, armnn::DataType::Float32); |
| 2416 | |
| 2417 | armnn::SliceDescriptor descriptor({ 0, 0, 1, 0}, {2, 2, 2, 1}); |
| 2418 | |
| 2419 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2420 | |
| 2421 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2422 | armnn::IConnectableLayer* const sliceLayer = network->AddSliceLayer(descriptor, layerName.c_str()); |
| 2423 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2424 | |
| 2425 | inputLayer->GetOutputSlot(0).Connect(sliceLayer->GetInputSlot(0)); |
| 2426 | sliceLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2427 | |
| 2428 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2429 | sliceLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2430 | |
| 2431 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2432 | BOOST_CHECK(deserializedNetwork); |
| 2433 | |
| 2434 | SliceLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor); |
| 2435 | deserializedNetwork->Accept(verifier); |
| 2436 | } |
| 2437 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2438 | BOOST_AUTO_TEST_CASE(SerializeSoftmax) |
| 2439 | { |
| 2440 | class SoftmaxLayerVerifier : public LayerVerifierBase |
| 2441 | { |
| 2442 | public: |
| 2443 | SoftmaxLayerVerifier(const std::string& layerName, |
| 2444 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2445 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 2446 | const armnn::SoftmaxDescriptor& descriptor) |
| 2447 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 2448 | , m_Descriptor(descriptor) {} |
| 2449 | |
| 2450 | void VisitSoftmaxLayer(const armnn::IConnectableLayer* layer, |
| 2451 | const armnn::SoftmaxDescriptor& descriptor, |
| 2452 | const char* name) override |
| 2453 | { |
| 2454 | VerifyNameAndConnections(layer, name); |
| 2455 | VerifyDescriptor(descriptor); |
| 2456 | } |
| 2457 | |
| 2458 | private: |
| 2459 | void VerifyDescriptor(const armnn::SoftmaxDescriptor& descriptor) |
| 2460 | { |
| 2461 | BOOST_TEST(descriptor.m_Beta == m_Descriptor.m_Beta); |
| 2462 | } |
| 2463 | |
| 2464 | armnn::SoftmaxDescriptor m_Descriptor; |
| 2465 | }; |
| 2466 | |
| 2467 | const std::string layerName("softmax"); |
| 2468 | const armnn::TensorInfo info({1, 10}, armnn::DataType::Float32); |
| 2469 | |
| 2470 | armnn::SoftmaxDescriptor descriptor; |
| 2471 | descriptor.m_Beta = 1.0f; |
| 2472 | |
| 2473 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2474 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2475 | armnn::IConnectableLayer* const softmaxLayer = network->AddSoftmaxLayer(descriptor, layerName.c_str()); |
| 2476 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2477 | |
| 2478 | inputLayer->GetOutputSlot(0).Connect(softmaxLayer->GetInputSlot(0)); |
| 2479 | softmaxLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2480 | |
| 2481 | inputLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2482 | softmaxLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2483 | |
| 2484 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2485 | BOOST_CHECK(deserializedNetwork); |
| 2486 | |
| 2487 | SoftmaxLayerVerifier verifier(layerName, {info}, {info}, descriptor); |
| 2488 | deserializedNetwork->Accept(verifier); |
| 2489 | } |
| 2490 | |
| 2491 | BOOST_AUTO_TEST_CASE(SerializeSpaceToBatchNd) |
| 2492 | { |
| 2493 | class SpaceToBatchNdLayerVerifier : public LayerVerifierBase |
| 2494 | { |
| 2495 | public: |
| 2496 | SpaceToBatchNdLayerVerifier(const std::string& layerName, |
| 2497 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2498 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 2499 | const armnn::SpaceToBatchNdDescriptor& descriptor) |
| 2500 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 2501 | , m_Descriptor(descriptor) {} |
| 2502 | |
| 2503 | void VisitSpaceToBatchNdLayer(const armnn::IConnectableLayer* layer, |
| 2504 | const armnn::SpaceToBatchNdDescriptor& descriptor, |
| 2505 | const char* name) override |
| 2506 | { |
| 2507 | VerifyNameAndConnections(layer, name); |
| 2508 | VerifyDescriptor(descriptor); |
| 2509 | } |
| 2510 | |
| 2511 | private: |
| 2512 | void VerifyDescriptor(const armnn::SpaceToBatchNdDescriptor& descriptor) |
| 2513 | { |
| 2514 | BOOST_TEST(descriptor.m_PadList == m_Descriptor.m_PadList); |
| 2515 | BOOST_TEST(descriptor.m_BlockShape == m_Descriptor.m_BlockShape); |
| 2516 | BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout)); |
| 2517 | } |
| 2518 | |
| 2519 | armnn::SpaceToBatchNdDescriptor m_Descriptor; |
| 2520 | }; |
| 2521 | |
| 2522 | const std::string layerName("spaceToBatchNd"); |
| 2523 | const armnn::TensorInfo inputInfo({2, 1, 2, 4}, armnn::DataType::Float32); |
| 2524 | const armnn::TensorInfo outputInfo({8, 1, 1, 3}, armnn::DataType::Float32); |
| 2525 | |
| 2526 | armnn::SpaceToBatchNdDescriptor desc; |
| 2527 | desc.m_DataLayout = armnn::DataLayout::NCHW; |
| 2528 | desc.m_BlockShape = {2, 2}; |
| 2529 | desc.m_PadList = {{0, 0}, {2, 0}}; |
| 2530 | |
| 2531 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2532 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2533 | armnn::IConnectableLayer* const spaceToBatchNdLayer = network->AddSpaceToBatchNdLayer(desc, layerName.c_str()); |
| 2534 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2535 | |
| 2536 | inputLayer->GetOutputSlot(0).Connect(spaceToBatchNdLayer->GetInputSlot(0)); |
| 2537 | spaceToBatchNdLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2538 | |
| 2539 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2540 | spaceToBatchNdLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2541 | |
| 2542 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2543 | BOOST_CHECK(deserializedNetwork); |
| 2544 | |
| 2545 | SpaceToBatchNdLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc); |
| 2546 | deserializedNetwork->Accept(verifier); |
| 2547 | } |
| 2548 | |
Aron Virginas-Tar | aa06714 | 2019-06-11 16:01:44 +0100 | [diff] [blame] | 2549 | BOOST_AUTO_TEST_CASE(SerializeSpaceToDepth) |
| 2550 | { |
| 2551 | class SpaceToDepthLayerVerifier : public LayerVerifierBase |
| 2552 | { |
| 2553 | public: |
| 2554 | SpaceToDepthLayerVerifier(const std::string& layerName, |
| 2555 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2556 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 2557 | const armnn::SpaceToDepthDescriptor& descriptor) |
| 2558 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 2559 | , m_Descriptor(descriptor) {} |
| 2560 | |
| 2561 | void VisitSpaceToDepthLayer(const armnn::IConnectableLayer* layer, |
| 2562 | const armnn::SpaceToDepthDescriptor& descriptor, |
| 2563 | const char* name) override |
| 2564 | { |
| 2565 | VerifyNameAndConnections(layer, name); |
| 2566 | VerifyDescriptor(descriptor); |
| 2567 | } |
| 2568 | |
| 2569 | private: |
| 2570 | void VerifyDescriptor(const armnn::SpaceToDepthDescriptor& descriptor) |
| 2571 | { |
| 2572 | BOOST_TEST(descriptor.m_BlockSize == m_Descriptor.m_BlockSize); |
| 2573 | BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout)); |
| 2574 | } |
| 2575 | |
| 2576 | armnn::SpaceToDepthDescriptor m_Descriptor; |
| 2577 | }; |
| 2578 | |
| 2579 | const std::string layerName("spaceToDepth"); |
| 2580 | |
| 2581 | const armnn::TensorInfo inputInfo ({ 1, 16, 8, 3 }, armnn::DataType::Float32); |
| 2582 | const armnn::TensorInfo outputInfo({ 1, 8, 4, 12 }, armnn::DataType::Float32); |
| 2583 | |
| 2584 | armnn::SpaceToDepthDescriptor desc; |
| 2585 | desc.m_BlockSize = 2; |
| 2586 | desc.m_DataLayout = armnn::DataLayout::NHWC; |
| 2587 | |
| 2588 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2589 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2590 | armnn::IConnectableLayer* const spaceToDepthLayer = network->AddSpaceToDepthLayer(desc, layerName.c_str()); |
| 2591 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2592 | |
| 2593 | inputLayer->GetOutputSlot(0).Connect(spaceToDepthLayer->GetInputSlot(0)); |
| 2594 | spaceToDepthLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2595 | |
| 2596 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2597 | spaceToDepthLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2598 | |
| 2599 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2600 | BOOST_CHECK(deserializedNetwork); |
| 2601 | |
| 2602 | SpaceToDepthLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc); |
| 2603 | deserializedNetwork->Accept(verifier); |
| 2604 | } |
| 2605 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2606 | BOOST_AUTO_TEST_CASE(SerializeSplitter) |
| 2607 | { |
| 2608 | class SplitterLayerVerifier : public LayerVerifierBase |
| 2609 | { |
| 2610 | public: |
| 2611 | SplitterLayerVerifier(const std::string& layerName, |
| 2612 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2613 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 2614 | const armnn::ViewsDescriptor& descriptor) |
| 2615 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 2616 | , m_Descriptor(descriptor) {} |
| 2617 | |
| 2618 | void VisitSplitterLayer(const armnn::IConnectableLayer* layer, |
| 2619 | const armnn::ViewsDescriptor& descriptor, |
| 2620 | const char* name) override |
| 2621 | { |
| 2622 | VerifyNameAndConnections(layer, name); |
| 2623 | VerifyDescriptor(descriptor); |
| 2624 | } |
| 2625 | |
| 2626 | private: |
| 2627 | void VerifyDescriptor(const armnn::ViewsDescriptor& descriptor) |
| 2628 | { |
| 2629 | BOOST_TEST(descriptor.GetNumViews() == m_Descriptor.GetNumViews()); |
| 2630 | BOOST_TEST(descriptor.GetNumDimensions() == m_Descriptor.GetNumDimensions()); |
| 2631 | |
| 2632 | for (uint32_t i = 0; i < descriptor.GetNumViews(); i++) |
| 2633 | { |
| 2634 | for (uint32_t j = 0; j < descriptor.GetNumDimensions(); j++) |
| 2635 | { |
| 2636 | BOOST_TEST(descriptor.GetViewOrigin(i)[j] == m_Descriptor.GetViewOrigin(i)[j]); |
| 2637 | BOOST_TEST(descriptor.GetViewSizes(i)[j] == m_Descriptor.GetViewSizes(i)[j]); |
| 2638 | } |
| 2639 | } |
| 2640 | } |
| 2641 | |
| 2642 | armnn::ViewsDescriptor m_Descriptor; |
| 2643 | }; |
| 2644 | |
| 2645 | const unsigned int numViews = 3; |
| 2646 | const unsigned int numDimensions = 4; |
| 2647 | const unsigned int inputShape[] = {1, 18, 4, 4}; |
| 2648 | const unsigned int outputShape[] = {1, 6, 4, 4}; |
| 2649 | |
| 2650 | // This is modelled on how the caffe parser sets up a splitter layer to partition an input along dimension one. |
| 2651 | unsigned int splitterDimSizes[4] = {static_cast<unsigned int>(inputShape[0]), |
| 2652 | static_cast<unsigned int>(inputShape[1]), |
| 2653 | static_cast<unsigned int>(inputShape[2]), |
| 2654 | static_cast<unsigned int>(inputShape[3])}; |
| 2655 | splitterDimSizes[1] /= numViews; |
| 2656 | armnn::ViewsDescriptor desc(numViews, numDimensions); |
| 2657 | |
| 2658 | for (unsigned int g = 0; g < numViews; ++g) |
| 2659 | { |
| 2660 | desc.SetViewOriginCoord(g, 1, splitterDimSizes[1] * g); |
| 2661 | |
| 2662 | for (unsigned int dimIdx=0; dimIdx < 4; dimIdx++) |
| 2663 | { |
| 2664 | desc.SetViewSize(g, dimIdx, splitterDimSizes[dimIdx]); |
| 2665 | } |
| 2666 | } |
| 2667 | |
| 2668 | const std::string layerName("splitter"); |
| 2669 | const armnn::TensorInfo inputInfo(numDimensions, inputShape, armnn::DataType::Float32); |
| 2670 | const armnn::TensorInfo outputInfo(numDimensions, outputShape, armnn::DataType::Float32); |
| 2671 | |
| 2672 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2673 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2674 | armnn::IConnectableLayer* const splitterLayer = network->AddSplitterLayer(desc, layerName.c_str()); |
| 2675 | armnn::IConnectableLayer* const outputLayer0 = network->AddOutputLayer(0); |
| 2676 | armnn::IConnectableLayer* const outputLayer1 = network->AddOutputLayer(1); |
| 2677 | armnn::IConnectableLayer* const outputLayer2 = network->AddOutputLayer(2); |
| 2678 | |
| 2679 | inputLayer->GetOutputSlot(0).Connect(splitterLayer->GetInputSlot(0)); |
| 2680 | splitterLayer->GetOutputSlot(0).Connect(outputLayer0->GetInputSlot(0)); |
| 2681 | splitterLayer->GetOutputSlot(1).Connect(outputLayer1->GetInputSlot(0)); |
| 2682 | splitterLayer->GetOutputSlot(2).Connect(outputLayer2->GetInputSlot(0)); |
| 2683 | |
| 2684 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2685 | splitterLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2686 | splitterLayer->GetOutputSlot(1).SetTensorInfo(outputInfo); |
| 2687 | splitterLayer->GetOutputSlot(2).SetTensorInfo(outputInfo); |
| 2688 | |
| 2689 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2690 | BOOST_CHECK(deserializedNetwork); |
| 2691 | |
| 2692 | SplitterLayerVerifier verifier(layerName, {inputInfo}, {outputInfo, outputInfo, outputInfo}, desc); |
| 2693 | deserializedNetwork->Accept(verifier); |
| 2694 | } |
| 2695 | |
Matthew Jackson | b5433ee | 2019-07-11 15:54:20 +0100 | [diff] [blame] | 2696 | BOOST_AUTO_TEST_CASE(SerializeStack) |
| 2697 | { |
| 2698 | class StackLayerVerifier : public LayerVerifierBase |
| 2699 | { |
| 2700 | public: |
| 2701 | StackLayerVerifier(const std::string& layerName, |
| 2702 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2703 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 2704 | const armnn::StackDescriptor& descriptor) |
| 2705 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 2706 | , m_Descriptor(descriptor) {} |
| 2707 | |
| 2708 | void VisitStackLayer(const armnn::IConnectableLayer* layer, |
| 2709 | const armnn::StackDescriptor& descriptor, |
| 2710 | const char* name) override |
| 2711 | { |
| 2712 | VerifyNameAndConnections(layer, name); |
| 2713 | VerifyDescriptor(descriptor); |
| 2714 | } |
| 2715 | |
| 2716 | private: |
| 2717 | void VerifyDescriptor(const armnn::StackDescriptor& descriptor) |
| 2718 | { |
| 2719 | BOOST_TEST(descriptor.m_Axis == m_Descriptor.m_Axis); |
| 2720 | BOOST_TEST(descriptor.m_InputShape == m_Descriptor.m_InputShape); |
| 2721 | BOOST_TEST(descriptor.m_NumInputs == m_Descriptor.m_NumInputs); |
| 2722 | } |
| 2723 | |
| 2724 | armnn::StackDescriptor m_Descriptor; |
| 2725 | }; |
| 2726 | |
| 2727 | const std::string layerName("stack"); |
| 2728 | |
| 2729 | armnn::TensorInfo inputTensorInfo ({4, 3, 5}, armnn::DataType::Float32); |
| 2730 | armnn::TensorInfo outputTensorInfo({4, 3, 2, 5}, armnn::DataType::Float32); |
| 2731 | |
| 2732 | armnn::StackDescriptor descriptor(2, 2, {4, 3, 5}); |
| 2733 | |
| 2734 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2735 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(0); |
| 2736 | armnn::IConnectableLayer* const inputLayer2 = network->AddInputLayer(1); |
| 2737 | armnn::IConnectableLayer* const stackLayer = network->AddStackLayer(descriptor, layerName.c_str()); |
| 2738 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2739 | |
| 2740 | inputLayer1->GetOutputSlot(0).Connect(stackLayer->GetInputSlot(0)); |
| 2741 | inputLayer2->GetOutputSlot(0).Connect(stackLayer->GetInputSlot(1)); |
| 2742 | stackLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2743 | |
| 2744 | inputLayer1->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 2745 | inputLayer2->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 2746 | stackLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| 2747 | |
| 2748 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2749 | BOOST_CHECK(deserializedNetwork); |
| 2750 | |
| 2751 | StackLayerVerifier verifier(layerName, {inputTensorInfo, inputTensorInfo}, {outputTensorInfo}, descriptor); |
| 2752 | deserializedNetwork->Accept(verifier); |
| 2753 | } |
| 2754 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2755 | BOOST_AUTO_TEST_CASE(SerializeStridedSlice) |
| 2756 | { |
| 2757 | class StridedSliceLayerVerifier : public LayerVerifierBase |
| 2758 | { |
| 2759 | public: |
| 2760 | StridedSliceLayerVerifier(const std::string& layerName, |
| 2761 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2762 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 2763 | const armnn::StridedSliceDescriptor& descriptor) |
| 2764 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 2765 | , m_Descriptor(descriptor) {} |
| 2766 | |
| 2767 | void VisitStridedSliceLayer(const armnn::IConnectableLayer* layer, |
| 2768 | const armnn::StridedSliceDescriptor& descriptor, |
| 2769 | const char* name) override |
| 2770 | { |
| 2771 | VerifyNameAndConnections(layer, name); |
| 2772 | VerifyDescriptor(descriptor); |
| 2773 | } |
| 2774 | |
| 2775 | private: |
| 2776 | void VerifyDescriptor(const armnn::StridedSliceDescriptor& descriptor) |
| 2777 | { |
| 2778 | BOOST_TEST(descriptor.m_Begin == m_Descriptor.m_Begin); |
| 2779 | BOOST_TEST(descriptor.m_End == m_Descriptor.m_End); |
| 2780 | BOOST_TEST(descriptor.m_Stride == m_Descriptor.m_Stride); |
| 2781 | BOOST_TEST(descriptor.m_BeginMask == m_Descriptor.m_BeginMask); |
| 2782 | BOOST_TEST(descriptor.m_EndMask == m_Descriptor.m_EndMask); |
| 2783 | BOOST_TEST(descriptor.m_ShrinkAxisMask == m_Descriptor.m_ShrinkAxisMask); |
| 2784 | BOOST_TEST(descriptor.m_EllipsisMask == m_Descriptor.m_EllipsisMask); |
| 2785 | BOOST_TEST(descriptor.m_NewAxisMask == m_Descriptor.m_NewAxisMask); |
| 2786 | BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout)); |
| 2787 | } |
| 2788 | armnn::StridedSliceDescriptor m_Descriptor; |
| 2789 | }; |
| 2790 | |
| 2791 | const std::string layerName("stridedSlice"); |
| 2792 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({3, 2, 3, 1}, armnn::DataType::Float32); |
| 2793 | const armnn::TensorInfo outputInfo = armnn::TensorInfo({3, 1}, armnn::DataType::Float32); |
| 2794 | |
| 2795 | armnn::StridedSliceDescriptor desc({0, 0, 1, 0}, {1, 1, 1, 1}, {1, 1, 1, 1}); |
| 2796 | desc.m_EndMask = (1 << 4) - 1; |
| 2797 | desc.m_ShrinkAxisMask = (1 << 1) | (1 << 2); |
| 2798 | desc.m_DataLayout = armnn::DataLayout::NCHW; |
| 2799 | |
| 2800 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2801 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2802 | armnn::IConnectableLayer* const stridedSliceLayer = network->AddStridedSliceLayer(desc, layerName.c_str()); |
| 2803 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2804 | |
| 2805 | inputLayer->GetOutputSlot(0).Connect(stridedSliceLayer->GetInputSlot(0)); |
| 2806 | stridedSliceLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2807 | |
| 2808 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2809 | stridedSliceLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2810 | |
| 2811 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2812 | BOOST_CHECK(deserializedNetwork); |
| 2813 | |
| 2814 | StridedSliceLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc); |
| 2815 | deserializedNetwork->Accept(verifier); |
| 2816 | } |
| 2817 | |
| 2818 | BOOST_AUTO_TEST_CASE(SerializeSubtraction) |
| 2819 | { |
| 2820 | class SubtractionLayerVerifier : public LayerVerifierBase |
| 2821 | { |
| 2822 | public: |
| 2823 | SubtractionLayerVerifier(const std::string& layerName, |
| 2824 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2825 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 2826 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 2827 | |
| 2828 | void VisitSubtractionLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 2829 | { |
| 2830 | VerifyNameAndConnections(layer, name); |
| 2831 | } |
| 2832 | }; |
| 2833 | |
| 2834 | const std::string layerName("subtraction"); |
| 2835 | const armnn::TensorInfo info({ 1, 4 }, armnn::DataType::Float32); |
| 2836 | |
| 2837 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2838 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 2839 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 2840 | armnn::IConnectableLayer* const subtractionLayer = network->AddSubtractionLayer(layerName.c_str()); |
| 2841 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2842 | |
| 2843 | inputLayer0->GetOutputSlot(0).Connect(subtractionLayer->GetInputSlot(0)); |
| 2844 | inputLayer1->GetOutputSlot(0).Connect(subtractionLayer->GetInputSlot(1)); |
| 2845 | subtractionLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2846 | |
| 2847 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 2848 | inputLayer1->GetOutputSlot(0).SetTensorInfo(info); |
| 2849 | subtractionLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2850 | |
| 2851 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2852 | BOOST_CHECK(deserializedNetwork); |
| 2853 | |
| 2854 | SubtractionLayerVerifier verifier(layerName, {info, info}, {info}); |
| 2855 | deserializedNetwork->Accept(verifier); |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 2856 | } |
| 2857 | |
Sadik Armagan | eff363d | 2019-04-05 15:25:46 +0100 | [diff] [blame] | 2858 | BOOST_AUTO_TEST_CASE(SerializeSwitch) |
| 2859 | { |
| 2860 | class SwitchLayerVerifier : public LayerVerifierBase |
| 2861 | { |
| 2862 | public: |
| 2863 | SwitchLayerVerifier(const std::string& layerName, |
| 2864 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2865 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 2866 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 2867 | |
| 2868 | void VisitSwitchLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 2869 | { |
| 2870 | VerifyNameAndConnections(layer, name); |
| 2871 | } |
| 2872 | |
| 2873 | void VisitConstantLayer(const armnn::IConnectableLayer* layer, |
| 2874 | const armnn::ConstTensor& input, |
| 2875 | const char *name) override {} |
| 2876 | }; |
| 2877 | |
| 2878 | const std::string layerName("switch"); |
| 2879 | const armnn::TensorInfo info({ 1, 4 }, armnn::DataType::Float32); |
| 2880 | |
| 2881 | std::vector<float> constantData = GenerateRandomData<float>(info.GetNumElements()); |
| 2882 | armnn::ConstTensor constTensor(info, constantData); |
| 2883 | |
| 2884 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2885 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2886 | armnn::IConnectableLayer* const constantLayer = network->AddConstantLayer(constTensor, "constant"); |
| 2887 | armnn::IConnectableLayer* const switchLayer = network->AddSwitchLayer(layerName.c_str()); |
| 2888 | armnn::IConnectableLayer* const trueOutputLayer = network->AddOutputLayer(0); |
| 2889 | armnn::IConnectableLayer* const falseOutputLayer = network->AddOutputLayer(1); |
| 2890 | |
| 2891 | inputLayer->GetOutputSlot(0).Connect(switchLayer->GetInputSlot(0)); |
| 2892 | constantLayer->GetOutputSlot(0).Connect(switchLayer->GetInputSlot(1)); |
| 2893 | switchLayer->GetOutputSlot(0).Connect(trueOutputLayer->GetInputSlot(0)); |
| 2894 | switchLayer->GetOutputSlot(1).Connect(falseOutputLayer->GetInputSlot(0)); |
| 2895 | |
| 2896 | inputLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2897 | constantLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2898 | switchLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2899 | switchLayer->GetOutputSlot(1).SetTensorInfo(info); |
| 2900 | |
| 2901 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2902 | BOOST_CHECK(deserializedNetwork); |
| 2903 | |
| 2904 | SwitchLayerVerifier verifier(layerName, {info, info}, {info, info}); |
| 2905 | deserializedNetwork->Accept(verifier); |
| 2906 | } |
| 2907 | |
Aron Virginas-Tar | cb54930 | 2019-06-21 13:53:38 +0100 | [diff] [blame] | 2908 | BOOST_AUTO_TEST_CASE(SerializeTransposeConvolution2d) |
| 2909 | { |
| 2910 | class TransposeConvolution2dLayerVerifier : public LayerVerifierBase |
| 2911 | { |
| 2912 | public: |
| 2913 | TransposeConvolution2dLayerVerifier(const std::string& layerName, |
| 2914 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2915 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 2916 | const armnn::TransposeConvolution2dDescriptor& descriptor, |
| 2917 | const armnn::ConstTensor& weights, |
| 2918 | const armnn::Optional<armnn::ConstTensor>& biases) : |
| 2919 | LayerVerifierBase(layerName, inputInfos, outputInfos), |
| 2920 | m_Descriptor(descriptor), |
| 2921 | m_Weights(weights), |
| 2922 | m_Biases(biases) |
| 2923 | {} |
| 2924 | |
| 2925 | void VisitTransposeConvolution2dLayer(const armnn::IConnectableLayer* layer, |
| 2926 | const armnn::TransposeConvolution2dDescriptor& descriptor, |
| 2927 | const armnn::ConstTensor& weights, |
| 2928 | const armnn::Optional<armnn::ConstTensor>& biases, |
| 2929 | const char* name) override |
| 2930 | { |
| 2931 | VerifyNameAndConnections(layer, name); |
| 2932 | VerifyDescriptor(descriptor); |
| 2933 | |
| 2934 | // check weights |
| 2935 | CompareConstTensor(weights, m_Weights); |
| 2936 | |
| 2937 | // check biases |
| 2938 | BOOST_CHECK(biases.has_value() == descriptor.m_BiasEnabled); |
| 2939 | BOOST_CHECK(m_Biases.has_value() == m_Descriptor.m_BiasEnabled); |
| 2940 | |
| 2941 | BOOST_CHECK(biases.has_value() == m_Biases.has_value()); |
| 2942 | |
| 2943 | if (biases.has_value() && m_Biases.has_value()) |
| 2944 | { |
| 2945 | CompareConstTensor(biases.value(), m_Biases.value()); |
| 2946 | } |
| 2947 | } |
| 2948 | |
| 2949 | private: |
| 2950 | void VerifyDescriptor(const armnn::TransposeConvolution2dDescriptor& descriptor) |
| 2951 | { |
| 2952 | BOOST_CHECK(descriptor.m_PadLeft == m_Descriptor.m_PadLeft); |
| 2953 | BOOST_CHECK(descriptor.m_PadRight == m_Descriptor.m_PadRight); |
| 2954 | BOOST_CHECK(descriptor.m_PadTop == m_Descriptor.m_PadTop); |
| 2955 | BOOST_CHECK(descriptor.m_PadBottom == m_Descriptor.m_PadBottom); |
| 2956 | BOOST_CHECK(descriptor.m_StrideX == m_Descriptor.m_StrideX); |
| 2957 | BOOST_CHECK(descriptor.m_StrideY == m_Descriptor.m_StrideY); |
| 2958 | BOOST_CHECK(descriptor.m_BiasEnabled == m_Descriptor.m_BiasEnabled); |
| 2959 | BOOST_CHECK(descriptor.m_DataLayout == m_Descriptor.m_DataLayout); |
| 2960 | } |
| 2961 | |
| 2962 | armnn::TransposeConvolution2dDescriptor m_Descriptor; |
| 2963 | armnn::ConstTensor m_Weights; |
| 2964 | armnn::Optional<armnn::ConstTensor> m_Biases; |
| 2965 | }; |
| 2966 | |
| 2967 | const std::string layerName("transposeConvolution2d"); |
| 2968 | const armnn::TensorInfo inputInfo ({ 1, 7, 7, 1 }, armnn::DataType::Float32); |
| 2969 | const armnn::TensorInfo outputInfo({ 1, 9, 9, 1 }, armnn::DataType::Float32); |
| 2970 | |
| 2971 | const armnn::TensorInfo weightsInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32); |
| 2972 | const armnn::TensorInfo biasesInfo ({ 1 }, armnn::DataType::Float32); |
| 2973 | |
| 2974 | std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements()); |
| 2975 | armnn::ConstTensor weights(weightsInfo, weightsData); |
| 2976 | |
| 2977 | std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements()); |
| 2978 | armnn::ConstTensor biases(biasesInfo, biasesData); |
| 2979 | |
| 2980 | armnn::TransposeConvolution2dDescriptor descriptor; |
| 2981 | descriptor.m_PadLeft = 1; |
| 2982 | descriptor.m_PadRight = 1; |
| 2983 | descriptor.m_PadTop = 1; |
| 2984 | descriptor.m_PadBottom = 1; |
| 2985 | descriptor.m_StrideX = 1; |
| 2986 | descriptor.m_StrideY = 1; |
| 2987 | descriptor.m_BiasEnabled = true; |
| 2988 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 2989 | |
| 2990 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2991 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2992 | armnn::IConnectableLayer* const convLayer = |
| 2993 | network->AddTransposeConvolution2dLayer(descriptor, |
| 2994 | weights, |
| 2995 | armnn::Optional<armnn::ConstTensor>(biases), |
| 2996 | layerName.c_str()); |
| 2997 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2998 | |
| 2999 | inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0)); |
| 3000 | convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 3001 | |
| 3002 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 3003 | convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 3004 | |
| 3005 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 3006 | BOOST_CHECK(deserializedNetwork); |
| 3007 | |
| 3008 | TransposeConvolution2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases); |
| 3009 | deserializedNetwork->Accept(verifier); |
| 3010 | } |
| 3011 | |
Sadik Armagan | db059fd | 2019-03-20 12:28:32 +0000 | [diff] [blame] | 3012 | BOOST_AUTO_TEST_CASE(SerializeDeserializeNonLinearNetwork) |
| 3013 | { |
| 3014 | class ConstantLayerVerifier : public LayerVerifierBase |
| 3015 | { |
| 3016 | public: |
| 3017 | ConstantLayerVerifier(const std::string& layerName, |
| 3018 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 3019 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 3020 | const armnn::ConstTensor& layerInput) |
| 3021 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 3022 | , m_LayerInput(layerInput) {} |
| 3023 | |
| 3024 | void VisitConstantLayer(const armnn::IConnectableLayer* layer, |
| 3025 | const armnn::ConstTensor& input, |
| 3026 | const char* name) override |
| 3027 | { |
| 3028 | VerifyNameAndConnections(layer, name); |
| 3029 | |
| 3030 | CompareConstTensor(input, m_LayerInput); |
| 3031 | } |
| 3032 | |
| 3033 | void VisitAdditionLayer(const armnn::IConnectableLayer* layer, const char* name = nullptr) override {} |
| 3034 | |
| 3035 | private: |
| 3036 | armnn::ConstTensor m_LayerInput; |
| 3037 | }; |
| 3038 | |
| 3039 | const std::string layerName("constant"); |
| 3040 | const armnn::TensorInfo info({ 2, 3 }, armnn::DataType::Float32); |
| 3041 | |
| 3042 | std::vector<float> constantData = GenerateRandomData<float>(info.GetNumElements()); |
| 3043 | armnn::ConstTensor constTensor(info, constantData); |
| 3044 | |
| 3045 | armnn::INetworkPtr network(armnn::INetwork::Create()); |
| 3046 | armnn::IConnectableLayer* input = network->AddInputLayer(0); |
| 3047 | armnn::IConnectableLayer* add = network->AddAdditionLayer(); |
| 3048 | armnn::IConnectableLayer* constant = network->AddConstantLayer(constTensor, layerName.c_str()); |
| 3049 | armnn::IConnectableLayer* output = network->AddOutputLayer(0); |
| 3050 | |
| 3051 | input->GetOutputSlot(0).Connect(add->GetInputSlot(0)); |
| 3052 | constant->GetOutputSlot(0).Connect(add->GetInputSlot(1)); |
| 3053 | add->GetOutputSlot(0).Connect(output->GetInputSlot(0)); |
| 3054 | |
| 3055 | input->GetOutputSlot(0).SetTensorInfo(info); |
| 3056 | constant->GetOutputSlot(0).SetTensorInfo(info); |
| 3057 | add->GetOutputSlot(0).SetTensorInfo(info); |
| 3058 | |
| 3059 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 3060 | BOOST_CHECK(deserializedNetwork); |
| 3061 | |
| 3062 | ConstantLayerVerifier verifier(layerName, {}, {info}, constTensor); |
| 3063 | deserializedNetwork->Accept(verifier); |
| 3064 | } |
| 3065 | |
Jim Flynn | 11af375 | 2019-03-19 17:22:29 +0000 | [diff] [blame] | 3066 | class VerifyLstmLayer : public LayerVerifierBase |
| 3067 | { |
| 3068 | public: |
| 3069 | VerifyLstmLayer(const std::string& layerName, |
| 3070 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 3071 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 3072 | const armnn::LstmDescriptor& descriptor, |
| 3073 | const armnn::LstmInputParams& inputParams) : |
| 3074 | LayerVerifierBase(layerName, inputInfos, outputInfos), m_Descriptor(descriptor), m_InputParams(inputParams) |
| 3075 | { |
| 3076 | } |
| 3077 | void VisitLstmLayer(const armnn::IConnectableLayer* layer, |
| 3078 | const armnn::LstmDescriptor& descriptor, |
| 3079 | const armnn::LstmInputParams& params, |
| 3080 | const char* name) |
| 3081 | { |
| 3082 | VerifyNameAndConnections(layer, name); |
| 3083 | VerifyDescriptor(descriptor); |
| 3084 | VerifyInputParameters(params); |
| 3085 | } |
| 3086 | protected: |
| 3087 | void VerifyDescriptor(const armnn::LstmDescriptor& descriptor) |
| 3088 | { |
| 3089 | BOOST_TEST(m_Descriptor.m_ActivationFunc == descriptor.m_ActivationFunc); |
| 3090 | BOOST_TEST(m_Descriptor.m_ClippingThresCell == descriptor.m_ClippingThresCell); |
| 3091 | BOOST_TEST(m_Descriptor.m_ClippingThresProj == descriptor.m_ClippingThresProj); |
| 3092 | BOOST_TEST(m_Descriptor.m_CifgEnabled == descriptor.m_CifgEnabled); |
| 3093 | BOOST_TEST(m_Descriptor.m_PeepholeEnabled = descriptor.m_PeepholeEnabled); |
| 3094 | BOOST_TEST(m_Descriptor.m_ProjectionEnabled == descriptor.m_ProjectionEnabled); |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 3095 | BOOST_TEST(m_Descriptor.m_LayerNormEnabled == descriptor.m_LayerNormEnabled); |
Jim Flynn | 11af375 | 2019-03-19 17:22:29 +0000 | [diff] [blame] | 3096 | } |
| 3097 | void VerifyInputParameters(const armnn::LstmInputParams& params) |
| 3098 | { |
| 3099 | VerifyConstTensors( |
| 3100 | "m_InputToInputWeights", m_InputParams.m_InputToInputWeights, params.m_InputToInputWeights); |
| 3101 | VerifyConstTensors( |
| 3102 | "m_InputToForgetWeights", m_InputParams.m_InputToForgetWeights, params.m_InputToForgetWeights); |
| 3103 | VerifyConstTensors( |
| 3104 | "m_InputToCellWeights", m_InputParams.m_InputToCellWeights, params.m_InputToCellWeights); |
| 3105 | VerifyConstTensors( |
| 3106 | "m_InputToOutputWeights", m_InputParams.m_InputToOutputWeights, params.m_InputToOutputWeights); |
| 3107 | VerifyConstTensors( |
| 3108 | "m_RecurrentToInputWeights", m_InputParams.m_RecurrentToInputWeights, params.m_RecurrentToInputWeights); |
| 3109 | VerifyConstTensors( |
| 3110 | "m_RecurrentToForgetWeights", m_InputParams.m_RecurrentToForgetWeights, params.m_RecurrentToForgetWeights); |
| 3111 | VerifyConstTensors( |
| 3112 | "m_RecurrentToCellWeights", m_InputParams.m_RecurrentToCellWeights, params.m_RecurrentToCellWeights); |
| 3113 | VerifyConstTensors( |
| 3114 | "m_RecurrentToOutputWeights", m_InputParams.m_RecurrentToOutputWeights, params.m_RecurrentToOutputWeights); |
| 3115 | VerifyConstTensors( |
| 3116 | "m_CellToInputWeights", m_InputParams.m_CellToInputWeights, params.m_CellToInputWeights); |
| 3117 | VerifyConstTensors( |
| 3118 | "m_CellToForgetWeights", m_InputParams.m_CellToForgetWeights, params.m_CellToForgetWeights); |
| 3119 | VerifyConstTensors( |
| 3120 | "m_CellToOutputWeights", m_InputParams.m_CellToOutputWeights, params.m_CellToOutputWeights); |
| 3121 | VerifyConstTensors( |
| 3122 | "m_InputGateBias", m_InputParams.m_InputGateBias, params.m_InputGateBias); |
| 3123 | VerifyConstTensors( |
| 3124 | "m_ForgetGateBias", m_InputParams.m_ForgetGateBias, params.m_ForgetGateBias); |
| 3125 | VerifyConstTensors( |
| 3126 | "m_CellBias", m_InputParams.m_CellBias, params.m_CellBias); |
| 3127 | VerifyConstTensors( |
| 3128 | "m_OutputGateBias", m_InputParams.m_OutputGateBias, params.m_OutputGateBias); |
| 3129 | VerifyConstTensors( |
| 3130 | "m_ProjectionWeights", m_InputParams.m_ProjectionWeights, params.m_ProjectionWeights); |
| 3131 | VerifyConstTensors( |
| 3132 | "m_ProjectionBias", m_InputParams.m_ProjectionBias, params.m_ProjectionBias); |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 3133 | VerifyConstTensors( |
| 3134 | "m_InputLayerNormWeights", m_InputParams.m_InputLayerNormWeights, params.m_InputLayerNormWeights); |
| 3135 | VerifyConstTensors( |
| 3136 | "m_ForgetLayerNormWeights", m_InputParams.m_ForgetLayerNormWeights, params.m_ForgetLayerNormWeights); |
| 3137 | VerifyConstTensors( |
| 3138 | "m_CellLayerNormWeights", m_InputParams.m_CellLayerNormWeights, params.m_CellLayerNormWeights); |
| 3139 | VerifyConstTensors( |
| 3140 | "m_OutputLayerNormWeights", m_InputParams.m_OutputLayerNormWeights, params.m_OutputLayerNormWeights); |
Jim Flynn | 11af375 | 2019-03-19 17:22:29 +0000 | [diff] [blame] | 3141 | } |
Jim Flynn | 11af375 | 2019-03-19 17:22:29 +0000 | [diff] [blame] | 3142 | private: |
| 3143 | armnn::LstmDescriptor m_Descriptor; |
| 3144 | armnn::LstmInputParams m_InputParams; |
| 3145 | }; |
| 3146 | |
| 3147 | BOOST_AUTO_TEST_CASE(SerializeDeserializeLstmCifgPeepholeNoProjection) |
| 3148 | { |
| 3149 | armnn::LstmDescriptor descriptor; |
| 3150 | descriptor.m_ActivationFunc = 4; |
| 3151 | descriptor.m_ClippingThresProj = 0.0f; |
| 3152 | descriptor.m_ClippingThresCell = 0.0f; |
| 3153 | descriptor.m_CifgEnabled = true; // if this is true then we DON'T need to set the OptCifgParams |
| 3154 | descriptor.m_ProjectionEnabled = false; |
| 3155 | descriptor.m_PeepholeEnabled = true; |
| 3156 | |
| 3157 | const uint32_t batchSize = 1; |
| 3158 | const uint32_t inputSize = 2; |
| 3159 | const uint32_t numUnits = 4; |
| 3160 | const uint32_t outputSize = numUnits; |
| 3161 | |
| 3162 | armnn::TensorInfo inputWeightsInfo1({numUnits, inputSize}, armnn::DataType::Float32); |
| 3163 | std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements()); |
| 3164 | armnn::ConstTensor inputToForgetWeights(inputWeightsInfo1, inputToForgetWeightsData); |
| 3165 | |
| 3166 | std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements()); |
| 3167 | armnn::ConstTensor inputToCellWeights(inputWeightsInfo1, inputToCellWeightsData); |
| 3168 | |
| 3169 | std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements()); |
| 3170 | armnn::ConstTensor inputToOutputWeights(inputWeightsInfo1, inputToOutputWeightsData); |
| 3171 | |
| 3172 | armnn::TensorInfo inputWeightsInfo2({numUnits, outputSize}, armnn::DataType::Float32); |
| 3173 | std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements()); |
| 3174 | armnn::ConstTensor recurrentToForgetWeights(inputWeightsInfo2, recurrentToForgetWeightsData); |
| 3175 | |
| 3176 | std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements()); |
| 3177 | armnn::ConstTensor recurrentToCellWeights(inputWeightsInfo2, recurrentToCellWeightsData); |
| 3178 | |
| 3179 | std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements()); |
| 3180 | armnn::ConstTensor recurrentToOutputWeights(inputWeightsInfo2, recurrentToOutputWeightsData); |
| 3181 | |
| 3182 | armnn::TensorInfo inputWeightsInfo3({numUnits}, armnn::DataType::Float32); |
| 3183 | std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo3.GetNumElements()); |
| 3184 | armnn::ConstTensor cellToForgetWeights(inputWeightsInfo3, cellToForgetWeightsData); |
| 3185 | |
| 3186 | std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo3.GetNumElements()); |
| 3187 | armnn::ConstTensor cellToOutputWeights(inputWeightsInfo3, cellToOutputWeightsData); |
| 3188 | |
| 3189 | std::vector<float> forgetGateBiasData(numUnits, 1.0f); |
| 3190 | armnn::ConstTensor forgetGateBias(inputWeightsInfo3, forgetGateBiasData); |
| 3191 | |
| 3192 | std::vector<float> cellBiasData(numUnits, 0.0f); |
| 3193 | armnn::ConstTensor cellBias(inputWeightsInfo3, cellBiasData); |
| 3194 | |
| 3195 | std::vector<float> outputGateBiasData(numUnits, 0.0f); |
| 3196 | armnn::ConstTensor outputGateBias(inputWeightsInfo3, outputGateBiasData); |
| 3197 | |
| 3198 | armnn::LstmInputParams params; |
| 3199 | params.m_InputToForgetWeights = &inputToForgetWeights; |
| 3200 | params.m_InputToCellWeights = &inputToCellWeights; |
| 3201 | params.m_InputToOutputWeights = &inputToOutputWeights; |
| 3202 | params.m_RecurrentToForgetWeights = &recurrentToForgetWeights; |
| 3203 | params.m_RecurrentToCellWeights = &recurrentToCellWeights; |
| 3204 | params.m_RecurrentToOutputWeights = &recurrentToOutputWeights; |
| 3205 | params.m_ForgetGateBias = &forgetGateBias; |
| 3206 | params.m_CellBias = &cellBias; |
| 3207 | params.m_OutputGateBias = &outputGateBias; |
| 3208 | params.m_CellToForgetWeights = &cellToForgetWeights; |
| 3209 | params.m_CellToOutputWeights = &cellToOutputWeights; |
| 3210 | |
| 3211 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 3212 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 3213 | armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1); |
| 3214 | armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2); |
| 3215 | const std::string layerName("lstm"); |
| 3216 | armnn::IConnectableLayer* const lstmLayer = network->AddLstmLayer(descriptor, params, layerName.c_str()); |
| 3217 | armnn::IConnectableLayer* const scratchBuffer = network->AddOutputLayer(0); |
| 3218 | armnn::IConnectableLayer* const outputStateOut = network->AddOutputLayer(1); |
| 3219 | armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(2); |
| 3220 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(3); |
| 3221 | |
| 3222 | // connect up |
| 3223 | armnn::TensorInfo inputTensorInfo({ batchSize, inputSize }, armnn::DataType::Float32); |
| 3224 | armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32); |
| 3225 | armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32); |
| 3226 | armnn::TensorInfo lstmTensorInfoScratchBuff({ batchSize, numUnits * 3 }, armnn::DataType::Float32); |
| 3227 | |
| 3228 | inputLayer->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(0)); |
| 3229 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 3230 | |
| 3231 | outputStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(1)); |
| 3232 | outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo); |
| 3233 | |
| 3234 | cellStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(2)); |
| 3235 | cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo); |
| 3236 | |
| 3237 | lstmLayer->GetOutputSlot(0).Connect(scratchBuffer->GetInputSlot(0)); |
| 3238 | lstmLayer->GetOutputSlot(0).SetTensorInfo(lstmTensorInfoScratchBuff); |
| 3239 | |
| 3240 | lstmLayer->GetOutputSlot(1).Connect(outputStateOut->GetInputSlot(0)); |
| 3241 | lstmLayer->GetOutputSlot(1).SetTensorInfo(outputStateTensorInfo); |
| 3242 | |
| 3243 | lstmLayer->GetOutputSlot(2).Connect(cellStateOut->GetInputSlot(0)); |
| 3244 | lstmLayer->GetOutputSlot(2).SetTensorInfo(cellStateTensorInfo); |
| 3245 | |
| 3246 | lstmLayer->GetOutputSlot(3).Connect(outputLayer->GetInputSlot(0)); |
| 3247 | lstmLayer->GetOutputSlot(3).SetTensorInfo(outputStateTensorInfo); |
| 3248 | |
| 3249 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 3250 | BOOST_CHECK(deserializedNetwork); |
| 3251 | |
| 3252 | VerifyLstmLayer checker( |
| 3253 | layerName, |
| 3254 | {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo}, |
| 3255 | {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo}, |
| 3256 | descriptor, |
| 3257 | params); |
| 3258 | deserializedNetwork->Accept(checker); |
| 3259 | } |
| 3260 | |
| 3261 | BOOST_AUTO_TEST_CASE(SerializeDeserializeLstmNoCifgWithPeepholeAndProjection) |
| 3262 | { |
| 3263 | armnn::LstmDescriptor descriptor; |
| 3264 | descriptor.m_ActivationFunc = 4; |
| 3265 | descriptor.m_ClippingThresProj = 0.0f; |
| 3266 | descriptor.m_ClippingThresCell = 0.0f; |
| 3267 | descriptor.m_CifgEnabled = false; // if this is true then we DON'T need to set the OptCifgParams |
| 3268 | descriptor.m_ProjectionEnabled = true; |
| 3269 | descriptor.m_PeepholeEnabled = true; |
| 3270 | |
| 3271 | const uint32_t batchSize = 2; |
| 3272 | const uint32_t inputSize = 5; |
| 3273 | const uint32_t numUnits = 20; |
| 3274 | const uint32_t outputSize = 16; |
| 3275 | |
| 3276 | armnn::TensorInfo tensorInfo20x5({numUnits, inputSize}, armnn::DataType::Float32); |
| 3277 | std::vector<float> inputToInputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3278 | armnn::ConstTensor inputToInputWeights(tensorInfo20x5, inputToInputWeightsData); |
| 3279 | |
| 3280 | std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3281 | armnn::ConstTensor inputToForgetWeights(tensorInfo20x5, inputToForgetWeightsData); |
| 3282 | |
| 3283 | std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3284 | armnn::ConstTensor inputToCellWeights(tensorInfo20x5, inputToCellWeightsData); |
| 3285 | |
| 3286 | std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3287 | armnn::ConstTensor inputToOutputWeights(tensorInfo20x5, inputToOutputWeightsData); |
| 3288 | |
| 3289 | armnn::TensorInfo tensorInfo20({numUnits}, armnn::DataType::Float32); |
| 3290 | std::vector<float> inputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3291 | armnn::ConstTensor inputGateBias(tensorInfo20, inputGateBiasData); |
| 3292 | |
| 3293 | std::vector<float> forgetGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3294 | armnn::ConstTensor forgetGateBias(tensorInfo20, forgetGateBiasData); |
| 3295 | |
| 3296 | std::vector<float> cellBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3297 | armnn::ConstTensor cellBias(tensorInfo20, cellBiasData); |
| 3298 | |
| 3299 | std::vector<float> outputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3300 | armnn::ConstTensor outputGateBias(tensorInfo20, outputGateBiasData); |
| 3301 | |
| 3302 | armnn::TensorInfo tensorInfo20x16({numUnits, outputSize}, armnn::DataType::Float32); |
| 3303 | std::vector<float> recurrentToInputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3304 | armnn::ConstTensor recurrentToInputWeights(tensorInfo20x16, recurrentToInputWeightsData); |
| 3305 | |
| 3306 | std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3307 | armnn::ConstTensor recurrentToForgetWeights(tensorInfo20x16, recurrentToForgetWeightsData); |
| 3308 | |
| 3309 | std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3310 | armnn::ConstTensor recurrentToCellWeights(tensorInfo20x16, recurrentToCellWeightsData); |
| 3311 | |
| 3312 | std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3313 | armnn::ConstTensor recurrentToOutputWeights(tensorInfo20x16, recurrentToOutputWeightsData); |
| 3314 | |
| 3315 | std::vector<float> cellToInputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3316 | armnn::ConstTensor cellToInputWeights(tensorInfo20, cellToInputWeightsData); |
| 3317 | |
| 3318 | std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3319 | armnn::ConstTensor cellToForgetWeights(tensorInfo20, cellToForgetWeightsData); |
| 3320 | |
| 3321 | std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3322 | armnn::ConstTensor cellToOutputWeights(tensorInfo20, cellToOutputWeightsData); |
| 3323 | |
| 3324 | armnn::TensorInfo tensorInfo16x20({outputSize, numUnits}, armnn::DataType::Float32); |
| 3325 | std::vector<float> projectionWeightsData = GenerateRandomData<float>(tensorInfo16x20.GetNumElements()); |
| 3326 | armnn::ConstTensor projectionWeights(tensorInfo16x20, projectionWeightsData); |
| 3327 | |
| 3328 | armnn::TensorInfo tensorInfo16({outputSize}, armnn::DataType::Float32); |
| 3329 | std::vector<float> projectionBiasData(outputSize, 0.f); |
| 3330 | armnn::ConstTensor projectionBias(tensorInfo16, projectionBiasData); |
| 3331 | |
| 3332 | armnn::LstmInputParams params; |
| 3333 | params.m_InputToForgetWeights = &inputToForgetWeights; |
| 3334 | params.m_InputToCellWeights = &inputToCellWeights; |
| 3335 | params.m_InputToOutputWeights = &inputToOutputWeights; |
| 3336 | params.m_RecurrentToForgetWeights = &recurrentToForgetWeights; |
| 3337 | params.m_RecurrentToCellWeights = &recurrentToCellWeights; |
| 3338 | params.m_RecurrentToOutputWeights = &recurrentToOutputWeights; |
| 3339 | params.m_ForgetGateBias = &forgetGateBias; |
| 3340 | params.m_CellBias = &cellBias; |
| 3341 | params.m_OutputGateBias = &outputGateBias; |
| 3342 | |
| 3343 | // additional params because: descriptor.m_CifgEnabled = false |
| 3344 | params.m_InputToInputWeights = &inputToInputWeights; |
| 3345 | params.m_RecurrentToInputWeights = &recurrentToInputWeights; |
| 3346 | params.m_CellToInputWeights = &cellToInputWeights; |
| 3347 | params.m_InputGateBias = &inputGateBias; |
| 3348 | |
| 3349 | // additional params because: descriptor.m_ProjectionEnabled = true |
| 3350 | params.m_ProjectionWeights = &projectionWeights; |
| 3351 | params.m_ProjectionBias = &projectionBias; |
| 3352 | |
| 3353 | // additional params because: descriptor.m_PeepholeEnabled = true |
| 3354 | params.m_CellToForgetWeights = &cellToForgetWeights; |
| 3355 | params.m_CellToOutputWeights = &cellToOutputWeights; |
| 3356 | |
| 3357 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 3358 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 3359 | armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1); |
| 3360 | armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2); |
| 3361 | const std::string layerName("lstm"); |
| 3362 | armnn::IConnectableLayer* const lstmLayer = network->AddLstmLayer(descriptor, params, layerName.c_str()); |
| 3363 | armnn::IConnectableLayer* const scratchBuffer = network->AddOutputLayer(0); |
| 3364 | armnn::IConnectableLayer* const outputStateOut = network->AddOutputLayer(1); |
| 3365 | armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(2); |
| 3366 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(3); |
| 3367 | |
| 3368 | // connect up |
| 3369 | armnn::TensorInfo inputTensorInfo({ batchSize, inputSize }, armnn::DataType::Float32); |
| 3370 | armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32); |
| 3371 | armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32); |
| 3372 | armnn::TensorInfo lstmTensorInfoScratchBuff({ batchSize, numUnits * 4 }, armnn::DataType::Float32); |
| 3373 | |
| 3374 | inputLayer->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(0)); |
| 3375 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 3376 | |
| 3377 | outputStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(1)); |
| 3378 | outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo); |
| 3379 | |
| 3380 | cellStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(2)); |
| 3381 | cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo); |
| 3382 | |
| 3383 | lstmLayer->GetOutputSlot(0).Connect(scratchBuffer->GetInputSlot(0)); |
| 3384 | lstmLayer->GetOutputSlot(0).SetTensorInfo(lstmTensorInfoScratchBuff); |
| 3385 | |
| 3386 | lstmLayer->GetOutputSlot(1).Connect(outputStateOut->GetInputSlot(0)); |
| 3387 | lstmLayer->GetOutputSlot(1).SetTensorInfo(outputStateTensorInfo); |
| 3388 | |
| 3389 | lstmLayer->GetOutputSlot(2).Connect(cellStateOut->GetInputSlot(0)); |
| 3390 | lstmLayer->GetOutputSlot(2).SetTensorInfo(cellStateTensorInfo); |
| 3391 | |
| 3392 | lstmLayer->GetOutputSlot(3).Connect(outputLayer->GetInputSlot(0)); |
| 3393 | lstmLayer->GetOutputSlot(3).SetTensorInfo(outputStateTensorInfo); |
| 3394 | |
| 3395 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 3396 | BOOST_CHECK(deserializedNetwork); |
| 3397 | |
| 3398 | VerifyLstmLayer checker( |
| 3399 | layerName, |
| 3400 | {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo}, |
| 3401 | {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo}, |
| 3402 | descriptor, |
| 3403 | params); |
| 3404 | deserializedNetwork->Accept(checker); |
| 3405 | } |
| 3406 | |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 3407 | BOOST_AUTO_TEST_CASE(SerializeDeserializeLstmNoCifgWithPeepholeWithProjectionWithLayerNorm) |
| 3408 | { |
| 3409 | armnn::LstmDescriptor descriptor; |
| 3410 | descriptor.m_ActivationFunc = 4; |
| 3411 | descriptor.m_ClippingThresProj = 0.0f; |
| 3412 | descriptor.m_ClippingThresCell = 0.0f; |
| 3413 | descriptor.m_CifgEnabled = false; // if this is true then we DON'T need to set the OptCifgParams |
| 3414 | descriptor.m_ProjectionEnabled = true; |
| 3415 | descriptor.m_PeepholeEnabled = true; |
| 3416 | descriptor.m_LayerNormEnabled = true; |
| 3417 | |
| 3418 | const uint32_t batchSize = 2; |
| 3419 | const uint32_t inputSize = 5; |
| 3420 | const uint32_t numUnits = 20; |
| 3421 | const uint32_t outputSize = 16; |
| 3422 | |
| 3423 | armnn::TensorInfo tensorInfo20x5({numUnits, inputSize}, armnn::DataType::Float32); |
| 3424 | std::vector<float> inputToInputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3425 | armnn::ConstTensor inputToInputWeights(tensorInfo20x5, inputToInputWeightsData); |
| 3426 | |
| 3427 | std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3428 | armnn::ConstTensor inputToForgetWeights(tensorInfo20x5, inputToForgetWeightsData); |
| 3429 | |
| 3430 | std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3431 | armnn::ConstTensor inputToCellWeights(tensorInfo20x5, inputToCellWeightsData); |
| 3432 | |
| 3433 | std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3434 | armnn::ConstTensor inputToOutputWeights(tensorInfo20x5, inputToOutputWeightsData); |
| 3435 | |
| 3436 | armnn::TensorInfo tensorInfo20({numUnits}, armnn::DataType::Float32); |
| 3437 | std::vector<float> inputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3438 | armnn::ConstTensor inputGateBias(tensorInfo20, inputGateBiasData); |
| 3439 | |
| 3440 | std::vector<float> forgetGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3441 | armnn::ConstTensor forgetGateBias(tensorInfo20, forgetGateBiasData); |
| 3442 | |
| 3443 | std::vector<float> cellBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3444 | armnn::ConstTensor cellBias(tensorInfo20, cellBiasData); |
| 3445 | |
| 3446 | std::vector<float> outputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3447 | armnn::ConstTensor outputGateBias(tensorInfo20, outputGateBiasData); |
| 3448 | |
| 3449 | armnn::TensorInfo tensorInfo20x16({numUnits, outputSize}, armnn::DataType::Float32); |
| 3450 | std::vector<float> recurrentToInputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3451 | armnn::ConstTensor recurrentToInputWeights(tensorInfo20x16, recurrentToInputWeightsData); |
| 3452 | |
| 3453 | std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3454 | armnn::ConstTensor recurrentToForgetWeights(tensorInfo20x16, recurrentToForgetWeightsData); |
| 3455 | |
| 3456 | std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3457 | armnn::ConstTensor recurrentToCellWeights(tensorInfo20x16, recurrentToCellWeightsData); |
| 3458 | |
| 3459 | std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3460 | armnn::ConstTensor recurrentToOutputWeights(tensorInfo20x16, recurrentToOutputWeightsData); |
| 3461 | |
| 3462 | std::vector<float> cellToInputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3463 | armnn::ConstTensor cellToInputWeights(tensorInfo20, cellToInputWeightsData); |
| 3464 | |
| 3465 | std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3466 | armnn::ConstTensor cellToForgetWeights(tensorInfo20, cellToForgetWeightsData); |
| 3467 | |
| 3468 | std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3469 | armnn::ConstTensor cellToOutputWeights(tensorInfo20, cellToOutputWeightsData); |
| 3470 | |
| 3471 | armnn::TensorInfo tensorInfo16x20({outputSize, numUnits}, armnn::DataType::Float32); |
| 3472 | std::vector<float> projectionWeightsData = GenerateRandomData<float>(tensorInfo16x20.GetNumElements()); |
| 3473 | armnn::ConstTensor projectionWeights(tensorInfo16x20, projectionWeightsData); |
| 3474 | |
| 3475 | armnn::TensorInfo tensorInfo16({outputSize}, armnn::DataType::Float32); |
| 3476 | std::vector<float> projectionBiasData(outputSize, 0.f); |
| 3477 | armnn::ConstTensor projectionBias(tensorInfo16, projectionBiasData); |
| 3478 | |
| 3479 | std::vector<float> inputLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3480 | armnn::ConstTensor inputLayerNormWeights(tensorInfo20, forgetGateBiasData); |
| 3481 | |
| 3482 | std::vector<float> forgetLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3483 | armnn::ConstTensor forgetLayerNormWeights(tensorInfo20, forgetGateBiasData); |
| 3484 | |
| 3485 | std::vector<float> cellLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3486 | armnn::ConstTensor cellLayerNormWeights(tensorInfo20, forgetGateBiasData); |
| 3487 | |
| 3488 | std::vector<float> outLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3489 | armnn::ConstTensor outLayerNormWeights(tensorInfo20, forgetGateBiasData); |
| 3490 | |
| 3491 | armnn::LstmInputParams params; |
| 3492 | params.m_InputToForgetWeights = &inputToForgetWeights; |
| 3493 | params.m_InputToCellWeights = &inputToCellWeights; |
| 3494 | params.m_InputToOutputWeights = &inputToOutputWeights; |
| 3495 | params.m_RecurrentToForgetWeights = &recurrentToForgetWeights; |
| 3496 | params.m_RecurrentToCellWeights = &recurrentToCellWeights; |
| 3497 | params.m_RecurrentToOutputWeights = &recurrentToOutputWeights; |
| 3498 | params.m_ForgetGateBias = &forgetGateBias; |
| 3499 | params.m_CellBias = &cellBias; |
| 3500 | params.m_OutputGateBias = &outputGateBias; |
| 3501 | |
| 3502 | // additional params because: descriptor.m_CifgEnabled = false |
| 3503 | params.m_InputToInputWeights = &inputToInputWeights; |
| 3504 | params.m_RecurrentToInputWeights = &recurrentToInputWeights; |
| 3505 | params.m_CellToInputWeights = &cellToInputWeights; |
| 3506 | params.m_InputGateBias = &inputGateBias; |
| 3507 | |
| 3508 | // additional params because: descriptor.m_ProjectionEnabled = true |
| 3509 | params.m_ProjectionWeights = &projectionWeights; |
| 3510 | params.m_ProjectionBias = &projectionBias; |
| 3511 | |
| 3512 | // additional params because: descriptor.m_PeepholeEnabled = true |
| 3513 | params.m_CellToForgetWeights = &cellToForgetWeights; |
| 3514 | params.m_CellToOutputWeights = &cellToOutputWeights; |
| 3515 | |
| 3516 | // additional params because: despriptor.m_LayerNormEnabled = true |
| 3517 | params.m_InputLayerNormWeights = &inputLayerNormWeights; |
| 3518 | params.m_ForgetLayerNormWeights = &forgetLayerNormWeights; |
| 3519 | params.m_CellLayerNormWeights = &cellLayerNormWeights; |
| 3520 | params.m_OutputLayerNormWeights = &outLayerNormWeights; |
| 3521 | |
| 3522 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 3523 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 3524 | armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1); |
| 3525 | armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2); |
| 3526 | const std::string layerName("lstm"); |
| 3527 | armnn::IConnectableLayer* const lstmLayer = network->AddLstmLayer(descriptor, params, layerName.c_str()); |
| 3528 | armnn::IConnectableLayer* const scratchBuffer = network->AddOutputLayer(0); |
| 3529 | armnn::IConnectableLayer* const outputStateOut = network->AddOutputLayer(1); |
| 3530 | armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(2); |
| 3531 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(3); |
| 3532 | |
| 3533 | // connect up |
| 3534 | armnn::TensorInfo inputTensorInfo({ batchSize, inputSize }, armnn::DataType::Float32); |
| 3535 | armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32); |
| 3536 | armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32); |
| 3537 | armnn::TensorInfo lstmTensorInfoScratchBuff({ batchSize, numUnits * 4 }, armnn::DataType::Float32); |
| 3538 | |
| 3539 | inputLayer->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(0)); |
| 3540 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 3541 | |
| 3542 | outputStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(1)); |
| 3543 | outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo); |
| 3544 | |
| 3545 | cellStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(2)); |
| 3546 | cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo); |
| 3547 | |
| 3548 | lstmLayer->GetOutputSlot(0).Connect(scratchBuffer->GetInputSlot(0)); |
| 3549 | lstmLayer->GetOutputSlot(0).SetTensorInfo(lstmTensorInfoScratchBuff); |
| 3550 | |
| 3551 | lstmLayer->GetOutputSlot(1).Connect(outputStateOut->GetInputSlot(0)); |
| 3552 | lstmLayer->GetOutputSlot(1).SetTensorInfo(outputStateTensorInfo); |
| 3553 | |
| 3554 | lstmLayer->GetOutputSlot(2).Connect(cellStateOut->GetInputSlot(0)); |
| 3555 | lstmLayer->GetOutputSlot(2).SetTensorInfo(cellStateTensorInfo); |
| 3556 | |
| 3557 | lstmLayer->GetOutputSlot(3).Connect(outputLayer->GetInputSlot(0)); |
| 3558 | lstmLayer->GetOutputSlot(3).SetTensorInfo(outputStateTensorInfo); |
| 3559 | |
| 3560 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 3561 | BOOST_CHECK(deserializedNetwork); |
| 3562 | |
| 3563 | VerifyLstmLayer checker( |
| 3564 | layerName, |
| 3565 | {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo}, |
| 3566 | {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo}, |
| 3567 | descriptor, |
| 3568 | params); |
| 3569 | deserializedNetwork->Accept(checker); |
| 3570 | } |
| 3571 | |
| 3572 | BOOST_AUTO_TEST_CASE(EnsureLstmLayersBackwardCompatibility) |
| 3573 | { |
| 3574 | // The hex array below is a flat buffer containing a lstm layer with no Cifg, with peephole and projection |
| 3575 | // enabled. That array is created before additional layer normalization parameters where added to the |
| 3576 | // lstm serializer. That way it can be tested if a lstm model with the old parameter configuration can still be |
| 3577 | // loaded |
| 3578 | unsigned int size = 10900; |
| 3579 | const unsigned char LstmNoCifgWithPeepholeAndProjection_Model[] = { |
| 3580 | 0x10,0x00,0x00,0x00,0x00,0x00,0x0A,0x00,0x10,0x00,0x04,0x00,0x08,0x00,0x0C,0x00,0x0A,0x00,0x00,0x00, |
| 3581 | 0x0C,0x00,0x00,0x00,0x2C,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0xDC,0x29,0x00,0x00, |
| 3582 | 0x38,0x29,0x00,0x00,0xB4,0x28,0x00,0x00,0x94,0x01,0x00,0x00,0x3C,0x01,0x00,0x00,0xE0,0x00,0x00,0x00, |
| 3583 | 0x84,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 3584 | 0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x06,0x00,0x00,0x00, |
| 3585 | 0x07,0x00,0x00,0x00,0x70,0xD6,0xFF,0xFF,0x00,0x00,0x00,0x0B,0x04,0x00,0x00,0x00,0x06,0xD7,0xFF,0xFF, |
| 3586 | 0x04,0x00,0x00,0x00,0x88,0xD7,0xFF,0xFF,0x08,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0xF6,0xD6,0xFF,0xFF, |
| 3587 | 0x07,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x14,0x00,0x00,0x00, |
| 3588 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3589 | 0xE8,0xD7,0xFF,0xFF,0x03,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0xC8,0xD6,0xFF,0xFF,0x00,0x00,0x00,0x0B, |
| 3590 | 0x04,0x00,0x00,0x00,0x5E,0xD7,0xFF,0xFF,0x04,0x00,0x00,0x00,0xE0,0xD7,0xFF,0xFF,0x08,0x00,0x00,0x00, |
| 3591 | 0x02,0x00,0x00,0x00,0x4E,0xD7,0xFF,0xFF,0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x03,0x00,0x00,0x00, |
| 3592 | 0x10,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 3593 | 0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x40,0xD8,0xFF,0xFF,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00, |
| 3594 | 0x20,0xD7,0xFF,0xFF,0x00,0x00,0x00,0x0B,0x04,0x00,0x00,0x00,0xB6,0xD7,0xFF,0xFF,0x04,0x00,0x00,0x00, |
| 3595 | 0x38,0xD8,0xFF,0xFF,0x08,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0xA6,0xD7,0xFF,0xFF,0x05,0x00,0x00,0x00, |
| 3596 | 0x10,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3597 | 0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x98,0xD8,0xFF,0xFF, |
| 3598 | 0x03,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x78,0xD7,0xFF,0xFF,0x00,0x00,0x00,0x0B,0x04,0x00,0x00,0x00, |
| 3599 | 0x0E,0xD8,0xFF,0xFF,0x04,0x00,0x00,0x00,0x16,0xD8,0xFF,0xFF,0x04,0x00,0x00,0x00,0xFA,0xD7,0xFF,0xFF, |
| 3600 | 0x04,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x14,0x00,0x00,0x00, |
| 3601 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3602 | 0xEC,0xD8,0xFF,0xFF,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x6C,0xD8,0xFF,0xFF,0x00,0x00,0x00,0x23, |
| 3603 | 0x10,0x00,0x00,0x00,0x00,0x00,0x0A,0x00,0x12,0x00,0x04,0x00,0x08,0x00,0x0C,0x00,0x0A,0x00,0x00,0x00, |
| 3604 | 0xE0,0x25,0x00,0x00,0xD0,0x25,0x00,0x00,0x2C,0x00,0x00,0x00,0x00,0x00,0x26,0x00,0x48,0x00,0x04,0x00, |
| 3605 | 0x08,0x00,0x0C,0x00,0x10,0x00,0x14,0x00,0x18,0x00,0x1C,0x00,0x20,0x00,0x24,0x00,0x28,0x00,0x2C,0x00, |
| 3606 | 0x30,0x00,0x34,0x00,0x38,0x00,0x3C,0x00,0x40,0x00,0x44,0x00,0x26,0x00,0x00,0x00,0xC4,0x23,0x00,0x00, |
| 3607 | 0xF8,0x21,0x00,0x00,0x2C,0x20,0x00,0x00,0xF0,0x1A,0x00,0x00,0xB4,0x15,0x00,0x00,0x78,0x10,0x00,0x00, |
| 3608 | 0xF0,0x0F,0x00,0x00,0x68,0x0F,0x00,0x00,0xE0,0x0E,0x00,0x00,0x14,0x0D,0x00,0x00,0xD8,0x07,0x00,0x00, |
| 3609 | 0x50,0x07,0x00,0x00,0xC8,0x06,0x00,0x00,0x8C,0x01,0x00,0x00,0x14,0x01,0x00,0x00,0x8C,0x00,0x00,0x00, |
| 3610 | 0x04,0x00,0x00,0x00,0xEE,0xD7,0xFF,0xFF,0x00,0x00,0x00,0x03,0x64,0x00,0x00,0x00,0x04,0x00,0x00,0x00, |
| 3611 | 0xFE,0xD8,0xFF,0xFF,0x04,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3612 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3613 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3614 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3615 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x5A,0xD8,0xFF,0xFF,0x00,0x00,0x00,0x01, |
| 3616 | 0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x72,0xD8,0xFF,0xFF, |
| 3617 | 0x00,0x00,0x00,0x03,0x64,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x82,0xD9,0xFF,0xFF,0x04,0x00,0x00,0x00, |
| 3618 | 0x14,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3619 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3620 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3621 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3622 | 0x00,0x00,0x00,0x00,0xDE,0xD8,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3623 | 0x01,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0xF6,0xD8,0xFF,0xFF,0x00,0x00,0x00,0x03,0x54,0x00,0x00,0x00, |
| 3624 | 0x04,0x00,0x00,0x00,0x06,0xDA,0xFF,0xFF,0x04,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3625 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3626 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3627 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3628 | 0x52,0xD9,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 3629 | 0x10,0x00,0x00,0x00,0x6A,0xD9,0xFF,0xFF,0x00,0x00,0x00,0x03,0x14,0x05,0x00,0x00,0x04,0x00,0x00,0x00, |
| 3630 | 0x7A,0xDA,0xFF,0xFF,0x04,0x00,0x00,0x00,0x40,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3631 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3632 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3633 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3634 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3635 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3636 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3637 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3638 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3639 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3640 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3641 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3642 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3643 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3644 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3645 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3646 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3647 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3648 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3649 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3650 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3651 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3652 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3653 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3654 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3655 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3656 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3657 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3658 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3659 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3660 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3661 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3662 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3663 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3664 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3665 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3666 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3667 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3668 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3669 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3670 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3671 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3672 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3673 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3674 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3675 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3676 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3677 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3678 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3679 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3680 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3681 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3682 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3683 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3684 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3685 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3686 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3687 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3688 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3689 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3690 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3691 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3692 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3693 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3694 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x86,0xDE,0xFF,0xFF,0x00,0x00,0x00,0x01, |
| 3695 | 0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x14,0x00,0x00,0x00, |
| 3696 | 0xA2,0xDE,0xFF,0xFF,0x00,0x00,0x00,0x03,0x64,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0xB2,0xDF,0xFF,0xFF, |
| 3697 | 0x04,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3698 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3699 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3700 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3701 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x0E,0xDF,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00, |
| 3702 | 0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x26,0xDF,0xFF,0xFF,0x00,0x00,0x00,0x03, |
| 3703 | 0x64,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x36,0xE0,0xFF,0xFF,0x04,0x00,0x00,0x00,0x14,0x00,0x00,0x00, |
| 3704 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3705 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3706 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3707 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3708 | 0x92,0xDF,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 3709 | 0x14,0x00,0x00,0x00,0xAA,0xDF,0xFF,0xFF,0x00,0x00,0x00,0x03,0x14,0x05,0x00,0x00,0x04,0x00,0x00,0x00, |
| 3710 | 0xBA,0xE0,0xFF,0xFF,0x04,0x00,0x00,0x00,0x40,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3711 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3712 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3713 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3714 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3715 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3716 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3717 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3718 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3719 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3720 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3721 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3722 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3723 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3724 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3725 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3726 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3727 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3728 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3729 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3730 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3731 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3732 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3733 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3734 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3735 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3736 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3737 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3738 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3739 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3740 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3741 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3742 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3743 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3744 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3745 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3746 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3747 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3748 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3749 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3750 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3751 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3752 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3753 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3754 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3755 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3756 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3757 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3758 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3759 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3760 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3761 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3762 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3763 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3764 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3765 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3766 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3767 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3768 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3769 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3770 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3771 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3772 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3773 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3774 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xC6,0xE4,0xFF,0xFF,0x00,0x00,0x00,0x01, |
| 3775 | 0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x10,0x00,0x00,0x00, |
| 3776 | 0xE2,0xE4,0xFF,0xFF,0x00,0x00,0x00,0x03,0xA4,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0xF2,0xE5,0xFF,0xFF, |
| 3777 | 0x04,0x00,0x00,0x00,0x64,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3778 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3779 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3780 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3781 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3782 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3783 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3784 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3785 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3786 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3787 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3788 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3789 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3790 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3791 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3792 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3793 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3794 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3795 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3796 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3797 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x8E,0xE6,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00, |
| 3798 | 0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0xAA,0xE6,0xFF,0xFF, |
| 3799 | 0x00,0x00,0x00,0x03,0x64,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0xBA,0xE7,0xFF,0xFF,0x04,0x00,0x00,0x00, |
| 3800 | 0x14,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3801 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3802 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3803 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3804 | 0x00,0x00,0x00,0x00,0x16,0xE7,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3805 | 0x01,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x2E,0xE7,0xFF,0xFF,0x00,0x00,0x00,0x03,0x64,0x00,0x00,0x00, |
| 3806 | 0x04,0x00,0x00,0x00,0x3E,0xE8,0xFF,0xFF,0x04,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3807 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3808 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3809 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3810 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x9A,0xE7,0xFF,0xFF, |
| 3811 | 0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x14,0x00,0x00,0x00, |
| 3812 | 0xB2,0xE7,0xFF,0xFF,0x00,0x00,0x00,0x03,0x64,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0xC2,0xE8,0xFF,0xFF, |
| 3813 | 0x04,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3814 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3815 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3816 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3817 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x1E,0xE8,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00, |
| 3818 | 0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x36,0xE8,0xFF,0xFF,0x00,0x00,0x00,0x03, |
| 3819 | 0x14,0x05,0x00,0x00,0x04,0x00,0x00,0x00,0x46,0xE9,0xFF,0xFF,0x04,0x00,0x00,0x00,0x40,0x01,0x00,0x00, |
| 3820 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3821 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3822 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3823 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3824 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3825 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3826 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3827 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3828 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3829 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3830 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3831 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3832 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3833 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3834 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3835 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3836 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3837 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3838 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3839 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3840 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3841 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3842 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3843 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3844 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3845 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3846 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3847 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3848 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3849 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3850 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3851 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3852 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3853 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3854 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3855 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3856 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3857 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3858 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3859 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3860 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3861 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3862 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3863 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3864 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3865 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3866 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3867 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3868 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3869 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3870 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3871 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3872 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3873 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3874 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3875 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3876 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3877 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3878 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3879 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3880 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3881 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3882 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3883 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3884 | 0x52,0xED,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x00, |
| 3885 | 0x14,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x6E,0xED,0xFF,0xFF,0x00,0x00,0x00,0x03,0x14,0x05,0x00,0x00, |
| 3886 | 0x04,0x00,0x00,0x00,0x7E,0xEE,0xFF,0xFF,0x04,0x00,0x00,0x00,0x40,0x01,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3887 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3888 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3889 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3890 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3891 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3892 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3893 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3894 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3895 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3896 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3897 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3898 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3899 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3900 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3901 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3902 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3903 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3904 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3905 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3906 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3907 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3908 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3909 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3910 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3911 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3912 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3913 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3914 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3915 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3916 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3917 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3918 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3919 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3920 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3921 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3922 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3923 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3924 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3925 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3926 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3927 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3928 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3929 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3930 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3931 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3932 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3933 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3934 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3935 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3936 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3937 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3938 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3939 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3940 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3941 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3942 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3943 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3944 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3945 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3946 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3947 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3948 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3949 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3950 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x8A,0xF2,0xFF,0xFF, |
| 3951 | 0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x14,0x00,0x00,0x00, |
| 3952 | 0x10,0x00,0x00,0x00,0xA6,0xF2,0xFF,0xFF,0x00,0x00,0x00,0x03,0x14,0x05,0x00,0x00,0x04,0x00,0x00,0x00, |
| 3953 | 0xB6,0xF3,0xFF,0xFF,0x04,0x00,0x00,0x00,0x40,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3954 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3955 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3956 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3957 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3958 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3959 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3960 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3961 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3962 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3963 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3964 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3965 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3966 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3967 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3968 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3969 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3970 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3971 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3972 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3973 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3974 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3975 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3976 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3977 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3978 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3979 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3980 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3981 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3982 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3983 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3984 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3985 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3986 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3987 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3988 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3989 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3990 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3991 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3992 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3993 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3994 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3995 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3996 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3997 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3998 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 3999 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4000 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4001 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4002 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4003 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4004 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4005 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4006 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4007 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4008 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4009 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4010 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4011 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4012 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4013 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4014 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4015 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4016 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4017 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xC2,0xF7,0xFF,0xFF,0x00,0x00,0x00,0x01, |
| 4018 | 0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x10,0x00,0x00,0x00, |
| 4019 | 0xDE,0xF7,0xFF,0xFF,0x00,0x00,0x00,0x03,0xA4,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0xEE,0xF8,0xFF,0xFF, |
| 4020 | 0x04,0x00,0x00,0x00,0x64,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4021 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4022 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4023 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4024 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4025 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4026 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4027 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4028 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4029 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4030 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4031 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4032 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4033 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4034 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4035 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4036 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4037 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4038 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4039 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4040 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x8A,0xF9,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00, |
| 4041 | 0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0xA6,0xF9,0xFF,0xFF, |
| 4042 | 0x00,0x00,0x00,0x03,0xA4,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0xB6,0xFA,0xFF,0xFF,0x04,0x00,0x00,0x00, |
| 4043 | 0x64,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4044 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4045 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4046 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4047 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4048 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4049 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4050 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4051 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4052 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4053 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4054 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4055 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4056 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4057 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4058 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4059 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4060 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4061 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4062 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4063 | 0x00,0x00,0x00,0x00,0x52,0xFB,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4064 | 0x02,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x6E,0xFB,0xFF,0xFF,0x00,0x00,0x00,0x03, |
| 4065 | 0xA4,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x7E,0xFC,0xFF,0xFF,0x04,0x00,0x00,0x00,0x64,0x00,0x00,0x00, |
| 4066 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4067 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4068 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4069 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4070 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4071 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4072 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4073 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4074 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4075 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4076 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4077 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4078 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4079 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4080 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4081 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4082 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4083 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4084 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4085 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4086 | 0x1A,0xFD,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x00, |
| 4087 | 0x14,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x10,0x00,0x0C,0x00,0x08,0x00,0x00,0x00,0x00,0x00,0x05,0x00, |
| 4088 | 0x06,0x00,0x07,0x00,0x10,0x00,0x00,0x00,0x00,0x00,0x01,0x01,0x04,0x00,0x00,0x00,0x2E,0xFE,0xFF,0xFF, |
| 4089 | 0x03,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x20,0x00,0x00,0x00, |
| 4090 | 0x04,0x00,0x00,0x00,0x6C,0x73,0x74,0x6D,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0xEC,0x00,0x00,0x00, |
| 4091 | 0xD0,0x00,0x00,0x00,0xB4,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x88,0x00,0x00,0x00,0x5C,0x00,0x00,0x00, |
| 4092 | 0x30,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x14,0xFF,0xFF,0xFF,0x03,0x00,0x00,0x00,0x04,0x00,0x00,0x00, |
| 4093 | 0xA6,0xFD,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x00, |
| 4094 | 0x02,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x3C,0xFF,0xFF,0xFF,0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00, |
| 4095 | 0xCE,0xFD,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x00, |
| 4096 | 0x02,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x64,0xFF,0xFF,0xFF,0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00, |
| 4097 | 0xF6,0xFD,0xFF,0xFF,0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x00, |
| 4098 | 0x02,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0xB4,0xFE,0xFF,0xFF,0x04,0x00,0x00,0x00,0x1A,0xFE,0xFF,0xFF, |
| 4099 | 0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x02,0x00,0x00,0x00, |
| 4100 | 0x50,0x00,0x00,0x00,0xF0,0xFF,0xFF,0xFF,0x02,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4101 | 0x08,0x00,0x10,0x00,0x04,0x00,0x08,0x00,0x08,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00, |
| 4102 | 0x00,0x00,0x00,0x00,0x08,0x00,0x0C,0x00,0x00,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4103 | 0x00,0x00,0x00,0x00,0xE8,0xFE,0xFF,0xFF,0x00,0x00,0x00,0x09,0x04,0x00,0x00,0x00,0x7E,0xFF,0xFF,0xFF, |
| 4104 | 0x0C,0x00,0x00,0x00,0x08,0x00,0x0C,0x00,0x04,0x00,0x08,0x00,0x08,0x00,0x00,0x00,0x08,0x00,0x00,0x00, |
| 4105 | 0x02,0x00,0x00,0x00,0x76,0xFF,0xFF,0xFF,0x02,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 4106 | 0x10,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00, |
| 4107 | 0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x68,0xFF,0xFF,0xFF,0x04,0x00,0x00,0x00,0xCE,0xFE,0xFF,0xFF, |
| 4108 | 0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x02,0x00,0x00,0x00, |
| 4109 | 0x10,0x00,0x00,0x00,0x08,0x00,0x0E,0x00,0x07,0x00,0x08,0x00,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x09, |
| 4110 | 0x0C,0x00,0x00,0x00,0x00,0x00,0x06,0x00,0x08,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0C,0x00,0x00,0x00, |
| 4111 | 0x08,0x00,0x0E,0x00,0x04,0x00,0x08,0x00,0x08,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 4112 | 0x00,0x00,0x0E,0x00,0x18,0x00,0x04,0x00,0x08,0x00,0x0C,0x00,0x10,0x00,0x14,0x00,0x0E,0x00,0x00,0x00, |
| 4113 | 0x01,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x10,0x00,0x00,0x00, |
| 4114 | 0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0C,0x00,0x00,0x00, |
| 4115 | 0x08,0x00,0x08,0x00,0x00,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6E,0xFF,0xFF,0xFF, |
| 4116 | 0x00,0x00,0x00,0x01,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x02,0x00,0x00,0x00, |
| 4117 | 0x14,0x00,0x00,0x00,0x08,0x00,0x0C,0x00,0x07,0x00,0x08,0x00,0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x09, |
| 4118 | 0x04,0x00,0x00,0x00,0xF6,0xFF,0xFF,0xFF,0x0C,0x00,0x00,0x00,0x00,0x00,0x06,0x00,0x0A,0x00,0x04,0x00, |
| 4119 | 0x06,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x00,0x00,0x0E,0x00,0x14,0x00,0x00,0x00,0x04,0x00,0x08,0x00, |
| 4120 | 0x0C,0x00,0x10,0x00,0x0E,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x10,0x00,0x00,0x00, |
| 4121 | 0x10,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00, |
| 4122 | 0x0C,0x00,0x00,0x00,0x08,0x00,0x0A,0x00,0x00,0x00,0x04,0x00,0x08,0x00,0x00,0x00,0x10,0x00,0x00,0x00, |
| 4123 | 0x00,0x00,0x0A,0x00,0x10,0x00,0x08,0x00,0x07,0x00,0x0C,0x00,0x0A,0x00,0x00,0x00,0x00,0x00,0x00,0x01, |
| 4124 | 0x08,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0 }; |
| 4125 | |
| 4126 | std::stringstream ss; |
| 4127 | for (unsigned int i = 0; i < size; ++i) |
| 4128 | { |
| 4129 | ss << LstmNoCifgWithPeepholeAndProjection_Model[i]; |
| 4130 | } |
| 4131 | std::string lstmLayerNetwork = ss.str(); |
| 4132 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(lstmLayerNetwork); |
| 4133 | BOOST_CHECK(deserializedNetwork); |
| 4134 | |
| 4135 | // generating the same model parameters which where used to serialize the model (Layer norm is not specified) |
| 4136 | armnn::LstmDescriptor descriptor; |
| 4137 | descriptor.m_ActivationFunc = 4; |
| 4138 | descriptor.m_ClippingThresProj = 0.0f; |
| 4139 | descriptor.m_ClippingThresCell = 0.0f; |
| 4140 | descriptor.m_CifgEnabled = false; |
| 4141 | descriptor.m_ProjectionEnabled = true; |
| 4142 | descriptor.m_PeepholeEnabled = true; |
| 4143 | |
| 4144 | const uint32_t batchSize = 2; |
| 4145 | const uint32_t inputSize = 5; |
| 4146 | const uint32_t numUnits = 20; |
| 4147 | const uint32_t outputSize = 16; |
| 4148 | |
| 4149 | armnn::TensorInfo tensorInfo20x5({numUnits, inputSize}, armnn::DataType::Float32); |
| 4150 | std::vector<float> inputToInputWeightsData(tensorInfo20x5.GetNumElements(), 0.0f); |
| 4151 | armnn::ConstTensor inputToInputWeights(tensorInfo20x5, inputToInputWeightsData); |
| 4152 | |
| 4153 | std::vector<float> inputToForgetWeightsData(tensorInfo20x5.GetNumElements(), 0.0f); |
| 4154 | armnn::ConstTensor inputToForgetWeights(tensorInfo20x5, inputToForgetWeightsData); |
| 4155 | |
| 4156 | std::vector<float> inputToCellWeightsData(tensorInfo20x5.GetNumElements(), 0.0f); |
| 4157 | armnn::ConstTensor inputToCellWeights(tensorInfo20x5, inputToCellWeightsData); |
| 4158 | |
| 4159 | std::vector<float> inputToOutputWeightsData(tensorInfo20x5.GetNumElements(), 0.0f); |
| 4160 | armnn::ConstTensor inputToOutputWeights(tensorInfo20x5, inputToOutputWeightsData); |
| 4161 | |
| 4162 | armnn::TensorInfo tensorInfo20({numUnits}, armnn::DataType::Float32); |
| 4163 | std::vector<float> inputGateBiasData(tensorInfo20.GetNumElements(), 0.0f); |
| 4164 | armnn::ConstTensor inputGateBias(tensorInfo20, inputGateBiasData); |
| 4165 | |
| 4166 | std::vector<float> forgetGateBiasData(tensorInfo20.GetNumElements(), 0.0f); |
| 4167 | armnn::ConstTensor forgetGateBias(tensorInfo20, forgetGateBiasData); |
| 4168 | |
| 4169 | std::vector<float> cellBiasData(tensorInfo20.GetNumElements(), 0.0f); |
| 4170 | armnn::ConstTensor cellBias(tensorInfo20, cellBiasData); |
| 4171 | |
| 4172 | std::vector<float> outputGateBiasData(tensorInfo20.GetNumElements(), 0.0f); |
| 4173 | armnn::ConstTensor outputGateBias(tensorInfo20, outputGateBiasData); |
| 4174 | |
| 4175 | armnn::TensorInfo tensorInfo20x16({numUnits, outputSize}, armnn::DataType::Float32); |
| 4176 | std::vector<float> recurrentToInputWeightsData(tensorInfo20x16.GetNumElements(), 0.0f); |
| 4177 | armnn::ConstTensor recurrentToInputWeights(tensorInfo20x16, recurrentToInputWeightsData); |
| 4178 | |
| 4179 | std::vector<float> recurrentToForgetWeightsData(tensorInfo20x16.GetNumElements(), 0.0f); |
| 4180 | armnn::ConstTensor recurrentToForgetWeights(tensorInfo20x16, recurrentToForgetWeightsData); |
| 4181 | |
| 4182 | std::vector<float> recurrentToCellWeightsData(tensorInfo20x16.GetNumElements(), 0.0f); |
| 4183 | armnn::ConstTensor recurrentToCellWeights(tensorInfo20x16, recurrentToCellWeightsData); |
| 4184 | |
| 4185 | std::vector<float> recurrentToOutputWeightsData(tensorInfo20x16.GetNumElements(), 0.0f); |
| 4186 | armnn::ConstTensor recurrentToOutputWeights(tensorInfo20x16, recurrentToOutputWeightsData); |
| 4187 | |
| 4188 | std::vector<float> cellToInputWeightsData(tensorInfo20.GetNumElements(), 0.0f); |
| 4189 | armnn::ConstTensor cellToInputWeights(tensorInfo20, cellToInputWeightsData); |
| 4190 | |
| 4191 | std::vector<float> cellToForgetWeightsData(tensorInfo20.GetNumElements(), 0.0f); |
| 4192 | armnn::ConstTensor cellToForgetWeights(tensorInfo20, cellToForgetWeightsData); |
| 4193 | |
| 4194 | std::vector<float> cellToOutputWeightsData(tensorInfo20.GetNumElements(), 0.0f); |
| 4195 | armnn::ConstTensor cellToOutputWeights(tensorInfo20, cellToOutputWeightsData); |
| 4196 | |
| 4197 | armnn::TensorInfo tensorInfo16x20({outputSize, numUnits}, armnn::DataType::Float32); |
| 4198 | std::vector<float> projectionWeightsData(tensorInfo16x20.GetNumElements(), 0.0f); |
| 4199 | armnn::ConstTensor projectionWeights(tensorInfo16x20, projectionWeightsData); |
| 4200 | |
| 4201 | armnn::TensorInfo tensorInfo16({outputSize}, armnn::DataType::Float32); |
| 4202 | std::vector<float> projectionBiasData(outputSize, 0.0f); |
| 4203 | armnn::ConstTensor projectionBias(tensorInfo16, projectionBiasData); |
| 4204 | |
| 4205 | armnn::LstmInputParams params; |
| 4206 | params.m_InputToForgetWeights = &inputToForgetWeights; |
| 4207 | params.m_InputToCellWeights = &inputToCellWeights; |
| 4208 | params.m_InputToOutputWeights = &inputToOutputWeights; |
| 4209 | params.m_RecurrentToForgetWeights = &recurrentToForgetWeights; |
| 4210 | params.m_RecurrentToCellWeights = &recurrentToCellWeights; |
| 4211 | params.m_RecurrentToOutputWeights = &recurrentToOutputWeights; |
| 4212 | params.m_ForgetGateBias = &forgetGateBias; |
| 4213 | params.m_CellBias = &cellBias; |
| 4214 | params.m_OutputGateBias = &outputGateBias; |
| 4215 | |
| 4216 | // additional params because: descriptor.m_CifgEnabled = false |
| 4217 | params.m_InputToInputWeights = &inputToInputWeights; |
| 4218 | params.m_RecurrentToInputWeights = &recurrentToInputWeights; |
| 4219 | params.m_CellToInputWeights = &cellToInputWeights; |
| 4220 | params.m_InputGateBias = &inputGateBias; |
| 4221 | |
| 4222 | // additional params because: descriptor.m_ProjectionEnabled = true |
| 4223 | params.m_ProjectionWeights = &projectionWeights; |
| 4224 | params.m_ProjectionBias = &projectionBias; |
| 4225 | |
| 4226 | // additional params because: descriptor.m_PeepholeEnabled = true |
| 4227 | params.m_CellToForgetWeights = &cellToForgetWeights; |
| 4228 | params.m_CellToOutputWeights = &cellToOutputWeights; |
| 4229 | |
| 4230 | const std::string layerName("lstm"); |
| 4231 | armnn::TensorInfo inputTensorInfo({ batchSize, inputSize }, armnn::DataType::Float32); |
| 4232 | armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32); |
| 4233 | armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32); |
| 4234 | armnn::TensorInfo lstmTensorInfoScratchBuff({ batchSize, numUnits * 4 }, armnn::DataType::Float32); |
| 4235 | |
| 4236 | // lets verify that the deserialized model without the new layer normalization parameters still works |
| 4237 | VerifyLstmLayer checker( |
| 4238 | layerName, |
| 4239 | {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo}, |
| 4240 | {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo}, |
| 4241 | descriptor, |
| 4242 | params); |
| 4243 | deserializedNetwork->Accept(checker); |
| 4244 | } |
| 4245 | |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4246 | class VerifyQuantizedLstmLayer : public LayerVerifierBase |
| 4247 | { |
| 4248 | |
| 4249 | public: |
| 4250 | VerifyQuantizedLstmLayer(const std::string& layerName, |
| 4251 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 4252 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 4253 | const armnn::QuantizedLstmInputParams& inputParams) : |
| 4254 | LayerVerifierBase(layerName, inputInfos, outputInfos), m_InputParams(inputParams) |
| 4255 | { |
| 4256 | } |
| 4257 | |
| 4258 | void VisitQuantizedLstmLayer(const armnn::IConnectableLayer* layer, |
| 4259 | const armnn::QuantizedLstmInputParams& params, |
| 4260 | const char* name) |
| 4261 | { |
| 4262 | VerifyNameAndConnections(layer, name); |
| 4263 | VerifyInputParameters(params); |
| 4264 | } |
| 4265 | |
| 4266 | protected: |
| 4267 | void VerifyInputParameters(const armnn::QuantizedLstmInputParams& params) |
| 4268 | { |
| 4269 | VerifyConstTensors("m_InputToInputWeights", |
| 4270 | m_InputParams.m_InputToInputWeights, params.m_InputToInputWeights); |
| 4271 | VerifyConstTensors("m_InputToForgetWeights", |
| 4272 | m_InputParams.m_InputToForgetWeights, params.m_InputToForgetWeights); |
| 4273 | VerifyConstTensors("m_InputToCellWeights", |
| 4274 | m_InputParams.m_InputToCellWeights, params.m_InputToCellWeights); |
| 4275 | VerifyConstTensors("m_InputToOutputWeights", |
| 4276 | m_InputParams.m_InputToOutputWeights, params.m_InputToOutputWeights); |
| 4277 | VerifyConstTensors("m_RecurrentToInputWeights", |
| 4278 | m_InputParams.m_RecurrentToInputWeights, params.m_RecurrentToInputWeights); |
| 4279 | VerifyConstTensors("m_RecurrentToForgetWeights", |
| 4280 | m_InputParams.m_RecurrentToForgetWeights, params.m_RecurrentToForgetWeights); |
| 4281 | VerifyConstTensors("m_RecurrentToCellWeights", |
| 4282 | m_InputParams.m_RecurrentToCellWeights, params.m_RecurrentToCellWeights); |
| 4283 | VerifyConstTensors("m_RecurrentToOutputWeights", |
| 4284 | m_InputParams.m_RecurrentToOutputWeights, params.m_RecurrentToOutputWeights); |
| 4285 | VerifyConstTensors("m_InputGateBias", |
| 4286 | m_InputParams.m_InputGateBias, params.m_InputGateBias); |
| 4287 | VerifyConstTensors("m_ForgetGateBias", |
| 4288 | m_InputParams.m_ForgetGateBias, params.m_ForgetGateBias); |
| 4289 | VerifyConstTensors("m_CellBias", |
| 4290 | m_InputParams.m_CellBias, params.m_CellBias); |
| 4291 | VerifyConstTensors("m_OutputGateBias", |
| 4292 | m_InputParams.m_OutputGateBias, params.m_OutputGateBias); |
| 4293 | } |
| 4294 | |
| 4295 | private: |
| 4296 | armnn::QuantizedLstmInputParams m_InputParams; |
| 4297 | }; |
| 4298 | |
| 4299 | BOOST_AUTO_TEST_CASE(SerializeDeserializeQuantizedLstm) |
| 4300 | { |
| 4301 | const uint32_t batchSize = 1; |
| 4302 | const uint32_t inputSize = 2; |
| 4303 | const uint32_t numUnits = 4; |
| 4304 | const uint32_t outputSize = numUnits; |
| 4305 | |
| 4306 | std::vector<uint8_t> inputToInputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9}; |
| 4307 | std::vector<unsigned int> inputToInputWeightsDimensions = {1, 1, 3, 3}; |
| 4308 | armnn::ConstTensor inputToInputWeights(armnn::TensorInfo( |
| 4309 | 4, inputToInputWeightsDimensions.data(), |
| 4310 | armnn::DataType::QuantisedAsymm8), inputToInputWeightsData); |
| 4311 | |
| 4312 | std::vector<uint8_t> inputToForgetWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9}; |
| 4313 | std::vector<unsigned int> inputToForgetWeightsDimensions = {1, 1, 3, 3}; |
| 4314 | armnn::ConstTensor inputToForgetWeights(armnn::TensorInfo( |
| 4315 | 4, inputToForgetWeightsDimensions.data(), |
| 4316 | armnn::DataType::QuantisedAsymm8), inputToForgetWeightsData); |
| 4317 | |
| 4318 | std::vector<uint8_t> inputToCellWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9}; |
| 4319 | std::vector<unsigned int> inputToCellWeightsDimensions = {1, 1, 3, 3}; |
| 4320 | armnn::ConstTensor inputToCellWeights(armnn::TensorInfo( |
| 4321 | 4, inputToCellWeightsDimensions.data(), |
| 4322 | armnn::DataType::QuantisedAsymm8), inputToCellWeightsData); |
| 4323 | |
| 4324 | std::vector<uint8_t> inputToOutputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9}; |
| 4325 | std::vector<unsigned int> inputToOutputWeightsDimensions = {1, 1, 3, 3}; |
| 4326 | armnn::ConstTensor inputToOutputWeights(armnn::TensorInfo( |
| 4327 | 4, inputToOutputWeightsDimensions.data(), |
| 4328 | armnn::DataType::QuantisedAsymm8), inputToOutputWeightsData); |
| 4329 | |
| 4330 | std::vector<uint8_t> recurrentToInputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9}; |
| 4331 | std::vector<unsigned int> recurrentToInputWeightsDimensions = {1, 1, 3, 3}; |
| 4332 | armnn::ConstTensor recurrentToInputWeights(armnn::TensorInfo( |
| 4333 | 4, recurrentToInputWeightsDimensions.data(), |
| 4334 | armnn::DataType::QuantisedAsymm8), recurrentToInputWeightsData); |
| 4335 | |
| 4336 | std::vector<uint8_t> recurrentToForgetWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9}; |
| 4337 | std::vector<unsigned int> recurrentToForgetWeightsDimensions = {1, 1, 3, 3}; |
| 4338 | armnn::ConstTensor recurrentToForgetWeights(armnn::TensorInfo( |
| 4339 | 4, recurrentToForgetWeightsDimensions.data(), |
| 4340 | armnn::DataType::QuantisedAsymm8), recurrentToForgetWeightsData); |
| 4341 | |
| 4342 | std::vector<uint8_t> recurrentToCellWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9}; |
| 4343 | std::vector<unsigned int> recurrentToCellWeightsDimensions = {1, 1, 3, 3}; |
| 4344 | armnn::ConstTensor recurrentToCellWeights(armnn::TensorInfo( |
| 4345 | 4, recurrentToCellWeightsDimensions.data(), |
| 4346 | armnn::DataType::QuantisedAsymm8), recurrentToCellWeightsData); |
| 4347 | |
| 4348 | std::vector<uint8_t> recurrentToOutputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9}; |
| 4349 | std::vector<unsigned int> recurrentToOutputWeightsDimensions = {1, 1, 3, 3}; |
| 4350 | armnn::ConstTensor recurrentToOutputWeights(armnn::TensorInfo( |
| 4351 | 4, recurrentToOutputWeightsDimensions.data(), |
| 4352 | armnn::DataType::QuantisedAsymm8), recurrentToOutputWeightsData); |
| 4353 | |
| 4354 | |
| 4355 | std::vector<int32_t> inputGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9}; |
| 4356 | std::vector<unsigned int> inputGateBiasDimensions = {1, 1, 3, 3}; |
| 4357 | armnn::ConstTensor inputGateBias(armnn::TensorInfo( |
| 4358 | 4, inputGateBiasDimensions.data(), |
| 4359 | armnn::DataType::Signed32), inputGateBiasData); |
| 4360 | |
| 4361 | std::vector<int32_t> forgetGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9}; |
| 4362 | std::vector<unsigned int> forgetGateBiasDimensions = {1, 1, 3, 3}; |
| 4363 | armnn::ConstTensor forgetGateBias(armnn::TensorInfo( |
| 4364 | 4, forgetGateBiasDimensions.data(), |
| 4365 | armnn::DataType::Signed32), forgetGateBiasData); |
| 4366 | |
| 4367 | std::vector<int32_t> cellBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9}; |
| 4368 | std::vector<unsigned int> cellBiasDimensions = {1, 1, 3, 3}; |
| 4369 | armnn::ConstTensor cellBias(armnn::TensorInfo( |
| 4370 | 4, cellBiasDimensions.data(), |
| 4371 | armnn::DataType::Signed32), cellBiasData); |
| 4372 | |
| 4373 | std::vector<int32_t> outputGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9}; |
| 4374 | std::vector<unsigned int> outputGateBiasDimensions = {1, 1, 3, 3}; |
| 4375 | armnn::ConstTensor outputGateBias(armnn::TensorInfo( |
| 4376 | 4, outputGateBiasDimensions.data(), |
| 4377 | armnn::DataType::Signed32), outputGateBiasData); |
| 4378 | |
| 4379 | armnn::QuantizedLstmInputParams params; |
| 4380 | params.m_InputToInputWeights = &inputToInputWeights; |
| 4381 | params.m_InputToForgetWeights = &inputToForgetWeights; |
| 4382 | params.m_InputToCellWeights = &inputToCellWeights; |
| 4383 | params.m_InputToOutputWeights = &inputToOutputWeights; |
| 4384 | params.m_RecurrentToInputWeights = &recurrentToInputWeights; |
| 4385 | params.m_RecurrentToForgetWeights = &recurrentToForgetWeights; |
| 4386 | params.m_RecurrentToCellWeights = &recurrentToCellWeights; |
| 4387 | params.m_RecurrentToOutputWeights = &recurrentToOutputWeights; |
| 4388 | params.m_InputGateBias = &inputGateBias; |
| 4389 | params.m_ForgetGateBias = &forgetGateBias; |
| 4390 | params.m_CellBias = &cellBias; |
| 4391 | params.m_OutputGateBias = &outputGateBias; |
| 4392 | |
| 4393 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 4394 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 4395 | armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1); |
| 4396 | armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2); |
| 4397 | const std::string layerName("QuantizedLstm"); |
| 4398 | armnn::IConnectableLayer* const quantizedLstmLayer = network->AddQuantizedLstmLayer(params, layerName.c_str()); |
| 4399 | armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(0); |
| 4400 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(1); |
| 4401 | |
| 4402 | // connect up |
| 4403 | armnn::TensorInfo inputTensorInfo({ batchSize, inputSize }, armnn::DataType::QuantisedAsymm8); |
| 4404 | armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Signed32); |
| 4405 | armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::QuantisedAsymm8); |
| 4406 | |
| 4407 | inputLayer->GetOutputSlot(0).Connect(quantizedLstmLayer->GetInputSlot(0)); |
| 4408 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 4409 | |
| 4410 | cellStateIn->GetOutputSlot(0).Connect(quantizedLstmLayer->GetInputSlot(1)); |
| 4411 | cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo); |
| 4412 | |
| 4413 | outputStateIn->GetOutputSlot(0).Connect(quantizedLstmLayer->GetInputSlot(2)); |
| 4414 | outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo); |
| 4415 | |
| 4416 | quantizedLstmLayer->GetOutputSlot(0).Connect(cellStateOut->GetInputSlot(0)); |
| 4417 | quantizedLstmLayer->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo); |
| 4418 | |
| 4419 | quantizedLstmLayer->GetOutputSlot(1).Connect(outputLayer->GetInputSlot(0)); |
| 4420 | quantizedLstmLayer->GetOutputSlot(1).SetTensorInfo(outputStateTensorInfo); |
| 4421 | |
| 4422 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 4423 | BOOST_CHECK(deserializedNetwork); |
| 4424 | |
| 4425 | VerifyQuantizedLstmLayer checker( |
| 4426 | layerName, |
| 4427 | {inputTensorInfo, cellStateTensorInfo, outputStateTensorInfo}, |
| 4428 | {cellStateTensorInfo, outputStateTensorInfo}, |
| 4429 | params); |
| 4430 | |
| 4431 | deserializedNetwork->Accept(checker); |
| 4432 | } |
| 4433 | |
Nattapat Chaimanowong | 30b0020 | 2019-02-20 17:31:34 +0000 | [diff] [blame] | 4434 | BOOST_AUTO_TEST_SUITE_END() |