Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 1 | // |
Teresa Charlin | 5266473 | 2020-06-29 16:27:03 +0100 | [diff] [blame] | 2 | // Copyright © 2017 Arm Ltd and Contributors. All rights reserved. |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 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 | |
Matthew Bentham | ff130e2 | 2020-01-17 11:47:42 +0000 | [diff] [blame] | 8 | #include <armnn/Descriptors.hpp> |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 9 | #include <armnn/INetwork.hpp> |
Matthew Bentham | ff130e2 | 2020-01-17 11:47:42 +0000 | [diff] [blame] | 10 | #include <armnn/TypesUtils.hpp> |
| 11 | #include <armnn/LstmParams.hpp> |
| 12 | #include <armnn/QuantizedLstmParams.hpp> |
Derek Lamberti | 0028d1b | 2019-02-20 13:57:42 +0000 | [diff] [blame] | 13 | #include <armnnDeserializer/IDeserializer.hpp> |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 14 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 15 | #include <random> |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 16 | #include <vector> |
| 17 | |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 18 | #include <boost/test/unit_test.hpp> |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 19 | |
Derek Lamberti | 0028d1b | 2019-02-20 13:57:42 +0000 | [diff] [blame] | 20 | using armnnDeserializer::IDeserializer; |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 21 | |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 22 | namespace |
| 23 | { |
| 24 | |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 25 | #define DECLARE_LAYER_VERIFIER_CLASS(name) \ |
| 26 | class name##LayerVerifier : public LayerVerifierBase \ |
| 27 | { \ |
| 28 | public: \ |
| 29 | name##LayerVerifier(const std::string& layerName, \ |
| 30 | const std::vector<armnn::TensorInfo>& inputInfos, \ |
| 31 | const std::vector<armnn::TensorInfo>& outputInfos) \ |
| 32 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} \ |
| 33 | \ |
| 34 | void Visit##name##Layer(const armnn::IConnectableLayer* layer, const char* name) override \ |
| 35 | { \ |
| 36 | VerifyNameAndConnections(layer, name); \ |
| 37 | } \ |
| 38 | }; |
| 39 | |
| 40 | #define DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(name) \ |
| 41 | class name##LayerVerifier : public LayerVerifierBaseWithDescriptor<armnn::name##Descriptor> \ |
| 42 | { \ |
| 43 | public: \ |
| 44 | name##LayerVerifier(const std::string& layerName, \ |
| 45 | const std::vector<armnn::TensorInfo>& inputInfos, \ |
| 46 | const std::vector<armnn::TensorInfo>& outputInfos, \ |
| 47 | const armnn::name##Descriptor& descriptor) \ |
| 48 | : LayerVerifierBaseWithDescriptor<armnn::name##Descriptor>( \ |
| 49 | layerName, inputInfos, outputInfos, descriptor) {} \ |
| 50 | \ |
| 51 | void Visit##name##Layer(const armnn::IConnectableLayer* layer, \ |
| 52 | const armnn::name##Descriptor& descriptor, \ |
| 53 | const char* name) override \ |
| 54 | { \ |
| 55 | VerifyNameAndConnections(layer, name); \ |
| 56 | VerifyDescriptor(descriptor); \ |
| 57 | } \ |
| 58 | }; |
| 59 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 60 | struct DefaultLayerVerifierPolicy |
| 61 | { |
Derek Lamberti | 859f9ce | 2019-12-10 22:05:21 +0000 | [diff] [blame] | 62 | static void Apply(const std::string) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 63 | { |
| 64 | BOOST_TEST_MESSAGE("Unexpected layer found in network"); |
| 65 | BOOST_TEST(false); |
| 66 | } |
| 67 | }; |
| 68 | |
| 69 | class LayerVerifierBase : public armnn::LayerVisitorBase<DefaultLayerVerifierPolicy> |
| 70 | { |
| 71 | public: |
| 72 | LayerVerifierBase(const std::string& layerName, |
| 73 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 74 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 75 | : m_LayerName(layerName) |
| 76 | , m_InputTensorInfos(inputInfos) |
| 77 | , m_OutputTensorInfos(outputInfos) {} |
| 78 | |
| 79 | void VisitInputLayer(const armnn::IConnectableLayer*, armnn::LayerBindingId, const char*) override {} |
| 80 | |
Derek Lamberti | 859f9ce | 2019-12-10 22:05:21 +0000 | [diff] [blame] | 81 | void VisitOutputLayer(const armnn::IConnectableLayer*, armnn::LayerBindingId, const char*) override {} |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 82 | |
| 83 | protected: |
| 84 | void VerifyNameAndConnections(const armnn::IConnectableLayer* layer, const char* name) |
| 85 | { |
| 86 | BOOST_TEST(name == m_LayerName.c_str()); |
| 87 | |
| 88 | BOOST_TEST(layer->GetNumInputSlots() == m_InputTensorInfos.size()); |
| 89 | BOOST_TEST(layer->GetNumOutputSlots() == m_OutputTensorInfos.size()); |
| 90 | |
| 91 | for (unsigned int i = 0; i < m_InputTensorInfos.size(); i++) |
| 92 | { |
| 93 | const armnn::IOutputSlot* connectedOutput = layer->GetInputSlot(i).GetConnection(); |
| 94 | BOOST_CHECK(connectedOutput); |
| 95 | |
| 96 | const armnn::TensorInfo& connectedInfo = connectedOutput->GetTensorInfo(); |
| 97 | BOOST_TEST(connectedInfo.GetShape() == m_InputTensorInfos[i].GetShape()); |
| 98 | BOOST_TEST( |
| 99 | GetDataTypeName(connectedInfo.GetDataType()) == GetDataTypeName(m_InputTensorInfos[i].GetDataType())); |
Nattapat Chaimanowong | e4294fd | 2019-03-28 09:56:53 +0000 | [diff] [blame] | 100 | |
| 101 | BOOST_TEST(connectedInfo.GetQuantizationScale() == m_InputTensorInfos[i].GetQuantizationScale()); |
| 102 | BOOST_TEST(connectedInfo.GetQuantizationOffset() == m_InputTensorInfos[i].GetQuantizationOffset()); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 103 | } |
| 104 | |
| 105 | for (unsigned int i = 0; i < m_OutputTensorInfos.size(); i++) |
| 106 | { |
| 107 | const armnn::TensorInfo& outputInfo = layer->GetOutputSlot(i).GetTensorInfo(); |
| 108 | BOOST_TEST(outputInfo.GetShape() == m_OutputTensorInfos[i].GetShape()); |
| 109 | BOOST_TEST( |
| 110 | GetDataTypeName(outputInfo.GetDataType()) == GetDataTypeName(m_OutputTensorInfos[i].GetDataType())); |
Nattapat Chaimanowong | e4294fd | 2019-03-28 09:56:53 +0000 | [diff] [blame] | 111 | |
| 112 | BOOST_TEST(outputInfo.GetQuantizationScale() == m_OutputTensorInfos[i].GetQuantizationScale()); |
| 113 | BOOST_TEST(outputInfo.GetQuantizationOffset() == m_OutputTensorInfos[i].GetQuantizationOffset()); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 114 | } |
| 115 | } |
| 116 | |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 117 | void VerifyConstTensors(const std::string& tensorName, |
| 118 | const armnn::ConstTensor* expectedPtr, |
| 119 | const armnn::ConstTensor* actualPtr) |
| 120 | { |
| 121 | if (expectedPtr == nullptr) |
| 122 | { |
| 123 | BOOST_CHECK_MESSAGE(actualPtr == nullptr, tensorName + " should not exist"); |
| 124 | } |
| 125 | else |
| 126 | { |
| 127 | BOOST_CHECK_MESSAGE(actualPtr != nullptr, tensorName + " should have been set"); |
| 128 | if (actualPtr != nullptr) |
| 129 | { |
| 130 | const armnn::TensorInfo& expectedInfo = expectedPtr->GetInfo(); |
| 131 | const armnn::TensorInfo& actualInfo = actualPtr->GetInfo(); |
| 132 | |
| 133 | BOOST_CHECK_MESSAGE(expectedInfo.GetShape() == actualInfo.GetShape(), |
| 134 | tensorName + " shapes don't match"); |
| 135 | BOOST_CHECK_MESSAGE( |
| 136 | GetDataTypeName(expectedInfo.GetDataType()) == GetDataTypeName(actualInfo.GetDataType()), |
| 137 | tensorName + " data types don't match"); |
| 138 | |
| 139 | BOOST_CHECK_MESSAGE(expectedPtr->GetNumBytes() == actualPtr->GetNumBytes(), |
| 140 | tensorName + " (GetNumBytes) data sizes do not match"); |
| 141 | if (expectedPtr->GetNumBytes() == actualPtr->GetNumBytes()) |
| 142 | { |
| 143 | //check the data is identical |
| 144 | const char* expectedData = static_cast<const char*>(expectedPtr->GetMemoryArea()); |
| 145 | const char* actualData = static_cast<const char*>(actualPtr->GetMemoryArea()); |
| 146 | bool same = true; |
| 147 | for (unsigned int i = 0; i < expectedPtr->GetNumBytes(); ++i) |
| 148 | { |
| 149 | same = expectedData[i] == actualData[i]; |
| 150 | if (!same) |
| 151 | { |
| 152 | break; |
| 153 | } |
| 154 | } |
| 155 | BOOST_CHECK_MESSAGE(same, tensorName + " data does not match"); |
| 156 | } |
| 157 | } |
| 158 | } |
| 159 | } |
| 160 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 161 | private: |
| 162 | std::string m_LayerName; |
| 163 | std::vector<armnn::TensorInfo> m_InputTensorInfos; |
| 164 | std::vector<armnn::TensorInfo> m_OutputTensorInfos; |
| 165 | }; |
| 166 | |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 167 | template<typename Descriptor> |
| 168 | class LayerVerifierBaseWithDescriptor : public LayerVerifierBase |
| 169 | { |
| 170 | public: |
| 171 | LayerVerifierBaseWithDescriptor(const std::string& layerName, |
| 172 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 173 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 174 | const Descriptor& descriptor) |
| 175 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 176 | , m_Descriptor(descriptor) {} |
| 177 | |
| 178 | protected: |
| 179 | void VerifyDescriptor(const Descriptor& descriptor) |
| 180 | { |
| 181 | BOOST_CHECK(descriptor == m_Descriptor); |
| 182 | } |
| 183 | |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 184 | Descriptor m_Descriptor; |
| 185 | }; |
| 186 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 187 | template<typename T> |
| 188 | void CompareConstTensorData(const void* data1, const void* data2, unsigned int numElements) |
| 189 | { |
| 190 | T typedData1 = static_cast<T>(data1); |
| 191 | T typedData2 = static_cast<T>(data2); |
| 192 | BOOST_CHECK(typedData1); |
| 193 | BOOST_CHECK(typedData2); |
| 194 | |
| 195 | for (unsigned int i = 0; i < numElements; i++) |
| 196 | { |
| 197 | BOOST_TEST(typedData1[i] == typedData2[i]); |
| 198 | } |
| 199 | } |
| 200 | |
| 201 | void CompareConstTensor(const armnn::ConstTensor& tensor1, const armnn::ConstTensor& tensor2) |
| 202 | { |
| 203 | BOOST_TEST(tensor1.GetShape() == tensor2.GetShape()); |
| 204 | BOOST_TEST(GetDataTypeName(tensor1.GetDataType()) == GetDataTypeName(tensor2.GetDataType())); |
| 205 | |
| 206 | switch (tensor1.GetDataType()) |
| 207 | { |
| 208 | case armnn::DataType::Float32: |
| 209 | CompareConstTensorData<const float*>( |
| 210 | tensor1.GetMemoryArea(), tensor2.GetMemoryArea(), tensor1.GetNumElements()); |
| 211 | break; |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 212 | case armnn::DataType::QAsymmU8: |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 213 | case armnn::DataType::Boolean: |
| 214 | CompareConstTensorData<const uint8_t*>( |
| 215 | tensor1.GetMemoryArea(), tensor2.GetMemoryArea(), tensor1.GetNumElements()); |
| 216 | break; |
Sadik Armagan | 1a84fe3 | 2020-03-27 15:56:57 +0000 | [diff] [blame] | 217 | case armnn::DataType::QSymmS8: |
| 218 | CompareConstTensorData<const int8_t*>( |
| 219 | tensor1.GetMemoryArea(), tensor2.GetMemoryArea(), tensor1.GetNumElements()); |
| 220 | break; |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 221 | case armnn::DataType::Signed32: |
| 222 | CompareConstTensorData<const int32_t*>( |
| 223 | tensor1.GetMemoryArea(), tensor2.GetMemoryArea(), tensor1.GetNumElements()); |
| 224 | break; |
| 225 | default: |
| 226 | // Note that Float16 is not yet implemented |
| 227 | BOOST_TEST_MESSAGE("Unexpected datatype"); |
| 228 | BOOST_TEST(false); |
| 229 | } |
| 230 | } |
| 231 | |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 232 | armnn::INetworkPtr DeserializeNetwork(const std::string& serializerString) |
| 233 | { |
| 234 | std::vector<std::uint8_t> const serializerVector{serializerString.begin(), serializerString.end()}; |
Derek Lamberti | 0028d1b | 2019-02-20 13:57:42 +0000 | [diff] [blame] | 235 | return IDeserializer::Create()->CreateNetworkFromBinary(serializerVector); |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 236 | } |
| 237 | |
| 238 | std::string SerializeNetwork(const armnn::INetwork& network) |
| 239 | { |
Finn Williams | 85d3671 | 2021-01-26 22:30:06 +0000 | [diff] [blame^] | 240 | armnnSerializer::ISerializerPtr serializer = armnnSerializer::ISerializer::Create(); |
| 241 | |
| 242 | serializer->Serialize(network); |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 243 | |
| 244 | std::stringstream stream; |
Finn Williams | 85d3671 | 2021-01-26 22:30:06 +0000 | [diff] [blame^] | 245 | serializer->SaveSerializedToStream(stream); |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 246 | |
| 247 | std::string serializerString{stream.str()}; |
| 248 | return serializerString; |
| 249 | } |
| 250 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 251 | template<typename DataType> |
| 252 | static std::vector<DataType> GenerateRandomData(size_t size) |
| 253 | { |
| 254 | constexpr bool isIntegerType = std::is_integral<DataType>::value; |
| 255 | using Distribution = |
| 256 | typename std::conditional<isIntegerType, |
| 257 | std::uniform_int_distribution<DataType>, |
| 258 | std::uniform_real_distribution<DataType>>::type; |
| 259 | |
| 260 | static constexpr DataType lowerLimit = std::numeric_limits<DataType>::min(); |
| 261 | static constexpr DataType upperLimit = std::numeric_limits<DataType>::max(); |
| 262 | |
| 263 | static Distribution distribution(lowerLimit, upperLimit); |
| 264 | static std::default_random_engine generator; |
| 265 | |
| 266 | std::vector<DataType> randomData(size); |
| 267 | std::generate(randomData.begin(), randomData.end(), []() { return distribution(generator); }); |
| 268 | |
| 269 | return randomData; |
| 270 | } |
| 271 | |
Saoirse Stewart | 3166c3e | 2019-02-18 15:24:53 +0000 | [diff] [blame] | 272 | } // anonymous namespace |
| 273 | |
| 274 | BOOST_AUTO_TEST_SUITE(SerializerTests) |
Aron Virginas-Tar | fc413c0 | 2019-02-13 15:41:52 +0000 | [diff] [blame] | 275 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 276 | BOOST_AUTO_TEST_CASE(SerializeAddition) |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 277 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 278 | DECLARE_LAYER_VERIFIER_CLASS(Addition) |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 279 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 280 | const std::string layerName("addition"); |
| 281 | const armnn::TensorInfo tensorInfo({1, 2, 3}, armnn::DataType::Float32); |
| 282 | |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 283 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 284 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 285 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 286 | armnn::IConnectableLayer* const additionLayer = network->AddAdditionLayer(layerName.c_str()); |
| 287 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 288 | |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 289 | inputLayer0->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(0)); |
| 290 | inputLayer1->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(1)); |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 291 | additionLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 292 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 293 | inputLayer0->GetOutputSlot(0).SetTensorInfo(tensorInfo); |
| 294 | inputLayer1->GetOutputSlot(0).SetTensorInfo(tensorInfo); |
| 295 | additionLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo); |
Jim Flynn | 3091b06 | 2019-02-15 14:45:04 +0000 | [diff] [blame] | 296 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 297 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 298 | BOOST_CHECK(deserializedNetwork); |
| 299 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 300 | AdditionLayerVerifier verifier(layerName, {tensorInfo, tensorInfo}, {tensorInfo}); |
| 301 | deserializedNetwork->Accept(verifier); |
| 302 | } |
Jim Flynn | ac25a1b | 2019-02-28 10:40:49 +0000 | [diff] [blame] | 303 | |
Narumol Prangnawarat | 0cfcf23 | 2019-09-09 17:16:24 +0100 | [diff] [blame] | 304 | BOOST_AUTO_TEST_CASE(SerializeArgMinMax) |
| 305 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 306 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(ArgMinMax) |
Narumol Prangnawarat | 0cfcf23 | 2019-09-09 17:16:24 +0100 | [diff] [blame] | 307 | |
| 308 | const std::string layerName("argminmax"); |
| 309 | const armnn::TensorInfo inputInfo({1, 2, 3}, armnn::DataType::Float32); |
| 310 | const armnn::TensorInfo outputInfo({1, 3}, armnn::DataType::Signed32); |
| 311 | |
| 312 | armnn::ArgMinMaxDescriptor descriptor; |
| 313 | descriptor.m_Function = armnn::ArgMinMaxFunction::Max; |
| 314 | descriptor.m_Axis = 1; |
| 315 | |
| 316 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 317 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 318 | armnn::IConnectableLayer* const argMinMaxLayer = network->AddArgMinMaxLayer(descriptor, layerName.c_str()); |
| 319 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 320 | |
| 321 | inputLayer->GetOutputSlot(0).Connect(argMinMaxLayer->GetInputSlot(0)); |
| 322 | argMinMaxLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 323 | |
| 324 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 325 | argMinMaxLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 326 | |
| 327 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 328 | BOOST_CHECK(deserializedNetwork); |
| 329 | |
| 330 | ArgMinMaxLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor); |
| 331 | deserializedNetwork->Accept(verifier); |
| 332 | } |
| 333 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 334 | BOOST_AUTO_TEST_CASE(SerializeBatchNormalization) |
| 335 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 336 | using Descriptor = armnn::BatchNormalizationDescriptor; |
| 337 | class BatchNormalizationLayerVerifier : public LayerVerifierBaseWithDescriptor<Descriptor> |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 338 | { |
| 339 | public: |
| 340 | BatchNormalizationLayerVerifier(const std::string& layerName, |
| 341 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 342 | const std::vector<armnn::TensorInfo>& outputInfos, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 343 | const Descriptor& descriptor, |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 344 | const armnn::ConstTensor& mean, |
| 345 | const armnn::ConstTensor& variance, |
| 346 | const armnn::ConstTensor& beta, |
| 347 | const armnn::ConstTensor& gamma) |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 348 | : LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor) |
| 349 | , m_Mean(mean) |
| 350 | , m_Variance(variance) |
| 351 | , m_Beta(beta) |
| 352 | , m_Gamma(gamma) {} |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 353 | |
| 354 | void VisitBatchNormalizationLayer(const armnn::IConnectableLayer* layer, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 355 | const Descriptor& descriptor, |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 356 | const armnn::ConstTensor& mean, |
| 357 | const armnn::ConstTensor& variance, |
| 358 | const armnn::ConstTensor& beta, |
| 359 | const armnn::ConstTensor& gamma, |
| 360 | const char* name) override |
| 361 | { |
| 362 | VerifyNameAndConnections(layer, name); |
| 363 | VerifyDescriptor(descriptor); |
| 364 | |
| 365 | CompareConstTensor(mean, m_Mean); |
| 366 | CompareConstTensor(variance, m_Variance); |
| 367 | CompareConstTensor(beta, m_Beta); |
| 368 | CompareConstTensor(gamma, m_Gamma); |
| 369 | } |
| 370 | |
| 371 | private: |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 372 | armnn::ConstTensor m_Mean; |
| 373 | armnn::ConstTensor m_Variance; |
| 374 | armnn::ConstTensor m_Beta; |
| 375 | armnn::ConstTensor m_Gamma; |
| 376 | }; |
| 377 | |
| 378 | const std::string layerName("batchNormalization"); |
| 379 | const armnn::TensorInfo inputInfo ({ 1, 3, 3, 1 }, armnn::DataType::Float32); |
| 380 | const armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32); |
| 381 | |
| 382 | const armnn::TensorInfo meanInfo({1}, armnn::DataType::Float32); |
| 383 | const armnn::TensorInfo varianceInfo({1}, armnn::DataType::Float32); |
| 384 | const armnn::TensorInfo betaInfo({1}, armnn::DataType::Float32); |
| 385 | const armnn::TensorInfo gammaInfo({1}, armnn::DataType::Float32); |
| 386 | |
| 387 | armnn::BatchNormalizationDescriptor descriptor; |
| 388 | descriptor.m_Eps = 0.0010000000475f; |
| 389 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 390 | |
| 391 | std::vector<float> meanData({5.0}); |
| 392 | std::vector<float> varianceData({2.0}); |
| 393 | std::vector<float> betaData({1.0}); |
| 394 | std::vector<float> gammaData({0.0}); |
| 395 | |
| 396 | armnn::ConstTensor mean(meanInfo, meanData); |
| 397 | armnn::ConstTensor variance(varianceInfo, varianceData); |
| 398 | armnn::ConstTensor beta(betaInfo, betaData); |
| 399 | armnn::ConstTensor gamma(gammaInfo, gammaData); |
| 400 | |
| 401 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 402 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 403 | armnn::IConnectableLayer* const batchNormalizationLayer = |
| 404 | network->AddBatchNormalizationLayer(descriptor, mean, variance, beta, gamma, layerName.c_str()); |
| 405 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 406 | |
| 407 | inputLayer->GetOutputSlot(0).Connect(batchNormalizationLayer->GetInputSlot(0)); |
| 408 | batchNormalizationLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 409 | |
| 410 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 411 | batchNormalizationLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 412 | |
| 413 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 414 | BOOST_CHECK(deserializedNetwork); |
| 415 | |
| 416 | BatchNormalizationLayerVerifier verifier( |
| 417 | layerName, {inputInfo}, {outputInfo}, descriptor, mean, variance, beta, gamma); |
| 418 | deserializedNetwork->Accept(verifier); |
| 419 | } |
| 420 | |
| 421 | BOOST_AUTO_TEST_CASE(SerializeBatchToSpaceNd) |
| 422 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 423 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(BatchToSpaceNd) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 424 | |
| 425 | const std::string layerName("spaceToBatchNd"); |
| 426 | const armnn::TensorInfo inputInfo({4, 1, 2, 2}, armnn::DataType::Float32); |
| 427 | const armnn::TensorInfo outputInfo({1, 1, 4, 4}, armnn::DataType::Float32); |
| 428 | |
| 429 | armnn::BatchToSpaceNdDescriptor desc; |
| 430 | desc.m_DataLayout = armnn::DataLayout::NCHW; |
| 431 | desc.m_BlockShape = {2, 2}; |
| 432 | desc.m_Crops = {{0, 0}, {0, 0}}; |
| 433 | |
| 434 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 435 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 436 | armnn::IConnectableLayer* const batchToSpaceNdLayer = network->AddBatchToSpaceNdLayer(desc, layerName.c_str()); |
| 437 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 438 | |
| 439 | inputLayer->GetOutputSlot(0).Connect(batchToSpaceNdLayer->GetInputSlot(0)); |
| 440 | batchToSpaceNdLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 441 | |
| 442 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 443 | batchToSpaceNdLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 444 | |
| 445 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 446 | BOOST_CHECK(deserializedNetwork); |
| 447 | |
| 448 | BatchToSpaceNdLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc); |
| 449 | deserializedNetwork->Accept(verifier); |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 450 | } |
| 451 | |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 452 | BOOST_AUTO_TEST_CASE(SerializeComparison) |
| 453 | { |
| 454 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(Comparison) |
| 455 | |
| 456 | const std::string layerName("comparison"); |
| 457 | |
| 458 | const armnn::TensorShape shape{2, 1, 2, 4}; |
| 459 | |
| 460 | const armnn::TensorInfo inputInfo = armnn::TensorInfo(shape, armnn::DataType::Float32); |
| 461 | const armnn::TensorInfo outputInfo = armnn::TensorInfo(shape, armnn::DataType::Boolean); |
| 462 | |
| 463 | armnn::ComparisonDescriptor descriptor(armnn::ComparisonOperation::NotEqual); |
| 464 | |
| 465 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 466 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 467 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 468 | armnn::IConnectableLayer* const comparisonLayer = network->AddComparisonLayer(descriptor, layerName.c_str()); |
| 469 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 470 | |
| 471 | inputLayer0->GetOutputSlot(0).Connect(comparisonLayer->GetInputSlot(0)); |
| 472 | inputLayer1->GetOutputSlot(0).Connect(comparisonLayer->GetInputSlot(1)); |
| 473 | comparisonLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 474 | |
| 475 | inputLayer0->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 476 | inputLayer1->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 477 | comparisonLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 478 | |
| 479 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 480 | BOOST_CHECK(deserializedNetwork); |
| 481 | |
| 482 | ComparisonLayerVerifier verifier(layerName, { inputInfo, inputInfo }, { outputInfo }, descriptor); |
| 483 | deserializedNetwork->Accept(verifier); |
| 484 | } |
| 485 | |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 486 | BOOST_AUTO_TEST_CASE(SerializeConstant) |
| 487 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 488 | class ConstantLayerVerifier : public LayerVerifierBase |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 489 | { |
| 490 | public: |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 491 | ConstantLayerVerifier(const std::string& layerName, |
| 492 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 493 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 494 | const armnn::ConstTensor& layerInput) |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 495 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 496 | , m_LayerInput(layerInput) {} |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 497 | |
| 498 | void VisitConstantLayer(const armnn::IConnectableLayer* layer, |
| 499 | const armnn::ConstTensor& input, |
| 500 | const char* name) override |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 501 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 502 | VerifyNameAndConnections(layer, name); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 503 | CompareConstTensor(input, m_LayerInput); |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 504 | } |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 505 | |
Derek Lamberti | 859f9ce | 2019-12-10 22:05:21 +0000 | [diff] [blame] | 506 | void VisitAdditionLayer(const armnn::IConnectableLayer*, const char*) override {} |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 507 | |
| 508 | private: |
| 509 | armnn::ConstTensor m_LayerInput; |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 510 | }; |
| 511 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 512 | const std::string layerName("constant"); |
| 513 | const armnn::TensorInfo info({ 2, 3 }, armnn::DataType::Float32); |
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 | std::vector<float> constantData = GenerateRandomData<float>(info.GetNumElements()); |
| 516 | armnn::ConstTensor constTensor(info, constantData); |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 517 | |
Matteo Martincigh | f81edaa | 2019-03-04 14:34:30 +0000 | [diff] [blame] | 518 | armnn::INetworkPtr network(armnn::INetwork::Create()); |
Matteo Martincigh | f81edaa | 2019-03-04 14:34:30 +0000 | [diff] [blame] | 519 | armnn::IConnectableLayer* input = network->AddInputLayer(0); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 520 | armnn::IConnectableLayer* constant = network->AddConstantLayer(constTensor, layerName.c_str()); |
Matteo Martincigh | f81edaa | 2019-03-04 14:34:30 +0000 | [diff] [blame] | 521 | armnn::IConnectableLayer* add = network->AddAdditionLayer(); |
| 522 | armnn::IConnectableLayer* output = network->AddOutputLayer(0); |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 523 | |
| 524 | input->GetOutputSlot(0).Connect(add->GetInputSlot(0)); |
| 525 | constant->GetOutputSlot(0).Connect(add->GetInputSlot(1)); |
| 526 | add->GetOutputSlot(0).Connect(output->GetInputSlot(0)); |
| 527 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 528 | input->GetOutputSlot(0).SetTensorInfo(info); |
| 529 | constant->GetOutputSlot(0).SetTensorInfo(info); |
| 530 | add->GetOutputSlot(0).SetTensorInfo(info); |
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 deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 533 | BOOST_CHECK(deserializedNetwork); |
| 534 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 535 | ConstantLayerVerifier verifier(layerName, {}, {info}, constTensor); |
| 536 | deserializedNetwork->Accept(verifier); |
Conor Kennedy | 7627788 | 2019-02-26 08:29:54 +0000 | [diff] [blame] | 537 | } |
| 538 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 539 | BOOST_AUTO_TEST_CASE(SerializeConvolution2d) |
Finn Williams | dd2ba7e | 2019-03-01 11:51:52 +0000 | [diff] [blame] | 540 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 541 | using Descriptor = armnn::Convolution2dDescriptor; |
| 542 | class Convolution2dLayerVerifier : public LayerVerifierBaseWithDescriptor<Descriptor> |
Finn Williams | dd2ba7e | 2019-03-01 11:51:52 +0000 | [diff] [blame] | 543 | { |
| 544 | public: |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 545 | Convolution2dLayerVerifier(const std::string& layerName, |
| 546 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 547 | const std::vector<armnn::TensorInfo>& outputInfos, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 548 | const Descriptor& descriptor, |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 549 | const armnn::ConstTensor& weights, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 550 | const armnn::Optional<armnn::ConstTensor>& biases) |
| 551 | : LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor) |
| 552 | , m_Weights(weights) |
| 553 | , m_Biases(biases) {} |
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 | void VisitConvolution2dLayer(const armnn::IConnectableLayer* layer, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 556 | const Descriptor& descriptor, |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 557 | const armnn::ConstTensor& weights, |
| 558 | const armnn::Optional<armnn::ConstTensor>& biases, |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 559 | const char* name) override |
| 560 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 561 | VerifyNameAndConnections(layer, name); |
| 562 | VerifyDescriptor(descriptor); |
| 563 | |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 564 | // check weights |
| 565 | CompareConstTensor(weights, m_Weights); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 566 | |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 567 | // check biases |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 568 | BOOST_CHECK(biases.has_value() == descriptor.m_BiasEnabled); |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 569 | BOOST_CHECK(biases.has_value() == m_Biases.has_value()); |
| 570 | |
| 571 | if (biases.has_value() && m_Biases.has_value()) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 572 | { |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 573 | CompareConstTensor(biases.value(), m_Biases.value()); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 574 | } |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 575 | } |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 576 | |
| 577 | private: |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 578 | armnn::ConstTensor m_Weights; |
| 579 | armnn::Optional<armnn::ConstTensor> m_Biases; |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 580 | }; |
| 581 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 582 | const std::string layerName("convolution2d"); |
| 583 | const armnn::TensorInfo inputInfo ({ 1, 5, 5, 1 }, armnn::DataType::Float32); |
| 584 | const armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32); |
Saoirse Stewart | 263829c | 2019-02-19 15:54:14 +0000 | [diff] [blame] | 585 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 586 | const armnn::TensorInfo weightsInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32); |
| 587 | const armnn::TensorInfo biasesInfo ({ 1 }, armnn::DataType::Float32); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 588 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 589 | std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements()); |
| 590 | armnn::ConstTensor weights(weightsInfo, weightsData); |
| 591 | |
| 592 | std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements()); |
| 593 | armnn::ConstTensor biases(biasesInfo, biasesData); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 594 | |
| 595 | armnn::Convolution2dDescriptor descriptor; |
| 596 | descriptor.m_PadLeft = 1; |
| 597 | descriptor.m_PadRight = 1; |
| 598 | descriptor.m_PadTop = 1; |
| 599 | descriptor.m_PadBottom = 1; |
| 600 | descriptor.m_StrideX = 2; |
| 601 | descriptor.m_StrideY = 2; |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 602 | descriptor.m_DilationX = 2; |
| 603 | descriptor.m_DilationY = 2; |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 604 | descriptor.m_BiasEnabled = true; |
| 605 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 606 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 607 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 608 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 609 | armnn::IConnectableLayer* const convLayer = |
Matteo Martincigh | fc598e1 | 2019-05-14 10:36:13 +0100 | [diff] [blame] | 610 | network->AddConvolution2dLayer(descriptor, |
| 611 | weights, |
| 612 | armnn::Optional<armnn::ConstTensor>(biases), |
| 613 | layerName.c_str()); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 614 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 615 | |
| 616 | inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0)); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 617 | convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 618 | |
| 619 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 620 | convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 621 | |
| 622 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 623 | BOOST_CHECK(deserializedNetwork); |
| 624 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 625 | Convolution2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases); |
| 626 | deserializedNetwork->Accept(verifier); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 627 | } |
| 628 | |
Sadik Armagan | 1a84fe3 | 2020-03-27 15:56:57 +0000 | [diff] [blame] | 629 | BOOST_AUTO_TEST_CASE(SerializeConvolution2dWithPerAxisParams) |
| 630 | { |
| 631 | using Descriptor = armnn::Convolution2dDescriptor; |
| 632 | class Convolution2dLayerVerifier : public LayerVerifierBaseWithDescriptor<Descriptor> |
| 633 | { |
| 634 | public: |
| 635 | Convolution2dLayerVerifier(const std::string& layerName, |
| 636 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 637 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 638 | const Descriptor& descriptor, |
| 639 | const armnn::ConstTensor& weights, |
| 640 | const armnn::Optional<armnn::ConstTensor>& biases) |
| 641 | : LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor) |
| 642 | , m_Weights(weights) |
| 643 | , m_Biases(biases) {} |
| 644 | |
| 645 | void VisitConvolution2dLayer(const armnn::IConnectableLayer* layer, |
| 646 | const Descriptor& descriptor, |
| 647 | const armnn::ConstTensor& weights, |
| 648 | const armnn::Optional<armnn::ConstTensor>& biases, |
| 649 | const char* name) override |
| 650 | { |
| 651 | VerifyNameAndConnections(layer, name); |
| 652 | VerifyDescriptor(descriptor); |
| 653 | |
| 654 | // check weights |
| 655 | CompareConstTensor(weights, m_Weights); |
| 656 | |
| 657 | // check biases |
| 658 | BOOST_CHECK(biases.has_value() == descriptor.m_BiasEnabled); |
| 659 | BOOST_CHECK(biases.has_value() == m_Biases.has_value()); |
| 660 | |
| 661 | if (biases.has_value() && m_Biases.has_value()) |
| 662 | { |
| 663 | CompareConstTensor(biases.value(), m_Biases.value()); |
| 664 | } |
| 665 | } |
| 666 | |
| 667 | private: |
| 668 | armnn::ConstTensor m_Weights; |
| 669 | armnn::Optional<armnn::ConstTensor> m_Biases; |
| 670 | }; |
| 671 | |
| 672 | using namespace armnn; |
| 673 | |
| 674 | const std::string layerName("convolution2dWithPerAxis"); |
| 675 | const TensorInfo inputInfo ({ 1, 3, 1, 2 }, DataType::QAsymmU8, 0.55f, 128); |
| 676 | const TensorInfo outputInfo({ 1, 3, 1, 3 }, DataType::QAsymmU8, 0.75f, 128); |
| 677 | |
| 678 | const std::vector<float> quantScales{ 0.75f, 0.65f, 0.85f }; |
| 679 | constexpr unsigned int quantDimension = 0; |
| 680 | |
| 681 | const TensorInfo kernelInfo({ 3, 1, 1, 2 }, DataType::QSymmS8, quantScales, quantDimension); |
| 682 | |
| 683 | const std::vector<float> biasQuantScales{ 0.25f, 0.50f, 0.75f }; |
| 684 | const TensorInfo biasInfo({ 3 }, DataType::Signed32, biasQuantScales, quantDimension); |
| 685 | |
| 686 | std::vector<int8_t> kernelData = GenerateRandomData<int8_t>(kernelInfo.GetNumElements()); |
| 687 | armnn::ConstTensor weights(kernelInfo, kernelData); |
| 688 | std::vector<int32_t> biasData = GenerateRandomData<int32_t>(biasInfo.GetNumElements()); |
| 689 | armnn::ConstTensor biases(biasInfo, biasData); |
| 690 | |
| 691 | Convolution2dDescriptor descriptor; |
| 692 | descriptor.m_StrideX = 1; |
| 693 | descriptor.m_StrideY = 1; |
| 694 | descriptor.m_PadLeft = 0; |
| 695 | descriptor.m_PadRight = 0; |
| 696 | descriptor.m_PadTop = 0; |
| 697 | descriptor.m_PadBottom = 0; |
| 698 | descriptor.m_BiasEnabled = true; |
| 699 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 700 | |
| 701 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 702 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 703 | armnn::IConnectableLayer* const convLayer = |
| 704 | network->AddConvolution2dLayer(descriptor, |
| 705 | weights, |
| 706 | armnn::Optional<armnn::ConstTensor>(biases), |
| 707 | layerName.c_str()); |
| 708 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 709 | |
| 710 | inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0)); |
| 711 | convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 712 | |
| 713 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 714 | convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 715 | |
| 716 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 717 | BOOST_CHECK(deserializedNetwork); |
| 718 | |
| 719 | Convolution2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases); |
| 720 | deserializedNetwork->Accept(verifier); |
| 721 | } |
| 722 | |
Aron Virginas-Tar | da9d2d3 | 2019-09-20 10:42:02 +0100 | [diff] [blame] | 723 | BOOST_AUTO_TEST_CASE(SerializeDepthToSpace) |
| 724 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 725 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(DepthToSpace) |
Aron Virginas-Tar | da9d2d3 | 2019-09-20 10:42:02 +0100 | [diff] [blame] | 726 | |
| 727 | const std::string layerName("depthToSpace"); |
| 728 | |
| 729 | const armnn::TensorInfo inputInfo ({ 1, 8, 4, 12 }, armnn::DataType::Float32); |
| 730 | const armnn::TensorInfo outputInfo({ 1, 16, 8, 3 }, armnn::DataType::Float32); |
| 731 | |
| 732 | armnn::DepthToSpaceDescriptor desc; |
| 733 | desc.m_BlockSize = 2; |
| 734 | desc.m_DataLayout = armnn::DataLayout::NHWC; |
| 735 | |
| 736 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 737 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 738 | armnn::IConnectableLayer* const depthToSpaceLayer = network->AddDepthToSpaceLayer(desc, layerName.c_str()); |
| 739 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 740 | |
| 741 | inputLayer->GetOutputSlot(0).Connect(depthToSpaceLayer->GetInputSlot(0)); |
| 742 | depthToSpaceLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 743 | |
| 744 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 745 | depthToSpaceLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 746 | |
| 747 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 748 | BOOST_CHECK(deserializedNetwork); |
| 749 | |
| 750 | DepthToSpaceLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc); |
| 751 | deserializedNetwork->Accept(verifier); |
| 752 | } |
| 753 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 754 | BOOST_AUTO_TEST_CASE(SerializeDepthwiseConvolution2d) |
Conor Kennedy | 79ffdf5 | 2019-03-01 14:24:54 +0000 | [diff] [blame] | 755 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 756 | using Descriptor = armnn::DepthwiseConvolution2dDescriptor; |
| 757 | class DepthwiseConvolution2dLayerVerifier : public LayerVerifierBaseWithDescriptor<Descriptor> |
Conor Kennedy | 79ffdf5 | 2019-03-01 14:24:54 +0000 | [diff] [blame] | 758 | { |
| 759 | public: |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 760 | DepthwiseConvolution2dLayerVerifier(const std::string& layerName, |
| 761 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 762 | const std::vector<armnn::TensorInfo>& outputInfos, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 763 | const Descriptor& descriptor, |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 764 | const armnn::ConstTensor& weights, |
| 765 | const armnn::Optional<armnn::ConstTensor>& biases) : |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 766 | LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor), |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 767 | m_Weights(weights), |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 768 | m_Biases(biases) {} |
Conor Kennedy | 79ffdf5 | 2019-03-01 14:24:54 +0000 | [diff] [blame] | 769 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 770 | void VisitDepthwiseConvolution2dLayer(const armnn::IConnectableLayer* layer, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 771 | const Descriptor& descriptor, |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 772 | const armnn::ConstTensor& weights, |
| 773 | const armnn::Optional<armnn::ConstTensor>& biases, |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 774 | const char* name) override |
| 775 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 776 | VerifyNameAndConnections(layer, name); |
| 777 | VerifyDescriptor(descriptor); |
| 778 | |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 779 | // check weights |
| 780 | CompareConstTensor(weights, m_Weights); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 781 | |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 782 | // check biases |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 783 | BOOST_CHECK(biases.has_value() == descriptor.m_BiasEnabled); |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 784 | BOOST_CHECK(biases.has_value() == m_Biases.has_value()); |
| 785 | |
| 786 | if (biases.has_value() && m_Biases.has_value()) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 787 | { |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 788 | CompareConstTensor(biases.value(), m_Biases.value()); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 789 | } |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 790 | } |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 791 | |
| 792 | private: |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 793 | armnn::ConstTensor m_Weights; |
| 794 | armnn::Optional<armnn::ConstTensor> m_Biases; |
Éanna Ó Catháin | 633f859 | 2019-02-25 16:26:29 +0000 | [diff] [blame] | 795 | }; |
| 796 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 797 | const std::string layerName("depwiseConvolution2d"); |
| 798 | const armnn::TensorInfo inputInfo ({ 1, 5, 5, 3 }, armnn::DataType::Float32); |
| 799 | const armnn::TensorInfo outputInfo({ 1, 3, 3, 3 }, armnn::DataType::Float32); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 800 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 801 | const armnn::TensorInfo weightsInfo({ 1, 3, 3, 3 }, armnn::DataType::Float32); |
| 802 | const armnn::TensorInfo biasesInfo ({ 3 }, armnn::DataType::Float32); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 803 | |
| 804 | std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements()); |
| 805 | armnn::ConstTensor weights(weightsInfo, weightsData); |
| 806 | |
| 807 | std::vector<int32_t> biasesData = GenerateRandomData<int32_t>(biasesInfo.GetNumElements()); |
| 808 | armnn::ConstTensor biases(biasesInfo, biasesData); |
| 809 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 810 | armnn::DepthwiseConvolution2dDescriptor descriptor; |
Aron Virginas-Tar | 5e1b0cf | 2019-06-21 14:20:11 +0100 | [diff] [blame] | 811 | descriptor.m_PadLeft = 1; |
| 812 | descriptor.m_PadRight = 1; |
| 813 | descriptor.m_PadTop = 1; |
| 814 | descriptor.m_PadBottom = 1; |
| 815 | descriptor.m_StrideX = 2; |
| 816 | descriptor.m_StrideY = 2; |
| 817 | descriptor.m_DilationX = 2; |
| 818 | descriptor.m_DilationY = 2; |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 819 | descriptor.m_BiasEnabled = true; |
| 820 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 821 | |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 822 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 823 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 824 | armnn::IConnectableLayer* const depthwiseConvLayer = |
Matteo Martincigh | fc598e1 | 2019-05-14 10:36:13 +0100 | [diff] [blame] | 825 | network->AddDepthwiseConvolution2dLayer(descriptor, |
| 826 | weights, |
| 827 | armnn::Optional<armnn::ConstTensor>(biases), |
| 828 | layerName.c_str()); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 829 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 830 | |
| 831 | inputLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(0)); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 832 | depthwiseConvLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 833 | |
| 834 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
Aron Virginas-Tar | c04125f | 2019-02-19 16:31:08 +0000 | [diff] [blame] | 835 | depthwiseConvLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 836 | |
| 837 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 838 | BOOST_CHECK(deserializedNetwork); |
| 839 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 840 | DepthwiseConvolution2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases); |
| 841 | deserializedNetwork->Accept(verifier); |
Jim Flynn | 18ce338 | 2019-03-08 11:08:30 +0000 | [diff] [blame] | 842 | } |
| 843 | |
Sadik Armagan | 1a84fe3 | 2020-03-27 15:56:57 +0000 | [diff] [blame] | 844 | BOOST_AUTO_TEST_CASE(SerializeDepthwiseConvolution2dWithPerAxisParams) |
| 845 | { |
| 846 | using Descriptor = armnn::DepthwiseConvolution2dDescriptor; |
| 847 | class DepthwiseConvolution2dLayerVerifier : public LayerVerifierBaseWithDescriptor<Descriptor> |
| 848 | { |
| 849 | public: |
| 850 | DepthwiseConvolution2dLayerVerifier(const std::string& layerName, |
| 851 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 852 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 853 | const Descriptor& descriptor, |
| 854 | const armnn::ConstTensor& weights, |
| 855 | const armnn::Optional<armnn::ConstTensor>& biases) : |
| 856 | LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor), |
| 857 | m_Weights(weights), |
| 858 | m_Biases(biases) {} |
| 859 | |
| 860 | void VisitDepthwiseConvolution2dLayer(const armnn::IConnectableLayer* layer, |
| 861 | const Descriptor& descriptor, |
| 862 | const armnn::ConstTensor& weights, |
| 863 | const armnn::Optional<armnn::ConstTensor>& biases, |
| 864 | const char* name) override |
| 865 | { |
| 866 | VerifyNameAndConnections(layer, name); |
| 867 | VerifyDescriptor(descriptor); |
| 868 | |
| 869 | // check weights |
| 870 | CompareConstTensor(weights, m_Weights); |
| 871 | |
| 872 | // check biases |
| 873 | BOOST_CHECK(biases.has_value() == descriptor.m_BiasEnabled); |
| 874 | BOOST_CHECK(biases.has_value() == m_Biases.has_value()); |
| 875 | |
| 876 | if (biases.has_value() && m_Biases.has_value()) |
| 877 | { |
| 878 | CompareConstTensor(biases.value(), m_Biases.value()); |
| 879 | } |
| 880 | } |
| 881 | |
| 882 | private: |
| 883 | armnn::ConstTensor m_Weights; |
| 884 | armnn::Optional<armnn::ConstTensor> m_Biases; |
| 885 | }; |
| 886 | |
| 887 | using namespace armnn; |
| 888 | |
| 889 | const std::string layerName("depwiseConvolution2dWithPerAxis"); |
| 890 | const TensorInfo inputInfo ({ 1, 3, 3, 2 }, DataType::QAsymmU8, 0.55f, 128); |
| 891 | const TensorInfo outputInfo({ 1, 2, 2, 4 }, DataType::QAsymmU8, 0.75f, 128); |
| 892 | |
| 893 | const std::vector<float> quantScales{ 0.75f, 0.80f, 0.90f, 0.95f }; |
| 894 | const unsigned int quantDimension = 0; |
| 895 | TensorInfo kernelInfo({ 2, 2, 2, 2 }, DataType::QSymmS8, quantScales, quantDimension); |
| 896 | |
| 897 | const std::vector<float> biasQuantScales{ 0.25f, 0.35f, 0.45f, 0.55f }; |
| 898 | constexpr unsigned int biasQuantDimension = 0; |
| 899 | TensorInfo biasInfo({ 4 }, DataType::Signed32, biasQuantScales, biasQuantDimension); |
| 900 | |
| 901 | std::vector<int8_t> kernelData = GenerateRandomData<int8_t>(kernelInfo.GetNumElements()); |
| 902 | armnn::ConstTensor weights(kernelInfo, kernelData); |
| 903 | std::vector<int32_t> biasData = GenerateRandomData<int32_t>(biasInfo.GetNumElements()); |
| 904 | armnn::ConstTensor biases(biasInfo, biasData); |
| 905 | |
| 906 | DepthwiseConvolution2dDescriptor descriptor; |
| 907 | descriptor.m_StrideX = 1; |
| 908 | descriptor.m_StrideY = 1; |
| 909 | descriptor.m_PadLeft = 0; |
| 910 | descriptor.m_PadRight = 0; |
| 911 | descriptor.m_PadTop = 0; |
| 912 | descriptor.m_PadBottom = 0; |
| 913 | descriptor.m_DilationX = 1; |
| 914 | descriptor.m_DilationY = 1; |
| 915 | descriptor.m_BiasEnabled = true; |
| 916 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 917 | |
| 918 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 919 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 920 | armnn::IConnectableLayer* const depthwiseConvLayer = |
| 921 | network->AddDepthwiseConvolution2dLayer(descriptor, |
| 922 | weights, |
| 923 | armnn::Optional<armnn::ConstTensor>(biases), |
| 924 | layerName.c_str()); |
| 925 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 926 | |
| 927 | inputLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(0)); |
| 928 | depthwiseConvLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 929 | |
| 930 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 931 | depthwiseConvLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 932 | |
| 933 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 934 | BOOST_CHECK(deserializedNetwork); |
| 935 | |
| 936 | DepthwiseConvolution2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases); |
| 937 | deserializedNetwork->Accept(verifier); |
| 938 | } |
| 939 | |
Nattapat Chaimanowong | e4294fd | 2019-03-28 09:56:53 +0000 | [diff] [blame] | 940 | BOOST_AUTO_TEST_CASE(SerializeDequantize) |
| 941 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 942 | DECLARE_LAYER_VERIFIER_CLASS(Dequantize) |
Nattapat Chaimanowong | e4294fd | 2019-03-28 09:56:53 +0000 | [diff] [blame] | 943 | |
| 944 | const std::string layerName("dequantize"); |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 945 | const armnn::TensorInfo inputInfo({ 1, 5, 2, 3 }, armnn::DataType::QAsymmU8, 0.5f, 1); |
Nattapat Chaimanowong | e4294fd | 2019-03-28 09:56:53 +0000 | [diff] [blame] | 946 | const armnn::TensorInfo outputInfo({ 1, 5, 2, 3 }, armnn::DataType::Float32); |
| 947 | |
| 948 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 949 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 950 | armnn::IConnectableLayer* const dequantizeLayer = network->AddDequantizeLayer(layerName.c_str()); |
| 951 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 952 | |
| 953 | inputLayer->GetOutputSlot(0).Connect(dequantizeLayer->GetInputSlot(0)); |
| 954 | dequantizeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 955 | |
| 956 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 957 | dequantizeLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 958 | |
| 959 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 960 | BOOST_CHECK(deserializedNetwork); |
| 961 | |
| 962 | DequantizeLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}); |
| 963 | deserializedNetwork->Accept(verifier); |
| 964 | } |
| 965 | |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 966 | BOOST_AUTO_TEST_CASE(SerializeDeserializeDetectionPostProcess) |
| 967 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 968 | using Descriptor = armnn::DetectionPostProcessDescriptor; |
| 969 | class DetectionPostProcessLayerVerifier : public LayerVerifierBaseWithDescriptor<Descriptor> |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 970 | { |
| 971 | public: |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 972 | DetectionPostProcessLayerVerifier(const std::string& layerName, |
| 973 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 974 | const std::vector<armnn::TensorInfo>& outputInfos, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 975 | const Descriptor& descriptor, |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 976 | const armnn::ConstTensor& anchors) |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 977 | : LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor) |
| 978 | , m_Anchors(anchors) {} |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 979 | |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 980 | void VisitDetectionPostProcessLayer(const armnn::IConnectableLayer* layer, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 981 | const Descriptor& descriptor, |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 982 | const armnn::ConstTensor& anchors, |
| 983 | const char* name) override |
| 984 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 985 | VerifyNameAndConnections(layer, name); |
| 986 | VerifyDescriptor(descriptor); |
| 987 | |
| 988 | CompareConstTensor(anchors, m_Anchors); |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 989 | } |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 990 | |
| 991 | private: |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 992 | armnn::ConstTensor m_Anchors; |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 993 | }; |
| 994 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 995 | const std::string layerName("detectionPostProcess"); |
| 996 | |
| 997 | const std::vector<armnn::TensorInfo> inputInfos({ |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 998 | armnn::TensorInfo({ 1, 6, 4 }, armnn::DataType::Float32), |
| 999 | armnn::TensorInfo({ 1, 6, 3}, armnn::DataType::Float32) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1000 | }); |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 1001 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1002 | const std::vector<armnn::TensorInfo> outputInfos({ |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 1003 | armnn::TensorInfo({ 1, 3, 4 }, armnn::DataType::Float32), |
| 1004 | armnn::TensorInfo({ 1, 3 }, armnn::DataType::Float32), |
| 1005 | armnn::TensorInfo({ 1, 3 }, armnn::DataType::Float32), |
| 1006 | armnn::TensorInfo({ 1 }, armnn::DataType::Float32) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1007 | }); |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 1008 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1009 | armnn::DetectionPostProcessDescriptor descriptor; |
| 1010 | descriptor.m_UseRegularNms = true; |
| 1011 | descriptor.m_MaxDetections = 3; |
| 1012 | descriptor.m_MaxClassesPerDetection = 1; |
| 1013 | descriptor.m_DetectionsPerClass =1; |
| 1014 | descriptor.m_NmsScoreThreshold = 0.0; |
| 1015 | descriptor.m_NmsIouThreshold = 0.5; |
| 1016 | descriptor.m_NumClasses = 2; |
| 1017 | descriptor.m_ScaleY = 10.0; |
| 1018 | descriptor.m_ScaleX = 10.0; |
| 1019 | descriptor.m_ScaleH = 5.0; |
| 1020 | descriptor.m_ScaleW = 5.0; |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 1021 | |
| 1022 | const armnn::TensorInfo anchorsInfo({ 6, 4 }, armnn::DataType::Float32); |
| 1023 | const std::vector<float> anchorsData({ |
| 1024 | 0.5f, 0.5f, 1.0f, 1.0f, |
| 1025 | 0.5f, 0.5f, 1.0f, 1.0f, |
| 1026 | 0.5f, 0.5f, 1.0f, 1.0f, |
| 1027 | 0.5f, 10.5f, 1.0f, 1.0f, |
| 1028 | 0.5f, 10.5f, 1.0f, 1.0f, |
| 1029 | 0.5f, 100.5f, 1.0f, 1.0f |
| 1030 | }); |
| 1031 | armnn::ConstTensor anchors(anchorsInfo, anchorsData); |
| 1032 | |
| 1033 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 1034 | armnn::IConnectableLayer* const detectionLayer = |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1035 | network->AddDetectionPostProcessLayer(descriptor, anchors, layerName.c_str()); |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 1036 | |
| 1037 | for (unsigned int i = 0; i < 2; i++) |
| 1038 | { |
| 1039 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(static_cast<int>(i)); |
| 1040 | inputLayer->GetOutputSlot(0).Connect(detectionLayer->GetInputSlot(i)); |
| 1041 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfos[i]); |
| 1042 | } |
| 1043 | |
| 1044 | for (unsigned int i = 0; i < 4; i++) |
| 1045 | { |
| 1046 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(static_cast<int>(i)); |
| 1047 | detectionLayer->GetOutputSlot(i).Connect(outputLayer->GetInputSlot(0)); |
| 1048 | detectionLayer->GetOutputSlot(i).SetTensorInfo(outputInfos[i]); |
| 1049 | } |
| 1050 | |
| 1051 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1052 | BOOST_CHECK(deserializedNetwork); |
| 1053 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1054 | DetectionPostProcessLayerVerifier verifier(layerName, inputInfos, outputInfos, descriptor, anchors); |
| 1055 | deserializedNetwork->Accept(verifier); |
| 1056 | } |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 1057 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1058 | BOOST_AUTO_TEST_CASE(SerializeDivision) |
| 1059 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1060 | DECLARE_LAYER_VERIFIER_CLASS(Division) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1061 | |
| 1062 | const std::string layerName("division"); |
| 1063 | const armnn::TensorInfo info({ 1, 5, 2, 3 }, armnn::DataType::Float32); |
| 1064 | |
| 1065 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1066 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 1067 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 1068 | armnn::IConnectableLayer* const divisionLayer = network->AddDivisionLayer(layerName.c_str()); |
| 1069 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1070 | |
| 1071 | inputLayer0->GetOutputSlot(0).Connect(divisionLayer->GetInputSlot(0)); |
| 1072 | inputLayer1->GetOutputSlot(0).Connect(divisionLayer->GetInputSlot(1)); |
| 1073 | divisionLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1074 | |
| 1075 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 1076 | inputLayer1->GetOutputSlot(0).SetTensorInfo(info); |
| 1077 | divisionLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1078 | |
| 1079 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1080 | BOOST_CHECK(deserializedNetwork); |
| 1081 | |
| 1082 | DivisionLayerVerifier verifier(layerName, {info, info}, {info}); |
| 1083 | deserializedNetwork->Accept(verifier); |
| 1084 | } |
| 1085 | |
Aron Virginas-Tar | 6d2e659 | 2019-10-22 11:44:47 +0100 | [diff] [blame] | 1086 | class EqualLayerVerifier : public LayerVerifierBase |
| 1087 | { |
| 1088 | public: |
| 1089 | EqualLayerVerifier(const std::string& layerName, |
| 1090 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1091 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 1092 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 1093 | |
| 1094 | void VisitComparisonLayer(const armnn::IConnectableLayer* layer, |
| 1095 | const armnn::ComparisonDescriptor& descriptor, |
| 1096 | const char* name) override |
| 1097 | { |
| 1098 | VerifyNameAndConnections(layer, name); |
| 1099 | BOOST_CHECK(descriptor.m_Operation == armnn::ComparisonOperation::Equal); |
| 1100 | } |
| 1101 | |
Derek Lamberti | 859f9ce | 2019-12-10 22:05:21 +0000 | [diff] [blame] | 1102 | void VisitEqualLayer(const armnn::IConnectableLayer*, const char*) override |
Aron Virginas-Tar | 6d2e659 | 2019-10-22 11:44:47 +0100 | [diff] [blame] | 1103 | { |
| 1104 | throw armnn::Exception("EqualLayer should have translated to ComparisonLayer"); |
| 1105 | } |
| 1106 | }; |
| 1107 | |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1108 | // NOTE: Until the deprecated AddEqualLayer disappears this test checks that calling |
| 1109 | // AddEqualLayer places a ComparisonLayer into the serialized format and that |
| 1110 | // when this deserialises we have a ComparisonLayer |
| 1111 | BOOST_AUTO_TEST_CASE(SerializeEqual) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1112 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1113 | const std::string layerName("equal"); |
| 1114 | |
| 1115 | const armnn::TensorShape shape{2, 1, 2, 4}; |
| 1116 | |
| 1117 | const armnn::TensorInfo inputInfo = armnn::TensorInfo(shape, armnn::DataType::Float32); |
| 1118 | const armnn::TensorInfo outputInfo = armnn::TensorInfo(shape, armnn::DataType::Boolean); |
| 1119 | |
| 1120 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1121 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 1122 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 1123 | ARMNN_NO_DEPRECATE_WARN_BEGIN |
| 1124 | armnn::IConnectableLayer* const equalLayer = network->AddEqualLayer(layerName.c_str()); |
| 1125 | ARMNN_NO_DEPRECATE_WARN_END |
| 1126 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1127 | |
| 1128 | inputLayer0->GetOutputSlot(0).Connect(equalLayer->GetInputSlot(0)); |
| 1129 | inputLayer1->GetOutputSlot(0).Connect(equalLayer->GetInputSlot(1)); |
| 1130 | equalLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1131 | |
| 1132 | inputLayer0->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1133 | inputLayer1->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1134 | equalLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 1135 | |
| 1136 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1137 | BOOST_CHECK(deserializedNetwork); |
| 1138 | |
| 1139 | EqualLayerVerifier verifier(layerName, { inputInfo, inputInfo }, { outputInfo }); |
| 1140 | deserializedNetwork->Accept(verifier); |
| 1141 | } |
| 1142 | |
Aron Virginas-Tar | 6d2e659 | 2019-10-22 11:44:47 +0100 | [diff] [blame] | 1143 | BOOST_AUTO_TEST_CASE(EnsureEqualBackwardCompatibility) |
| 1144 | { |
| 1145 | // The hex data below is a flat buffer containing a simple network with two inputs, |
| 1146 | // an EqualLayer (now deprecated) and an output |
| 1147 | // |
| 1148 | // This test verifies that we can still deserialize this old-style model by replacing |
| 1149 | // the EqualLayer with an equivalent ComparisonLayer |
| 1150 | const std::vector<uint8_t> equalModel = |
| 1151 | { |
| 1152 | 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00, |
| 1153 | 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, |
| 1154 | 0xCC, 0x01, 0x00, 0x00, 0x20, 0x01, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x02, 0x00, |
| 1155 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, |
| 1156 | 0x60, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B, 0x04, 0x00, 0x00, 0x00, 0xFE, 0xFE, 0xFF, 0xFF, 0x04, 0x00, |
| 1157 | 0x00, 0x00, 0x06, 0xFF, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0xEA, 0xFE, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, |
| 1158 | 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1159 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1160 | 0x64, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xB4, 0xFE, 0xFF, 0xFF, 0x00, 0x00, |
| 1161 | 0x00, 0x13, 0x04, 0x00, 0x00, 0x00, 0x52, 0xFF, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x36, 0xFF, 0xFF, 0xFF, |
| 1162 | 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x11, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x1C, 0x00, |
| 1163 | 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x65, 0x71, 0x75, 0x61, 0x6C, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, |
| 1164 | 0x5C, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x34, 0xFF, |
| 1165 | 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x92, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x04, 0x08, 0x00, 0x00, 0x00, |
| 1166 | 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, |
| 1167 | 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x08, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, |
| 1168 | 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x00, 0x00, |
| 1169 | 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0E, 0x00, |
| 1170 | 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1171 | 0x06, 0x00, 0x08, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0E, 0x00, |
| 1172 | 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1173 | 0x0E, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x14, 0x00, 0x0E, 0x00, 0x00, 0x00, |
| 1174 | 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, |
| 1175 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, |
| 1176 | 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, |
| 1177 | 0x00, 0x00, 0x66, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1178 | 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x04, 0x00, |
| 1179 | 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, |
| 1180 | 0x04, 0x00, 0x00, 0x00, 0xF6, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x0A, 0x00, |
| 1181 | 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x14, 0x00, 0x00, 0x00, |
| 1182 | 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x0E, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, |
| 1183 | 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1184 | 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0A, 0x00, 0x00, 0x00, |
| 1185 | 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x08, 0x00, |
| 1186 | 0x07, 0x00, 0x0C, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1187 | 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, |
| 1188 | 0x04, 0x00, 0x00, 0x00 |
| 1189 | }; |
| 1190 | |
| 1191 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(std::string(equalModel.begin(), equalModel.end())); |
| 1192 | BOOST_CHECK(deserializedNetwork); |
| 1193 | |
| 1194 | const armnn::TensorShape shape{ 2, 1, 2, 4 }; |
| 1195 | |
| 1196 | const armnn::TensorInfo inputInfo = armnn::TensorInfo(shape, armnn::DataType::Float32); |
| 1197 | const armnn::TensorInfo outputInfo = armnn::TensorInfo(shape, armnn::DataType::Boolean); |
| 1198 | |
| 1199 | EqualLayerVerifier verifier("equal", { inputInfo, inputInfo }, { outputInfo }); |
| 1200 | deserializedNetwork->Accept(verifier); |
| 1201 | } |
| 1202 | |
Keith Davis | 300ad56 | 2020-06-04 16:34:23 +0100 | [diff] [blame] | 1203 | BOOST_AUTO_TEST_CASE(SerializeFill) |
| 1204 | { |
| 1205 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(Fill) |
| 1206 | |
| 1207 | const std::string layerName("fill"); |
Teresa Charlin | 4b10fef | 2020-07-29 09:36:41 +0100 | [diff] [blame] | 1208 | const armnn::TensorInfo inputInfo({4}, armnn::DataType::Signed32); |
Keith Davis | 300ad56 | 2020-06-04 16:34:23 +0100 | [diff] [blame] | 1209 | const armnn::TensorInfo outputInfo({1, 3, 3, 1}, armnn::DataType::Float32); |
| 1210 | |
| 1211 | armnn::FillDescriptor descriptor(1.0f); |
| 1212 | |
| 1213 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1214 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 1215 | armnn::IConnectableLayer* const fillLayer = network->AddFillLayer(descriptor, layerName.c_str()); |
| 1216 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1217 | |
| 1218 | inputLayer->GetOutputSlot(0).Connect(fillLayer->GetInputSlot(0)); |
| 1219 | fillLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1220 | |
| 1221 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1222 | fillLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 1223 | |
| 1224 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1225 | BOOST_CHECK(deserializedNetwork); |
| 1226 | |
| 1227 | FillLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor); |
| 1228 | |
| 1229 | deserializedNetwork->Accept(verifier); |
| 1230 | } |
| 1231 | |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1232 | BOOST_AUTO_TEST_CASE(SerializeFloor) |
| 1233 | { |
| 1234 | DECLARE_LAYER_VERIFIER_CLASS(Floor) |
| 1235 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1236 | const std::string layerName("floor"); |
| 1237 | const armnn::TensorInfo info({4,4}, armnn::DataType::Float32); |
| 1238 | |
| 1239 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1240 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 1241 | armnn::IConnectableLayer* const floorLayer = network->AddFloorLayer(layerName.c_str()); |
| 1242 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1243 | |
| 1244 | inputLayer->GetOutputSlot(0).Connect(floorLayer->GetInputSlot(0)); |
| 1245 | floorLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1246 | |
| 1247 | inputLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1248 | floorLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1249 | |
| 1250 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1251 | BOOST_CHECK(deserializedNetwork); |
| 1252 | |
| 1253 | FloorLayerVerifier verifier(layerName, {info}, {info}); |
| 1254 | deserializedNetwork->Accept(verifier); |
| 1255 | } |
| 1256 | |
| 1257 | BOOST_AUTO_TEST_CASE(SerializeFullyConnected) |
| 1258 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1259 | using Descriptor = armnn::FullyConnectedDescriptor; |
| 1260 | class FullyConnectedLayerVerifier : public LayerVerifierBaseWithDescriptor<Descriptor> |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1261 | { |
| 1262 | public: |
| 1263 | FullyConnectedLayerVerifier(const std::string& layerName, |
| 1264 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1265 | const std::vector<armnn::TensorInfo>& outputInfos, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1266 | const Descriptor& descriptor, |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1267 | const armnn::ConstTensor& weight, |
| 1268 | const armnn::Optional<armnn::ConstTensor>& bias) |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1269 | : LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor) |
| 1270 | , m_Weight(weight) |
| 1271 | , m_Bias(bias) {} |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1272 | |
| 1273 | void VisitFullyConnectedLayer(const armnn::IConnectableLayer* layer, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1274 | const Descriptor& descriptor, |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1275 | const armnn::ConstTensor& weight, |
| 1276 | const armnn::Optional<armnn::ConstTensor>& bias, |
| 1277 | const char* name) override |
| 1278 | { |
| 1279 | VerifyNameAndConnections(layer, name); |
| 1280 | VerifyDescriptor(descriptor); |
| 1281 | |
| 1282 | CompareConstTensor(weight, m_Weight); |
| 1283 | |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1284 | BOOST_TEST(bias.has_value() == descriptor.m_BiasEnabled); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1285 | BOOST_TEST(bias.has_value() == m_Bias.has_value()); |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1286 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1287 | if (bias.has_value() && m_Bias.has_value()) |
| 1288 | { |
| 1289 | CompareConstTensor(bias.value(), m_Bias.value()); |
| 1290 | } |
| 1291 | } |
| 1292 | |
| 1293 | private: |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1294 | armnn::ConstTensor m_Weight; |
| 1295 | armnn::Optional<armnn::ConstTensor> m_Bias; |
| 1296 | }; |
| 1297 | |
| 1298 | const std::string layerName("fullyConnected"); |
| 1299 | const armnn::TensorInfo inputInfo ({ 2, 5, 1, 1 }, armnn::DataType::Float32); |
| 1300 | const armnn::TensorInfo outputInfo({ 2, 3 }, armnn::DataType::Float32); |
| 1301 | |
| 1302 | const armnn::TensorInfo weightsInfo({ 5, 3 }, armnn::DataType::Float32); |
| 1303 | const armnn::TensorInfo biasesInfo ({ 3 }, armnn::DataType::Float32); |
| 1304 | std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements()); |
| 1305 | std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements()); |
| 1306 | armnn::ConstTensor weights(weightsInfo, weightsData); |
| 1307 | armnn::ConstTensor biases(biasesInfo, biasesData); |
| 1308 | |
| 1309 | armnn::FullyConnectedDescriptor descriptor; |
| 1310 | descriptor.m_BiasEnabled = true; |
| 1311 | descriptor.m_TransposeWeightMatrix = false; |
| 1312 | |
| 1313 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1314 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 1315 | armnn::IConnectableLayer* const fullyConnectedLayer = |
Matteo Martincigh | fc598e1 | 2019-05-14 10:36:13 +0100 | [diff] [blame] | 1316 | network->AddFullyConnectedLayer(descriptor, |
| 1317 | weights, |
| 1318 | armnn::Optional<armnn::ConstTensor>(biases), |
| 1319 | layerName.c_str()); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1320 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1321 | |
| 1322 | inputLayer->GetOutputSlot(0).Connect(fullyConnectedLayer->GetInputSlot(0)); |
| 1323 | fullyConnectedLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1324 | |
| 1325 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1326 | fullyConnectedLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 1327 | |
| 1328 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1329 | BOOST_CHECK(deserializedNetwork); |
| 1330 | |
| 1331 | FullyConnectedLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases); |
| 1332 | deserializedNetwork->Accept(verifier); |
| 1333 | } |
| 1334 | |
| 1335 | BOOST_AUTO_TEST_CASE(SerializeGather) |
| 1336 | { |
Teresa Charlin | 5266473 | 2020-06-29 16:27:03 +0100 | [diff] [blame] | 1337 | using GatherDescriptor = armnn::GatherDescriptor; |
| 1338 | class GatherLayerVerifier : public LayerVerifierBaseWithDescriptor<GatherDescriptor> |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1339 | { |
| 1340 | public: |
| 1341 | GatherLayerVerifier(const std::string& layerName, |
| 1342 | const std::vector<armnn::TensorInfo>& inputInfos, |
Teresa Charlin | 5266473 | 2020-06-29 16:27:03 +0100 | [diff] [blame] | 1343 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 1344 | const GatherDescriptor& descriptor) |
| 1345 | : LayerVerifierBaseWithDescriptor<GatherDescriptor>(layerName, inputInfos, outputInfos, descriptor) {} |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1346 | |
Teresa Charlin | 5266473 | 2020-06-29 16:27:03 +0100 | [diff] [blame] | 1347 | void VisitGatherLayer(const armnn::IConnectableLayer* layer, |
| 1348 | const GatherDescriptor& descriptor, |
| 1349 | const char *name) override |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1350 | { |
| 1351 | VerifyNameAndConnections(layer, name); |
Teresa Charlin | 5266473 | 2020-06-29 16:27:03 +0100 | [diff] [blame] | 1352 | BOOST_CHECK(descriptor.m_Axis == m_Descriptor.m_Axis); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1353 | } |
| 1354 | |
Derek Lamberti | 859f9ce | 2019-12-10 22:05:21 +0000 | [diff] [blame] | 1355 | void VisitConstantLayer(const armnn::IConnectableLayer*, |
| 1356 | const armnn::ConstTensor&, |
| 1357 | const char*) override {} |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1358 | }; |
| 1359 | |
| 1360 | const std::string layerName("gather"); |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 1361 | armnn::TensorInfo paramsInfo({ 8 }, armnn::DataType::QAsymmU8); |
| 1362 | armnn::TensorInfo outputInfo({ 3 }, armnn::DataType::QAsymmU8); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1363 | const armnn::TensorInfo indicesInfo({ 3 }, armnn::DataType::Signed32); |
Teresa Charlin | 5266473 | 2020-06-29 16:27:03 +0100 | [diff] [blame] | 1364 | GatherDescriptor descriptor; |
| 1365 | descriptor.m_Axis = 1; |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1366 | |
| 1367 | paramsInfo.SetQuantizationScale(1.0f); |
| 1368 | paramsInfo.SetQuantizationOffset(0); |
| 1369 | outputInfo.SetQuantizationScale(1.0f); |
| 1370 | outputInfo.SetQuantizationOffset(0); |
| 1371 | |
| 1372 | const std::vector<int32_t>& indicesData = {7, 6, 5}; |
| 1373 | |
| 1374 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1375 | armnn::IConnectableLayer *const inputLayer = network->AddInputLayer(0); |
| 1376 | armnn::IConnectableLayer *const constantLayer = |
| 1377 | network->AddConstantLayer(armnn::ConstTensor(indicesInfo, indicesData)); |
Teresa Charlin | 5266473 | 2020-06-29 16:27:03 +0100 | [diff] [blame] | 1378 | armnn::IConnectableLayer *const gatherLayer = network->AddGatherLayer(descriptor, layerName.c_str()); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1379 | armnn::IConnectableLayer *const outputLayer = network->AddOutputLayer(0); |
| 1380 | |
| 1381 | inputLayer->GetOutputSlot(0).Connect(gatherLayer->GetInputSlot(0)); |
| 1382 | constantLayer->GetOutputSlot(0).Connect(gatherLayer->GetInputSlot(1)); |
| 1383 | gatherLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1384 | |
| 1385 | inputLayer->GetOutputSlot(0).SetTensorInfo(paramsInfo); |
| 1386 | constantLayer->GetOutputSlot(0).SetTensorInfo(indicesInfo); |
| 1387 | gatherLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 1388 | |
| 1389 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1390 | BOOST_CHECK(deserializedNetwork); |
| 1391 | |
Teresa Charlin | 5266473 | 2020-06-29 16:27:03 +0100 | [diff] [blame] | 1392 | GatherLayerVerifier verifier(layerName, {paramsInfo, indicesInfo}, {outputInfo}, descriptor); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1393 | deserializedNetwork->Accept(verifier); |
| 1394 | } |
| 1395 | |
Aron Virginas-Tar | 6d2e659 | 2019-10-22 11:44:47 +0100 | [diff] [blame] | 1396 | class GreaterLayerVerifier : public LayerVerifierBase |
| 1397 | { |
| 1398 | public: |
| 1399 | GreaterLayerVerifier(const std::string& layerName, |
| 1400 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1401 | const std::vector<armnn::TensorInfo>& outputInfos) |
| 1402 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 1403 | |
| 1404 | void VisitComparisonLayer(const armnn::IConnectableLayer* layer, |
| 1405 | const armnn::ComparisonDescriptor& descriptor, |
| 1406 | const char* name) override |
| 1407 | { |
| 1408 | VerifyNameAndConnections(layer, name); |
| 1409 | BOOST_CHECK(descriptor.m_Operation == armnn::ComparisonOperation::Greater); |
| 1410 | } |
| 1411 | |
Derek Lamberti | 859f9ce | 2019-12-10 22:05:21 +0000 | [diff] [blame] | 1412 | void VisitGreaterLayer(const armnn::IConnectableLayer*, const char*) override |
Aron Virginas-Tar | 6d2e659 | 2019-10-22 11:44:47 +0100 | [diff] [blame] | 1413 | { |
| 1414 | throw armnn::Exception("GreaterLayer should have translated to ComparisonLayer"); |
| 1415 | } |
| 1416 | }; |
| 1417 | |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1418 | // NOTE: Until the deprecated AddGreaterLayer disappears this test checks that calling |
| 1419 | // AddGreaterLayer places a ComparisonLayer into the serialized format and that |
| 1420 | // when this deserialises we have a ComparisonLayer |
| 1421 | BOOST_AUTO_TEST_CASE(SerializeGreater) |
Aron Virginas-Tar | 781ced9 | 2019-10-03 11:15:39 +0100 | [diff] [blame] | 1422 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1423 | const std::string layerName("greater"); |
| 1424 | |
| 1425 | const armnn::TensorShape shape{2, 1, 2, 4}; |
| 1426 | |
| 1427 | const armnn::TensorInfo inputInfo = armnn::TensorInfo(shape, armnn::DataType::Float32); |
| 1428 | const armnn::TensorInfo outputInfo = armnn::TensorInfo(shape, armnn::DataType::Boolean); |
| 1429 | |
| 1430 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1431 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 1432 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 1433 | ARMNN_NO_DEPRECATE_WARN_BEGIN |
| 1434 | armnn::IConnectableLayer* const equalLayer = network->AddGreaterLayer(layerName.c_str()); |
| 1435 | ARMNN_NO_DEPRECATE_WARN_END |
| 1436 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1437 | |
| 1438 | inputLayer0->GetOutputSlot(0).Connect(equalLayer->GetInputSlot(0)); |
| 1439 | inputLayer1->GetOutputSlot(0).Connect(equalLayer->GetInputSlot(1)); |
| 1440 | equalLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1441 | |
| 1442 | inputLayer0->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1443 | inputLayer1->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1444 | equalLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 1445 | |
| 1446 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1447 | BOOST_CHECK(deserializedNetwork); |
| 1448 | |
| 1449 | GreaterLayerVerifier verifier(layerName, { inputInfo, inputInfo }, { outputInfo }); |
| 1450 | deserializedNetwork->Accept(verifier); |
| 1451 | } |
| 1452 | |
Aron Virginas-Tar | 6d2e659 | 2019-10-22 11:44:47 +0100 | [diff] [blame] | 1453 | BOOST_AUTO_TEST_CASE(EnsureGreaterBackwardCompatibility) |
| 1454 | { |
| 1455 | // The hex data below is a flat buffer containing a simple network with two inputs, |
| 1456 | // an GreaterLayer (now deprecated) and an output |
| 1457 | // |
| 1458 | // This test verifies that we can still deserialize this old-style model by replacing |
| 1459 | // the GreaterLayer with an equivalent ComparisonLayer |
| 1460 | const std::vector<uint8_t> greaterModel = |
| 1461 | { |
| 1462 | 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00, |
| 1463 | 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, |
| 1464 | 0xCC, 0x01, 0x00, 0x00, 0x20, 0x01, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x02, 0x00, |
| 1465 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, |
| 1466 | 0x60, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B, 0x04, 0x00, 0x00, 0x00, 0xFE, 0xFE, 0xFF, 0xFF, 0x04, 0x00, |
| 1467 | 0x00, 0x00, 0x06, 0xFF, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0xEA, 0xFE, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, |
| 1468 | 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1469 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1470 | 0x64, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xB4, 0xFE, 0xFF, 0xFF, 0x00, 0x00, |
| 1471 | 0x00, 0x19, 0x04, 0x00, 0x00, 0x00, 0x52, 0xFF, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x36, 0xFF, 0xFF, 0xFF, |
| 1472 | 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x1C, 0x00, |
| 1473 | 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x67, 0x72, 0x65, 0x61, 0x74, 0x65, 0x72, 0x00, 0x02, 0x00, 0x00, 0x00, |
| 1474 | 0x5C, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x34, 0xFF, |
| 1475 | 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x92, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x04, 0x08, 0x00, 0x00, 0x00, |
| 1476 | 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, |
| 1477 | 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x08, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, |
| 1478 | 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x00, 0x00, |
| 1479 | 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0E, 0x00, |
| 1480 | 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1481 | 0x06, 0x00, 0x08, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0E, 0x00, |
| 1482 | 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1483 | 0x0E, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x14, 0x00, 0x0E, 0x00, 0x00, 0x00, |
| 1484 | 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, |
| 1485 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, |
| 1486 | 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, |
| 1487 | 0x00, 0x00, 0x66, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1488 | 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, |
| 1489 | 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, |
| 1490 | 0x04, 0x00, 0x00, 0x00, 0xF6, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x0A, 0x00, |
| 1491 | 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x14, 0x00, 0x00, 0x00, |
| 1492 | 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x0E, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, |
| 1493 | 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1494 | 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0A, 0x00, 0x00, 0x00, |
| 1495 | 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x08, 0x00, |
| 1496 | 0x07, 0x00, 0x0C, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1497 | 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, |
| 1498 | 0x02, 0x00, 0x00, 0x00 |
| 1499 | }; |
| 1500 | |
| 1501 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(std::string(greaterModel.begin(), greaterModel.end())); |
| 1502 | BOOST_CHECK(deserializedNetwork); |
| 1503 | |
| 1504 | const armnn::TensorShape shape{ 1, 2, 2, 2 }; |
| 1505 | |
| 1506 | const armnn::TensorInfo inputInfo = armnn::TensorInfo(shape, armnn::DataType::Float32); |
| 1507 | const armnn::TensorInfo outputInfo = armnn::TensorInfo(shape, armnn::DataType::Boolean); |
| 1508 | |
| 1509 | GreaterLayerVerifier verifier("greater", { inputInfo, inputInfo }, { outputInfo }); |
| 1510 | deserializedNetwork->Accept(verifier); |
| 1511 | } |
| 1512 | |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1513 | BOOST_AUTO_TEST_CASE(SerializeInstanceNormalization) |
| 1514 | { |
| 1515 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(InstanceNormalization) |
| 1516 | |
Aron Virginas-Tar | 781ced9 | 2019-10-03 11:15:39 +0100 | [diff] [blame] | 1517 | const std::string layerName("instanceNormalization"); |
| 1518 | const armnn::TensorInfo info({ 1, 2, 1, 5 }, armnn::DataType::Float32); |
| 1519 | |
| 1520 | armnn::InstanceNormalizationDescriptor descriptor; |
| 1521 | descriptor.m_Gamma = 1.1f; |
| 1522 | descriptor.m_Beta = 0.1f; |
| 1523 | descriptor.m_Eps = 0.0001f; |
| 1524 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 1525 | |
| 1526 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1527 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 1528 | armnn::IConnectableLayer* const instanceNormLayer = |
| 1529 | network->AddInstanceNormalizationLayer(descriptor, layerName.c_str()); |
| 1530 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1531 | |
| 1532 | inputLayer->GetOutputSlot(0).Connect(instanceNormLayer->GetInputSlot(0)); |
| 1533 | instanceNormLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1534 | |
| 1535 | inputLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1536 | instanceNormLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1537 | |
| 1538 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1539 | BOOST_CHECK(deserializedNetwork); |
| 1540 | |
| 1541 | InstanceNormalizationLayerVerifier verifier(layerName, {info}, {info}, descriptor); |
| 1542 | deserializedNetwork->Accept(verifier); |
| 1543 | } |
| 1544 | |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1545 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(L2Normalization) |
Ferran Balaguer | 0dcffec | 2019-06-18 16:25:06 +0100 | [diff] [blame] | 1546 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1547 | BOOST_AUTO_TEST_CASE(SerializeL2Normalization) |
| 1548 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1549 | const std::string l2NormLayerName("l2Normalization"); |
| 1550 | const armnn::TensorInfo info({1, 2, 1, 5}, armnn::DataType::Float32); |
| 1551 | |
| 1552 | armnn::L2NormalizationDescriptor desc; |
| 1553 | desc.m_DataLayout = armnn::DataLayout::NCHW; |
Ferran Balaguer | 0dcffec | 2019-06-18 16:25:06 +0100 | [diff] [blame] | 1554 | desc.m_Eps = 0.0001f; |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1555 | |
| 1556 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1557 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 1558 | armnn::IConnectableLayer* const l2NormLayer = network->AddL2NormalizationLayer(desc, l2NormLayerName.c_str()); |
| 1559 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1560 | |
| 1561 | inputLayer0->GetOutputSlot(0).Connect(l2NormLayer->GetInputSlot(0)); |
| 1562 | l2NormLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1563 | |
| 1564 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 1565 | l2NormLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1566 | |
| 1567 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1568 | BOOST_CHECK(deserializedNetwork); |
| 1569 | |
| 1570 | L2NormalizationLayerVerifier verifier(l2NormLayerName, {info}, {info}, desc); |
| 1571 | deserializedNetwork->Accept(verifier); |
| 1572 | } |
| 1573 | |
Ferran Balaguer | 0dcffec | 2019-06-18 16:25:06 +0100 | [diff] [blame] | 1574 | BOOST_AUTO_TEST_CASE(EnsureL2NormalizationBackwardCompatibility) |
| 1575 | { |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 1576 | // The hex data below is a flat buffer containing a simple network with one input |
Ferran Balaguer | 0dcffec | 2019-06-18 16:25:06 +0100 | [diff] [blame] | 1577 | // a L2Normalization layer and an output layer with dimensions as per the tensor infos below. |
| 1578 | // |
| 1579 | // This test verifies that we can still read back these old style |
| 1580 | // models without the normalization epsilon value. |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 1581 | const std::vector<uint8_t> l2NormalizationModel = |
Ferran Balaguer | 0dcffec | 2019-06-18 16:25:06 +0100 | [diff] [blame] | 1582 | { |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 1583 | 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00, |
| 1584 | 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, |
| 1585 | 0x3C, 0x01, 0x00, 0x00, 0x74, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1586 | 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0xE8, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B, |
| 1587 | 0x04, 0x00, 0x00, 0x00, 0xD6, 0xFE, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x08, 0x00, |
| 1588 | 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x9E, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00, |
| 1589 | 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1590 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1591 | 0x4C, 0xFF, 0xFF, 0xFF, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x44, 0xFF, 0xFF, 0xFF, 0x00, 0x00, |
| 1592 | 0x00, 0x20, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, |
| 1593 | 0x20, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x06, 0x00, 0x04, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1594 | 0x0E, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x14, 0x00, 0x0E, 0x00, 0x00, 0x00, |
| 1595 | 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x1F, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00, 0x20, 0x00, |
| 1596 | 0x00, 0x00, 0x0F, 0x00, 0x00, 0x00, 0x6C, 0x32, 0x4E, 0x6F, 0x72, 0x6D, 0x61, 0x6C, 0x69, 0x7A, 0x61, 0x74, |
| 1597 | 0x69, 0x6F, 0x6E, 0x00, 0x01, 0x00, 0x00, 0x00, 0x48, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, |
| 1598 | 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, |
| 1599 | 0x52, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, |
| 1600 | 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, |
| 1601 | 0x08, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1602 | 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, |
| 1603 | 0x04, 0x00, 0x00, 0x00, 0xF6, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x0A, 0x00, |
| 1604 | 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x14, 0x00, 0x00, 0x00, |
| 1605 | 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x0E, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, |
| 1606 | 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1607 | 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0A, 0x00, 0x00, 0x00, |
| 1608 | 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x08, 0x00, |
| 1609 | 0x07, 0x00, 0x0C, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1610 | 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, |
| 1611 | 0x05, 0x00, 0x00, 0x00, 0x00 |
| 1612 | }; |
| 1613 | |
| 1614 | armnn::INetworkPtr deserializedNetwork = |
| 1615 | DeserializeNetwork(std::string(l2NormalizationModel.begin(), l2NormalizationModel.end())); |
Ferran Balaguer | 0dcffec | 2019-06-18 16:25:06 +0100 | [diff] [blame] | 1616 | BOOST_CHECK(deserializedNetwork); |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 1617 | |
Ferran Balaguer | 0dcffec | 2019-06-18 16:25:06 +0100 | [diff] [blame] | 1618 | const std::string layerName("l2Normalization"); |
| 1619 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({1, 2, 1, 5}, armnn::DataType::Float32); |
| 1620 | |
| 1621 | armnn::L2NormalizationDescriptor desc; |
| 1622 | desc.m_DataLayout = armnn::DataLayout::NCHW; |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 1623 | // Since this variable does not exist in the l2NormalizationModel dump, the default value will be loaded |
Ferran Balaguer | 0dcffec | 2019-06-18 16:25:06 +0100 | [diff] [blame] | 1624 | desc.m_Eps = 1e-12f; |
| 1625 | |
| 1626 | L2NormalizationLayerVerifier verifier(layerName, {inputInfo}, {inputInfo}, desc); |
| 1627 | deserializedNetwork->Accept(verifier); |
| 1628 | } |
| 1629 | |
James Conroy | aba90cd | 2020-11-06 16:28:18 +0000 | [diff] [blame] | 1630 | BOOST_AUTO_TEST_CASE(SerializeLogicalBinary) |
| 1631 | { |
| 1632 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(LogicalBinary) |
| 1633 | |
| 1634 | const std::string layerName("logicalBinaryAnd"); |
| 1635 | |
| 1636 | const armnn::TensorShape shape{2, 1, 2, 2}; |
| 1637 | |
| 1638 | const armnn::TensorInfo inputInfo = armnn::TensorInfo(shape, armnn::DataType::Boolean); |
| 1639 | const armnn::TensorInfo outputInfo = armnn::TensorInfo(shape, armnn::DataType::Boolean); |
| 1640 | |
| 1641 | armnn::LogicalBinaryDescriptor descriptor(armnn::LogicalBinaryOperation::LogicalAnd); |
| 1642 | |
| 1643 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1644 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 1645 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 1646 | armnn::IConnectableLayer* const logicalBinaryLayer = network->AddLogicalBinaryLayer(descriptor, layerName.c_str()); |
| 1647 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1648 | |
| 1649 | inputLayer0->GetOutputSlot(0).Connect(logicalBinaryLayer->GetInputSlot(0)); |
| 1650 | inputLayer1->GetOutputSlot(0).Connect(logicalBinaryLayer->GetInputSlot(1)); |
| 1651 | logicalBinaryLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1652 | |
| 1653 | inputLayer0->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1654 | inputLayer1->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1655 | logicalBinaryLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 1656 | |
| 1657 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1658 | BOOST_CHECK(deserializedNetwork); |
| 1659 | |
| 1660 | LogicalBinaryLayerVerifier verifier(layerName, { inputInfo, inputInfo }, { outputInfo }, descriptor); |
| 1661 | deserializedNetwork->Accept(verifier); |
| 1662 | } |
| 1663 | |
| 1664 | BOOST_AUTO_TEST_CASE(SerializeLogicalUnary) |
| 1665 | { |
| 1666 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(ElementwiseUnary) |
| 1667 | |
| 1668 | const std::string layerName("elementwiseUnaryLogicalNot"); |
| 1669 | |
| 1670 | const armnn::TensorShape shape{2, 1, 2, 2}; |
| 1671 | |
| 1672 | const armnn::TensorInfo inputInfo = armnn::TensorInfo(shape, armnn::DataType::Boolean); |
| 1673 | const armnn::TensorInfo outputInfo = armnn::TensorInfo(shape, armnn::DataType::Boolean); |
| 1674 | |
| 1675 | armnn::ElementwiseUnaryDescriptor descriptor(armnn::UnaryOperation::LogicalNot); |
| 1676 | |
| 1677 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1678 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 1679 | armnn::IConnectableLayer* const elementwiseUnaryLayer = |
| 1680 | network->AddElementwiseUnaryLayer(descriptor, layerName.c_str()); |
| 1681 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1682 | |
| 1683 | inputLayer->GetOutputSlot(0).Connect(elementwiseUnaryLayer->GetInputSlot(0)); |
| 1684 | elementwiseUnaryLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1685 | |
| 1686 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1687 | elementwiseUnaryLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 1688 | |
| 1689 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1690 | |
| 1691 | BOOST_CHECK(deserializedNetwork); |
| 1692 | |
| 1693 | ElementwiseUnaryLayerVerifier verifier(layerName, { inputInfo }, { outputInfo }, descriptor); |
| 1694 | |
| 1695 | deserializedNetwork->Accept(verifier); |
| 1696 | } |
| 1697 | |
Sadik Armagan | 2625785 | 2019-10-14 13:00:47 +0100 | [diff] [blame] | 1698 | BOOST_AUTO_TEST_CASE(SerializeLogSoftmax) |
| 1699 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1700 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(LogSoftmax) |
Sadik Armagan | 2625785 | 2019-10-14 13:00:47 +0100 | [diff] [blame] | 1701 | |
| 1702 | const std::string layerName("log_softmax"); |
| 1703 | const armnn::TensorInfo info({1, 10}, armnn::DataType::Float32); |
| 1704 | |
| 1705 | armnn::LogSoftmaxDescriptor descriptor; |
| 1706 | descriptor.m_Beta = 1.0f; |
| 1707 | descriptor.m_Axis = -1; |
| 1708 | |
| 1709 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1710 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 1711 | armnn::IConnectableLayer* const logSoftmaxLayer = network->AddLogSoftmaxLayer(descriptor, layerName.c_str()); |
| 1712 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1713 | |
| 1714 | inputLayer->GetOutputSlot(0).Connect(logSoftmaxLayer->GetInputSlot(0)); |
| 1715 | logSoftmaxLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1716 | |
| 1717 | inputLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1718 | logSoftmaxLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1719 | |
| 1720 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1721 | BOOST_CHECK(deserializedNetwork); |
| 1722 | |
| 1723 | LogSoftmaxLayerVerifier verifier(layerName, {info}, {info}, descriptor); |
| 1724 | deserializedNetwork->Accept(verifier); |
| 1725 | } |
| 1726 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1727 | BOOST_AUTO_TEST_CASE(SerializeMaximum) |
| 1728 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1729 | DECLARE_LAYER_VERIFIER_CLASS(Maximum) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1730 | |
| 1731 | const std::string layerName("maximum"); |
| 1732 | const armnn::TensorInfo info({ 1, 2, 2, 3 }, armnn::DataType::Float32); |
| 1733 | |
| 1734 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1735 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 1736 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 1737 | armnn::IConnectableLayer* const maximumLayer = network->AddMaximumLayer(layerName.c_str()); |
| 1738 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1739 | |
| 1740 | inputLayer0->GetOutputSlot(0).Connect(maximumLayer->GetInputSlot(0)); |
| 1741 | inputLayer1->GetOutputSlot(0).Connect(maximumLayer->GetInputSlot(1)); |
| 1742 | maximumLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1743 | |
| 1744 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 1745 | inputLayer1->GetOutputSlot(0).SetTensorInfo(info); |
| 1746 | maximumLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1747 | |
| 1748 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1749 | BOOST_CHECK(deserializedNetwork); |
| 1750 | |
| 1751 | MaximumLayerVerifier verifier(layerName, {info, info}, {info}); |
| 1752 | deserializedNetwork->Accept(verifier); |
| 1753 | } |
| 1754 | |
| 1755 | BOOST_AUTO_TEST_CASE(SerializeMean) |
| 1756 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1757 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(Mean) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1758 | |
| 1759 | const std::string layerName("mean"); |
| 1760 | const armnn::TensorInfo inputInfo({1, 1, 3, 2}, armnn::DataType::Float32); |
| 1761 | const armnn::TensorInfo outputInfo({1, 1, 1, 2}, armnn::DataType::Float32); |
| 1762 | |
| 1763 | armnn::MeanDescriptor descriptor; |
| 1764 | descriptor.m_Axis = { 2 }; |
| 1765 | descriptor.m_KeepDims = true; |
| 1766 | |
| 1767 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1768 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 1769 | armnn::IConnectableLayer* const meanLayer = network->AddMeanLayer(descriptor, layerName.c_str()); |
| 1770 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1771 | |
| 1772 | inputLayer->GetOutputSlot(0).Connect(meanLayer->GetInputSlot(0)); |
| 1773 | meanLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1774 | |
| 1775 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1776 | meanLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 1777 | |
| 1778 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1779 | BOOST_CHECK(deserializedNetwork); |
| 1780 | |
| 1781 | MeanLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor); |
| 1782 | deserializedNetwork->Accept(verifier); |
| 1783 | } |
| 1784 | |
Nattapat Chaimanowong | 1f88630 | 2019-04-05 13:37:19 +0100 | [diff] [blame] | 1785 | BOOST_AUTO_TEST_CASE(SerializeMerge) |
| 1786 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1787 | DECLARE_LAYER_VERIFIER_CLASS(Merge) |
Nattapat Chaimanowong | 1f88630 | 2019-04-05 13:37:19 +0100 | [diff] [blame] | 1788 | |
| 1789 | const std::string layerName("merge"); |
| 1790 | const armnn::TensorInfo info({ 1, 2, 2, 3 }, armnn::DataType::Float32); |
| 1791 | |
| 1792 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1793 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 1794 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 1795 | armnn::IConnectableLayer* const mergeLayer = network->AddMergeLayer(layerName.c_str()); |
| 1796 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1797 | |
| 1798 | inputLayer0->GetOutputSlot(0).Connect(mergeLayer->GetInputSlot(0)); |
| 1799 | inputLayer1->GetOutputSlot(0).Connect(mergeLayer->GetInputSlot(1)); |
| 1800 | mergeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1801 | |
| 1802 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 1803 | inputLayer1->GetOutputSlot(0).SetTensorInfo(info); |
| 1804 | mergeLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 1805 | |
| 1806 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 1807 | BOOST_CHECK(deserializedNetwork); |
| 1808 | |
| 1809 | MergeLayerVerifier verifier(layerName, {info, info}, {info}); |
| 1810 | deserializedNetwork->Accept(verifier); |
| 1811 | } |
| 1812 | |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1813 | class MergerLayerVerifier : public LayerVerifierBaseWithDescriptor<armnn::OriginsDescriptor> |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1814 | { |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1815 | public: |
| 1816 | MergerLayerVerifier(const std::string& layerName, |
| 1817 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 1818 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 1819 | const armnn::OriginsDescriptor& descriptor) |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1820 | : LayerVerifierBaseWithDescriptor<armnn::OriginsDescriptor>(layerName, inputInfos, outputInfos, descriptor) {} |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1821 | |
Derek Lamberti | 859f9ce | 2019-12-10 22:05:21 +0000 | [diff] [blame] | 1822 | void VisitMergerLayer(const armnn::IConnectableLayer*, |
| 1823 | const armnn::OriginsDescriptor&, |
| 1824 | const char*) override |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1825 | { |
Jim Flynn | e242f2d | 2019-05-22 14:24:13 +0100 | [diff] [blame] | 1826 | throw armnn::Exception("MergerLayer should have translated to ConcatLayer"); |
| 1827 | } |
| 1828 | |
| 1829 | void VisitConcatLayer(const armnn::IConnectableLayer* layer, |
| 1830 | const armnn::OriginsDescriptor& descriptor, |
| 1831 | const char* name) override |
| 1832 | { |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1833 | VerifyNameAndConnections(layer, name); |
| 1834 | VerifyDescriptor(descriptor); |
| 1835 | } |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1836 | }; |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1837 | |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1838 | // NOTE: Until the deprecated AddMergerLayer disappears this test checks that calling |
Jim Flynn | e242f2d | 2019-05-22 14:24:13 +0100 | [diff] [blame] | 1839 | // AddMergerLayer places a ConcatLayer into the serialized format and that |
| 1840 | // when this deserialises we have a ConcatLayer |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1841 | BOOST_AUTO_TEST_CASE(SerializeMerger) |
| 1842 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1843 | const std::string layerName("merger"); |
| 1844 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({2, 3, 2, 2}, armnn::DataType::Float32); |
| 1845 | const armnn::TensorInfo outputInfo = armnn::TensorInfo({4, 3, 2, 2}, armnn::DataType::Float32); |
| 1846 | |
| 1847 | const std::vector<armnn::TensorShape> shapes({inputInfo.GetShape(), inputInfo.GetShape()}); |
| 1848 | |
| 1849 | armnn::OriginsDescriptor descriptor = |
Jim Flynn | 825af45 | 2019-05-20 12:49:28 +0100 | [diff] [blame] | 1850 | armnn::CreateDescriptorForConcatenation(shapes.begin(), shapes.end(), 0); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1851 | |
| 1852 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1853 | armnn::IConnectableLayer* const inputLayerOne = network->AddInputLayer(0); |
| 1854 | armnn::IConnectableLayer* const inputLayerTwo = network->AddInputLayer(1); |
Jim Flynn | 906f946 | 2019-05-10 13:55:21 +0100 | [diff] [blame] | 1855 | ARMNN_NO_DEPRECATE_WARN_BEGIN |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1856 | armnn::IConnectableLayer* const mergerLayer = network->AddMergerLayer(descriptor, layerName.c_str()); |
Jim Flynn | 906f946 | 2019-05-10 13:55:21 +0100 | [diff] [blame] | 1857 | ARMNN_NO_DEPRECATE_WARN_END |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1858 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1859 | |
| 1860 | inputLayerOne->GetOutputSlot(0).Connect(mergerLayer->GetInputSlot(0)); |
| 1861 | inputLayerTwo->GetOutputSlot(0).Connect(mergerLayer->GetInputSlot(1)); |
| 1862 | mergerLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1863 | |
| 1864 | inputLayerOne->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1865 | inputLayerTwo->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1866 | mergerLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 1867 | |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1868 | std::string mergerLayerNetwork = SerializeNetwork(*network); |
| 1869 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(mergerLayerNetwork); |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1870 | BOOST_CHECK(deserializedNetwork); |
| 1871 | |
| 1872 | MergerLayerVerifier verifier(layerName, {inputInfo, inputInfo}, {outputInfo}, descriptor); |
| 1873 | deserializedNetwork->Accept(verifier); |
| 1874 | } |
| 1875 | |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1876 | BOOST_AUTO_TEST_CASE(EnsureMergerLayerBackwardCompatibility) |
| 1877 | { |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 1878 | // The hex data below is a flat buffer containing a simple network with two inputs |
Jim Flynn | e242f2d | 2019-05-22 14:24:13 +0100 | [diff] [blame] | 1879 | // a merger layer (now deprecated) and an output layer with dimensions as per the tensor infos below. |
| 1880 | // |
| 1881 | // This test verifies that we can still read back these old style |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1882 | // models replacing the MergerLayers with ConcatLayers with the same parameters. |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 1883 | const std::vector<uint8_t> mergerModel = |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1884 | { |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 1885 | 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00, |
| 1886 | 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, |
| 1887 | 0x38, 0x02, 0x00, 0x00, 0x8C, 0x01, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x02, 0x00, |
| 1888 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, |
| 1889 | 0xF4, 0xFD, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B, 0x04, 0x00, 0x00, 0x00, 0x92, 0xFE, 0xFF, 0xFF, 0x04, 0x00, |
| 1890 | 0x00, 0x00, 0x9A, 0xFE, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x7E, 0xFE, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, |
| 1891 | 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1892 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1893 | 0xF8, 0xFE, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x48, 0xFE, 0xFF, 0xFF, 0x00, 0x00, |
| 1894 | 0x00, 0x1F, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, |
| 1895 | 0x68, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, |
| 1896 | 0x0C, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, |
| 1897 | 0x02, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x22, 0xFF, 0xFF, 0xFF, 0x04, 0x00, |
| 1898 | 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1899 | 0x00, 0x00, 0x00, 0x00, 0x3E, 0xFF, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1900 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x36, 0xFF, 0xFF, 0xFF, |
| 1901 | 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x1E, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x1C, 0x00, |
| 1902 | 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x6D, 0x65, 0x72, 0x67, 0x65, 0x72, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, |
| 1903 | 0x5C, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x34, 0xFF, |
| 1904 | 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x92, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, |
| 1905 | 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x02, 0x00, |
| 1906 | 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x08, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, |
| 1907 | 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x00, 0x00, |
| 1908 | 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0E, 0x00, |
| 1909 | 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1910 | 0x06, 0x00, 0x08, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0E, 0x00, |
| 1911 | 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1912 | 0x0E, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x14, 0x00, 0x0E, 0x00, 0x00, 0x00, |
| 1913 | 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, |
| 1914 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, |
| 1915 | 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, |
| 1916 | 0x00, 0x00, 0x66, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1917 | 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, |
| 1918 | 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, |
| 1919 | 0x04, 0x00, 0x00, 0x00, 0xF6, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x0A, 0x00, |
| 1920 | 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x14, 0x00, 0x00, 0x00, |
| 1921 | 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x0E, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, |
| 1922 | 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1923 | 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0A, 0x00, 0x00, 0x00, |
| 1924 | 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x08, 0x00, |
| 1925 | 0x07, 0x00, 0x0C, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 1926 | 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, |
| 1927 | 0x02, 0x00, 0x00, 0x00 |
| 1928 | }; |
| 1929 | |
| 1930 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(std::string(mergerModel.begin(), mergerModel.end())); |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1931 | BOOST_CHECK(deserializedNetwork); |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 1932 | |
| 1933 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({ 2, 3, 2, 2 }, armnn::DataType::Float32); |
| 1934 | const armnn::TensorInfo outputInfo = armnn::TensorInfo({ 4, 3, 2, 2 }, armnn::DataType::Float32); |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1935 | |
| 1936 | const std::vector<armnn::TensorShape> shapes({inputInfo.GetShape(), inputInfo.GetShape()}); |
| 1937 | |
| 1938 | armnn::OriginsDescriptor descriptor = |
Jim Flynn | 825af45 | 2019-05-20 12:49:28 +0100 | [diff] [blame] | 1939 | armnn::CreateDescriptorForConcatenation(shapes.begin(), shapes.end(), 0); |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1940 | |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 1941 | MergerLayerVerifier verifier("merger", { inputInfo, inputInfo }, { outputInfo }, descriptor); |
Jim Flynn | 5fa8393 | 2019-05-09 15:35:43 +0100 | [diff] [blame] | 1942 | deserializedNetwork->Accept(verifier); |
| 1943 | } |
| 1944 | |
Jim Flynn | e242f2d | 2019-05-22 14:24:13 +0100 | [diff] [blame] | 1945 | BOOST_AUTO_TEST_CASE(SerializeConcat) |
| 1946 | { |
| 1947 | const std::string layerName("concat"); |
| 1948 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({2, 3, 2, 2}, armnn::DataType::Float32); |
| 1949 | const armnn::TensorInfo outputInfo = armnn::TensorInfo({4, 3, 2, 2}, armnn::DataType::Float32); |
| 1950 | |
| 1951 | const std::vector<armnn::TensorShape> shapes({inputInfo.GetShape(), inputInfo.GetShape()}); |
| 1952 | |
| 1953 | armnn::OriginsDescriptor descriptor = |
| 1954 | armnn::CreateDescriptorForConcatenation(shapes.begin(), shapes.end(), 0); |
| 1955 | |
| 1956 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1957 | armnn::IConnectableLayer* const inputLayerOne = network->AddInputLayer(0); |
| 1958 | armnn::IConnectableLayer* const inputLayerTwo = network->AddInputLayer(1); |
| 1959 | armnn::IConnectableLayer* const concatLayer = network->AddConcatLayer(descriptor, layerName.c_str()); |
| 1960 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1961 | |
| 1962 | inputLayerOne->GetOutputSlot(0).Connect(concatLayer->GetInputSlot(0)); |
| 1963 | inputLayerTwo->GetOutputSlot(0).Connect(concatLayer->GetInputSlot(1)); |
| 1964 | concatLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1965 | |
| 1966 | inputLayerOne->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1967 | inputLayerTwo->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 1968 | concatLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 1969 | |
| 1970 | std::string concatLayerNetwork = SerializeNetwork(*network); |
| 1971 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(concatLayerNetwork); |
| 1972 | BOOST_CHECK(deserializedNetwork); |
| 1973 | |
| 1974 | // NOTE: using the MergerLayerVerifier to ensure that it is a concat layer and not a |
| 1975 | // merger layer that gets placed into the graph. |
| 1976 | MergerLayerVerifier verifier(layerName, {inputInfo, inputInfo}, {outputInfo}, descriptor); |
| 1977 | deserializedNetwork->Accept(verifier); |
| 1978 | } |
| 1979 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1980 | BOOST_AUTO_TEST_CASE(SerializeMinimum) |
| 1981 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 1982 | DECLARE_LAYER_VERIFIER_CLASS(Minimum) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 1983 | |
| 1984 | const std::string layerName("minimum"); |
| 1985 | const armnn::TensorInfo info({ 1, 2, 2, 3 }, armnn::DataType::Float32); |
| 1986 | |
| 1987 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 1988 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 1989 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 1990 | armnn::IConnectableLayer* const minimumLayer = network->AddMinimumLayer(layerName.c_str()); |
| 1991 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 1992 | |
| 1993 | inputLayer0->GetOutputSlot(0).Connect(minimumLayer->GetInputSlot(0)); |
| 1994 | inputLayer1->GetOutputSlot(0).Connect(minimumLayer->GetInputSlot(1)); |
| 1995 | minimumLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 1996 | |
| 1997 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 1998 | inputLayer1->GetOutputSlot(0).SetTensorInfo(info); |
| 1999 | minimumLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2000 | |
| 2001 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2002 | BOOST_CHECK(deserializedNetwork); |
| 2003 | |
| 2004 | MinimumLayerVerifier verifier(layerName, {info, info}, {info}); |
| 2005 | deserializedNetwork->Accept(verifier); |
| 2006 | } |
| 2007 | |
| 2008 | BOOST_AUTO_TEST_CASE(SerializeMultiplication) |
| 2009 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2010 | DECLARE_LAYER_VERIFIER_CLASS(Multiplication) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2011 | |
| 2012 | const std::string layerName("multiplication"); |
| 2013 | const armnn::TensorInfo info({ 1, 5, 2, 3 }, armnn::DataType::Float32); |
| 2014 | |
| 2015 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2016 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 2017 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 2018 | armnn::IConnectableLayer* const multiplicationLayer = network->AddMultiplicationLayer(layerName.c_str()); |
| 2019 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2020 | |
| 2021 | inputLayer0->GetOutputSlot(0).Connect(multiplicationLayer->GetInputSlot(0)); |
| 2022 | inputLayer1->GetOutputSlot(0).Connect(multiplicationLayer->GetInputSlot(1)); |
| 2023 | multiplicationLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2024 | |
| 2025 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 2026 | inputLayer1->GetOutputSlot(0).SetTensorInfo(info); |
| 2027 | multiplicationLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2028 | |
| 2029 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2030 | BOOST_CHECK(deserializedNetwork); |
| 2031 | |
| 2032 | MultiplicationLayerVerifier verifier(layerName, {info, info}, {info}); |
| 2033 | deserializedNetwork->Accept(verifier); |
| 2034 | } |
| 2035 | |
Ellen Norris-Thompson | 5198247 | 2019-06-19 11:46:21 +0100 | [diff] [blame] | 2036 | BOOST_AUTO_TEST_CASE(SerializePrelu) |
| 2037 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2038 | DECLARE_LAYER_VERIFIER_CLASS(Prelu) |
Ellen Norris-Thompson | 5198247 | 2019-06-19 11:46:21 +0100 | [diff] [blame] | 2039 | |
| 2040 | const std::string layerName("prelu"); |
| 2041 | |
| 2042 | armnn::TensorInfo inputTensorInfo ({ 4, 1, 2 }, armnn::DataType::Float32); |
| 2043 | armnn::TensorInfo alphaTensorInfo ({ 5, 4, 3, 1 }, armnn::DataType::Float32); |
| 2044 | armnn::TensorInfo outputTensorInfo({ 5, 4, 3, 2 }, armnn::DataType::Float32); |
| 2045 | |
| 2046 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2047 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2048 | armnn::IConnectableLayer* const alphaLayer = network->AddInputLayer(1); |
| 2049 | armnn::IConnectableLayer* const preluLayer = network->AddPreluLayer(layerName.c_str()); |
| 2050 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2051 | |
| 2052 | inputLayer->GetOutputSlot(0).Connect(preluLayer->GetInputSlot(0)); |
| 2053 | alphaLayer->GetOutputSlot(0).Connect(preluLayer->GetInputSlot(1)); |
| 2054 | preluLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2055 | |
| 2056 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 2057 | alphaLayer->GetOutputSlot(0).SetTensorInfo(alphaTensorInfo); |
| 2058 | preluLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| 2059 | |
| 2060 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2061 | BOOST_CHECK(deserializedNetwork); |
| 2062 | |
| 2063 | PreluLayerVerifier verifier(layerName, {inputTensorInfo, alphaTensorInfo}, {outputTensorInfo}); |
| 2064 | deserializedNetwork->Accept(verifier); |
| 2065 | } |
| 2066 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2067 | BOOST_AUTO_TEST_CASE(SerializeNormalization) |
| 2068 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2069 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(Normalization) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2070 | |
| 2071 | const std::string layerName("normalization"); |
| 2072 | const armnn::TensorInfo info({2, 1, 2, 2}, armnn::DataType::Float32); |
| 2073 | |
| 2074 | armnn::NormalizationDescriptor desc; |
| 2075 | desc.m_DataLayout = armnn::DataLayout::NCHW; |
| 2076 | desc.m_NormSize = 3; |
| 2077 | desc.m_Alpha = 1; |
| 2078 | desc.m_Beta = 1; |
| 2079 | desc.m_K = 1; |
| 2080 | |
| 2081 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2082 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2083 | armnn::IConnectableLayer* const normalizationLayer = network->AddNormalizationLayer(desc, layerName.c_str()); |
| 2084 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2085 | |
| 2086 | inputLayer->GetOutputSlot(0).Connect(normalizationLayer->GetInputSlot(0)); |
| 2087 | normalizationLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2088 | |
| 2089 | inputLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2090 | normalizationLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2091 | |
| 2092 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2093 | BOOST_CHECK(deserializedNetwork); |
| 2094 | |
| 2095 | NormalizationLayerVerifier verifier(layerName, {info}, {info}, desc); |
| 2096 | deserializedNetwork->Accept(verifier); |
| 2097 | } |
| 2098 | |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2099 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(Pad) |
Jim Flynn | 965c7c6 | 2019-06-24 14:32:41 +0100 | [diff] [blame] | 2100 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2101 | BOOST_AUTO_TEST_CASE(SerializePad) |
| 2102 | { |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2103 | const std::string layerName("pad"); |
| 2104 | const armnn::TensorInfo inputTensorInfo = armnn::TensorInfo({1, 2, 3, 4}, armnn::DataType::Float32); |
| 2105 | const armnn::TensorInfo outputTensorInfo = armnn::TensorInfo({1, 3, 5, 7}, armnn::DataType::Float32); |
| 2106 | |
| 2107 | armnn::PadDescriptor desc({{0, 0}, {1, 0}, {1, 1}, {1, 2}}); |
| 2108 | |
| 2109 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2110 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2111 | armnn::IConnectableLayer* const padLayer = network->AddPadLayer(desc, layerName.c_str()); |
| 2112 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2113 | |
| 2114 | inputLayer->GetOutputSlot(0).Connect(padLayer->GetInputSlot(0)); |
| 2115 | padLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2116 | |
| 2117 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 2118 | padLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| 2119 | |
| 2120 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2121 | BOOST_CHECK(deserializedNetwork); |
| 2122 | |
| 2123 | PadLayerVerifier verifier(layerName, {inputTensorInfo}, {outputTensorInfo}, desc); |
| 2124 | deserializedNetwork->Accept(verifier); |
| 2125 | } |
| 2126 | |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 2127 | BOOST_AUTO_TEST_CASE(EnsurePadBackwardCompatibility) |
Jim Flynn | 965c7c6 | 2019-06-24 14:32:41 +0100 | [diff] [blame] | 2128 | { |
| 2129 | // The PadDescriptor is being extended with a float PadValue (so a value other than 0 |
| 2130 | // can be used to pad the tensor. |
| 2131 | // |
| 2132 | // This test contains a binary representation of a simple input->pad->output network |
| 2133 | // prior to this change to test that the descriptor has been updated in a backward |
| 2134 | // compatible way with respect to Deserialization of older binary dumps |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 2135 | const std::vector<uint8_t> padModel = |
Jim Flynn | 965c7c6 | 2019-06-24 14:32:41 +0100 | [diff] [blame] | 2136 | { |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 2137 | 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00, |
| 2138 | 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, |
| 2139 | 0x54, 0x01, 0x00, 0x00, 0x6C, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 2140 | 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0xD0, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B, |
| 2141 | 0x04, 0x00, 0x00, 0x00, 0x96, 0xFF, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x9E, 0xFF, 0xFF, 0xFF, 0x04, 0x00, |
| 2142 | 0x00, 0x00, 0x72, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, |
| 2143 | 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, |
| 2144 | 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x2C, 0xFF, 0xFF, 0xFF, 0x01, 0x00, 0x00, 0x00, |
| 2145 | 0x00, 0x00, 0x00, 0x00, 0x24, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x16, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, |
| 2146 | 0x0E, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x4C, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, |
| 2147 | 0x00, 0x00, 0x06, 0x00, 0x08, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x08, 0x00, |
| 2148 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 2149 | 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 2150 | 0x0E, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x14, 0x00, 0x0E, 0x00, 0x00, 0x00, |
| 2151 | 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, |
| 2152 | 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x70, 0x61, 0x64, 0x00, 0x01, 0x00, 0x00, 0x00, 0x48, 0x00, 0x00, 0x00, |
| 2153 | 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, |
| 2154 | 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x52, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, |
| 2155 | 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x05, 0x00, |
| 2156 | 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, |
| 2157 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, |
| 2158 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x04, 0x00, 0x00, 0x00, 0xF6, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, |
| 2159 | 0x00, 0x00, 0x06, 0x00, 0x0A, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 2160 | 0x0E, 0x00, 0x14, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x0E, 0x00, 0x00, 0x00, |
| 2161 | 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 2162 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, |
| 2163 | 0x08, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 2164 | 0x0A, 0x00, 0x10, 0x00, 0x08, 0x00, 0x07, 0x00, 0x0C, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, |
| 2165 | 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, |
| 2166 | 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x00 |
| 2167 | }; |
| 2168 | |
| 2169 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(std::string(padModel.begin(), padModel.end())); |
Jim Flynn | 965c7c6 | 2019-06-24 14:32:41 +0100 | [diff] [blame] | 2170 | BOOST_CHECK(deserializedNetwork); |
| 2171 | |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 2172 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({ 1, 2, 3, 4 }, armnn::DataType::Float32); |
| 2173 | const armnn::TensorInfo outputInfo = armnn::TensorInfo({ 1, 3, 5, 7 }, armnn::DataType::Float32); |
Jim Flynn | 965c7c6 | 2019-06-24 14:32:41 +0100 | [diff] [blame] | 2174 | |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 2175 | armnn::PadDescriptor descriptor({{ 0, 0 }, { 1, 0 }, { 1, 1 }, { 1, 2 }}); |
Jim Flynn | 965c7c6 | 2019-06-24 14:32:41 +0100 | [diff] [blame] | 2176 | |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 2177 | PadLayerVerifier verifier("pad", { inputInfo }, { outputInfo }, descriptor); |
Jim Flynn | 965c7c6 | 2019-06-24 14:32:41 +0100 | [diff] [blame] | 2178 | deserializedNetwork->Accept(verifier); |
| 2179 | } |
| 2180 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2181 | BOOST_AUTO_TEST_CASE(SerializePermute) |
| 2182 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2183 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(Permute) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2184 | |
| 2185 | const std::string layerName("permute"); |
| 2186 | const armnn::TensorInfo inputTensorInfo({4, 3, 2, 1}, armnn::DataType::Float32); |
| 2187 | const armnn::TensorInfo outputTensorInfo({1, 2, 3, 4}, armnn::DataType::Float32); |
| 2188 | |
| 2189 | armnn::PermuteDescriptor descriptor(armnn::PermutationVector({3, 2, 1, 0})); |
| 2190 | |
| 2191 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2192 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2193 | armnn::IConnectableLayer* const permuteLayer = network->AddPermuteLayer(descriptor, layerName.c_str()); |
| 2194 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2195 | |
| 2196 | inputLayer->GetOutputSlot(0).Connect(permuteLayer->GetInputSlot(0)); |
| 2197 | permuteLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2198 | |
| 2199 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 2200 | permuteLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| 2201 | |
| 2202 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2203 | BOOST_CHECK(deserializedNetwork); |
| 2204 | |
| 2205 | PermuteLayerVerifier verifier(layerName, {inputTensorInfo}, {outputTensorInfo}, descriptor); |
| 2206 | deserializedNetwork->Accept(verifier); |
| 2207 | } |
| 2208 | |
| 2209 | BOOST_AUTO_TEST_CASE(SerializePooling2d) |
| 2210 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2211 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(Pooling2d) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2212 | |
| 2213 | const std::string layerName("pooling2d"); |
| 2214 | const armnn::TensorInfo inputInfo({1, 2, 2, 1}, armnn::DataType::Float32); |
| 2215 | const armnn::TensorInfo outputInfo({1, 1, 1, 1}, armnn::DataType::Float32); |
| 2216 | |
| 2217 | armnn::Pooling2dDescriptor desc; |
| 2218 | desc.m_DataLayout = armnn::DataLayout::NHWC; |
| 2219 | desc.m_PadTop = 0; |
| 2220 | desc.m_PadBottom = 0; |
| 2221 | desc.m_PadLeft = 0; |
| 2222 | desc.m_PadRight = 0; |
| 2223 | desc.m_PoolType = armnn::PoolingAlgorithm::Average; |
| 2224 | desc.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; |
| 2225 | desc.m_PaddingMethod = armnn::PaddingMethod::Exclude; |
| 2226 | desc.m_PoolHeight = 2; |
| 2227 | desc.m_PoolWidth = 2; |
| 2228 | desc.m_StrideX = 2; |
| 2229 | desc.m_StrideY = 2; |
| 2230 | |
| 2231 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2232 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2233 | armnn::IConnectableLayer* const pooling2dLayer = network->AddPooling2dLayer(desc, layerName.c_str()); |
| 2234 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2235 | |
| 2236 | inputLayer->GetOutputSlot(0).Connect(pooling2dLayer->GetInputSlot(0)); |
| 2237 | pooling2dLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2238 | |
| 2239 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2240 | pooling2dLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2241 | |
| 2242 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2243 | BOOST_CHECK(deserializedNetwork); |
| 2244 | |
| 2245 | Pooling2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc); |
| 2246 | deserializedNetwork->Accept(verifier); |
| 2247 | } |
| 2248 | |
Derek Lamberti | 87acb27 | 2019-03-27 16:51:31 +0000 | [diff] [blame] | 2249 | BOOST_AUTO_TEST_CASE(SerializeQuantize) |
| 2250 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2251 | DECLARE_LAYER_VERIFIER_CLASS(Quantize) |
Derek Lamberti | 87acb27 | 2019-03-27 16:51:31 +0000 | [diff] [blame] | 2252 | |
| 2253 | const std::string layerName("quantize"); |
| 2254 | const armnn::TensorInfo info({ 1, 2, 2, 3 }, armnn::DataType::Float32); |
| 2255 | |
| 2256 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2257 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2258 | armnn::IConnectableLayer* const quantizeLayer = network->AddQuantizeLayer(layerName.c_str()); |
| 2259 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2260 | |
| 2261 | inputLayer->GetOutputSlot(0).Connect(quantizeLayer->GetInputSlot(0)); |
| 2262 | quantizeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2263 | |
| 2264 | inputLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2265 | quantizeLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2266 | |
| 2267 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2268 | BOOST_CHECK(deserializedNetwork); |
| 2269 | |
| 2270 | QuantizeLayerVerifier verifier(layerName, {info}, {info}); |
| 2271 | deserializedNetwork->Accept(verifier); |
| 2272 | } |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2273 | |
Finn Williams | 2605b23 | 2020-06-10 15:53:46 +0100 | [diff] [blame] | 2274 | BOOST_AUTO_TEST_CASE(SerializeRank) |
| 2275 | { |
| 2276 | DECLARE_LAYER_VERIFIER_CLASS(Rank) |
| 2277 | |
| 2278 | const std::string layerName("rank"); |
| 2279 | const armnn::TensorInfo inputInfo({1, 9}, armnn::DataType::Float32); |
| 2280 | const armnn::TensorInfo outputInfo({1}, armnn::DataType::Signed32); |
| 2281 | |
| 2282 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2283 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2284 | armnn::IConnectableLayer* const rankLayer = network->AddRankLayer(layerName.c_str()); |
| 2285 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2286 | |
| 2287 | inputLayer->GetOutputSlot(0).Connect(rankLayer->GetInputSlot(0)); |
| 2288 | rankLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2289 | |
| 2290 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2291 | rankLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2292 | |
| 2293 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2294 | BOOST_CHECK(deserializedNetwork); |
| 2295 | |
| 2296 | RankLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}); |
| 2297 | deserializedNetwork->Accept(verifier); |
| 2298 | } |
| 2299 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2300 | BOOST_AUTO_TEST_CASE(SerializeReshape) |
| 2301 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2302 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(Reshape) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2303 | |
| 2304 | const std::string layerName("reshape"); |
| 2305 | const armnn::TensorInfo inputInfo({1, 9}, armnn::DataType::Float32); |
| 2306 | const armnn::TensorInfo outputInfo({3, 3}, armnn::DataType::Float32); |
| 2307 | |
| 2308 | armnn::ReshapeDescriptor descriptor({3, 3}); |
| 2309 | |
| 2310 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2311 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2312 | armnn::IConnectableLayer* const reshapeLayer = network->AddReshapeLayer(descriptor, layerName.c_str()); |
| 2313 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2314 | |
| 2315 | inputLayer->GetOutputSlot(0).Connect(reshapeLayer->GetInputSlot(0)); |
| 2316 | reshapeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2317 | |
| 2318 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2319 | reshapeLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2320 | |
| 2321 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2322 | BOOST_CHECK(deserializedNetwork); |
| 2323 | |
| 2324 | ReshapeLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor); |
| 2325 | deserializedNetwork->Accept(verifier); |
| 2326 | } |
| 2327 | |
FinnWilliamsArm | 6fb339a | 2019-06-28 15:07:10 +0100 | [diff] [blame] | 2328 | BOOST_AUTO_TEST_CASE(SerializeResize) |
| 2329 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2330 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(Resize) |
FinnWilliamsArm | 6fb339a | 2019-06-28 15:07:10 +0100 | [diff] [blame] | 2331 | |
| 2332 | const std::string layerName("resize"); |
Aron Virginas-Tar | fe414cf | 2019-10-31 14:35:58 +0000 | [diff] [blame] | 2333 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({1, 3, 5, 5}, armnn::DataType::Float32); |
FinnWilliamsArm | 6fb339a | 2019-06-28 15:07:10 +0100 | [diff] [blame] | 2334 | const armnn::TensorInfo outputInfo = armnn::TensorInfo({1, 3, 2, 4}, armnn::DataType::Float32); |
| 2335 | |
| 2336 | armnn::ResizeDescriptor desc; |
Aron Virginas-Tar | 169d2f1 | 2019-07-01 19:01:44 +0100 | [diff] [blame] | 2337 | desc.m_TargetWidth = 4; |
FinnWilliamsArm | 6fb339a | 2019-06-28 15:07:10 +0100 | [diff] [blame] | 2338 | desc.m_TargetHeight = 2; |
Aron Virginas-Tar | 169d2f1 | 2019-07-01 19:01:44 +0100 | [diff] [blame] | 2339 | desc.m_Method = armnn::ResizeMethod::NearestNeighbor; |
David Monahan | 4a0c9b9 | 2020-05-30 09:48:39 +0100 | [diff] [blame] | 2340 | desc.m_AlignCorners = true; |
| 2341 | desc.m_HalfPixelCenters = true; |
FinnWilliamsArm | 6fb339a | 2019-06-28 15:07:10 +0100 | [diff] [blame] | 2342 | |
| 2343 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2344 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2345 | armnn::IConnectableLayer* const resizeLayer = network->AddResizeLayer(desc, layerName.c_str()); |
| 2346 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2347 | |
| 2348 | inputLayer->GetOutputSlot(0).Connect(resizeLayer->GetInputSlot(0)); |
| 2349 | resizeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2350 | |
| 2351 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2352 | resizeLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2353 | |
| 2354 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2355 | BOOST_CHECK(deserializedNetwork); |
| 2356 | |
| 2357 | ResizeLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc); |
| 2358 | deserializedNetwork->Accept(verifier); |
| 2359 | } |
| 2360 | |
Aron Virginas-Tar | fe414cf | 2019-10-31 14:35:58 +0000 | [diff] [blame] | 2361 | class ResizeBilinearLayerVerifier : public LayerVerifierBaseWithDescriptor<armnn::ResizeBilinearDescriptor> |
| 2362 | { |
| 2363 | public: |
| 2364 | ResizeBilinearLayerVerifier(const std::string& layerName, |
| 2365 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2366 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 2367 | const armnn::ResizeBilinearDescriptor& descriptor) |
| 2368 | : LayerVerifierBaseWithDescriptor<armnn::ResizeBilinearDescriptor>( |
| 2369 | layerName, inputInfos, outputInfos, descriptor) {} |
| 2370 | |
| 2371 | void VisitResizeLayer(const armnn::IConnectableLayer* layer, |
| 2372 | const armnn::ResizeDescriptor& descriptor, |
| 2373 | const char* name) override |
| 2374 | { |
| 2375 | VerifyNameAndConnections(layer, name); |
| 2376 | |
David Monahan | 4a0c9b9 | 2020-05-30 09:48:39 +0100 | [diff] [blame] | 2377 | BOOST_CHECK(descriptor.m_Method == armnn::ResizeMethod::Bilinear); |
| 2378 | BOOST_CHECK(descriptor.m_TargetWidth == m_Descriptor.m_TargetWidth); |
| 2379 | BOOST_CHECK(descriptor.m_TargetHeight == m_Descriptor.m_TargetHeight); |
| 2380 | BOOST_CHECK(descriptor.m_DataLayout == m_Descriptor.m_DataLayout); |
| 2381 | BOOST_CHECK(descriptor.m_AlignCorners == m_Descriptor.m_AlignCorners); |
| 2382 | BOOST_CHECK(descriptor.m_HalfPixelCenters == m_Descriptor.m_HalfPixelCenters); |
Aron Virginas-Tar | fe414cf | 2019-10-31 14:35:58 +0000 | [diff] [blame] | 2383 | } |
| 2384 | |
| 2385 | void VisitResizeBilinearLayer(const armnn::IConnectableLayer*, |
| 2386 | const armnn::ResizeBilinearDescriptor&, |
| 2387 | const char*) override |
| 2388 | { |
| 2389 | throw armnn::Exception("ResizeBilinearLayer should have translated to ResizeLayer"); |
| 2390 | } |
| 2391 | }; |
| 2392 | |
| 2393 | // NOTE: Until the deprecated AddResizeBilinearLayer disappears this test checks that |
| 2394 | // calling AddResizeBilinearLayer places a ResizeLayer into the serialized format |
| 2395 | // and that when this deserialises we have a ResizeLayer |
| 2396 | BOOST_AUTO_TEST_CASE(SerializeResizeBilinear) |
| 2397 | { |
| 2398 | const std::string layerName("resizeBilinear"); |
| 2399 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({1, 3, 5, 5}, armnn::DataType::Float32); |
| 2400 | const armnn::TensorInfo outputInfo = armnn::TensorInfo({1, 3, 2, 4}, armnn::DataType::Float32); |
| 2401 | |
| 2402 | armnn::ResizeBilinearDescriptor desc; |
| 2403 | desc.m_TargetWidth = 4u; |
| 2404 | desc.m_TargetHeight = 2u; |
David Monahan | 4a0c9b9 | 2020-05-30 09:48:39 +0100 | [diff] [blame] | 2405 | desc.m_AlignCorners = true; |
| 2406 | desc.m_HalfPixelCenters = true; |
Aron Virginas-Tar | fe414cf | 2019-10-31 14:35:58 +0000 | [diff] [blame] | 2407 | |
| 2408 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2409 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2410 | ARMNN_NO_DEPRECATE_WARN_BEGIN |
| 2411 | armnn::IConnectableLayer* const resizeLayer = network->AddResizeBilinearLayer(desc, layerName.c_str()); |
| 2412 | ARMNN_NO_DEPRECATE_WARN_END |
| 2413 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2414 | |
| 2415 | inputLayer->GetOutputSlot(0).Connect(resizeLayer->GetInputSlot(0)); |
| 2416 | resizeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2417 | |
| 2418 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2419 | resizeLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2420 | |
| 2421 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2422 | BOOST_CHECK(deserializedNetwork); |
| 2423 | |
| 2424 | ResizeBilinearLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc); |
| 2425 | deserializedNetwork->Accept(verifier); |
| 2426 | } |
| 2427 | |
| 2428 | BOOST_AUTO_TEST_CASE(EnsureResizeBilinearBackwardCompatibility) |
| 2429 | { |
| 2430 | // The hex data below is a flat buffer containing a simple network with an input, |
| 2431 | // a ResizeBilinearLayer (now deprecated) and an output |
| 2432 | // |
| 2433 | // This test verifies that we can still deserialize this old-style model by replacing |
| 2434 | // the ResizeBilinearLayer with an equivalent ResizeLayer |
| 2435 | const std::vector<uint8_t> resizeBilinearModel = |
| 2436 | { |
| 2437 | 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00, |
| 2438 | 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, |
| 2439 | 0x50, 0x01, 0x00, 0x00, 0x74, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 2440 | 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0xD4, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B, |
| 2441 | 0x04, 0x00, 0x00, 0x00, 0xC2, 0xFE, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x08, 0x00, |
| 2442 | 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x8A, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00, |
| 2443 | 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 2444 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 2445 | 0x38, 0xFF, 0xFF, 0xFF, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x30, 0xFF, 0xFF, 0xFF, 0x00, 0x00, |
| 2446 | 0x00, 0x1A, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0E, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, |
| 2447 | 0x34, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x12, 0x00, 0x08, 0x00, 0x0C, 0x00, |
| 2448 | 0x07, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, |
| 2449 | 0x00, 0x00, 0x0E, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x14, 0x00, 0x0E, 0x00, |
| 2450 | 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x19, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00, |
| 2451 | 0x20, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x00, 0x00, 0x72, 0x65, 0x73, 0x69, 0x7A, 0x65, 0x42, 0x69, 0x6C, 0x69, |
| 2452 | 0x6E, 0x65, 0x61, 0x72, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x48, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, |
| 2453 | 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, |
| 2454 | 0x00, 0x00, 0x52, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 2455 | 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x04, 0x00, |
| 2456 | 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 2457 | 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 2458 | 0x00, 0x09, 0x04, 0x00, 0x00, 0x00, 0xF6, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, |
| 2459 | 0x0A, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x14, 0x00, |
| 2460 | 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x0E, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, |
| 2461 | 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 2462 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0A, 0x00, |
| 2463 | 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, |
| 2464 | 0x08, 0x00, 0x07, 0x00, 0x0C, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, |
| 2465 | 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x05, 0x00, |
| 2466 | 0x00, 0x00, 0x05, 0x00, 0x00, 0x00 |
| 2467 | }; |
| 2468 | |
| 2469 | armnn::INetworkPtr deserializedNetwork = |
| 2470 | DeserializeNetwork(std::string(resizeBilinearModel.begin(), resizeBilinearModel.end())); |
| 2471 | BOOST_CHECK(deserializedNetwork); |
| 2472 | |
| 2473 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({1, 3, 5, 5}, armnn::DataType::Float32); |
| 2474 | const armnn::TensorInfo outputInfo = armnn::TensorInfo({1, 3, 2, 4}, armnn::DataType::Float32); |
| 2475 | |
| 2476 | armnn::ResizeBilinearDescriptor descriptor; |
| 2477 | descriptor.m_TargetWidth = 4u; |
| 2478 | descriptor.m_TargetHeight = 2u; |
| 2479 | |
| 2480 | ResizeBilinearLayerVerifier verifier("resizeBilinear", { inputInfo }, { outputInfo }, descriptor); |
| 2481 | deserializedNetwork->Accept(verifier); |
| 2482 | } |
| 2483 | |
Aron Virginas-Tar | 2fda80b | 2019-09-18 13:36:52 +0100 | [diff] [blame] | 2484 | BOOST_AUTO_TEST_CASE(SerializeSlice) |
| 2485 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2486 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(Slice) |
Aron Virginas-Tar | 2fda80b | 2019-09-18 13:36:52 +0100 | [diff] [blame] | 2487 | |
| 2488 | const std::string layerName{"slice"}; |
| 2489 | |
| 2490 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({3, 2, 3, 1}, armnn::DataType::Float32); |
| 2491 | const armnn::TensorInfo outputInfo = armnn::TensorInfo({2, 2, 2, 1}, armnn::DataType::Float32); |
| 2492 | |
| 2493 | armnn::SliceDescriptor descriptor({ 0, 0, 1, 0}, {2, 2, 2, 1}); |
| 2494 | |
| 2495 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2496 | |
| 2497 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2498 | armnn::IConnectableLayer* const sliceLayer = network->AddSliceLayer(descriptor, layerName.c_str()); |
| 2499 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2500 | |
| 2501 | inputLayer->GetOutputSlot(0).Connect(sliceLayer->GetInputSlot(0)); |
| 2502 | sliceLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2503 | |
| 2504 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2505 | sliceLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2506 | |
| 2507 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2508 | BOOST_CHECK(deserializedNetwork); |
| 2509 | |
| 2510 | SliceLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor); |
| 2511 | deserializedNetwork->Accept(verifier); |
| 2512 | } |
| 2513 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2514 | BOOST_AUTO_TEST_CASE(SerializeSoftmax) |
| 2515 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2516 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(Softmax) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2517 | |
| 2518 | const std::string layerName("softmax"); |
| 2519 | const armnn::TensorInfo info({1, 10}, armnn::DataType::Float32); |
| 2520 | |
| 2521 | armnn::SoftmaxDescriptor descriptor; |
| 2522 | descriptor.m_Beta = 1.0f; |
| 2523 | |
| 2524 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2525 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2526 | armnn::IConnectableLayer* const softmaxLayer = network->AddSoftmaxLayer(descriptor, layerName.c_str()); |
| 2527 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2528 | |
| 2529 | inputLayer->GetOutputSlot(0).Connect(softmaxLayer->GetInputSlot(0)); |
| 2530 | softmaxLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2531 | |
| 2532 | inputLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2533 | softmaxLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2534 | |
| 2535 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2536 | BOOST_CHECK(deserializedNetwork); |
| 2537 | |
| 2538 | SoftmaxLayerVerifier verifier(layerName, {info}, {info}, descriptor); |
| 2539 | deserializedNetwork->Accept(verifier); |
| 2540 | } |
| 2541 | |
| 2542 | BOOST_AUTO_TEST_CASE(SerializeSpaceToBatchNd) |
| 2543 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2544 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(SpaceToBatchNd) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2545 | |
| 2546 | const std::string layerName("spaceToBatchNd"); |
| 2547 | const armnn::TensorInfo inputInfo({2, 1, 2, 4}, armnn::DataType::Float32); |
| 2548 | const armnn::TensorInfo outputInfo({8, 1, 1, 3}, armnn::DataType::Float32); |
| 2549 | |
| 2550 | armnn::SpaceToBatchNdDescriptor desc; |
| 2551 | desc.m_DataLayout = armnn::DataLayout::NCHW; |
| 2552 | desc.m_BlockShape = {2, 2}; |
| 2553 | desc.m_PadList = {{0, 0}, {2, 0}}; |
| 2554 | |
| 2555 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2556 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2557 | armnn::IConnectableLayer* const spaceToBatchNdLayer = network->AddSpaceToBatchNdLayer(desc, layerName.c_str()); |
| 2558 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2559 | |
| 2560 | inputLayer->GetOutputSlot(0).Connect(spaceToBatchNdLayer->GetInputSlot(0)); |
| 2561 | spaceToBatchNdLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2562 | |
| 2563 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2564 | spaceToBatchNdLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2565 | |
| 2566 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2567 | BOOST_CHECK(deserializedNetwork); |
| 2568 | |
| 2569 | SpaceToBatchNdLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc); |
| 2570 | deserializedNetwork->Accept(verifier); |
| 2571 | } |
| 2572 | |
Aron Virginas-Tar | aa06714 | 2019-06-11 16:01:44 +0100 | [diff] [blame] | 2573 | BOOST_AUTO_TEST_CASE(SerializeSpaceToDepth) |
| 2574 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2575 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(SpaceToDepth) |
Aron Virginas-Tar | aa06714 | 2019-06-11 16:01:44 +0100 | [diff] [blame] | 2576 | |
| 2577 | const std::string layerName("spaceToDepth"); |
| 2578 | |
| 2579 | const armnn::TensorInfo inputInfo ({ 1, 16, 8, 3 }, armnn::DataType::Float32); |
| 2580 | const armnn::TensorInfo outputInfo({ 1, 8, 4, 12 }, armnn::DataType::Float32); |
| 2581 | |
| 2582 | armnn::SpaceToDepthDescriptor desc; |
| 2583 | desc.m_BlockSize = 2; |
| 2584 | desc.m_DataLayout = armnn::DataLayout::NHWC; |
| 2585 | |
| 2586 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2587 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2588 | armnn::IConnectableLayer* const spaceToDepthLayer = network->AddSpaceToDepthLayer(desc, layerName.c_str()); |
| 2589 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2590 | |
| 2591 | inputLayer->GetOutputSlot(0).Connect(spaceToDepthLayer->GetInputSlot(0)); |
| 2592 | spaceToDepthLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2593 | |
| 2594 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2595 | spaceToDepthLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2596 | |
| 2597 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2598 | BOOST_CHECK(deserializedNetwork); |
| 2599 | |
| 2600 | SpaceToDepthLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc); |
| 2601 | deserializedNetwork->Accept(verifier); |
| 2602 | } |
| 2603 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2604 | BOOST_AUTO_TEST_CASE(SerializeSplitter) |
| 2605 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2606 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(Splitter) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2607 | |
| 2608 | const unsigned int numViews = 3; |
| 2609 | const unsigned int numDimensions = 4; |
| 2610 | const unsigned int inputShape[] = {1, 18, 4, 4}; |
| 2611 | const unsigned int outputShape[] = {1, 6, 4, 4}; |
| 2612 | |
| 2613 | // This is modelled on how the caffe parser sets up a splitter layer to partition an input along dimension one. |
| 2614 | unsigned int splitterDimSizes[4] = {static_cast<unsigned int>(inputShape[0]), |
| 2615 | static_cast<unsigned int>(inputShape[1]), |
| 2616 | static_cast<unsigned int>(inputShape[2]), |
| 2617 | static_cast<unsigned int>(inputShape[3])}; |
| 2618 | splitterDimSizes[1] /= numViews; |
| 2619 | armnn::ViewsDescriptor desc(numViews, numDimensions); |
| 2620 | |
| 2621 | for (unsigned int g = 0; g < numViews; ++g) |
| 2622 | { |
| 2623 | desc.SetViewOriginCoord(g, 1, splitterDimSizes[1] * g); |
| 2624 | |
| 2625 | for (unsigned int dimIdx=0; dimIdx < 4; dimIdx++) |
| 2626 | { |
| 2627 | desc.SetViewSize(g, dimIdx, splitterDimSizes[dimIdx]); |
| 2628 | } |
| 2629 | } |
| 2630 | |
| 2631 | const std::string layerName("splitter"); |
| 2632 | const armnn::TensorInfo inputInfo(numDimensions, inputShape, armnn::DataType::Float32); |
| 2633 | const armnn::TensorInfo outputInfo(numDimensions, outputShape, armnn::DataType::Float32); |
| 2634 | |
| 2635 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2636 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2637 | armnn::IConnectableLayer* const splitterLayer = network->AddSplitterLayer(desc, layerName.c_str()); |
| 2638 | armnn::IConnectableLayer* const outputLayer0 = network->AddOutputLayer(0); |
| 2639 | armnn::IConnectableLayer* const outputLayer1 = network->AddOutputLayer(1); |
| 2640 | armnn::IConnectableLayer* const outputLayer2 = network->AddOutputLayer(2); |
| 2641 | |
| 2642 | inputLayer->GetOutputSlot(0).Connect(splitterLayer->GetInputSlot(0)); |
| 2643 | splitterLayer->GetOutputSlot(0).Connect(outputLayer0->GetInputSlot(0)); |
| 2644 | splitterLayer->GetOutputSlot(1).Connect(outputLayer1->GetInputSlot(0)); |
| 2645 | splitterLayer->GetOutputSlot(2).Connect(outputLayer2->GetInputSlot(0)); |
| 2646 | |
| 2647 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2648 | splitterLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2649 | splitterLayer->GetOutputSlot(1).SetTensorInfo(outputInfo); |
| 2650 | splitterLayer->GetOutputSlot(2).SetTensorInfo(outputInfo); |
| 2651 | |
| 2652 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2653 | BOOST_CHECK(deserializedNetwork); |
| 2654 | |
| 2655 | SplitterLayerVerifier verifier(layerName, {inputInfo}, {outputInfo, outputInfo, outputInfo}, desc); |
| 2656 | deserializedNetwork->Accept(verifier); |
| 2657 | } |
| 2658 | |
Matthew Jackson | b5433ee | 2019-07-11 15:54:20 +0100 | [diff] [blame] | 2659 | BOOST_AUTO_TEST_CASE(SerializeStack) |
| 2660 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2661 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(Stack) |
Matthew Jackson | b5433ee | 2019-07-11 15:54:20 +0100 | [diff] [blame] | 2662 | |
| 2663 | const std::string layerName("stack"); |
| 2664 | |
| 2665 | armnn::TensorInfo inputTensorInfo ({4, 3, 5}, armnn::DataType::Float32); |
| 2666 | armnn::TensorInfo outputTensorInfo({4, 3, 2, 5}, armnn::DataType::Float32); |
| 2667 | |
| 2668 | armnn::StackDescriptor descriptor(2, 2, {4, 3, 5}); |
| 2669 | |
| 2670 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2671 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(0); |
| 2672 | armnn::IConnectableLayer* const inputLayer2 = network->AddInputLayer(1); |
| 2673 | armnn::IConnectableLayer* const stackLayer = network->AddStackLayer(descriptor, layerName.c_str()); |
| 2674 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2675 | |
| 2676 | inputLayer1->GetOutputSlot(0).Connect(stackLayer->GetInputSlot(0)); |
| 2677 | inputLayer2->GetOutputSlot(0).Connect(stackLayer->GetInputSlot(1)); |
| 2678 | stackLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2679 | |
| 2680 | inputLayer1->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 2681 | inputLayer2->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 2682 | stackLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| 2683 | |
| 2684 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2685 | BOOST_CHECK(deserializedNetwork); |
| 2686 | |
| 2687 | StackLayerVerifier verifier(layerName, {inputTensorInfo, inputTensorInfo}, {outputTensorInfo}, descriptor); |
| 2688 | deserializedNetwork->Accept(verifier); |
| 2689 | } |
| 2690 | |
Aron Virginas-Tar | 85121a2 | 2019-10-23 10:41:35 +0100 | [diff] [blame] | 2691 | BOOST_AUTO_TEST_CASE(SerializeStandIn) |
| 2692 | { |
| 2693 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(StandIn) |
| 2694 | |
| 2695 | const std::string layerName("standIn"); |
| 2696 | |
| 2697 | armnn::TensorInfo tensorInfo({ 1u }, armnn::DataType::Float32); |
| 2698 | armnn::StandInDescriptor descriptor(2u, 2u); |
| 2699 | |
| 2700 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2701 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 2702 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 2703 | armnn::IConnectableLayer* const standInLayer = network->AddStandInLayer(descriptor, layerName.c_str()); |
| 2704 | armnn::IConnectableLayer* const outputLayer0 = network->AddOutputLayer(0); |
| 2705 | armnn::IConnectableLayer* const outputLayer1 = network->AddOutputLayer(1); |
| 2706 | |
| 2707 | inputLayer0->GetOutputSlot(0).Connect(standInLayer->GetInputSlot(0)); |
| 2708 | inputLayer0->GetOutputSlot(0).SetTensorInfo(tensorInfo); |
| 2709 | |
| 2710 | inputLayer1->GetOutputSlot(0).Connect(standInLayer->GetInputSlot(1)); |
| 2711 | inputLayer1->GetOutputSlot(0).SetTensorInfo(tensorInfo); |
| 2712 | |
| 2713 | standInLayer->GetOutputSlot(0).Connect(outputLayer0->GetInputSlot(0)); |
| 2714 | standInLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo); |
| 2715 | |
| 2716 | standInLayer->GetOutputSlot(1).Connect(outputLayer1->GetInputSlot(0)); |
| 2717 | standInLayer->GetOutputSlot(1).SetTensorInfo(tensorInfo); |
| 2718 | |
| 2719 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2720 | BOOST_CHECK(deserializedNetwork); |
| 2721 | |
| 2722 | StandInLayerVerifier verifier(layerName, { tensorInfo, tensorInfo }, { tensorInfo, tensorInfo }, descriptor); |
| 2723 | deserializedNetwork->Accept(verifier); |
| 2724 | } |
| 2725 | |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2726 | BOOST_AUTO_TEST_CASE(SerializeStridedSlice) |
| 2727 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2728 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(StridedSlice) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2729 | |
| 2730 | const std::string layerName("stridedSlice"); |
| 2731 | const armnn::TensorInfo inputInfo = armnn::TensorInfo({3, 2, 3, 1}, armnn::DataType::Float32); |
| 2732 | const armnn::TensorInfo outputInfo = armnn::TensorInfo({3, 1}, armnn::DataType::Float32); |
| 2733 | |
| 2734 | armnn::StridedSliceDescriptor desc({0, 0, 1, 0}, {1, 1, 1, 1}, {1, 1, 1, 1}); |
| 2735 | desc.m_EndMask = (1 << 4) - 1; |
| 2736 | desc.m_ShrinkAxisMask = (1 << 1) | (1 << 2); |
| 2737 | desc.m_DataLayout = armnn::DataLayout::NCHW; |
| 2738 | |
| 2739 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2740 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2741 | armnn::IConnectableLayer* const stridedSliceLayer = network->AddStridedSliceLayer(desc, layerName.c_str()); |
| 2742 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2743 | |
| 2744 | inputLayer->GetOutputSlot(0).Connect(stridedSliceLayer->GetInputSlot(0)); |
| 2745 | stridedSliceLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2746 | |
| 2747 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2748 | stridedSliceLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2749 | |
| 2750 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2751 | BOOST_CHECK(deserializedNetwork); |
| 2752 | |
| 2753 | StridedSliceLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc); |
| 2754 | deserializedNetwork->Accept(verifier); |
| 2755 | } |
| 2756 | |
| 2757 | BOOST_AUTO_TEST_CASE(SerializeSubtraction) |
| 2758 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2759 | DECLARE_LAYER_VERIFIER_CLASS(Subtraction) |
Nattapat Chaimanowong | 03acd68 | 2019-03-20 11:19:52 +0000 | [diff] [blame] | 2760 | |
| 2761 | const std::string layerName("subtraction"); |
| 2762 | const armnn::TensorInfo info({ 1, 4 }, armnn::DataType::Float32); |
| 2763 | |
| 2764 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2765 | armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0); |
| 2766 | armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1); |
| 2767 | armnn::IConnectableLayer* const subtractionLayer = network->AddSubtractionLayer(layerName.c_str()); |
| 2768 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2769 | |
| 2770 | inputLayer0->GetOutputSlot(0).Connect(subtractionLayer->GetInputSlot(0)); |
| 2771 | inputLayer1->GetOutputSlot(0).Connect(subtractionLayer->GetInputSlot(1)); |
| 2772 | subtractionLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2773 | |
| 2774 | inputLayer0->GetOutputSlot(0).SetTensorInfo(info); |
| 2775 | inputLayer1->GetOutputSlot(0).SetTensorInfo(info); |
| 2776 | subtractionLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2777 | |
| 2778 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2779 | BOOST_CHECK(deserializedNetwork); |
| 2780 | |
| 2781 | SubtractionLayerVerifier verifier(layerName, {info, info}, {info}); |
| 2782 | deserializedNetwork->Accept(verifier); |
Nattapat Chaimanowong | 3e14a9d | 2019-03-18 12:37:06 +0000 | [diff] [blame] | 2783 | } |
| 2784 | |
Sadik Armagan | eff363d | 2019-04-05 15:25:46 +0100 | [diff] [blame] | 2785 | BOOST_AUTO_TEST_CASE(SerializeSwitch) |
| 2786 | { |
| 2787 | class SwitchLayerVerifier : public LayerVerifierBase |
| 2788 | { |
| 2789 | public: |
| 2790 | SwitchLayerVerifier(const std::string& layerName, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2791 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2792 | const std::vector<armnn::TensorInfo>& outputInfos) |
Sadik Armagan | eff363d | 2019-04-05 15:25:46 +0100 | [diff] [blame] | 2793 | : LayerVerifierBase(layerName, inputInfos, outputInfos) {} |
| 2794 | |
| 2795 | void VisitSwitchLayer(const armnn::IConnectableLayer* layer, const char* name) override |
| 2796 | { |
| 2797 | VerifyNameAndConnections(layer, name); |
| 2798 | } |
| 2799 | |
Derek Lamberti | 859f9ce | 2019-12-10 22:05:21 +0000 | [diff] [blame] | 2800 | void VisitConstantLayer(const armnn::IConnectableLayer*, |
| 2801 | const armnn::ConstTensor&, |
| 2802 | const char*) override {} |
Sadik Armagan | eff363d | 2019-04-05 15:25:46 +0100 | [diff] [blame] | 2803 | }; |
| 2804 | |
| 2805 | const std::string layerName("switch"); |
| 2806 | const armnn::TensorInfo info({ 1, 4 }, armnn::DataType::Float32); |
| 2807 | |
| 2808 | std::vector<float> constantData = GenerateRandomData<float>(info.GetNumElements()); |
| 2809 | armnn::ConstTensor constTensor(info, constantData); |
| 2810 | |
| 2811 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2812 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2813 | armnn::IConnectableLayer* const constantLayer = network->AddConstantLayer(constTensor, "constant"); |
| 2814 | armnn::IConnectableLayer* const switchLayer = network->AddSwitchLayer(layerName.c_str()); |
| 2815 | armnn::IConnectableLayer* const trueOutputLayer = network->AddOutputLayer(0); |
| 2816 | armnn::IConnectableLayer* const falseOutputLayer = network->AddOutputLayer(1); |
| 2817 | |
| 2818 | inputLayer->GetOutputSlot(0).Connect(switchLayer->GetInputSlot(0)); |
| 2819 | constantLayer->GetOutputSlot(0).Connect(switchLayer->GetInputSlot(1)); |
| 2820 | switchLayer->GetOutputSlot(0).Connect(trueOutputLayer->GetInputSlot(0)); |
| 2821 | switchLayer->GetOutputSlot(1).Connect(falseOutputLayer->GetInputSlot(0)); |
| 2822 | |
| 2823 | inputLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2824 | constantLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2825 | switchLayer->GetOutputSlot(0).SetTensorInfo(info); |
| 2826 | switchLayer->GetOutputSlot(1).SetTensorInfo(info); |
| 2827 | |
| 2828 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2829 | BOOST_CHECK(deserializedNetwork); |
| 2830 | |
| 2831 | SwitchLayerVerifier verifier(layerName, {info, info}, {info, info}); |
| 2832 | deserializedNetwork->Accept(verifier); |
| 2833 | } |
| 2834 | |
Mike Kelly | c9ea45a | 2020-02-28 18:11:58 +0000 | [diff] [blame] | 2835 | BOOST_AUTO_TEST_CASE(SerializeTranspose) |
| 2836 | { |
| 2837 | DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(Transpose) |
| 2838 | |
| 2839 | const std::string layerName("transpose"); |
| 2840 | const armnn::TensorInfo inputTensorInfo({4, 3, 2, 1}, armnn::DataType::Float32); |
| 2841 | const armnn::TensorInfo outputTensorInfo({1, 2, 3, 4}, armnn::DataType::Float32); |
| 2842 | |
| 2843 | armnn::TransposeDescriptor descriptor(armnn::PermutationVector({3, 2, 1, 0})); |
| 2844 | |
| 2845 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2846 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2847 | armnn::IConnectableLayer* const transposeLayer = network->AddTransposeLayer(descriptor, layerName.c_str()); |
| 2848 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2849 | |
| 2850 | inputLayer->GetOutputSlot(0).Connect(transposeLayer->GetInputSlot(0)); |
| 2851 | transposeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2852 | |
| 2853 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 2854 | transposeLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); |
| 2855 | |
| 2856 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2857 | BOOST_CHECK(deserializedNetwork); |
| 2858 | |
| 2859 | TransposeLayerVerifier verifier(layerName, {inputTensorInfo}, {outputTensorInfo}, descriptor); |
| 2860 | deserializedNetwork->Accept(verifier); |
| 2861 | } |
| 2862 | |
Aron Virginas-Tar | cb54930 | 2019-06-21 13:53:38 +0100 | [diff] [blame] | 2863 | BOOST_AUTO_TEST_CASE(SerializeTransposeConvolution2d) |
| 2864 | { |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2865 | using Descriptor = armnn::TransposeConvolution2dDescriptor; |
| 2866 | class TransposeConvolution2dLayerVerifier : public LayerVerifierBaseWithDescriptor<Descriptor> |
Aron Virginas-Tar | cb54930 | 2019-06-21 13:53:38 +0100 | [diff] [blame] | 2867 | { |
| 2868 | public: |
| 2869 | TransposeConvolution2dLayerVerifier(const std::string& layerName, |
| 2870 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2871 | const std::vector<armnn::TensorInfo>& outputInfos, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2872 | const Descriptor& descriptor, |
Aron Virginas-Tar | cb54930 | 2019-06-21 13:53:38 +0100 | [diff] [blame] | 2873 | const armnn::ConstTensor& weights, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2874 | const armnn::Optional<armnn::ConstTensor>& biases) |
| 2875 | : LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor) |
| 2876 | , m_Weights(weights) |
| 2877 | , m_Biases(biases) |
Aron Virginas-Tar | cb54930 | 2019-06-21 13:53:38 +0100 | [diff] [blame] | 2878 | {} |
| 2879 | |
| 2880 | void VisitTransposeConvolution2dLayer(const armnn::IConnectableLayer* layer, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2881 | const Descriptor& descriptor, |
Aron Virginas-Tar | cb54930 | 2019-06-21 13:53:38 +0100 | [diff] [blame] | 2882 | const armnn::ConstTensor& weights, |
| 2883 | const armnn::Optional<armnn::ConstTensor>& biases, |
| 2884 | const char* name) override |
| 2885 | { |
| 2886 | VerifyNameAndConnections(layer, name); |
| 2887 | VerifyDescriptor(descriptor); |
| 2888 | |
| 2889 | // check weights |
| 2890 | CompareConstTensor(weights, m_Weights); |
| 2891 | |
| 2892 | // check biases |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 2893 | BOOST_CHECK(biases.has_value() == descriptor.m_BiasEnabled); |
Aron Virginas-Tar | cb54930 | 2019-06-21 13:53:38 +0100 | [diff] [blame] | 2894 | BOOST_CHECK(biases.has_value() == m_Biases.has_value()); |
| 2895 | |
| 2896 | if (biases.has_value() && m_Biases.has_value()) |
| 2897 | { |
| 2898 | CompareConstTensor(biases.value(), m_Biases.value()); |
| 2899 | } |
| 2900 | } |
| 2901 | |
| 2902 | private: |
Aron Virginas-Tar | cb54930 | 2019-06-21 13:53:38 +0100 | [diff] [blame] | 2903 | armnn::ConstTensor m_Weights; |
| 2904 | armnn::Optional<armnn::ConstTensor> m_Biases; |
| 2905 | }; |
| 2906 | |
| 2907 | const std::string layerName("transposeConvolution2d"); |
| 2908 | const armnn::TensorInfo inputInfo ({ 1, 7, 7, 1 }, armnn::DataType::Float32); |
| 2909 | const armnn::TensorInfo outputInfo({ 1, 9, 9, 1 }, armnn::DataType::Float32); |
| 2910 | |
| 2911 | const armnn::TensorInfo weightsInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32); |
| 2912 | const armnn::TensorInfo biasesInfo ({ 1 }, armnn::DataType::Float32); |
| 2913 | |
| 2914 | std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements()); |
| 2915 | armnn::ConstTensor weights(weightsInfo, weightsData); |
| 2916 | |
| 2917 | std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements()); |
| 2918 | armnn::ConstTensor biases(biasesInfo, biasesData); |
| 2919 | |
| 2920 | armnn::TransposeConvolution2dDescriptor descriptor; |
| 2921 | descriptor.m_PadLeft = 1; |
| 2922 | descriptor.m_PadRight = 1; |
| 2923 | descriptor.m_PadTop = 1; |
| 2924 | descriptor.m_PadBottom = 1; |
| 2925 | descriptor.m_StrideX = 1; |
| 2926 | descriptor.m_StrideY = 1; |
| 2927 | descriptor.m_BiasEnabled = true; |
| 2928 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 2929 | |
| 2930 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 2931 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 2932 | armnn::IConnectableLayer* const convLayer = |
| 2933 | network->AddTransposeConvolution2dLayer(descriptor, |
| 2934 | weights, |
| 2935 | armnn::Optional<armnn::ConstTensor>(biases), |
| 2936 | layerName.c_str()); |
| 2937 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); |
| 2938 | |
| 2939 | inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0)); |
| 2940 | convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| 2941 | |
| 2942 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 2943 | convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| 2944 | |
| 2945 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2946 | BOOST_CHECK(deserializedNetwork); |
| 2947 | |
| 2948 | TransposeConvolution2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases); |
| 2949 | deserializedNetwork->Accept(verifier); |
| 2950 | } |
| 2951 | |
Sadik Armagan | db059fd | 2019-03-20 12:28:32 +0000 | [diff] [blame] | 2952 | BOOST_AUTO_TEST_CASE(SerializeDeserializeNonLinearNetwork) |
| 2953 | { |
| 2954 | class ConstantLayerVerifier : public LayerVerifierBase |
| 2955 | { |
| 2956 | public: |
| 2957 | ConstantLayerVerifier(const std::string& layerName, |
| 2958 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 2959 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 2960 | const armnn::ConstTensor& layerInput) |
| 2961 | : LayerVerifierBase(layerName, inputInfos, outputInfos) |
| 2962 | , m_LayerInput(layerInput) {} |
| 2963 | |
| 2964 | void VisitConstantLayer(const armnn::IConnectableLayer* layer, |
| 2965 | const armnn::ConstTensor& input, |
| 2966 | const char* name) override |
| 2967 | { |
| 2968 | VerifyNameAndConnections(layer, name); |
Sadik Armagan | db059fd | 2019-03-20 12:28:32 +0000 | [diff] [blame] | 2969 | CompareConstTensor(input, m_LayerInput); |
| 2970 | } |
| 2971 | |
Derek Lamberti | 859f9ce | 2019-12-10 22:05:21 +0000 | [diff] [blame] | 2972 | void VisitAdditionLayer(const armnn::IConnectableLayer*, const char*) override {} |
Sadik Armagan | db059fd | 2019-03-20 12:28:32 +0000 | [diff] [blame] | 2973 | |
| 2974 | private: |
| 2975 | armnn::ConstTensor m_LayerInput; |
| 2976 | }; |
| 2977 | |
| 2978 | const std::string layerName("constant"); |
| 2979 | const armnn::TensorInfo info({ 2, 3 }, armnn::DataType::Float32); |
| 2980 | |
| 2981 | std::vector<float> constantData = GenerateRandomData<float>(info.GetNumElements()); |
| 2982 | armnn::ConstTensor constTensor(info, constantData); |
| 2983 | |
| 2984 | armnn::INetworkPtr network(armnn::INetwork::Create()); |
| 2985 | armnn::IConnectableLayer* input = network->AddInputLayer(0); |
| 2986 | armnn::IConnectableLayer* add = network->AddAdditionLayer(); |
| 2987 | armnn::IConnectableLayer* constant = network->AddConstantLayer(constTensor, layerName.c_str()); |
| 2988 | armnn::IConnectableLayer* output = network->AddOutputLayer(0); |
| 2989 | |
| 2990 | input->GetOutputSlot(0).Connect(add->GetInputSlot(0)); |
| 2991 | constant->GetOutputSlot(0).Connect(add->GetInputSlot(1)); |
| 2992 | add->GetOutputSlot(0).Connect(output->GetInputSlot(0)); |
| 2993 | |
| 2994 | input->GetOutputSlot(0).SetTensorInfo(info); |
| 2995 | constant->GetOutputSlot(0).SetTensorInfo(info); |
| 2996 | add->GetOutputSlot(0).SetTensorInfo(info); |
| 2997 | |
| 2998 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 2999 | BOOST_CHECK(deserializedNetwork); |
| 3000 | |
| 3001 | ConstantLayerVerifier verifier(layerName, {}, {info}, constTensor); |
| 3002 | deserializedNetwork->Accept(verifier); |
| 3003 | } |
| 3004 | |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 3005 | class VerifyLstmLayer : public LayerVerifierBaseWithDescriptor<armnn::LstmDescriptor> |
Jim Flynn | 11af375 | 2019-03-19 17:22:29 +0000 | [diff] [blame] | 3006 | { |
| 3007 | public: |
| 3008 | VerifyLstmLayer(const std::string& layerName, |
| 3009 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 3010 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 3011 | const armnn::LstmDescriptor& descriptor, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 3012 | const armnn::LstmInputParams& inputParams) |
| 3013 | : LayerVerifierBaseWithDescriptor<armnn::LstmDescriptor>(layerName, inputInfos, outputInfos, descriptor) |
| 3014 | , m_InputParams(inputParams) {} |
| 3015 | |
Jim Flynn | 11af375 | 2019-03-19 17:22:29 +0000 | [diff] [blame] | 3016 | void VisitLstmLayer(const armnn::IConnectableLayer* layer, |
| 3017 | const armnn::LstmDescriptor& descriptor, |
| 3018 | const armnn::LstmInputParams& params, |
| 3019 | const char* name) |
| 3020 | { |
| 3021 | VerifyNameAndConnections(layer, name); |
| 3022 | VerifyDescriptor(descriptor); |
| 3023 | VerifyInputParameters(params); |
| 3024 | } |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 3025 | |
Jim Flynn | 11af375 | 2019-03-19 17:22:29 +0000 | [diff] [blame] | 3026 | protected: |
Jim Flynn | 11af375 | 2019-03-19 17:22:29 +0000 | [diff] [blame] | 3027 | void VerifyInputParameters(const armnn::LstmInputParams& params) |
| 3028 | { |
| 3029 | VerifyConstTensors( |
| 3030 | "m_InputToInputWeights", m_InputParams.m_InputToInputWeights, params.m_InputToInputWeights); |
| 3031 | VerifyConstTensors( |
| 3032 | "m_InputToForgetWeights", m_InputParams.m_InputToForgetWeights, params.m_InputToForgetWeights); |
| 3033 | VerifyConstTensors( |
| 3034 | "m_InputToCellWeights", m_InputParams.m_InputToCellWeights, params.m_InputToCellWeights); |
| 3035 | VerifyConstTensors( |
| 3036 | "m_InputToOutputWeights", m_InputParams.m_InputToOutputWeights, params.m_InputToOutputWeights); |
| 3037 | VerifyConstTensors( |
| 3038 | "m_RecurrentToInputWeights", m_InputParams.m_RecurrentToInputWeights, params.m_RecurrentToInputWeights); |
| 3039 | VerifyConstTensors( |
| 3040 | "m_RecurrentToForgetWeights", m_InputParams.m_RecurrentToForgetWeights, params.m_RecurrentToForgetWeights); |
| 3041 | VerifyConstTensors( |
| 3042 | "m_RecurrentToCellWeights", m_InputParams.m_RecurrentToCellWeights, params.m_RecurrentToCellWeights); |
| 3043 | VerifyConstTensors( |
| 3044 | "m_RecurrentToOutputWeights", m_InputParams.m_RecurrentToOutputWeights, params.m_RecurrentToOutputWeights); |
| 3045 | VerifyConstTensors( |
| 3046 | "m_CellToInputWeights", m_InputParams.m_CellToInputWeights, params.m_CellToInputWeights); |
| 3047 | VerifyConstTensors( |
| 3048 | "m_CellToForgetWeights", m_InputParams.m_CellToForgetWeights, params.m_CellToForgetWeights); |
| 3049 | VerifyConstTensors( |
| 3050 | "m_CellToOutputWeights", m_InputParams.m_CellToOutputWeights, params.m_CellToOutputWeights); |
| 3051 | VerifyConstTensors( |
| 3052 | "m_InputGateBias", m_InputParams.m_InputGateBias, params.m_InputGateBias); |
| 3053 | VerifyConstTensors( |
| 3054 | "m_ForgetGateBias", m_InputParams.m_ForgetGateBias, params.m_ForgetGateBias); |
| 3055 | VerifyConstTensors( |
| 3056 | "m_CellBias", m_InputParams.m_CellBias, params.m_CellBias); |
| 3057 | VerifyConstTensors( |
| 3058 | "m_OutputGateBias", m_InputParams.m_OutputGateBias, params.m_OutputGateBias); |
| 3059 | VerifyConstTensors( |
| 3060 | "m_ProjectionWeights", m_InputParams.m_ProjectionWeights, params.m_ProjectionWeights); |
| 3061 | VerifyConstTensors( |
| 3062 | "m_ProjectionBias", m_InputParams.m_ProjectionBias, params.m_ProjectionBias); |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 3063 | VerifyConstTensors( |
| 3064 | "m_InputLayerNormWeights", m_InputParams.m_InputLayerNormWeights, params.m_InputLayerNormWeights); |
| 3065 | VerifyConstTensors( |
| 3066 | "m_ForgetLayerNormWeights", m_InputParams.m_ForgetLayerNormWeights, params.m_ForgetLayerNormWeights); |
| 3067 | VerifyConstTensors( |
| 3068 | "m_CellLayerNormWeights", m_InputParams.m_CellLayerNormWeights, params.m_CellLayerNormWeights); |
| 3069 | VerifyConstTensors( |
| 3070 | "m_OutputLayerNormWeights", m_InputParams.m_OutputLayerNormWeights, params.m_OutputLayerNormWeights); |
Jim Flynn | 11af375 | 2019-03-19 17:22:29 +0000 | [diff] [blame] | 3071 | } |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 3072 | |
Jim Flynn | 11af375 | 2019-03-19 17:22:29 +0000 | [diff] [blame] | 3073 | private: |
Jim Flynn | 11af375 | 2019-03-19 17:22:29 +0000 | [diff] [blame] | 3074 | armnn::LstmInputParams m_InputParams; |
| 3075 | }; |
| 3076 | |
| 3077 | BOOST_AUTO_TEST_CASE(SerializeDeserializeLstmCifgPeepholeNoProjection) |
| 3078 | { |
| 3079 | armnn::LstmDescriptor descriptor; |
| 3080 | descriptor.m_ActivationFunc = 4; |
| 3081 | descriptor.m_ClippingThresProj = 0.0f; |
| 3082 | descriptor.m_ClippingThresCell = 0.0f; |
| 3083 | descriptor.m_CifgEnabled = true; // if this is true then we DON'T need to set the OptCifgParams |
| 3084 | descriptor.m_ProjectionEnabled = false; |
| 3085 | descriptor.m_PeepholeEnabled = true; |
| 3086 | |
| 3087 | const uint32_t batchSize = 1; |
| 3088 | const uint32_t inputSize = 2; |
| 3089 | const uint32_t numUnits = 4; |
| 3090 | const uint32_t outputSize = numUnits; |
| 3091 | |
| 3092 | armnn::TensorInfo inputWeightsInfo1({numUnits, inputSize}, armnn::DataType::Float32); |
| 3093 | std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements()); |
| 3094 | armnn::ConstTensor inputToForgetWeights(inputWeightsInfo1, inputToForgetWeightsData); |
| 3095 | |
| 3096 | std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements()); |
| 3097 | armnn::ConstTensor inputToCellWeights(inputWeightsInfo1, inputToCellWeightsData); |
| 3098 | |
| 3099 | std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements()); |
| 3100 | armnn::ConstTensor inputToOutputWeights(inputWeightsInfo1, inputToOutputWeightsData); |
| 3101 | |
| 3102 | armnn::TensorInfo inputWeightsInfo2({numUnits, outputSize}, armnn::DataType::Float32); |
| 3103 | std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements()); |
| 3104 | armnn::ConstTensor recurrentToForgetWeights(inputWeightsInfo2, recurrentToForgetWeightsData); |
| 3105 | |
| 3106 | std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements()); |
| 3107 | armnn::ConstTensor recurrentToCellWeights(inputWeightsInfo2, recurrentToCellWeightsData); |
| 3108 | |
| 3109 | std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements()); |
| 3110 | armnn::ConstTensor recurrentToOutputWeights(inputWeightsInfo2, recurrentToOutputWeightsData); |
| 3111 | |
| 3112 | armnn::TensorInfo inputWeightsInfo3({numUnits}, armnn::DataType::Float32); |
| 3113 | std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo3.GetNumElements()); |
| 3114 | armnn::ConstTensor cellToForgetWeights(inputWeightsInfo3, cellToForgetWeightsData); |
| 3115 | |
| 3116 | std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo3.GetNumElements()); |
| 3117 | armnn::ConstTensor cellToOutputWeights(inputWeightsInfo3, cellToOutputWeightsData); |
| 3118 | |
| 3119 | std::vector<float> forgetGateBiasData(numUnits, 1.0f); |
| 3120 | armnn::ConstTensor forgetGateBias(inputWeightsInfo3, forgetGateBiasData); |
| 3121 | |
| 3122 | std::vector<float> cellBiasData(numUnits, 0.0f); |
| 3123 | armnn::ConstTensor cellBias(inputWeightsInfo3, cellBiasData); |
| 3124 | |
| 3125 | std::vector<float> outputGateBiasData(numUnits, 0.0f); |
| 3126 | armnn::ConstTensor outputGateBias(inputWeightsInfo3, outputGateBiasData); |
| 3127 | |
| 3128 | armnn::LstmInputParams params; |
| 3129 | params.m_InputToForgetWeights = &inputToForgetWeights; |
| 3130 | params.m_InputToCellWeights = &inputToCellWeights; |
| 3131 | params.m_InputToOutputWeights = &inputToOutputWeights; |
| 3132 | params.m_RecurrentToForgetWeights = &recurrentToForgetWeights; |
| 3133 | params.m_RecurrentToCellWeights = &recurrentToCellWeights; |
| 3134 | params.m_RecurrentToOutputWeights = &recurrentToOutputWeights; |
| 3135 | params.m_ForgetGateBias = &forgetGateBias; |
| 3136 | params.m_CellBias = &cellBias; |
| 3137 | params.m_OutputGateBias = &outputGateBias; |
| 3138 | params.m_CellToForgetWeights = &cellToForgetWeights; |
| 3139 | params.m_CellToOutputWeights = &cellToOutputWeights; |
| 3140 | |
| 3141 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 3142 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 3143 | armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1); |
| 3144 | armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2); |
| 3145 | const std::string layerName("lstm"); |
| 3146 | armnn::IConnectableLayer* const lstmLayer = network->AddLstmLayer(descriptor, params, layerName.c_str()); |
| 3147 | armnn::IConnectableLayer* const scratchBuffer = network->AddOutputLayer(0); |
| 3148 | armnn::IConnectableLayer* const outputStateOut = network->AddOutputLayer(1); |
| 3149 | armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(2); |
| 3150 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(3); |
| 3151 | |
| 3152 | // connect up |
| 3153 | armnn::TensorInfo inputTensorInfo({ batchSize, inputSize }, armnn::DataType::Float32); |
| 3154 | armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32); |
| 3155 | armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32); |
| 3156 | armnn::TensorInfo lstmTensorInfoScratchBuff({ batchSize, numUnits * 3 }, armnn::DataType::Float32); |
| 3157 | |
| 3158 | inputLayer->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(0)); |
| 3159 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 3160 | |
| 3161 | outputStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(1)); |
| 3162 | outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo); |
| 3163 | |
| 3164 | cellStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(2)); |
| 3165 | cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo); |
| 3166 | |
| 3167 | lstmLayer->GetOutputSlot(0).Connect(scratchBuffer->GetInputSlot(0)); |
| 3168 | lstmLayer->GetOutputSlot(0).SetTensorInfo(lstmTensorInfoScratchBuff); |
| 3169 | |
| 3170 | lstmLayer->GetOutputSlot(1).Connect(outputStateOut->GetInputSlot(0)); |
| 3171 | lstmLayer->GetOutputSlot(1).SetTensorInfo(outputStateTensorInfo); |
| 3172 | |
| 3173 | lstmLayer->GetOutputSlot(2).Connect(cellStateOut->GetInputSlot(0)); |
| 3174 | lstmLayer->GetOutputSlot(2).SetTensorInfo(cellStateTensorInfo); |
| 3175 | |
| 3176 | lstmLayer->GetOutputSlot(3).Connect(outputLayer->GetInputSlot(0)); |
| 3177 | lstmLayer->GetOutputSlot(3).SetTensorInfo(outputStateTensorInfo); |
| 3178 | |
| 3179 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 3180 | BOOST_CHECK(deserializedNetwork); |
| 3181 | |
| 3182 | VerifyLstmLayer checker( |
| 3183 | layerName, |
| 3184 | {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo}, |
| 3185 | {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo}, |
| 3186 | descriptor, |
| 3187 | params); |
| 3188 | deserializedNetwork->Accept(checker); |
| 3189 | } |
| 3190 | |
| 3191 | BOOST_AUTO_TEST_CASE(SerializeDeserializeLstmNoCifgWithPeepholeAndProjection) |
| 3192 | { |
| 3193 | armnn::LstmDescriptor descriptor; |
| 3194 | descriptor.m_ActivationFunc = 4; |
| 3195 | descriptor.m_ClippingThresProj = 0.0f; |
| 3196 | descriptor.m_ClippingThresCell = 0.0f; |
| 3197 | descriptor.m_CifgEnabled = false; // if this is true then we DON'T need to set the OptCifgParams |
| 3198 | descriptor.m_ProjectionEnabled = true; |
| 3199 | descriptor.m_PeepholeEnabled = true; |
| 3200 | |
| 3201 | const uint32_t batchSize = 2; |
| 3202 | const uint32_t inputSize = 5; |
| 3203 | const uint32_t numUnits = 20; |
| 3204 | const uint32_t outputSize = 16; |
| 3205 | |
| 3206 | armnn::TensorInfo tensorInfo20x5({numUnits, inputSize}, armnn::DataType::Float32); |
| 3207 | std::vector<float> inputToInputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3208 | armnn::ConstTensor inputToInputWeights(tensorInfo20x5, inputToInputWeightsData); |
| 3209 | |
| 3210 | std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3211 | armnn::ConstTensor inputToForgetWeights(tensorInfo20x5, inputToForgetWeightsData); |
| 3212 | |
| 3213 | std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3214 | armnn::ConstTensor inputToCellWeights(tensorInfo20x5, inputToCellWeightsData); |
| 3215 | |
| 3216 | std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3217 | armnn::ConstTensor inputToOutputWeights(tensorInfo20x5, inputToOutputWeightsData); |
| 3218 | |
| 3219 | armnn::TensorInfo tensorInfo20({numUnits}, armnn::DataType::Float32); |
| 3220 | std::vector<float> inputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3221 | armnn::ConstTensor inputGateBias(tensorInfo20, inputGateBiasData); |
| 3222 | |
| 3223 | std::vector<float> forgetGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3224 | armnn::ConstTensor forgetGateBias(tensorInfo20, forgetGateBiasData); |
| 3225 | |
| 3226 | std::vector<float> cellBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3227 | armnn::ConstTensor cellBias(tensorInfo20, cellBiasData); |
| 3228 | |
| 3229 | std::vector<float> outputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3230 | armnn::ConstTensor outputGateBias(tensorInfo20, outputGateBiasData); |
| 3231 | |
| 3232 | armnn::TensorInfo tensorInfo20x16({numUnits, outputSize}, armnn::DataType::Float32); |
| 3233 | std::vector<float> recurrentToInputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3234 | armnn::ConstTensor recurrentToInputWeights(tensorInfo20x16, recurrentToInputWeightsData); |
| 3235 | |
| 3236 | std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3237 | armnn::ConstTensor recurrentToForgetWeights(tensorInfo20x16, recurrentToForgetWeightsData); |
| 3238 | |
| 3239 | std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3240 | armnn::ConstTensor recurrentToCellWeights(tensorInfo20x16, recurrentToCellWeightsData); |
| 3241 | |
| 3242 | std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3243 | armnn::ConstTensor recurrentToOutputWeights(tensorInfo20x16, recurrentToOutputWeightsData); |
| 3244 | |
| 3245 | std::vector<float> cellToInputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3246 | armnn::ConstTensor cellToInputWeights(tensorInfo20, cellToInputWeightsData); |
| 3247 | |
| 3248 | std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3249 | armnn::ConstTensor cellToForgetWeights(tensorInfo20, cellToForgetWeightsData); |
| 3250 | |
| 3251 | std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3252 | armnn::ConstTensor cellToOutputWeights(tensorInfo20, cellToOutputWeightsData); |
| 3253 | |
| 3254 | armnn::TensorInfo tensorInfo16x20({outputSize, numUnits}, armnn::DataType::Float32); |
| 3255 | std::vector<float> projectionWeightsData = GenerateRandomData<float>(tensorInfo16x20.GetNumElements()); |
| 3256 | armnn::ConstTensor projectionWeights(tensorInfo16x20, projectionWeightsData); |
| 3257 | |
| 3258 | armnn::TensorInfo tensorInfo16({outputSize}, armnn::DataType::Float32); |
| 3259 | std::vector<float> projectionBiasData(outputSize, 0.f); |
| 3260 | armnn::ConstTensor projectionBias(tensorInfo16, projectionBiasData); |
| 3261 | |
| 3262 | armnn::LstmInputParams params; |
| 3263 | params.m_InputToForgetWeights = &inputToForgetWeights; |
| 3264 | params.m_InputToCellWeights = &inputToCellWeights; |
| 3265 | params.m_InputToOutputWeights = &inputToOutputWeights; |
| 3266 | params.m_RecurrentToForgetWeights = &recurrentToForgetWeights; |
| 3267 | params.m_RecurrentToCellWeights = &recurrentToCellWeights; |
| 3268 | params.m_RecurrentToOutputWeights = &recurrentToOutputWeights; |
| 3269 | params.m_ForgetGateBias = &forgetGateBias; |
| 3270 | params.m_CellBias = &cellBias; |
| 3271 | params.m_OutputGateBias = &outputGateBias; |
| 3272 | |
| 3273 | // additional params because: descriptor.m_CifgEnabled = false |
| 3274 | params.m_InputToInputWeights = &inputToInputWeights; |
| 3275 | params.m_RecurrentToInputWeights = &recurrentToInputWeights; |
| 3276 | params.m_CellToInputWeights = &cellToInputWeights; |
| 3277 | params.m_InputGateBias = &inputGateBias; |
| 3278 | |
| 3279 | // additional params because: descriptor.m_ProjectionEnabled = true |
| 3280 | params.m_ProjectionWeights = &projectionWeights; |
| 3281 | params.m_ProjectionBias = &projectionBias; |
| 3282 | |
| 3283 | // additional params because: descriptor.m_PeepholeEnabled = true |
| 3284 | params.m_CellToForgetWeights = &cellToForgetWeights; |
| 3285 | params.m_CellToOutputWeights = &cellToOutputWeights; |
| 3286 | |
| 3287 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 3288 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 3289 | armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1); |
| 3290 | armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2); |
| 3291 | const std::string layerName("lstm"); |
| 3292 | armnn::IConnectableLayer* const lstmLayer = network->AddLstmLayer(descriptor, params, layerName.c_str()); |
| 3293 | armnn::IConnectableLayer* const scratchBuffer = network->AddOutputLayer(0); |
| 3294 | armnn::IConnectableLayer* const outputStateOut = network->AddOutputLayer(1); |
| 3295 | armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(2); |
| 3296 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(3); |
| 3297 | |
| 3298 | // connect up |
| 3299 | armnn::TensorInfo inputTensorInfo({ batchSize, inputSize }, armnn::DataType::Float32); |
| 3300 | armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32); |
| 3301 | armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32); |
| 3302 | armnn::TensorInfo lstmTensorInfoScratchBuff({ batchSize, numUnits * 4 }, armnn::DataType::Float32); |
| 3303 | |
| 3304 | inputLayer->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(0)); |
| 3305 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 3306 | |
| 3307 | outputStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(1)); |
| 3308 | outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo); |
| 3309 | |
| 3310 | cellStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(2)); |
| 3311 | cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo); |
| 3312 | |
| 3313 | lstmLayer->GetOutputSlot(0).Connect(scratchBuffer->GetInputSlot(0)); |
| 3314 | lstmLayer->GetOutputSlot(0).SetTensorInfo(lstmTensorInfoScratchBuff); |
| 3315 | |
| 3316 | lstmLayer->GetOutputSlot(1).Connect(outputStateOut->GetInputSlot(0)); |
| 3317 | lstmLayer->GetOutputSlot(1).SetTensorInfo(outputStateTensorInfo); |
| 3318 | |
| 3319 | lstmLayer->GetOutputSlot(2).Connect(cellStateOut->GetInputSlot(0)); |
| 3320 | lstmLayer->GetOutputSlot(2).SetTensorInfo(cellStateTensorInfo); |
| 3321 | |
| 3322 | lstmLayer->GetOutputSlot(3).Connect(outputLayer->GetInputSlot(0)); |
| 3323 | lstmLayer->GetOutputSlot(3).SetTensorInfo(outputStateTensorInfo); |
| 3324 | |
| 3325 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 3326 | BOOST_CHECK(deserializedNetwork); |
| 3327 | |
| 3328 | VerifyLstmLayer checker( |
| 3329 | layerName, |
| 3330 | {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo}, |
| 3331 | {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo}, |
| 3332 | descriptor, |
| 3333 | params); |
| 3334 | deserializedNetwork->Accept(checker); |
| 3335 | } |
| 3336 | |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 3337 | BOOST_AUTO_TEST_CASE(SerializeDeserializeLstmNoCifgWithPeepholeWithProjectionWithLayerNorm) |
| 3338 | { |
| 3339 | armnn::LstmDescriptor descriptor; |
| 3340 | descriptor.m_ActivationFunc = 4; |
| 3341 | descriptor.m_ClippingThresProj = 0.0f; |
| 3342 | descriptor.m_ClippingThresCell = 0.0f; |
| 3343 | descriptor.m_CifgEnabled = false; // if this is true then we DON'T need to set the OptCifgParams |
| 3344 | descriptor.m_ProjectionEnabled = true; |
| 3345 | descriptor.m_PeepholeEnabled = true; |
| 3346 | descriptor.m_LayerNormEnabled = true; |
| 3347 | |
| 3348 | const uint32_t batchSize = 2; |
| 3349 | const uint32_t inputSize = 5; |
| 3350 | const uint32_t numUnits = 20; |
| 3351 | const uint32_t outputSize = 16; |
| 3352 | |
| 3353 | armnn::TensorInfo tensorInfo20x5({numUnits, inputSize}, armnn::DataType::Float32); |
| 3354 | std::vector<float> inputToInputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3355 | armnn::ConstTensor inputToInputWeights(tensorInfo20x5, inputToInputWeightsData); |
| 3356 | |
| 3357 | std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3358 | armnn::ConstTensor inputToForgetWeights(tensorInfo20x5, inputToForgetWeightsData); |
| 3359 | |
| 3360 | std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3361 | armnn::ConstTensor inputToCellWeights(tensorInfo20x5, inputToCellWeightsData); |
| 3362 | |
| 3363 | std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements()); |
| 3364 | armnn::ConstTensor inputToOutputWeights(tensorInfo20x5, inputToOutputWeightsData); |
| 3365 | |
| 3366 | armnn::TensorInfo tensorInfo20({numUnits}, armnn::DataType::Float32); |
| 3367 | std::vector<float> inputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3368 | armnn::ConstTensor inputGateBias(tensorInfo20, inputGateBiasData); |
| 3369 | |
| 3370 | std::vector<float> forgetGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3371 | armnn::ConstTensor forgetGateBias(tensorInfo20, forgetGateBiasData); |
| 3372 | |
| 3373 | std::vector<float> cellBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3374 | armnn::ConstTensor cellBias(tensorInfo20, cellBiasData); |
| 3375 | |
| 3376 | std::vector<float> outputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3377 | armnn::ConstTensor outputGateBias(tensorInfo20, outputGateBiasData); |
| 3378 | |
| 3379 | armnn::TensorInfo tensorInfo20x16({numUnits, outputSize}, armnn::DataType::Float32); |
| 3380 | std::vector<float> recurrentToInputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3381 | armnn::ConstTensor recurrentToInputWeights(tensorInfo20x16, recurrentToInputWeightsData); |
| 3382 | |
| 3383 | std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3384 | armnn::ConstTensor recurrentToForgetWeights(tensorInfo20x16, recurrentToForgetWeightsData); |
| 3385 | |
| 3386 | std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3387 | armnn::ConstTensor recurrentToCellWeights(tensorInfo20x16, recurrentToCellWeightsData); |
| 3388 | |
| 3389 | std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements()); |
| 3390 | armnn::ConstTensor recurrentToOutputWeights(tensorInfo20x16, recurrentToOutputWeightsData); |
| 3391 | |
| 3392 | std::vector<float> cellToInputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3393 | armnn::ConstTensor cellToInputWeights(tensorInfo20, cellToInputWeightsData); |
| 3394 | |
| 3395 | std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3396 | armnn::ConstTensor cellToForgetWeights(tensorInfo20, cellToForgetWeightsData); |
| 3397 | |
| 3398 | std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3399 | armnn::ConstTensor cellToOutputWeights(tensorInfo20, cellToOutputWeightsData); |
| 3400 | |
| 3401 | armnn::TensorInfo tensorInfo16x20({outputSize, numUnits}, armnn::DataType::Float32); |
| 3402 | std::vector<float> projectionWeightsData = GenerateRandomData<float>(tensorInfo16x20.GetNumElements()); |
| 3403 | armnn::ConstTensor projectionWeights(tensorInfo16x20, projectionWeightsData); |
| 3404 | |
| 3405 | armnn::TensorInfo tensorInfo16({outputSize}, armnn::DataType::Float32); |
| 3406 | std::vector<float> projectionBiasData(outputSize, 0.f); |
| 3407 | armnn::ConstTensor projectionBias(tensorInfo16, projectionBiasData); |
| 3408 | |
| 3409 | std::vector<float> inputLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3410 | armnn::ConstTensor inputLayerNormWeights(tensorInfo20, forgetGateBiasData); |
| 3411 | |
| 3412 | std::vector<float> forgetLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3413 | armnn::ConstTensor forgetLayerNormWeights(tensorInfo20, forgetGateBiasData); |
| 3414 | |
| 3415 | std::vector<float> cellLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3416 | armnn::ConstTensor cellLayerNormWeights(tensorInfo20, forgetGateBiasData); |
| 3417 | |
| 3418 | std::vector<float> outLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements()); |
| 3419 | armnn::ConstTensor outLayerNormWeights(tensorInfo20, forgetGateBiasData); |
| 3420 | |
| 3421 | armnn::LstmInputParams params; |
| 3422 | params.m_InputToForgetWeights = &inputToForgetWeights; |
| 3423 | params.m_InputToCellWeights = &inputToCellWeights; |
| 3424 | params.m_InputToOutputWeights = &inputToOutputWeights; |
| 3425 | params.m_RecurrentToForgetWeights = &recurrentToForgetWeights; |
| 3426 | params.m_RecurrentToCellWeights = &recurrentToCellWeights; |
| 3427 | params.m_RecurrentToOutputWeights = &recurrentToOutputWeights; |
| 3428 | params.m_ForgetGateBias = &forgetGateBias; |
| 3429 | params.m_CellBias = &cellBias; |
| 3430 | params.m_OutputGateBias = &outputGateBias; |
| 3431 | |
| 3432 | // additional params because: descriptor.m_CifgEnabled = false |
| 3433 | params.m_InputToInputWeights = &inputToInputWeights; |
| 3434 | params.m_RecurrentToInputWeights = &recurrentToInputWeights; |
| 3435 | params.m_CellToInputWeights = &cellToInputWeights; |
| 3436 | params.m_InputGateBias = &inputGateBias; |
| 3437 | |
| 3438 | // additional params because: descriptor.m_ProjectionEnabled = true |
| 3439 | params.m_ProjectionWeights = &projectionWeights; |
| 3440 | params.m_ProjectionBias = &projectionBias; |
| 3441 | |
| 3442 | // additional params because: descriptor.m_PeepholeEnabled = true |
| 3443 | params.m_CellToForgetWeights = &cellToForgetWeights; |
| 3444 | params.m_CellToOutputWeights = &cellToOutputWeights; |
| 3445 | |
| 3446 | // additional params because: despriptor.m_LayerNormEnabled = true |
| 3447 | params.m_InputLayerNormWeights = &inputLayerNormWeights; |
| 3448 | params.m_ForgetLayerNormWeights = &forgetLayerNormWeights; |
| 3449 | params.m_CellLayerNormWeights = &cellLayerNormWeights; |
| 3450 | params.m_OutputLayerNormWeights = &outLayerNormWeights; |
| 3451 | |
| 3452 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 3453 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
| 3454 | armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1); |
| 3455 | armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2); |
| 3456 | const std::string layerName("lstm"); |
| 3457 | armnn::IConnectableLayer* const lstmLayer = network->AddLstmLayer(descriptor, params, layerName.c_str()); |
| 3458 | armnn::IConnectableLayer* const scratchBuffer = network->AddOutputLayer(0); |
| 3459 | armnn::IConnectableLayer* const outputStateOut = network->AddOutputLayer(1); |
| 3460 | armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(2); |
| 3461 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(3); |
| 3462 | |
| 3463 | // connect up |
| 3464 | armnn::TensorInfo inputTensorInfo({ batchSize, inputSize }, armnn::DataType::Float32); |
| 3465 | armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32); |
| 3466 | armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32); |
| 3467 | armnn::TensorInfo lstmTensorInfoScratchBuff({ batchSize, numUnits * 4 }, armnn::DataType::Float32); |
| 3468 | |
| 3469 | inputLayer->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(0)); |
| 3470 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 3471 | |
| 3472 | outputStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(1)); |
| 3473 | outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo); |
| 3474 | |
| 3475 | cellStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(2)); |
| 3476 | cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo); |
| 3477 | |
| 3478 | lstmLayer->GetOutputSlot(0).Connect(scratchBuffer->GetInputSlot(0)); |
| 3479 | lstmLayer->GetOutputSlot(0).SetTensorInfo(lstmTensorInfoScratchBuff); |
| 3480 | |
| 3481 | lstmLayer->GetOutputSlot(1).Connect(outputStateOut->GetInputSlot(0)); |
| 3482 | lstmLayer->GetOutputSlot(1).SetTensorInfo(outputStateTensorInfo); |
| 3483 | |
| 3484 | lstmLayer->GetOutputSlot(2).Connect(cellStateOut->GetInputSlot(0)); |
| 3485 | lstmLayer->GetOutputSlot(2).SetTensorInfo(cellStateTensorInfo); |
| 3486 | |
| 3487 | lstmLayer->GetOutputSlot(3).Connect(outputLayer->GetInputSlot(0)); |
| 3488 | lstmLayer->GetOutputSlot(3).SetTensorInfo(outputStateTensorInfo); |
| 3489 | |
| 3490 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 3491 | BOOST_CHECK(deserializedNetwork); |
| 3492 | |
| 3493 | VerifyLstmLayer checker( |
| 3494 | layerName, |
| 3495 | {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo}, |
| 3496 | {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo}, |
| 3497 | descriptor, |
| 3498 | params); |
| 3499 | deserializedNetwork->Accept(checker); |
| 3500 | } |
| 3501 | |
| 3502 | BOOST_AUTO_TEST_CASE(EnsureLstmLayersBackwardCompatibility) |
| 3503 | { |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 3504 | // The hex data below is a flat buffer containing a lstm layer with no Cifg, with peephole and projection |
| 3505 | // enabled. That data was obtained before additional layer normalization parameters where added to the |
| 3506 | // lstm serializer. That way it can be tested if a lstm model with the old parameter configuration can |
| 3507 | // still be loaded |
| 3508 | const std::vector<uint8_t> lstmNoCifgWithPeepholeAndProjectionModel = |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 3509 | { |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 3510 | 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00, |
| 3511 | 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x2C, 0x00, 0x00, 0x00, 0x38, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, |
| 3512 | 0xDC, 0x29, 0x00, 0x00, 0x38, 0x29, 0x00, 0x00, 0xB4, 0x28, 0x00, 0x00, 0x94, 0x01, 0x00, 0x00, 0x3C, 0x01, |
| 3513 | 0x00, 0x00, 0xE0, 0x00, 0x00, 0x00, 0x84, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, |
| 3514 | 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x04, 0x00, |
| 3515 | 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x70, 0xD6, 0xFF, 0xFF, |
| 3516 | 0x00, 0x00, 0x00, 0x0B, 0x04, 0x00, 0x00, 0x00, 0x06, 0xD7, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x88, 0xD7, |
| 3517 | 0xFF, 0xFF, 0x08, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0xF6, 0xD6, 0xFF, 0xFF, 0x07, 0x00, 0x00, 0x00, |
| 3518 | 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3519 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3520 | 0xE8, 0xD7, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0xC8, 0xD6, 0xFF, 0xFF, 0x00, 0x00, |
| 3521 | 0x00, 0x0B, 0x04, 0x00, 0x00, 0x00, 0x5E, 0xD7, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0xE0, 0xD7, 0xFF, 0xFF, |
| 3522 | 0x08, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x4E, 0xD7, 0xFF, 0xFF, 0x06, 0x00, 0x00, 0x00, 0x10, 0x00, |
| 3523 | 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3524 | 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x40, 0xD8, |
| 3525 | 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x20, 0xD7, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B, |
| 3526 | 0x04, 0x00, 0x00, 0x00, 0xB6, 0xD7, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x38, 0xD8, 0xFF, 0xFF, 0x08, 0x00, |
| 3527 | 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0xA6, 0xD7, 0xFF, 0xFF, 0x05, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, |
| 3528 | 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3529 | 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x98, 0xD8, 0xFF, 0xFF, |
| 3530 | 0x03, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x78, 0xD7, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B, 0x04, 0x00, |
| 3531 | 0x00, 0x00, 0x0E, 0xD8, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x16, 0xD8, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, |
| 3532 | 0xFA, 0xD7, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, |
| 3533 | 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, |
| 3534 | 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xEC, 0xD8, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3535 | 0x00, 0x00, 0x6C, 0xD8, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x23, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, |
| 3536 | 0x12, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00, 0x00, 0x00, 0xE0, 0x25, 0x00, 0x00, 0xD0, 0x25, |
| 3537 | 0x00, 0x00, 0x2C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x26, 0x00, 0x48, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, |
| 3538 | 0x10, 0x00, 0x14, 0x00, 0x18, 0x00, 0x1C, 0x00, 0x20, 0x00, 0x24, 0x00, 0x28, 0x00, 0x2C, 0x00, 0x30, 0x00, |
| 3539 | 0x34, 0x00, 0x38, 0x00, 0x3C, 0x00, 0x40, 0x00, 0x44, 0x00, 0x26, 0x00, 0x00, 0x00, 0xC4, 0x23, 0x00, 0x00, |
| 3540 | 0xF8, 0x21, 0x00, 0x00, 0x2C, 0x20, 0x00, 0x00, 0xF0, 0x1A, 0x00, 0x00, 0xB4, 0x15, 0x00, 0x00, 0x78, 0x10, |
| 3541 | 0x00, 0x00, 0xF0, 0x0F, 0x00, 0x00, 0x68, 0x0F, 0x00, 0x00, 0xE0, 0x0E, 0x00, 0x00, 0x14, 0x0D, 0x00, 0x00, |
| 3542 | 0xD8, 0x07, 0x00, 0x00, 0x50, 0x07, 0x00, 0x00, 0xC8, 0x06, 0x00, 0x00, 0x8C, 0x01, 0x00, 0x00, 0x14, 0x01, |
| 3543 | 0x00, 0x00, 0x8C, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xEE, 0xD7, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, |
| 3544 | 0x64, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xFE, 0xD8, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x14, 0x00, |
| 3545 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3546 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3547 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3548 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3549 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x5A, 0xD8, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, |
| 3550 | 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x72, 0xD8, |
| 3551 | 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, 0x64, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x82, 0xD9, 0xFF, 0xFF, |
| 3552 | 0x04, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3553 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3554 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3555 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3556 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xDE, 0xD8, |
| 3557 | 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, |
| 3558 | 0x14, 0x00, 0x00, 0x00, 0xF6, 0xD8, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, 0x54, 0x00, 0x00, 0x00, 0x04, 0x00, |
| 3559 | 0x00, 0x00, 0x06, 0xDA, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3560 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3561 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3562 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3563 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x52, 0xD9, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, |
| 3564 | 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x6A, 0xD9, 0xFF, 0xFF, 0x00, 0x00, |
| 3565 | 0x00, 0x03, 0x14, 0x05, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x7A, 0xDA, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, |
| 3566 | 0x40, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3567 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3568 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3569 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3570 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3571 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3572 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3573 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3574 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3575 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3576 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3577 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3578 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3579 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3580 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3581 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3582 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3583 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3584 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3585 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3586 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3587 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3588 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3589 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3590 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3591 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3592 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3593 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3594 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3595 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3596 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3597 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3598 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3599 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3600 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3601 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3602 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3603 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3604 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3605 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3606 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3607 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3608 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3609 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3610 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3611 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 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, |
| 3613 | 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, |
| 3615 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3616 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3617 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3618 | 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, |
| 3620 | 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, |
| 3622 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3623 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3624 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 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, |
| 3626 | 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, |
| 3628 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3629 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3630 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 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, |
| 3632 | 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, |
| 3634 | 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, |
| 3636 | 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, 0x86, 0xDE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, |
| 3638 | 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0xA2, 0xDE, |
| 3639 | 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, 0x64, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xB2, 0xDF, 0xFF, 0xFF, |
| 3640 | 0x04, 0x00, 0x00, 0x00, 0x14, 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, |
| 3642 | 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, |
| 3644 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0E, 0xDF, |
| 3645 | 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, |
| 3646 | 0x14, 0x00, 0x00, 0x00, 0x26, 0xDF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, 0x64, 0x00, 0x00, 0x00, 0x04, 0x00, |
| 3647 | 0x00, 0x00, 0x36, 0xE0, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x14, 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, |
| 3649 | 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, |
| 3651 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3652 | 0x00, 0x00, 0x00, 0x00, 0x92, 0xDF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3653 | 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0xAA, 0xDF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, |
| 3654 | 0x14, 0x05, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xBA, 0xE0, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x40, 0x01, |
| 3655 | 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, |
| 3657 | 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, |
| 3659 | 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, |
| 3661 | 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, |
| 3663 | 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, |
| 3665 | 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, |
| 3667 | 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, |
| 3669 | 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, |
| 3671 | 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, |
| 3673 | 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, |
| 3675 | 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, |
| 3677 | 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, |
| 3679 | 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, |
| 3681 | 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, |
| 3683 | 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, |
| 3685 | 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, |
| 3687 | 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, |
| 3689 | 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, |
| 3691 | 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, |
| 3693 | 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, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3695 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3696 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3697 | 0x00, 0x00, 0x00, 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, |
| 3699 | 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, |
| 3701 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3702 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3703 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3704 | 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, |
| 3706 | 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, |
| 3708 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3709 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3710 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 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, |
| 3712 | 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, |
| 3714 | 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, |
| 3716 | 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, |
| 3718 | 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, |
| 3720 | 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, |
| 3722 | 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, |
| 3724 | 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, |
| 3726 | 0x00, 0x00, 0x00, 0x00, 0xC6, 0xE4, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3727 | 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0xE2, 0xE4, 0xFF, 0xFF, |
| 3728 | 0x00, 0x00, 0x00, 0x03, 0xA4, 0x01, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xF2, 0xE5, 0xFF, 0xFF, 0x04, 0x00, |
| 3729 | 0x00, 0x00, 0x64, 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, |
| 3731 | 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, |
| 3733 | 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, |
| 3735 | 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, |
| 3737 | 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, |
| 3739 | 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, |
| 3741 | 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, |
| 3743 | 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, |
| 3745 | 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, |
| 3747 | 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, |
| 3749 | 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, |
| 3751 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x8E, 0xE6, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, |
| 3752 | 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x05, 0x00, |
| 3753 | 0x00, 0x00, 0xAA, 0xE6, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, 0x64, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, |
| 3754 | 0xBA, 0xE7, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x14, 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, |
| 3756 | 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, |
| 3758 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3759 | 0x00, 0x00, 0x16, 0xE7, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3760 | 0x01, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x2E, 0xE7, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, 0x64, 0x00, |
| 3761 | 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x3E, 0xE8, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, |
| 3762 | 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, |
| 3764 | 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, |
| 3766 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x9A, 0xE7, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, |
| 3767 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0xB2, 0xE7, 0xFF, 0xFF, |
| 3768 | 0x00, 0x00, 0x00, 0x03, 0x64, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xC2, 0xE8, 0xFF, 0xFF, 0x04, 0x00, |
| 3769 | 0x00, 0x00, 0x14, 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, |
| 3771 | 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, |
| 3773 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x1E, 0xE8, 0xFF, 0xFF, |
| 3774 | 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x14, 0x00, |
| 3775 | 0x00, 0x00, 0x36, 0xE8, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, 0x14, 0x05, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, |
| 3776 | 0x46, 0xE9, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x40, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3777 | 0x00, 0x00, 0x00, 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, |
| 3779 | 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, |
| 3781 | 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, |
| 3783 | 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, |
| 3785 | 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, |
| 3787 | 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, |
| 3789 | 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, |
| 3791 | 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, |
| 3793 | 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, |
| 3795 | 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, |
| 3797 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3798 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3799 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3800 | 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, |
| 3802 | 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, |
| 3804 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3805 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3806 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 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, |
| 3808 | 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, |
| 3810 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3811 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3812 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3813 | 0x00, 0x00, 0x00, 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, |
| 3815 | 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, |
| 3817 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3818 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3819 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3820 | 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, |
| 3822 | 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, |
| 3824 | 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, |
| 3826 | 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, |
| 3828 | 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, |
| 3830 | 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, |
| 3832 | 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, |
| 3834 | 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, |
| 3836 | 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, |
| 3838 | 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, |
| 3840 | 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, |
| 3842 | 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, |
| 3844 | 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, |
| 3846 | 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, 0x52, 0xED, 0xFF, 0xFF, |
| 3848 | 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, |
| 3849 | 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x6E, 0xED, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, 0x14, 0x05, 0x00, 0x00, |
| 3850 | 0x04, 0x00, 0x00, 0x00, 0x7E, 0xEE, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x40, 0x01, 0x00, 0x00, 0x00, 0x00, |
| 3851 | 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, |
| 3853 | 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, |
| 3855 | 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, |
| 3857 | 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, |
| 3859 | 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, |
| 3861 | 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, |
| 3863 | 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, |
| 3865 | 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, |
| 3867 | 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, |
| 3869 | 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, |
| 3871 | 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, |
| 3873 | 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, |
| 3875 | 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, |
| 3877 | 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, |
| 3879 | 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, |
| 3881 | 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, |
| 3883 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3884 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3885 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3886 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 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, |
| 3888 | 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, |
| 3890 | 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, |
| 3892 | 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, |
| 3894 | 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, |
| 3896 | 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, |
| 3898 | 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, |
| 3900 | 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, |
| 3902 | 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, |
| 3904 | 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, |
| 3906 | 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, |
| 3908 | 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, |
| 3910 | 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, |
| 3912 | 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, |
| 3914 | 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, |
| 3916 | 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, |
| 3918 | 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, |
| 3920 | 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, |
| 3922 | 0x8A, 0xF2, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, |
| 3923 | 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0xA6, 0xF2, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, |
| 3924 | 0x14, 0x05, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xB6, 0xF3, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x40, 0x01, |
| 3925 | 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, |
| 3927 | 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, |
| 3929 | 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, |
| 3931 | 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, |
| 3933 | 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, |
| 3935 | 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, |
| 3937 | 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, |
| 3939 | 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, |
| 3941 | 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, |
| 3943 | 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, |
| 3945 | 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, |
| 3947 | 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, |
| 3949 | 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, 0x00, 0x00, |
| 3951 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3952 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3953 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 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, |
| 3955 | 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, |
| 3957 | 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, |
| 3959 | 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, |
| 3961 | 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, |
| 3963 | 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, |
| 3965 | 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, |
| 3967 | 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, |
| 3969 | 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, |
| 3971 | 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, |
| 3973 | 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, |
| 3975 | 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, |
| 3977 | 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, |
| 3979 | 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, |
| 3981 | 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, |
| 3983 | 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, |
| 3985 | 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, |
| 3987 | 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, |
| 3989 | 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, |
| 3991 | 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, |
| 3993 | 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, |
| 3995 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3996 | 0x00, 0x00, 0x00, 0x00, 0xC2, 0xF7, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 3997 | 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0xDE, 0xF7, 0xFF, 0xFF, |
| 3998 | 0x00, 0x00, 0x00, 0x03, 0xA4, 0x01, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xEE, 0xF8, 0xFF, 0xFF, 0x04, 0x00, |
| 3999 | 0x00, 0x00, 0x64, 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, |
| 4001 | 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, |
| 4003 | 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, |
| 4005 | 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, |
| 4007 | 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, |
| 4009 | 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, |
| 4011 | 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, |
| 4013 | 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, |
| 4015 | 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, |
| 4017 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4018 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4019 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4020 | 0x00, 0x00, 0x00, 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, 0x8A, 0xF9, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, |
| 4022 | 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x05, 0x00, |
| 4023 | 0x00, 0x00, 0xA6, 0xF9, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, 0xA4, 0x01, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, |
| 4024 | 0xB6, 0xFA, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x64, 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, |
| 4026 | 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, |
| 4028 | 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, |
| 4030 | 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, |
| 4032 | 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, |
| 4034 | 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, |
| 4036 | 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, |
| 4038 | 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, |
| 4040 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4041 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4042 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4043 | 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, |
| 4045 | 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, 0x52, 0xFB, |
| 4047 | 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, |
| 4048 | 0x14, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x6E, 0xFB, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, 0xA4, 0x01, |
| 4049 | 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x7E, 0xFC, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x64, 0x00, 0x00, 0x00, |
| 4050 | 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, |
| 4052 | 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, |
| 4054 | 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, |
| 4056 | 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, |
| 4058 | 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, |
| 4060 | 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, |
| 4062 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4063 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4064 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4065 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4066 | 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, |
| 4068 | 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, |
| 4070 | 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, |
| 4072 | 0x00, 0x00, 0x00, 0x00, 0x1A, 0xFD, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4073 | 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x10, 0x00, 0x0C, 0x00, |
| 4074 | 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x06, 0x00, 0x07, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4075 | 0x01, 0x01, 0x04, 0x00, 0x00, 0x00, 0x2E, 0xFE, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, |
| 4076 | 0x22, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6C, 0x73, |
| 4077 | 0x74, 0x6D, 0x00, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0xEC, 0x00, 0x00, 0x00, 0xD0, 0x00, 0x00, 0x00, |
| 4078 | 0xB4, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x88, 0x00, 0x00, 0x00, 0x5C, 0x00, 0x00, 0x00, 0x30, 0x00, |
| 4079 | 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x14, 0xFF, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, |
| 4080 | 0xA6, 0xFD, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, |
| 4081 | 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x3C, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00, |
| 4082 | 0x04, 0x00, 0x00, 0x00, 0xCE, 0xFD, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4083 | 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x64, 0xFF, 0xFF, 0xFF, |
| 4084 | 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xF6, 0xFD, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, |
| 4085 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, |
| 4086 | 0xB4, 0xFE, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x1A, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, |
| 4087 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x50, 0x00, 0x00, 0x00, |
| 4088 | 0xF0, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, |
| 4089 | 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, |
| 4090 | 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4091 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xE8, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x09, 0x04, 0x00, 0x00, 0x00, |
| 4092 | 0x7E, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, |
| 4093 | 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x76, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00, |
| 4094 | 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4095 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, |
| 4096 | 0x68, 0xFF, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0xCE, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, |
| 4097 | 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, |
| 4098 | 0x08, 0x00, 0x0E, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x0C, 0x00, |
| 4099 | 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x08, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, |
| 4100 | 0x08, 0x00, 0x0E, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x01, 0x00, |
| 4101 | 0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x14, 0x00, |
| 4102 | 0x0E, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, |
| 4103 | 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4104 | 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, |
| 4105 | 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6E, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, |
| 4106 | 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x08, 0x00, |
| 4107 | 0x0C, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x04, 0x00, 0x00, 0x00, |
| 4108 | 0xF6, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x0A, 0x00, 0x04, 0x00, 0x06, 0x00, |
| 4109 | 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x14, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, |
| 4110 | 0x0C, 0x00, 0x10, 0x00, 0x0E, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, |
| 4111 | 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, |
| 4112 | 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, |
| 4113 | 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x08, 0x00, 0x07, 0x00, 0x0C, 0x00, |
| 4114 | 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, |
| 4115 | 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x00 |
| 4116 | }; |
| 4117 | |
| 4118 | armnn::INetworkPtr deserializedNetwork = |
| 4119 | DeserializeNetwork(std::string(lstmNoCifgWithPeepholeAndProjectionModel.begin(), |
| 4120 | lstmNoCifgWithPeepholeAndProjectionModel.end())); |
| 4121 | |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 4122 | BOOST_CHECK(deserializedNetwork); |
| 4123 | |
| 4124 | // generating the same model parameters which where used to serialize the model (Layer norm is not specified) |
| 4125 | armnn::LstmDescriptor descriptor; |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 4126 | descriptor.m_ActivationFunc = 4; |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 4127 | descriptor.m_ClippingThresProj = 0.0f; |
| 4128 | descriptor.m_ClippingThresCell = 0.0f; |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 4129 | descriptor.m_CifgEnabled = false; |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 4130 | descriptor.m_ProjectionEnabled = true; |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 4131 | descriptor.m_PeepholeEnabled = true; |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 4132 | |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 4133 | const uint32_t batchSize = 2u; |
| 4134 | const uint32_t inputSize = 5u; |
| 4135 | const uint32_t numUnits = 20u; |
| 4136 | const uint32_t outputSize = 16u; |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 4137 | |
| 4138 | armnn::TensorInfo tensorInfo20x5({numUnits, inputSize}, armnn::DataType::Float32); |
| 4139 | std::vector<float> inputToInputWeightsData(tensorInfo20x5.GetNumElements(), 0.0f); |
| 4140 | armnn::ConstTensor inputToInputWeights(tensorInfo20x5, inputToInputWeightsData); |
| 4141 | |
| 4142 | std::vector<float> inputToForgetWeightsData(tensorInfo20x5.GetNumElements(), 0.0f); |
| 4143 | armnn::ConstTensor inputToForgetWeights(tensorInfo20x5, inputToForgetWeightsData); |
| 4144 | |
| 4145 | std::vector<float> inputToCellWeightsData(tensorInfo20x5.GetNumElements(), 0.0f); |
| 4146 | armnn::ConstTensor inputToCellWeights(tensorInfo20x5, inputToCellWeightsData); |
| 4147 | |
| 4148 | std::vector<float> inputToOutputWeightsData(tensorInfo20x5.GetNumElements(), 0.0f); |
| 4149 | armnn::ConstTensor inputToOutputWeights(tensorInfo20x5, inputToOutputWeightsData); |
| 4150 | |
| 4151 | armnn::TensorInfo tensorInfo20({numUnits}, armnn::DataType::Float32); |
| 4152 | std::vector<float> inputGateBiasData(tensorInfo20.GetNumElements(), 0.0f); |
| 4153 | armnn::ConstTensor inputGateBias(tensorInfo20, inputGateBiasData); |
| 4154 | |
| 4155 | std::vector<float> forgetGateBiasData(tensorInfo20.GetNumElements(), 0.0f); |
| 4156 | armnn::ConstTensor forgetGateBias(tensorInfo20, forgetGateBiasData); |
| 4157 | |
| 4158 | std::vector<float> cellBiasData(tensorInfo20.GetNumElements(), 0.0f); |
| 4159 | armnn::ConstTensor cellBias(tensorInfo20, cellBiasData); |
| 4160 | |
| 4161 | std::vector<float> outputGateBiasData(tensorInfo20.GetNumElements(), 0.0f); |
| 4162 | armnn::ConstTensor outputGateBias(tensorInfo20, outputGateBiasData); |
| 4163 | |
| 4164 | armnn::TensorInfo tensorInfo20x16({numUnits, outputSize}, armnn::DataType::Float32); |
| 4165 | std::vector<float> recurrentToInputWeightsData(tensorInfo20x16.GetNumElements(), 0.0f); |
| 4166 | armnn::ConstTensor recurrentToInputWeights(tensorInfo20x16, recurrentToInputWeightsData); |
| 4167 | |
| 4168 | std::vector<float> recurrentToForgetWeightsData(tensorInfo20x16.GetNumElements(), 0.0f); |
| 4169 | armnn::ConstTensor recurrentToForgetWeights(tensorInfo20x16, recurrentToForgetWeightsData); |
| 4170 | |
| 4171 | std::vector<float> recurrentToCellWeightsData(tensorInfo20x16.GetNumElements(), 0.0f); |
| 4172 | armnn::ConstTensor recurrentToCellWeights(tensorInfo20x16, recurrentToCellWeightsData); |
| 4173 | |
| 4174 | std::vector<float> recurrentToOutputWeightsData(tensorInfo20x16.GetNumElements(), 0.0f); |
| 4175 | armnn::ConstTensor recurrentToOutputWeights(tensorInfo20x16, recurrentToOutputWeightsData); |
| 4176 | |
| 4177 | std::vector<float> cellToInputWeightsData(tensorInfo20.GetNumElements(), 0.0f); |
| 4178 | armnn::ConstTensor cellToInputWeights(tensorInfo20, cellToInputWeightsData); |
| 4179 | |
| 4180 | std::vector<float> cellToForgetWeightsData(tensorInfo20.GetNumElements(), 0.0f); |
| 4181 | armnn::ConstTensor cellToForgetWeights(tensorInfo20, cellToForgetWeightsData); |
| 4182 | |
| 4183 | std::vector<float> cellToOutputWeightsData(tensorInfo20.GetNumElements(), 0.0f); |
| 4184 | armnn::ConstTensor cellToOutputWeights(tensorInfo20, cellToOutputWeightsData); |
| 4185 | |
| 4186 | armnn::TensorInfo tensorInfo16x20({outputSize, numUnits}, armnn::DataType::Float32); |
| 4187 | std::vector<float> projectionWeightsData(tensorInfo16x20.GetNumElements(), 0.0f); |
| 4188 | armnn::ConstTensor projectionWeights(tensorInfo16x20, projectionWeightsData); |
| 4189 | |
| 4190 | armnn::TensorInfo tensorInfo16({outputSize}, armnn::DataType::Float32); |
| 4191 | std::vector<float> projectionBiasData(outputSize, 0.0f); |
| 4192 | armnn::ConstTensor projectionBias(tensorInfo16, projectionBiasData); |
| 4193 | |
| 4194 | armnn::LstmInputParams params; |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 4195 | params.m_InputToForgetWeights = &inputToForgetWeights; |
| 4196 | params.m_InputToCellWeights = &inputToCellWeights; |
| 4197 | params.m_InputToOutputWeights = &inputToOutputWeights; |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 4198 | params.m_RecurrentToForgetWeights = &recurrentToForgetWeights; |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 4199 | params.m_RecurrentToCellWeights = &recurrentToCellWeights; |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 4200 | params.m_RecurrentToOutputWeights = &recurrentToOutputWeights; |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 4201 | params.m_ForgetGateBias = &forgetGateBias; |
| 4202 | params.m_CellBias = &cellBias; |
| 4203 | params.m_OutputGateBias = &outputGateBias; |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 4204 | |
| 4205 | // additional params because: descriptor.m_CifgEnabled = false |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 4206 | params.m_InputToInputWeights = &inputToInputWeights; |
| 4207 | params.m_RecurrentToInputWeights = &recurrentToInputWeights; |
| 4208 | params.m_CellToInputWeights = &cellToInputWeights; |
| 4209 | params.m_InputGateBias = &inputGateBias; |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 4210 | |
| 4211 | // additional params because: descriptor.m_ProjectionEnabled = true |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 4212 | params.m_ProjectionWeights = &projectionWeights; |
| 4213 | params.m_ProjectionBias = &projectionBias; |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 4214 | |
| 4215 | // additional params because: descriptor.m_PeepholeEnabled = true |
Aron Virginas-Tar | 6e0d962 | 2019-10-22 16:24:48 +0100 | [diff] [blame] | 4216 | params.m_CellToForgetWeights = &cellToForgetWeights; |
| 4217 | params.m_CellToOutputWeights = &cellToOutputWeights; |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 4218 | |
| 4219 | const std::string layerName("lstm"); |
| 4220 | armnn::TensorInfo inputTensorInfo({ batchSize, inputSize }, armnn::DataType::Float32); |
| 4221 | armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32); |
| 4222 | armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32); |
| 4223 | armnn::TensorInfo lstmTensorInfoScratchBuff({ batchSize, numUnits * 4 }, armnn::DataType::Float32); |
| 4224 | |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 4225 | VerifyLstmLayer checker( |
| 4226 | layerName, |
| 4227 | {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo}, |
| 4228 | {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo}, |
| 4229 | descriptor, |
| 4230 | params); |
| 4231 | deserializedNetwork->Accept(checker); |
| 4232 | } |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4233 | class VerifyQuantizedLstmLayer : public LayerVerifierBase |
| 4234 | { |
| 4235 | |
| 4236 | public: |
| 4237 | VerifyQuantizedLstmLayer(const std::string& layerName, |
| 4238 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 4239 | const std::vector<armnn::TensorInfo>& outputInfos, |
Aron Virginas-Tar | e80ebd1 | 2019-10-17 16:11:54 +0100 | [diff] [blame] | 4240 | const armnn::QuantizedLstmInputParams& inputParams) |
| 4241 | : LayerVerifierBase(layerName, inputInfos, outputInfos), m_InputParams(inputParams) {} |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4242 | |
| 4243 | void VisitQuantizedLstmLayer(const armnn::IConnectableLayer* layer, |
| 4244 | const armnn::QuantizedLstmInputParams& params, |
| 4245 | const char* name) |
| 4246 | { |
| 4247 | VerifyNameAndConnections(layer, name); |
| 4248 | VerifyInputParameters(params); |
| 4249 | } |
| 4250 | |
| 4251 | protected: |
| 4252 | void VerifyInputParameters(const armnn::QuantizedLstmInputParams& params) |
| 4253 | { |
| 4254 | VerifyConstTensors("m_InputToInputWeights", |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4255 | m_InputParams.m_InputToInputWeights, params.m_InputToInputWeights); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4256 | VerifyConstTensors("m_InputToForgetWeights", |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4257 | m_InputParams.m_InputToForgetWeights, params.m_InputToForgetWeights); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4258 | VerifyConstTensors("m_InputToCellWeights", |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4259 | m_InputParams.m_InputToCellWeights, params.m_InputToCellWeights); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4260 | VerifyConstTensors("m_InputToOutputWeights", |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4261 | m_InputParams.m_InputToOutputWeights, params.m_InputToOutputWeights); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4262 | VerifyConstTensors("m_RecurrentToInputWeights", |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4263 | m_InputParams.m_RecurrentToInputWeights, params.m_RecurrentToInputWeights); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4264 | VerifyConstTensors("m_RecurrentToForgetWeights", |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4265 | m_InputParams.m_RecurrentToForgetWeights, params.m_RecurrentToForgetWeights); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4266 | VerifyConstTensors("m_RecurrentToCellWeights", |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4267 | m_InputParams.m_RecurrentToCellWeights, params.m_RecurrentToCellWeights); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4268 | VerifyConstTensors("m_RecurrentToOutputWeights", |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4269 | m_InputParams.m_RecurrentToOutputWeights, params.m_RecurrentToOutputWeights); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4270 | VerifyConstTensors("m_InputGateBias", |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4271 | m_InputParams.m_InputGateBias, params.m_InputGateBias); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4272 | VerifyConstTensors("m_ForgetGateBias", |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4273 | m_InputParams.m_ForgetGateBias, params.m_ForgetGateBias); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4274 | VerifyConstTensors("m_CellBias", |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4275 | m_InputParams.m_CellBias, params.m_CellBias); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4276 | VerifyConstTensors("m_OutputGateBias", |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4277 | m_InputParams.m_OutputGateBias, params.m_OutputGateBias); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4278 | } |
| 4279 | |
| 4280 | private: |
| 4281 | armnn::QuantizedLstmInputParams m_InputParams; |
| 4282 | }; |
| 4283 | |
| 4284 | BOOST_AUTO_TEST_CASE(SerializeDeserializeQuantizedLstm) |
| 4285 | { |
| 4286 | const uint32_t batchSize = 1; |
| 4287 | const uint32_t inputSize = 2; |
| 4288 | const uint32_t numUnits = 4; |
| 4289 | const uint32_t outputSize = numUnits; |
| 4290 | |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4291 | // Scale/Offset for input/output, cellState In/Out, weights, bias |
| 4292 | float inputOutputScale = 0.0078125f; |
| 4293 | int32_t inputOutputOffset = 128; |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4294 | |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4295 | float cellStateScale = 0.00048828125f; |
| 4296 | int32_t cellStateOffset = 0; |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4297 | |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4298 | float weightsScale = 0.00408021f; |
| 4299 | int32_t weightsOffset = 100; |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4300 | |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4301 | float biasScale = 3.1876640625e-05f; |
| 4302 | int32_t biasOffset = 0; |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4303 | |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4304 | // The shape of weight data is {outputSize, inputSize} = {4, 2} |
| 4305 | armnn::TensorShape inputToInputWeightsShape = {4, 2}; |
| 4306 | std::vector<uint8_t> inputToInputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8}; |
| 4307 | armnn::TensorInfo inputToInputWeightsInfo(inputToInputWeightsShape, |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 4308 | armnn::DataType::QAsymmU8, |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4309 | weightsScale, |
| 4310 | weightsOffset); |
| 4311 | armnn::ConstTensor inputToInputWeights(inputToInputWeightsInfo, inputToInputWeightsData); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4312 | |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4313 | armnn::TensorShape inputToForgetWeightsShape = {4, 2}; |
| 4314 | std::vector<uint8_t> inputToForgetWeightsData = {1, 2, 3, 4, 5, 6, 7, 8}; |
| 4315 | armnn::TensorInfo inputToForgetWeightsInfo(inputToForgetWeightsShape, |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 4316 | armnn::DataType::QAsymmU8, |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4317 | weightsScale, |
| 4318 | weightsOffset); |
| 4319 | armnn::ConstTensor inputToForgetWeights(inputToForgetWeightsInfo, inputToForgetWeightsData); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4320 | |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4321 | armnn::TensorShape inputToCellWeightsShape = {4, 2}; |
| 4322 | std::vector<uint8_t> inputToCellWeightsData = {1, 2, 3, 4, 5, 6, 7, 8}; |
| 4323 | armnn::TensorInfo inputToCellWeightsInfo(inputToCellWeightsShape, |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 4324 | armnn::DataType::QAsymmU8, |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4325 | weightsScale, |
| 4326 | weightsOffset); |
| 4327 | armnn::ConstTensor inputToCellWeights(inputToCellWeightsInfo, inputToCellWeightsData); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4328 | |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4329 | armnn::TensorShape inputToOutputWeightsShape = {4, 2}; |
| 4330 | std::vector<uint8_t> inputToOutputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8}; |
| 4331 | armnn::TensorInfo inputToOutputWeightsInfo(inputToOutputWeightsShape, |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 4332 | armnn::DataType::QAsymmU8, |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4333 | weightsScale, |
| 4334 | weightsOffset); |
| 4335 | armnn::ConstTensor inputToOutputWeights(inputToOutputWeightsInfo, inputToOutputWeightsData); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4336 | |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4337 | // The shape of recurrent weight data is {outputSize, outputSize} = {4, 4} |
| 4338 | armnn::TensorShape recurrentToInputWeightsShape = {4, 4}; |
| 4339 | std::vector<uint8_t> recurrentToInputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}; |
| 4340 | armnn::TensorInfo recurrentToInputWeightsInfo(recurrentToInputWeightsShape, |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 4341 | armnn::DataType::QAsymmU8, |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4342 | weightsScale, |
| 4343 | weightsOffset); |
| 4344 | armnn::ConstTensor recurrentToInputWeights(recurrentToInputWeightsInfo, recurrentToInputWeightsData); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4345 | |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4346 | armnn::TensorShape recurrentToForgetWeightsShape = {4, 4}; |
| 4347 | std::vector<uint8_t> recurrentToForgetWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}; |
| 4348 | armnn::TensorInfo recurrentToForgetWeightsInfo(recurrentToForgetWeightsShape, |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 4349 | armnn::DataType::QAsymmU8, |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4350 | weightsScale, |
| 4351 | weightsOffset); |
| 4352 | armnn::ConstTensor recurrentToForgetWeights(recurrentToForgetWeightsInfo, recurrentToForgetWeightsData); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4353 | |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4354 | armnn::TensorShape recurrentToCellWeightsShape = {4, 4}; |
| 4355 | std::vector<uint8_t> recurrentToCellWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}; |
| 4356 | armnn::TensorInfo recurrentToCellWeightsInfo(recurrentToCellWeightsShape, |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 4357 | armnn::DataType::QAsymmU8, |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4358 | weightsScale, |
| 4359 | weightsOffset); |
| 4360 | armnn::ConstTensor recurrentToCellWeights(recurrentToCellWeightsInfo, recurrentToCellWeightsData); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4361 | |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4362 | armnn::TensorShape recurrentToOutputWeightsShape = {4, 4}; |
| 4363 | std::vector<uint8_t> recurrentToOutputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}; |
| 4364 | armnn::TensorInfo recurrentToOutputWeightsInfo(recurrentToOutputWeightsShape, |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 4365 | armnn::DataType::QAsymmU8, |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4366 | weightsScale, |
| 4367 | weightsOffset); |
| 4368 | armnn::ConstTensor recurrentToOutputWeights(recurrentToOutputWeightsInfo, recurrentToOutputWeightsData); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4369 | |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4370 | // The shape of bias data is {outputSize} = {4} |
| 4371 | armnn::TensorShape inputGateBiasShape = {4}; |
| 4372 | std::vector<int32_t> inputGateBiasData = {1, 2, 3, 4}; |
| 4373 | armnn::TensorInfo inputGateBiasInfo(inputGateBiasShape, |
| 4374 | armnn::DataType::Signed32, |
| 4375 | biasScale, |
| 4376 | biasOffset); |
| 4377 | armnn::ConstTensor inputGateBias(inputGateBiasInfo, inputGateBiasData); |
| 4378 | |
| 4379 | armnn::TensorShape forgetGateBiasShape = {4}; |
| 4380 | std::vector<int32_t> forgetGateBiasData = {1, 2, 3, 4}; |
| 4381 | armnn::TensorInfo forgetGateBiasInfo(forgetGateBiasShape, |
| 4382 | armnn::DataType::Signed32, |
| 4383 | biasScale, |
| 4384 | biasOffset); |
| 4385 | armnn::ConstTensor forgetGateBias(forgetGateBiasInfo, forgetGateBiasData); |
| 4386 | |
| 4387 | armnn::TensorShape cellBiasShape = {4}; |
| 4388 | std::vector<int32_t> cellBiasData = {1, 2, 3, 4}; |
| 4389 | armnn::TensorInfo cellBiasInfo(cellBiasShape, |
| 4390 | armnn::DataType::Signed32, |
| 4391 | biasScale, |
| 4392 | biasOffset); |
| 4393 | armnn::ConstTensor cellBias(cellBiasInfo, cellBiasData); |
| 4394 | |
| 4395 | armnn::TensorShape outputGateBiasShape = {4}; |
| 4396 | std::vector<int32_t> outputGateBiasData = {1, 2, 3, 4}; |
| 4397 | armnn::TensorInfo outputGateBiasInfo(outputGateBiasShape, |
| 4398 | armnn::DataType::Signed32, |
| 4399 | biasScale, |
| 4400 | biasOffset); |
| 4401 | armnn::ConstTensor outputGateBias(outputGateBiasInfo, outputGateBiasData); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4402 | |
| 4403 | armnn::QuantizedLstmInputParams params; |
| 4404 | params.m_InputToInputWeights = &inputToInputWeights; |
| 4405 | params.m_InputToForgetWeights = &inputToForgetWeights; |
| 4406 | params.m_InputToCellWeights = &inputToCellWeights; |
| 4407 | params.m_InputToOutputWeights = &inputToOutputWeights; |
| 4408 | params.m_RecurrentToInputWeights = &recurrentToInputWeights; |
| 4409 | params.m_RecurrentToForgetWeights = &recurrentToForgetWeights; |
| 4410 | params.m_RecurrentToCellWeights = &recurrentToCellWeights; |
| 4411 | params.m_RecurrentToOutputWeights = &recurrentToOutputWeights; |
| 4412 | params.m_InputGateBias = &inputGateBias; |
| 4413 | params.m_ForgetGateBias = &forgetGateBias; |
| 4414 | params.m_CellBias = &cellBias; |
| 4415 | params.m_OutputGateBias = &outputGateBias; |
| 4416 | |
| 4417 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4418 | armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4419 | armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1); |
| 4420 | armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2); |
| 4421 | const std::string layerName("QuantizedLstm"); |
| 4422 | armnn::IConnectableLayer* const quantizedLstmLayer = network->AddQuantizedLstmLayer(params, layerName.c_str()); |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4423 | armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(0); |
| 4424 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(1); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4425 | |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4426 | // Connect up |
| 4427 | armnn::TensorInfo inputTensorInfo({ batchSize, inputSize }, |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 4428 | armnn::DataType::QAsymmU8, |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4429 | inputOutputScale, |
| 4430 | inputOutputOffset); |
| 4431 | armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits }, |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 4432 | armnn::DataType::QSymmS16, |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4433 | cellStateScale, |
| 4434 | cellStateOffset); |
| 4435 | armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, |
Derek Lamberti | f90c56d | 2020-01-10 17:14:08 +0000 | [diff] [blame] | 4436 | armnn::DataType::QAsymmU8, |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4437 | inputOutputScale, |
| 4438 | inputOutputOffset); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4439 | |
| 4440 | inputLayer->GetOutputSlot(0).Connect(quantizedLstmLayer->GetInputSlot(0)); |
| 4441 | inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); |
| 4442 | |
| 4443 | cellStateIn->GetOutputSlot(0).Connect(quantizedLstmLayer->GetInputSlot(1)); |
| 4444 | cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo); |
| 4445 | |
| 4446 | outputStateIn->GetOutputSlot(0).Connect(quantizedLstmLayer->GetInputSlot(2)); |
| 4447 | outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo); |
| 4448 | |
| 4449 | quantizedLstmLayer->GetOutputSlot(0).Connect(cellStateOut->GetInputSlot(0)); |
| 4450 | quantizedLstmLayer->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo); |
| 4451 | |
| 4452 | quantizedLstmLayer->GetOutputSlot(1).Connect(outputLayer->GetInputSlot(0)); |
| 4453 | quantizedLstmLayer->GetOutputSlot(1).SetTensorInfo(outputStateTensorInfo); |
| 4454 | |
| 4455 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 4456 | BOOST_CHECK(deserializedNetwork); |
| 4457 | |
alanhsu5678 | 86324fc | 2019-10-25 23:44:16 +0800 | [diff] [blame] | 4458 | VerifyQuantizedLstmLayer checker(layerName, |
| 4459 | {inputTensorInfo, cellStateTensorInfo, outputStateTensorInfo}, |
| 4460 | {cellStateTensorInfo, outputStateTensorInfo}, |
| 4461 | params); |
Jan Eilers | 5b01a89 | 2019-07-23 09:47:43 +0100 | [diff] [blame] | 4462 | |
| 4463 | deserializedNetwork->Accept(checker); |
| 4464 | } |
| 4465 | |
James Conroy | 8d33318 | 2020-05-13 10:27:58 +0100 | [diff] [blame] | 4466 | class VerifyQLstmLayer : public LayerVerifierBaseWithDescriptor<armnn::QLstmDescriptor> |
| 4467 | { |
| 4468 | public: |
| 4469 | VerifyQLstmLayer(const std::string& layerName, |
| 4470 | const std::vector<armnn::TensorInfo>& inputInfos, |
| 4471 | const std::vector<armnn::TensorInfo>& outputInfos, |
| 4472 | const armnn::QLstmDescriptor& descriptor, |
| 4473 | const armnn::LstmInputParams& inputParams) |
| 4474 | : LayerVerifierBaseWithDescriptor<armnn::QLstmDescriptor>(layerName, inputInfos, outputInfos, descriptor) |
| 4475 | , m_InputParams(inputParams) {} |
| 4476 | |
| 4477 | void VisitQLstmLayer(const armnn::IConnectableLayer* layer, |
| 4478 | const armnn::QLstmDescriptor& descriptor, |
| 4479 | const armnn::LstmInputParams& params, |
| 4480 | const char* name) |
| 4481 | { |
| 4482 | VerifyNameAndConnections(layer, name); |
| 4483 | VerifyDescriptor(descriptor); |
| 4484 | VerifyInputParameters(params); |
| 4485 | } |
| 4486 | |
| 4487 | protected: |
| 4488 | void VerifyInputParameters(const armnn::LstmInputParams& params) |
| 4489 | { |
| 4490 | VerifyConstTensors( |
| 4491 | "m_InputToInputWeights", m_InputParams.m_InputToInputWeights, params.m_InputToInputWeights); |
| 4492 | VerifyConstTensors( |
| 4493 | "m_InputToForgetWeights", m_InputParams.m_InputToForgetWeights, params.m_InputToForgetWeights); |
| 4494 | VerifyConstTensors( |
| 4495 | "m_InputToCellWeights", m_InputParams.m_InputToCellWeights, params.m_InputToCellWeights); |
| 4496 | VerifyConstTensors( |
| 4497 | "m_InputToOutputWeights", m_InputParams.m_InputToOutputWeights, params.m_InputToOutputWeights); |
| 4498 | VerifyConstTensors( |
| 4499 | "m_RecurrentToInputWeights", m_InputParams.m_RecurrentToInputWeights, params.m_RecurrentToInputWeights); |
| 4500 | VerifyConstTensors( |
| 4501 | "m_RecurrentToForgetWeights", m_InputParams.m_RecurrentToForgetWeights, params.m_RecurrentToForgetWeights); |
| 4502 | VerifyConstTensors( |
| 4503 | "m_RecurrentToCellWeights", m_InputParams.m_RecurrentToCellWeights, params.m_RecurrentToCellWeights); |
| 4504 | VerifyConstTensors( |
| 4505 | "m_RecurrentToOutputWeights", m_InputParams.m_RecurrentToOutputWeights, params.m_RecurrentToOutputWeights); |
| 4506 | VerifyConstTensors( |
| 4507 | "m_CellToInputWeights", m_InputParams.m_CellToInputWeights, params.m_CellToInputWeights); |
| 4508 | VerifyConstTensors( |
| 4509 | "m_CellToForgetWeights", m_InputParams.m_CellToForgetWeights, params.m_CellToForgetWeights); |
| 4510 | VerifyConstTensors( |
| 4511 | "m_CellToOutputWeights", m_InputParams.m_CellToOutputWeights, params.m_CellToOutputWeights); |
| 4512 | VerifyConstTensors( |
| 4513 | "m_InputGateBias", m_InputParams.m_InputGateBias, params.m_InputGateBias); |
| 4514 | VerifyConstTensors( |
| 4515 | "m_ForgetGateBias", m_InputParams.m_ForgetGateBias, params.m_ForgetGateBias); |
| 4516 | VerifyConstTensors( |
| 4517 | "m_CellBias", m_InputParams.m_CellBias, params.m_CellBias); |
| 4518 | VerifyConstTensors( |
| 4519 | "m_OutputGateBias", m_InputParams.m_OutputGateBias, params.m_OutputGateBias); |
| 4520 | VerifyConstTensors( |
| 4521 | "m_ProjectionWeights", m_InputParams.m_ProjectionWeights, params.m_ProjectionWeights); |
| 4522 | VerifyConstTensors( |
| 4523 | "m_ProjectionBias", m_InputParams.m_ProjectionBias, params.m_ProjectionBias); |
| 4524 | VerifyConstTensors( |
| 4525 | "m_InputLayerNormWeights", m_InputParams.m_InputLayerNormWeights, params.m_InputLayerNormWeights); |
| 4526 | VerifyConstTensors( |
| 4527 | "m_ForgetLayerNormWeights", m_InputParams.m_ForgetLayerNormWeights, params.m_ForgetLayerNormWeights); |
| 4528 | VerifyConstTensors( |
| 4529 | "m_CellLayerNormWeights", m_InputParams.m_CellLayerNormWeights, params.m_CellLayerNormWeights); |
| 4530 | VerifyConstTensors( |
| 4531 | "m_OutputLayerNormWeights", m_InputParams.m_OutputLayerNormWeights, params.m_OutputLayerNormWeights); |
| 4532 | } |
| 4533 | |
| 4534 | private: |
| 4535 | armnn::LstmInputParams m_InputParams; |
| 4536 | }; |
| 4537 | |
| 4538 | BOOST_AUTO_TEST_CASE(SerializeDeserializeQLstmBasic) |
| 4539 | { |
| 4540 | armnn::QLstmDescriptor descriptor; |
| 4541 | |
| 4542 | descriptor.m_CifgEnabled = true; |
| 4543 | descriptor.m_ProjectionEnabled = false; |
| 4544 | descriptor.m_PeepholeEnabled = false; |
| 4545 | descriptor.m_LayerNormEnabled = false; |
| 4546 | |
| 4547 | descriptor.m_CellClip = 0.0f; |
| 4548 | descriptor.m_ProjectionClip = 0.0f; |
| 4549 | |
| 4550 | descriptor.m_InputIntermediateScale = 0.00001f; |
| 4551 | descriptor.m_ForgetIntermediateScale = 0.00001f; |
| 4552 | descriptor.m_CellIntermediateScale = 0.00001f; |
| 4553 | descriptor.m_OutputIntermediateScale = 0.00001f; |
| 4554 | |
| 4555 | descriptor.m_HiddenStateScale = 0.07f; |
| 4556 | descriptor.m_HiddenStateZeroPoint = 0; |
| 4557 | |
| 4558 | const unsigned int numBatches = 2; |
| 4559 | const unsigned int inputSize = 5; |
| 4560 | const unsigned int outputSize = 4; |
| 4561 | const unsigned int numUnits = 4; |
| 4562 | |
| 4563 | // Scale/Offset quantization info |
| 4564 | float inputScale = 0.0078f; |
| 4565 | int32_t inputOffset = 0; |
| 4566 | |
| 4567 | float outputScale = 0.0078f; |
| 4568 | int32_t outputOffset = 0; |
| 4569 | |
| 4570 | float cellStateScale = 3.5002e-05f; |
| 4571 | int32_t cellStateOffset = 0; |
| 4572 | |
| 4573 | float weightsScale = 0.007f; |
| 4574 | int32_t weightsOffset = 0; |
| 4575 | |
| 4576 | float biasScale = 3.5002e-05f / 1024; |
| 4577 | int32_t biasOffset = 0; |
| 4578 | |
| 4579 | // Weights and bias tensor and quantization info |
| 4580 | armnn::TensorInfo inputWeightsInfo({numUnits, inputSize}, |
| 4581 | armnn::DataType::QSymmS8, |
| 4582 | weightsScale, |
| 4583 | weightsOffset); |
| 4584 | |
| 4585 | armnn::TensorInfo recurrentWeightsInfo({numUnits, outputSize}, |
| 4586 | armnn::DataType::QSymmS8, |
| 4587 | weightsScale, |
| 4588 | weightsOffset); |
| 4589 | |
| 4590 | armnn::TensorInfo biasInfo({numUnits}, armnn::DataType::Signed32, biasScale, biasOffset); |
| 4591 | |
| 4592 | std::vector<int8_t> inputToForgetWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements()); |
| 4593 | std::vector<int8_t> inputToCellWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements()); |
| 4594 | std::vector<int8_t> inputToOutputWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements()); |
| 4595 | |
| 4596 | armnn::ConstTensor inputToForgetWeights(inputWeightsInfo, inputToForgetWeightsData); |
| 4597 | armnn::ConstTensor inputToCellWeights(inputWeightsInfo, inputToCellWeightsData); |
| 4598 | armnn::ConstTensor inputToOutputWeights(inputWeightsInfo, inputToOutputWeightsData); |
| 4599 | |
| 4600 | std::vector<int8_t> recurrentToForgetWeightsData = |
| 4601 | GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements()); |
| 4602 | std::vector<int8_t> recurrentToCellWeightsData = |
| 4603 | GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements()); |
| 4604 | std::vector<int8_t> recurrentToOutputWeightsData = |
| 4605 | GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements()); |
| 4606 | |
| 4607 | armnn::ConstTensor recurrentToForgetWeights(recurrentWeightsInfo, recurrentToForgetWeightsData); |
| 4608 | armnn::ConstTensor recurrentToCellWeights(recurrentWeightsInfo, recurrentToCellWeightsData); |
| 4609 | armnn::ConstTensor recurrentToOutputWeights(recurrentWeightsInfo, recurrentToOutputWeightsData); |
| 4610 | |
| 4611 | std::vector<int32_t> forgetGateBiasData(numUnits, 1); |
| 4612 | std::vector<int32_t> cellBiasData(numUnits, 0); |
| 4613 | std::vector<int32_t> outputGateBiasData(numUnits, 0); |
| 4614 | |
| 4615 | armnn::ConstTensor forgetGateBias(biasInfo, forgetGateBiasData); |
| 4616 | armnn::ConstTensor cellBias(biasInfo, cellBiasData); |
| 4617 | armnn::ConstTensor outputGateBias(biasInfo, outputGateBiasData); |
| 4618 | |
| 4619 | // Set up params |
| 4620 | armnn::LstmInputParams params; |
| 4621 | params.m_InputToForgetWeights = &inputToForgetWeights; |
| 4622 | params.m_InputToCellWeights = &inputToCellWeights; |
| 4623 | params.m_InputToOutputWeights = &inputToOutputWeights; |
| 4624 | |
| 4625 | params.m_RecurrentToForgetWeights = &recurrentToForgetWeights; |
| 4626 | params.m_RecurrentToCellWeights = &recurrentToCellWeights; |
| 4627 | params.m_RecurrentToOutputWeights = &recurrentToOutputWeights; |
| 4628 | |
| 4629 | params.m_ForgetGateBias = &forgetGateBias; |
| 4630 | params.m_CellBias = &cellBias; |
| 4631 | params.m_OutputGateBias = &outputGateBias; |
| 4632 | |
| 4633 | // Create network |
| 4634 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 4635 | const std::string layerName("qLstm"); |
| 4636 | |
| 4637 | armnn::IConnectableLayer* const input = network->AddInputLayer(0); |
| 4638 | armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(1); |
| 4639 | armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(2); |
| 4640 | |
| 4641 | armnn::IConnectableLayer* const qLstmLayer = network->AddQLstmLayer(descriptor, params, layerName.c_str()); |
| 4642 | |
| 4643 | armnn::IConnectableLayer* const outputStateOut = network->AddOutputLayer(0); |
| 4644 | armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(1); |
| 4645 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(2); |
| 4646 | |
| 4647 | // Input/Output tensor info |
| 4648 | armnn::TensorInfo inputInfo({numBatches , inputSize}, |
| 4649 | armnn::DataType::QAsymmS8, |
| 4650 | inputScale, |
| 4651 | inputOffset); |
| 4652 | |
| 4653 | armnn::TensorInfo cellStateInfo({numBatches , numUnits}, |
| 4654 | armnn::DataType::QSymmS16, |
| 4655 | cellStateScale, |
| 4656 | cellStateOffset); |
| 4657 | |
| 4658 | armnn::TensorInfo outputStateInfo({numBatches , outputSize}, |
| 4659 | armnn::DataType::QAsymmS8, |
| 4660 | outputScale, |
| 4661 | outputOffset); |
| 4662 | |
| 4663 | // Connect input/output slots |
| 4664 | input->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(0)); |
| 4665 | input->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 4666 | |
| 4667 | outputStateIn->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(1)); |
| 4668 | outputStateIn->GetOutputSlot(0).SetTensorInfo(cellStateInfo); |
| 4669 | |
| 4670 | cellStateIn->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(2)); |
| 4671 | cellStateIn->GetOutputSlot(0).SetTensorInfo(outputStateInfo); |
| 4672 | |
| 4673 | qLstmLayer->GetOutputSlot(0).Connect(outputStateOut->GetInputSlot(0)); |
| 4674 | qLstmLayer->GetOutputSlot(0).SetTensorInfo(outputStateInfo); |
| 4675 | |
| 4676 | qLstmLayer->GetOutputSlot(1).Connect(cellStateOut->GetInputSlot(0)); |
| 4677 | qLstmLayer->GetOutputSlot(1).SetTensorInfo(cellStateInfo); |
| 4678 | |
| 4679 | qLstmLayer->GetOutputSlot(2).Connect(outputLayer->GetInputSlot(0)); |
| 4680 | qLstmLayer->GetOutputSlot(2).SetTensorInfo(outputStateInfo); |
| 4681 | |
| 4682 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 4683 | BOOST_CHECK(deserializedNetwork); |
| 4684 | |
| 4685 | VerifyQLstmLayer checker(layerName, |
| 4686 | {inputInfo, cellStateInfo, outputStateInfo}, |
| 4687 | {outputStateInfo, cellStateInfo, outputStateInfo}, |
| 4688 | descriptor, |
| 4689 | params); |
| 4690 | |
| 4691 | deserializedNetwork->Accept(checker); |
| 4692 | } |
| 4693 | |
| 4694 | BOOST_AUTO_TEST_CASE(SerializeDeserializeQLstmCifgLayerNorm) |
| 4695 | { |
| 4696 | armnn::QLstmDescriptor descriptor; |
| 4697 | |
| 4698 | // CIFG params are used when CIFG is disabled |
| 4699 | descriptor.m_CifgEnabled = true; |
| 4700 | descriptor.m_ProjectionEnabled = false; |
| 4701 | descriptor.m_PeepholeEnabled = false; |
| 4702 | descriptor.m_LayerNormEnabled = true; |
| 4703 | |
| 4704 | descriptor.m_CellClip = 0.0f; |
| 4705 | descriptor.m_ProjectionClip = 0.0f; |
| 4706 | |
| 4707 | descriptor.m_InputIntermediateScale = 0.00001f; |
| 4708 | descriptor.m_ForgetIntermediateScale = 0.00001f; |
| 4709 | descriptor.m_CellIntermediateScale = 0.00001f; |
| 4710 | descriptor.m_OutputIntermediateScale = 0.00001f; |
| 4711 | |
| 4712 | descriptor.m_HiddenStateScale = 0.07f; |
| 4713 | descriptor.m_HiddenStateZeroPoint = 0; |
| 4714 | |
| 4715 | const unsigned int numBatches = 2; |
| 4716 | const unsigned int inputSize = 5; |
| 4717 | const unsigned int outputSize = 4; |
| 4718 | const unsigned int numUnits = 4; |
| 4719 | |
| 4720 | // Scale/Offset quantization info |
| 4721 | float inputScale = 0.0078f; |
| 4722 | int32_t inputOffset = 0; |
| 4723 | |
| 4724 | float outputScale = 0.0078f; |
| 4725 | int32_t outputOffset = 0; |
| 4726 | |
| 4727 | float cellStateScale = 3.5002e-05f; |
| 4728 | int32_t cellStateOffset = 0; |
| 4729 | |
| 4730 | float weightsScale = 0.007f; |
| 4731 | int32_t weightsOffset = 0; |
| 4732 | |
| 4733 | float layerNormScale = 3.5002e-05f; |
| 4734 | int32_t layerNormOffset = 0; |
| 4735 | |
| 4736 | float biasScale = layerNormScale / 1024; |
| 4737 | int32_t biasOffset = 0; |
| 4738 | |
| 4739 | // Weights and bias tensor and quantization info |
| 4740 | armnn::TensorInfo inputWeightsInfo({numUnits, inputSize}, |
| 4741 | armnn::DataType::QSymmS8, |
| 4742 | weightsScale, |
| 4743 | weightsOffset); |
| 4744 | |
| 4745 | armnn::TensorInfo recurrentWeightsInfo({numUnits, outputSize}, |
| 4746 | armnn::DataType::QSymmS8, |
| 4747 | weightsScale, |
| 4748 | weightsOffset); |
| 4749 | |
| 4750 | armnn::TensorInfo biasInfo({numUnits}, |
| 4751 | armnn::DataType::Signed32, |
| 4752 | biasScale, |
| 4753 | biasOffset); |
| 4754 | |
| 4755 | armnn::TensorInfo layerNormWeightsInfo({numUnits}, |
| 4756 | armnn::DataType::QSymmS16, |
| 4757 | layerNormScale, |
| 4758 | layerNormOffset); |
| 4759 | |
| 4760 | // Mandatory params |
| 4761 | std::vector<int8_t> inputToForgetWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements()); |
| 4762 | std::vector<int8_t> inputToCellWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements()); |
| 4763 | std::vector<int8_t> inputToOutputWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements()); |
| 4764 | |
| 4765 | armnn::ConstTensor inputToForgetWeights(inputWeightsInfo, inputToForgetWeightsData); |
| 4766 | armnn::ConstTensor inputToCellWeights(inputWeightsInfo, inputToCellWeightsData); |
| 4767 | armnn::ConstTensor inputToOutputWeights(inputWeightsInfo, inputToOutputWeightsData); |
| 4768 | |
| 4769 | std::vector<int8_t> recurrentToForgetWeightsData = |
| 4770 | GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements()); |
| 4771 | std::vector<int8_t> recurrentToCellWeightsData = |
| 4772 | GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements()); |
| 4773 | std::vector<int8_t> recurrentToOutputWeightsData = |
| 4774 | GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements()); |
| 4775 | |
| 4776 | armnn::ConstTensor recurrentToForgetWeights(recurrentWeightsInfo, recurrentToForgetWeightsData); |
| 4777 | armnn::ConstTensor recurrentToCellWeights(recurrentWeightsInfo, recurrentToCellWeightsData); |
| 4778 | armnn::ConstTensor recurrentToOutputWeights(recurrentWeightsInfo, recurrentToOutputWeightsData); |
| 4779 | |
| 4780 | std::vector<int32_t> forgetGateBiasData(numUnits, 1); |
| 4781 | std::vector<int32_t> cellBiasData(numUnits, 0); |
| 4782 | std::vector<int32_t> outputGateBiasData(numUnits, 0); |
| 4783 | |
| 4784 | armnn::ConstTensor forgetGateBias(biasInfo, forgetGateBiasData); |
| 4785 | armnn::ConstTensor cellBias(biasInfo, cellBiasData); |
| 4786 | armnn::ConstTensor outputGateBias(biasInfo, outputGateBiasData); |
| 4787 | |
| 4788 | // Layer Norm |
| 4789 | std::vector<int16_t> forgetLayerNormWeightsData = |
| 4790 | GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements()); |
| 4791 | std::vector<int16_t> cellLayerNormWeightsData = |
| 4792 | GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements()); |
| 4793 | std::vector<int16_t> outputLayerNormWeightsData = |
| 4794 | GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements()); |
| 4795 | |
| 4796 | armnn::ConstTensor forgetLayerNormWeights(layerNormWeightsInfo, forgetLayerNormWeightsData); |
| 4797 | armnn::ConstTensor cellLayerNormWeights(layerNormWeightsInfo, cellLayerNormWeightsData); |
| 4798 | armnn::ConstTensor outputLayerNormWeights(layerNormWeightsInfo, outputLayerNormWeightsData); |
| 4799 | |
| 4800 | // Set up params |
| 4801 | armnn::LstmInputParams params; |
| 4802 | |
| 4803 | // Mandatory params |
| 4804 | params.m_InputToForgetWeights = &inputToForgetWeights; |
| 4805 | params.m_InputToCellWeights = &inputToCellWeights; |
| 4806 | params.m_InputToOutputWeights = &inputToOutputWeights; |
| 4807 | |
| 4808 | params.m_RecurrentToForgetWeights = &recurrentToForgetWeights; |
| 4809 | params.m_RecurrentToCellWeights = &recurrentToCellWeights; |
| 4810 | params.m_RecurrentToOutputWeights = &recurrentToOutputWeights; |
| 4811 | |
| 4812 | params.m_ForgetGateBias = &forgetGateBias; |
| 4813 | params.m_CellBias = &cellBias; |
| 4814 | params.m_OutputGateBias = &outputGateBias; |
| 4815 | |
| 4816 | // Layer Norm |
| 4817 | params.m_ForgetLayerNormWeights = &forgetLayerNormWeights; |
| 4818 | params.m_CellLayerNormWeights = &cellLayerNormWeights; |
| 4819 | params.m_OutputLayerNormWeights = &outputLayerNormWeights; |
| 4820 | |
| 4821 | // Create network |
| 4822 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 4823 | const std::string layerName("qLstm"); |
| 4824 | |
| 4825 | armnn::IConnectableLayer* const input = network->AddInputLayer(0); |
| 4826 | armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(1); |
| 4827 | armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(2); |
| 4828 | |
| 4829 | armnn::IConnectableLayer* const qLstmLayer = network->AddQLstmLayer(descriptor, params, layerName.c_str()); |
| 4830 | |
| 4831 | armnn::IConnectableLayer* const outputStateOut = network->AddOutputLayer(0); |
| 4832 | armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(1); |
| 4833 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(2); |
| 4834 | |
| 4835 | // Input/Output tensor info |
| 4836 | armnn::TensorInfo inputInfo({numBatches , inputSize}, |
| 4837 | armnn::DataType::QAsymmS8, |
| 4838 | inputScale, |
| 4839 | inputOffset); |
| 4840 | |
| 4841 | armnn::TensorInfo cellStateInfo({numBatches , numUnits}, |
| 4842 | armnn::DataType::QSymmS16, |
| 4843 | cellStateScale, |
| 4844 | cellStateOffset); |
| 4845 | |
| 4846 | armnn::TensorInfo outputStateInfo({numBatches , outputSize}, |
| 4847 | armnn::DataType::QAsymmS8, |
| 4848 | outputScale, |
| 4849 | outputOffset); |
| 4850 | |
| 4851 | // Connect input/output slots |
| 4852 | input->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(0)); |
| 4853 | input->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 4854 | |
| 4855 | outputStateIn->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(1)); |
| 4856 | outputStateIn->GetOutputSlot(0).SetTensorInfo(cellStateInfo); |
| 4857 | |
| 4858 | cellStateIn->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(2)); |
| 4859 | cellStateIn->GetOutputSlot(0).SetTensorInfo(outputStateInfo); |
| 4860 | |
| 4861 | qLstmLayer->GetOutputSlot(0).Connect(outputStateOut->GetInputSlot(0)); |
| 4862 | qLstmLayer->GetOutputSlot(0).SetTensorInfo(outputStateInfo); |
| 4863 | |
| 4864 | qLstmLayer->GetOutputSlot(1).Connect(cellStateOut->GetInputSlot(0)); |
| 4865 | qLstmLayer->GetOutputSlot(1).SetTensorInfo(cellStateInfo); |
| 4866 | |
| 4867 | qLstmLayer->GetOutputSlot(2).Connect(outputLayer->GetInputSlot(0)); |
| 4868 | qLstmLayer->GetOutputSlot(2).SetTensorInfo(outputStateInfo); |
| 4869 | |
| 4870 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 4871 | BOOST_CHECK(deserializedNetwork); |
| 4872 | |
| 4873 | VerifyQLstmLayer checker(layerName, |
| 4874 | {inputInfo, cellStateInfo, outputStateInfo}, |
| 4875 | {outputStateInfo, cellStateInfo, outputStateInfo}, |
| 4876 | descriptor, |
| 4877 | params); |
| 4878 | |
| 4879 | deserializedNetwork->Accept(checker); |
| 4880 | } |
| 4881 | |
| 4882 | BOOST_AUTO_TEST_CASE(SerializeDeserializeQLstmAdvanced) |
| 4883 | { |
| 4884 | armnn::QLstmDescriptor descriptor; |
| 4885 | |
| 4886 | descriptor.m_CifgEnabled = false; |
| 4887 | descriptor.m_ProjectionEnabled = true; |
| 4888 | descriptor.m_PeepholeEnabled = true; |
| 4889 | descriptor.m_LayerNormEnabled = true; |
| 4890 | |
| 4891 | descriptor.m_CellClip = 0.1f; |
| 4892 | descriptor.m_ProjectionClip = 0.1f; |
| 4893 | |
| 4894 | descriptor.m_InputIntermediateScale = 0.00001f; |
| 4895 | descriptor.m_ForgetIntermediateScale = 0.00001f; |
| 4896 | descriptor.m_CellIntermediateScale = 0.00001f; |
| 4897 | descriptor.m_OutputIntermediateScale = 0.00001f; |
| 4898 | |
| 4899 | descriptor.m_HiddenStateScale = 0.07f; |
| 4900 | descriptor.m_HiddenStateZeroPoint = 0; |
| 4901 | |
| 4902 | const unsigned int numBatches = 2; |
| 4903 | const unsigned int inputSize = 5; |
| 4904 | const unsigned int outputSize = 4; |
| 4905 | const unsigned int numUnits = 4; |
| 4906 | |
| 4907 | // Scale/Offset quantization info |
| 4908 | float inputScale = 0.0078f; |
| 4909 | int32_t inputOffset = 0; |
| 4910 | |
| 4911 | float outputScale = 0.0078f; |
| 4912 | int32_t outputOffset = 0; |
| 4913 | |
| 4914 | float cellStateScale = 3.5002e-05f; |
| 4915 | int32_t cellStateOffset = 0; |
| 4916 | |
| 4917 | float weightsScale = 0.007f; |
| 4918 | int32_t weightsOffset = 0; |
| 4919 | |
| 4920 | float layerNormScale = 3.5002e-05f; |
| 4921 | int32_t layerNormOffset = 0; |
| 4922 | |
| 4923 | float biasScale = layerNormScale / 1024; |
| 4924 | int32_t biasOffset = 0; |
| 4925 | |
| 4926 | // Weights and bias tensor and quantization info |
| 4927 | armnn::TensorInfo inputWeightsInfo({numUnits, inputSize}, |
| 4928 | armnn::DataType::QSymmS8, |
| 4929 | weightsScale, |
| 4930 | weightsOffset); |
| 4931 | |
| 4932 | armnn::TensorInfo recurrentWeightsInfo({numUnits, outputSize}, |
| 4933 | armnn::DataType::QSymmS8, |
| 4934 | weightsScale, |
| 4935 | weightsOffset); |
| 4936 | |
| 4937 | armnn::TensorInfo biasInfo({numUnits}, |
| 4938 | armnn::DataType::Signed32, |
| 4939 | biasScale, |
| 4940 | biasOffset); |
| 4941 | |
| 4942 | armnn::TensorInfo peepholeWeightsInfo({numUnits}, |
| 4943 | armnn::DataType::QSymmS16, |
| 4944 | weightsScale, |
| 4945 | weightsOffset); |
| 4946 | |
| 4947 | armnn::TensorInfo layerNormWeightsInfo({numUnits}, |
| 4948 | armnn::DataType::QSymmS16, |
| 4949 | layerNormScale, |
| 4950 | layerNormOffset); |
| 4951 | |
| 4952 | armnn::TensorInfo projectionWeightsInfo({outputSize, numUnits}, |
| 4953 | armnn::DataType::QSymmS8, |
| 4954 | weightsScale, |
| 4955 | weightsOffset); |
| 4956 | |
| 4957 | // Mandatory params |
| 4958 | std::vector<int8_t> inputToForgetWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements()); |
| 4959 | std::vector<int8_t> inputToCellWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements()); |
| 4960 | std::vector<int8_t> inputToOutputWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements()); |
| 4961 | |
| 4962 | armnn::ConstTensor inputToForgetWeights(inputWeightsInfo, inputToForgetWeightsData); |
| 4963 | armnn::ConstTensor inputToCellWeights(inputWeightsInfo, inputToCellWeightsData); |
| 4964 | armnn::ConstTensor inputToOutputWeights(inputWeightsInfo, inputToOutputWeightsData); |
| 4965 | |
| 4966 | std::vector<int8_t> recurrentToForgetWeightsData = |
| 4967 | GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements()); |
| 4968 | std::vector<int8_t> recurrentToCellWeightsData = |
| 4969 | GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements()); |
| 4970 | std::vector<int8_t> recurrentToOutputWeightsData = |
| 4971 | GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements()); |
| 4972 | |
| 4973 | armnn::ConstTensor recurrentToForgetWeights(recurrentWeightsInfo, recurrentToForgetWeightsData); |
| 4974 | armnn::ConstTensor recurrentToCellWeights(recurrentWeightsInfo, recurrentToCellWeightsData); |
| 4975 | armnn::ConstTensor recurrentToOutputWeights(recurrentWeightsInfo, recurrentToOutputWeightsData); |
| 4976 | |
| 4977 | std::vector<int32_t> forgetGateBiasData(numUnits, 1); |
| 4978 | std::vector<int32_t> cellBiasData(numUnits, 0); |
| 4979 | std::vector<int32_t> outputGateBiasData(numUnits, 0); |
| 4980 | |
| 4981 | armnn::ConstTensor forgetGateBias(biasInfo, forgetGateBiasData); |
| 4982 | armnn::ConstTensor cellBias(biasInfo, cellBiasData); |
| 4983 | armnn::ConstTensor outputGateBias(biasInfo, outputGateBiasData); |
| 4984 | |
| 4985 | // CIFG |
| 4986 | std::vector<int8_t> inputToInputWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements()); |
| 4987 | std::vector<int8_t> recurrentToInputWeightsData = |
| 4988 | GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements()); |
| 4989 | std::vector<int32_t> inputGateBiasData(numUnits, 1); |
| 4990 | |
| 4991 | armnn::ConstTensor inputToInputWeights(inputWeightsInfo, inputToInputWeightsData); |
| 4992 | armnn::ConstTensor recurrentToInputWeights(recurrentWeightsInfo, recurrentToInputWeightsData); |
| 4993 | armnn::ConstTensor inputGateBias(biasInfo, inputGateBiasData); |
| 4994 | |
| 4995 | // Peephole |
| 4996 | std::vector<int16_t> cellToInputWeightsData = GenerateRandomData<int16_t>(peepholeWeightsInfo.GetNumElements()); |
| 4997 | std::vector<int16_t> cellToForgetWeightsData = GenerateRandomData<int16_t>(peepholeWeightsInfo.GetNumElements()); |
| 4998 | std::vector<int16_t> cellToOutputWeightsData = GenerateRandomData<int16_t>(peepholeWeightsInfo.GetNumElements()); |
| 4999 | |
| 5000 | armnn::ConstTensor cellToInputWeights(peepholeWeightsInfo, cellToInputWeightsData); |
| 5001 | armnn::ConstTensor cellToForgetWeights(peepholeWeightsInfo, cellToForgetWeightsData); |
| 5002 | armnn::ConstTensor cellToOutputWeights(peepholeWeightsInfo, cellToOutputWeightsData); |
| 5003 | |
| 5004 | // Projection |
| 5005 | std::vector<int8_t> projectionWeightsData = GenerateRandomData<int8_t>(projectionWeightsInfo.GetNumElements()); |
| 5006 | std::vector<int32_t> projectionBiasData(outputSize, 1); |
| 5007 | |
| 5008 | armnn::ConstTensor projectionWeights(projectionWeightsInfo, projectionWeightsData); |
| 5009 | armnn::ConstTensor projectionBias(biasInfo, projectionBiasData); |
| 5010 | |
| 5011 | // Layer Norm |
| 5012 | std::vector<int16_t> inputLayerNormWeightsData = |
| 5013 | GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements()); |
| 5014 | std::vector<int16_t> forgetLayerNormWeightsData = |
| 5015 | GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements()); |
| 5016 | std::vector<int16_t> cellLayerNormWeightsData = |
| 5017 | GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements()); |
| 5018 | std::vector<int16_t> outputLayerNormWeightsData = |
| 5019 | GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements()); |
| 5020 | |
| 5021 | armnn::ConstTensor inputLayerNormWeights(layerNormWeightsInfo, inputLayerNormWeightsData); |
| 5022 | armnn::ConstTensor forgetLayerNormWeights(layerNormWeightsInfo, forgetLayerNormWeightsData); |
| 5023 | armnn::ConstTensor cellLayerNormWeights(layerNormWeightsInfo, cellLayerNormWeightsData); |
| 5024 | armnn::ConstTensor outputLayerNormWeights(layerNormWeightsInfo, outputLayerNormWeightsData); |
| 5025 | |
| 5026 | // Set up params |
| 5027 | armnn::LstmInputParams params; |
| 5028 | |
| 5029 | // Mandatory params |
| 5030 | params.m_InputToForgetWeights = &inputToForgetWeights; |
| 5031 | params.m_InputToCellWeights = &inputToCellWeights; |
| 5032 | params.m_InputToOutputWeights = &inputToOutputWeights; |
| 5033 | |
| 5034 | params.m_RecurrentToForgetWeights = &recurrentToForgetWeights; |
| 5035 | params.m_RecurrentToCellWeights = &recurrentToCellWeights; |
| 5036 | params.m_RecurrentToOutputWeights = &recurrentToOutputWeights; |
| 5037 | |
| 5038 | params.m_ForgetGateBias = &forgetGateBias; |
| 5039 | params.m_CellBias = &cellBias; |
| 5040 | params.m_OutputGateBias = &outputGateBias; |
| 5041 | |
| 5042 | // CIFG |
| 5043 | params.m_InputToInputWeights = &inputToInputWeights; |
| 5044 | params.m_RecurrentToInputWeights = &recurrentToInputWeights; |
| 5045 | params.m_InputGateBias = &inputGateBias; |
| 5046 | |
| 5047 | // Peephole |
| 5048 | params.m_CellToInputWeights = &cellToInputWeights; |
| 5049 | params.m_CellToForgetWeights = &cellToForgetWeights; |
| 5050 | params.m_CellToOutputWeights = &cellToOutputWeights; |
| 5051 | |
| 5052 | // Projection |
| 5053 | params.m_ProjectionWeights = &projectionWeights; |
| 5054 | params.m_ProjectionBias = &projectionBias; |
| 5055 | |
| 5056 | // Layer Norm |
| 5057 | params.m_InputLayerNormWeights = &inputLayerNormWeights; |
| 5058 | params.m_ForgetLayerNormWeights = &forgetLayerNormWeights; |
| 5059 | params.m_CellLayerNormWeights = &cellLayerNormWeights; |
| 5060 | params.m_OutputLayerNormWeights = &outputLayerNormWeights; |
| 5061 | |
| 5062 | // Create network |
| 5063 | armnn::INetworkPtr network = armnn::INetwork::Create(); |
| 5064 | const std::string layerName("qLstm"); |
| 5065 | |
| 5066 | armnn::IConnectableLayer* const input = network->AddInputLayer(0); |
| 5067 | armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(1); |
| 5068 | armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(2); |
| 5069 | |
| 5070 | armnn::IConnectableLayer* const qLstmLayer = network->AddQLstmLayer(descriptor, params, layerName.c_str()); |
| 5071 | |
| 5072 | armnn::IConnectableLayer* const outputStateOut = network->AddOutputLayer(0); |
| 5073 | armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(1); |
| 5074 | armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(2); |
| 5075 | |
| 5076 | // Input/Output tensor info |
| 5077 | armnn::TensorInfo inputInfo({numBatches , inputSize}, |
| 5078 | armnn::DataType::QAsymmS8, |
| 5079 | inputScale, |
| 5080 | inputOffset); |
| 5081 | |
| 5082 | armnn::TensorInfo cellStateInfo({numBatches , numUnits}, |
| 5083 | armnn::DataType::QSymmS16, |
| 5084 | cellStateScale, |
| 5085 | cellStateOffset); |
| 5086 | |
| 5087 | armnn::TensorInfo outputStateInfo({numBatches , outputSize}, |
| 5088 | armnn::DataType::QAsymmS8, |
| 5089 | outputScale, |
| 5090 | outputOffset); |
| 5091 | |
| 5092 | // Connect input/output slots |
| 5093 | input->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(0)); |
| 5094 | input->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| 5095 | |
| 5096 | outputStateIn->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(1)); |
| 5097 | outputStateIn->GetOutputSlot(0).SetTensorInfo(cellStateInfo); |
| 5098 | |
| 5099 | cellStateIn->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(2)); |
| 5100 | cellStateIn->GetOutputSlot(0).SetTensorInfo(outputStateInfo); |
| 5101 | |
| 5102 | qLstmLayer->GetOutputSlot(0).Connect(outputStateOut->GetInputSlot(0)); |
| 5103 | qLstmLayer->GetOutputSlot(0).SetTensorInfo(outputStateInfo); |
| 5104 | |
| 5105 | qLstmLayer->GetOutputSlot(1).Connect(cellStateOut->GetInputSlot(0)); |
| 5106 | qLstmLayer->GetOutputSlot(1).SetTensorInfo(cellStateInfo); |
| 5107 | |
| 5108 | qLstmLayer->GetOutputSlot(2).Connect(outputLayer->GetInputSlot(0)); |
| 5109 | qLstmLayer->GetOutputSlot(2).SetTensorInfo(outputStateInfo); |
| 5110 | |
| 5111 | armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); |
| 5112 | BOOST_CHECK(deserializedNetwork); |
| 5113 | |
| 5114 | VerifyQLstmLayer checker(layerName, |
| 5115 | {inputInfo, cellStateInfo, outputStateInfo}, |
| 5116 | {outputStateInfo, cellStateInfo, outputStateInfo}, |
| 5117 | descriptor, |
| 5118 | params); |
| 5119 | |
| 5120 | deserializedNetwork->Accept(checker); |
| 5121 | } |
| 5122 | |
Nattapat Chaimanowong | 30b0020 | 2019-02-20 17:31:34 +0000 | [diff] [blame] | 5123 | BOOST_AUTO_TEST_SUITE_END() |