6 #include "../Serializer.hpp" 18 #include <boost/test/unit_test.hpp> 25 #define DECLARE_LAYER_VERIFIER_CLASS(name) \ 26 class name##LayerVerifier : public LayerVerifierBase \ 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) {} \ 34 void Visit##name##Layer(const armnn::IConnectableLayer* layer, const char* name) override \ 36 VerifyNameAndConnections(layer, name); \ 40 #define DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(name) \ 41 class name##LayerVerifier : public LayerVerifierBaseWithDescriptor<armnn::name##Descriptor> \ 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) {} \ 51 void Visit##name##Layer(const armnn::IConnectableLayer* layer, \ 52 const armnn::name##Descriptor& descriptor, \ 53 const char* name) override \ 55 VerifyNameAndConnections(layer, name); \ 56 VerifyDescriptor(descriptor); \ 60 struct DefaultLayerVerifierPolicy
62 static void Apply(
const std::string)
64 BOOST_TEST_MESSAGE(
"Unexpected layer found in network");
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) {}
86 BOOST_TEST(name == m_LayerName.c_str());
91 for (
unsigned int i = 0; i < m_InputTensorInfos.size(); i++)
94 BOOST_CHECK(connectedOutput);
97 BOOST_TEST(connectedInfo.
GetShape() == m_InputTensorInfos[i].GetShape());
101 BOOST_TEST(connectedInfo.
GetQuantizationScale() == m_InputTensorInfos[i].GetQuantizationScale());
105 for (
unsigned int i = 0; i < m_OutputTensorInfos.size(); i++)
108 BOOST_TEST(outputInfo.
GetShape() == m_OutputTensorInfos[i].GetShape());
117 void VerifyConstTensors(
const std::string& tensorName,
121 if (expectedPtr ==
nullptr)
123 BOOST_CHECK_MESSAGE(actualPtr ==
nullptr, tensorName +
" should not exist");
127 BOOST_CHECK_MESSAGE(actualPtr !=
nullptr, tensorName +
" should have been set");
128 if (actualPtr !=
nullptr)
134 tensorName +
" shapes don't match");
137 tensorName +
" data types don't match");
140 tensorName +
" (GetNumBytes) data sizes do not match");
144 const char* expectedData =
static_cast<const char*
>(expectedPtr->
GetMemoryArea());
145 const char* actualData =
static_cast<const char*
>(actualPtr->
GetMemoryArea());
147 for (
unsigned int i = 0; i < expectedPtr->
GetNumBytes(); ++i)
149 same = expectedData[i] == actualData[i];
155 BOOST_CHECK_MESSAGE(same, tensorName +
" data does not match");
162 std::string m_LayerName;
163 std::vector<armnn::TensorInfo> m_InputTensorInfos;
164 std::vector<armnn::TensorInfo> m_OutputTensorInfos;
167 template<
typename Descriptor>
168 class LayerVerifierBaseWithDescriptor :
public LayerVerifierBase
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) {}
179 void VerifyDescriptor(
const Descriptor& descriptor)
181 BOOST_CHECK(descriptor == m_Descriptor);
184 Descriptor m_Descriptor;
188 void CompareConstTensorData(
const void* data1,
const void* data2,
unsigned int numElements)
190 T typedData1 =
static_cast<T
>(data1);
191 T typedData2 =
static_cast<T
>(data2);
192 BOOST_CHECK(typedData1);
193 BOOST_CHECK(typedData2);
195 for (
unsigned int i = 0; i < numElements; i++)
197 BOOST_TEST(typedData1[i] == typedData2[i]);
209 CompareConstTensorData<const float*>(
214 CompareConstTensorData<const uint8_t*>(
218 CompareConstTensorData<const int8_t*>(
222 CompareConstTensorData<const int32_t*>(
227 BOOST_TEST_MESSAGE(
"Unexpected datatype");
234 std::vector<std::uint8_t>
const serializerVector{serializerString.begin(), serializerString.end()};
235 return IDeserializer::Create()->CreateNetworkFromBinary(serializerVector);
243 std::stringstream stream;
246 std::string serializerString{stream.str()};
247 return serializerString;
250 template<
typename DataType>
251 static std::vector<DataType> GenerateRandomData(
size_t size)
253 constexpr
bool isIntegerType = std::is_integral<DataType>::value;
255 typename std::conditional<isIntegerType,
256 std::uniform_int_distribution<DataType>,
257 std::uniform_real_distribution<DataType>>::type;
259 static constexpr
DataType lowerLimit = std::numeric_limits<DataType>::min();
260 static constexpr
DataType upperLimit = std::numeric_limits<DataType>::max();
262 static Distribution distribution(lowerLimit, upperLimit);
263 static std::default_random_engine generator;
265 std::vector<DataType> randomData(size);
266 std::generate(randomData.begin(), randomData.end(), []() {
return distribution(generator); });
279 const std::string layerName(
"addition");
296 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
297 BOOST_CHECK(deserializedNetwork);
299 AdditionLayerVerifier verifier(layerName, {tensorInfo, tensorInfo}, {tensorInfo});
300 deserializedNetwork->Accept(verifier);
307 const std::string layerName(
"argminmax");
313 descriptor.m_Axis = 1;
326 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
327 BOOST_CHECK(deserializedNetwork);
329 ArgMinMaxLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor);
330 deserializedNetwork->Accept(verifier);
336 class BatchNormalizationLayerVerifier :
public LayerVerifierBaseWithDescriptor<Descriptor>
339 BatchNormalizationLayerVerifier(
const std::string& layerName,
340 const std::vector<armnn::TensorInfo>& inputInfos,
341 const std::vector<armnn::TensorInfo>& outputInfos,
342 const Descriptor& descriptor,
347 : LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor)
349 , m_Variance(variance)
354 const Descriptor& descriptor,
359 const char* name)
override 361 VerifyNameAndConnections(layer, name);
362 VerifyDescriptor(descriptor);
364 CompareConstTensor(mean, m_Mean);
365 CompareConstTensor(variance, m_Variance);
366 CompareConstTensor(beta, m_Beta);
367 CompareConstTensor(gamma, m_Gamma);
377 const std::string layerName(
"batchNormalization");
387 descriptor.
m_Eps = 0.0010000000475f;
390 std::vector<float> meanData({5.0});
391 std::vector<float> varianceData({2.0});
392 std::vector<float> betaData({1.0});
393 std::vector<float> gammaData({0.0});
403 network->AddBatchNormalizationLayer(descriptor, mean, variance, beta, gamma, layerName.c_str());
412 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
413 BOOST_CHECK(deserializedNetwork);
415 BatchNormalizationLayerVerifier verifier(
416 layerName, {inputInfo}, {outputInfo}, descriptor, mean, variance, beta, gamma);
417 deserializedNetwork->Accept(verifier);
424 const std::string layerName(
"spaceToBatchNd");
430 desc.m_BlockShape = {2, 2};
431 desc.m_Crops = {{0, 0}, {0, 0}};
444 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
445 BOOST_CHECK(deserializedNetwork);
447 BatchToSpaceNdLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc);
448 deserializedNetwork->Accept(verifier);
455 const std::string layerName(
"comparison");
478 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
479 BOOST_CHECK(deserializedNetwork);
481 ComparisonLayerVerifier verifier(layerName, { inputInfo, inputInfo }, { outputInfo }, descriptor);
482 deserializedNetwork->Accept(verifier);
487 class ConstantLayerVerifier :
public LayerVerifierBase
490 ConstantLayerVerifier(
const std::string& layerName,
491 const std::vector<armnn::TensorInfo>& inputInfos,
492 const std::vector<armnn::TensorInfo>& outputInfos,
494 : LayerVerifierBase(layerName, inputInfos, outputInfos)
495 , m_LayerInput(layerInput) {}
499 const char* name)
override 501 VerifyNameAndConnections(layer, name);
502 CompareConstTensor(input, m_LayerInput);
511 const std::string layerName(
"constant");
514 std::vector<float> constantData = GenerateRandomData<float>(info.GetNumElements());
531 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
532 BOOST_CHECK(deserializedNetwork);
534 ConstantLayerVerifier verifier(layerName, {}, {info}, constTensor);
535 deserializedNetwork->Accept(verifier);
541 class Convolution2dLayerVerifier :
public LayerVerifierBaseWithDescriptor<Descriptor>
544 Convolution2dLayerVerifier(
const std::string& layerName,
545 const std::vector<armnn::TensorInfo>& inputInfos,
546 const std::vector<armnn::TensorInfo>& outputInfos,
547 const Descriptor& descriptor,
550 : LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor)
552 , m_Biases(biases) {}
555 const Descriptor& descriptor,
558 const char* name)
override 560 VerifyNameAndConnections(layer, name);
561 VerifyDescriptor(descriptor);
564 CompareConstTensor(weights, m_Weights);
567 BOOST_CHECK(biases.
has_value() == descriptor.m_BiasEnabled);
568 BOOST_CHECK(biases.
has_value() == m_Biases.has_value());
570 if (biases.
has_value() && m_Biases.has_value())
572 CompareConstTensor(biases.
value(), m_Biases.value());
581 const std::string layerName(
"convolution2d");
588 std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements());
591 std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements());
609 network->AddConvolution2dLayer(descriptor,
621 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
622 BOOST_CHECK(deserializedNetwork);
624 Convolution2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases);
625 deserializedNetwork->Accept(verifier);
631 class Convolution2dLayerVerifier :
public LayerVerifierBaseWithDescriptor<Descriptor>
634 Convolution2dLayerVerifier(
const std::string& layerName,
635 const std::vector<armnn::TensorInfo>& inputInfos,
636 const std::vector<armnn::TensorInfo>& outputInfos,
637 const Descriptor& descriptor,
640 : LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor)
642 , m_Biases(biases) {}
645 const Descriptor& descriptor,
648 const char* name)
override 650 VerifyNameAndConnections(layer, name);
651 VerifyDescriptor(descriptor);
654 CompareConstTensor(weights, m_Weights);
657 BOOST_CHECK(biases.
has_value() == descriptor.m_BiasEnabled);
658 BOOST_CHECK(biases.
has_value() == m_Biases.has_value());
660 if (biases.
has_value() && m_Biases.has_value())
662 CompareConstTensor(biases.
value(), m_Biases.value());
671 using namespace armnn;
673 const std::string layerName(
"convolution2dWithPerAxis");
674 const TensorInfo inputInfo ({ 1, 3, 1, 2 }, DataType::QAsymmU8, 0.55f, 128);
675 const TensorInfo outputInfo({ 1, 3, 1, 3 }, DataType::QAsymmU8, 0.75f, 128);
677 const std::vector<float> quantScales{ 0.75f, 0.65f, 0.85f };
678 constexpr
unsigned int quantDimension = 0;
680 const TensorInfo kernelInfo({ 3, 1, 1, 2 }, DataType::QSymmS8, quantScales, quantDimension);
682 const std::vector<float> biasQuantScales{ 0.25f, 0.50f, 0.75f };
683 const TensorInfo biasInfo({ 3 }, DataType::Signed32, biasQuantScales, quantDimension);
685 std::vector<int8_t> kernelData = GenerateRandomData<int8_t>(kernelInfo.GetNumElements());
687 std::vector<int32_t> biasData = GenerateRandomData<int32_t>(biasInfo.GetNumElements());
703 network->AddConvolution2dLayer(descriptor,
715 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
716 BOOST_CHECK(deserializedNetwork);
718 Convolution2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases);
719 deserializedNetwork->Accept(verifier);
726 const std::string layerName(
"depthToSpace");
746 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
747 BOOST_CHECK(deserializedNetwork);
749 DepthToSpaceLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc);
750 deserializedNetwork->Accept(verifier);
756 class DepthwiseConvolution2dLayerVerifier :
public LayerVerifierBaseWithDescriptor<Descriptor>
759 DepthwiseConvolution2dLayerVerifier(
const std::string& layerName,
760 const std::vector<armnn::TensorInfo>& inputInfos,
761 const std::vector<armnn::TensorInfo>& outputInfos,
762 const Descriptor& descriptor,
765 LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor),
770 const Descriptor& descriptor,
773 const char* name)
override 775 VerifyNameAndConnections(layer, name);
776 VerifyDescriptor(descriptor);
779 CompareConstTensor(weights, m_Weights);
782 BOOST_CHECK(biases.
has_value() == descriptor.m_BiasEnabled);
783 BOOST_CHECK(biases.
has_value() == m_Biases.has_value());
785 if (biases.
has_value() && m_Biases.has_value())
787 CompareConstTensor(biases.
value(), m_Biases.value());
796 const std::string layerName(
"depwiseConvolution2d");
803 std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements());
806 std::vector<int32_t> biasesData = GenerateRandomData<int32_t>(biasesInfo.GetNumElements());
824 network->AddDepthwiseConvolution2dLayer(descriptor,
836 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
837 BOOST_CHECK(deserializedNetwork);
839 DepthwiseConvolution2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases);
840 deserializedNetwork->Accept(verifier);
846 class DepthwiseConvolution2dLayerVerifier :
public LayerVerifierBaseWithDescriptor<Descriptor>
849 DepthwiseConvolution2dLayerVerifier(
const std::string& layerName,
850 const std::vector<armnn::TensorInfo>& inputInfos,
851 const std::vector<armnn::TensorInfo>& outputInfos,
852 const Descriptor& descriptor,
855 LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor),
860 const Descriptor& descriptor,
863 const char* name)
override 865 VerifyNameAndConnections(layer, name);
866 VerifyDescriptor(descriptor);
869 CompareConstTensor(weights, m_Weights);
872 BOOST_CHECK(biases.
has_value() == descriptor.m_BiasEnabled);
873 BOOST_CHECK(biases.
has_value() == m_Biases.has_value());
875 if (biases.
has_value() && m_Biases.has_value())
877 CompareConstTensor(biases.
value(), m_Biases.value());
886 using namespace armnn;
888 const std::string layerName(
"depwiseConvolution2dWithPerAxis");
889 const TensorInfo inputInfo ({ 1, 3, 3, 2 }, DataType::QAsymmU8, 0.55f, 128);
890 const TensorInfo outputInfo({ 1, 2, 2, 4 }, DataType::QAsymmU8, 0.75f, 128);
892 const std::vector<float> quantScales{ 0.75f, 0.80f, 0.90f, 0.95f };
893 const unsigned int quantDimension = 0;
894 TensorInfo kernelInfo({ 2, 2, 2, 2 }, DataType::QSymmS8, quantScales, quantDimension);
896 const std::vector<float> biasQuantScales{ 0.25f, 0.35f, 0.45f, 0.55f };
897 constexpr
unsigned int biasQuantDimension = 0;
898 TensorInfo biasInfo({ 4 }, DataType::Signed32, biasQuantScales, biasQuantDimension);
900 std::vector<int8_t> kernelData = GenerateRandomData<int8_t>(kernelInfo.GetNumElements());
902 std::vector<int32_t> biasData = GenerateRandomData<int32_t>(biasInfo.GetNumElements());
920 network->AddDepthwiseConvolution2dLayer(descriptor,
932 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
933 BOOST_CHECK(deserializedNetwork);
935 DepthwiseConvolution2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases);
936 deserializedNetwork->Accept(verifier);
943 const std::string layerName(
"dequantize");
958 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
959 BOOST_CHECK(deserializedNetwork);
961 DequantizeLayerVerifier verifier(layerName, {inputInfo}, {outputInfo});
962 deserializedNetwork->Accept(verifier);
968 class DetectionPostProcessLayerVerifier :
public LayerVerifierBaseWithDescriptor<Descriptor>
971 DetectionPostProcessLayerVerifier(
const std::string& layerName,
972 const std::vector<armnn::TensorInfo>& inputInfos,
973 const std::vector<armnn::TensorInfo>& outputInfos,
974 const Descriptor& descriptor,
976 : LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor)
977 , m_Anchors(anchors) {}
980 const Descriptor& descriptor,
982 const char* name)
override 984 VerifyNameAndConnections(layer, name);
985 VerifyDescriptor(descriptor);
987 CompareConstTensor(anchors, m_Anchors);
994 const std::string layerName(
"detectionPostProcess");
996 const std::vector<armnn::TensorInfo> inputInfos({
1001 const std::vector<armnn::TensorInfo> outputInfos({
1022 const std::vector<float> anchorsData({
1023 0.5f, 0.5f, 1.0f, 1.0f,
1024 0.5f, 0.5f, 1.0f, 1.0f,
1025 0.5f, 0.5f, 1.0f, 1.0f,
1026 0.5f, 10.5f, 1.0f, 1.0f,
1027 0.5f, 10.5f, 1.0f, 1.0f,
1028 0.5f, 100.5f, 1.0f, 1.0f
1034 network->AddDetectionPostProcessLayer(descriptor, anchors, layerName.c_str());
1036 for (
unsigned int i = 0; i < 2; i++)
1043 for (
unsigned int i = 0; i < 4; i++)
1050 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1051 BOOST_CHECK(deserializedNetwork);
1053 DetectionPostProcessLayerVerifier verifier(layerName, inputInfos, outputInfos, descriptor, anchors);
1054 deserializedNetwork->Accept(verifier);
1061 const std::string layerName(
"division");
1078 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1079 BOOST_CHECK(deserializedNetwork);
1081 DivisionLayerVerifier verifier(layerName, {
info,
info}, {info});
1082 deserializedNetwork->Accept(verifier);
1085 class EqualLayerVerifier :
public LayerVerifierBase
1088 EqualLayerVerifier(
const std::string& layerName,
1089 const std::vector<armnn::TensorInfo>& inputInfos,
1090 const std::vector<armnn::TensorInfo>& outputInfos)
1091 : LayerVerifierBase(layerName, inputInfos, outputInfos) {}
1095 const char* name)
override 1097 VerifyNameAndConnections(layer, name);
1103 throw armnn::Exception(
"EqualLayer should have translated to ComparisonLayer");
1112 const std::string layerName(
"equal");
1129 equalLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
1133 equalLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
1135 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1136 BOOST_CHECK(deserializedNetwork);
1138 EqualLayerVerifier verifier(layerName, { inputInfo, inputInfo }, { outputInfo });
1139 deserializedNetwork->Accept(verifier);
1149 const std::vector<uint8_t> equalModel =
1151 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00,
1152 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
1153 0xCC, 0x01, 0x00, 0x00, 0x20, 0x01, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x02, 0x00,
1154 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,
1155 0x60, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B, 0x04, 0x00, 0x00, 0x00, 0xFE, 0xFE, 0xFF, 0xFF, 0x04, 0x00,
1156 0x00, 0x00, 0x06, 0xFF, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0xEA, 0xFE, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00,
1157 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00,
1158 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1159 0x64, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xB4, 0xFE, 0xFF, 0xFF, 0x00, 0x00,
1160 0x00, 0x13, 0x04, 0x00, 0x00, 0x00, 0x52, 0xFF, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x36, 0xFF, 0xFF, 0xFF,
1161 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x11, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x1C, 0x00,
1162 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x65, 0x71, 0x75, 0x61, 0x6C, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
1163 0x5C, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x34, 0xFF,
1164 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x92, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x04, 0x08, 0x00, 0x00, 0x00,
1165 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00,
1166 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x08, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00,
1167 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x00, 0x00,
1168 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0E, 0x00,
1169 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00,
1170 0x06, 0x00, 0x08, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0E, 0x00,
1171 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00,
1172 0x0E, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x14, 0x00, 0x0E, 0x00, 0x00, 0x00,
1173 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00,
1174 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
1175 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00,
1176 0x00, 0x00, 0x66, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1177 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x04, 0x00,
1178 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09,
1179 0x04, 0x00, 0x00, 0x00, 0xF6, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x0A, 0x00,
1180 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x14, 0x00, 0x00, 0x00,
1181 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x0E, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00,
1182 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1183 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0A, 0x00, 0x00, 0x00,
1184 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x08, 0x00,
1185 0x07, 0x00, 0x0C, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00,
1186 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
1187 0x04, 0x00, 0x00, 0x00
1190 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(std::string(equalModel.begin(), equalModel.end()));
1191 BOOST_CHECK(deserializedNetwork);
1198 EqualLayerVerifier verifier(
"equal", { inputInfo, inputInfo }, { outputInfo });
1199 deserializedNetwork->Accept(verifier);
1206 const std::string layerName(
"fill");
1223 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1224 BOOST_CHECK(deserializedNetwork);
1226 FillLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor);
1228 deserializedNetwork->Accept(verifier);
1235 const std::string layerName(
"floor");
1249 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1250 BOOST_CHECK(deserializedNetwork);
1252 FloorLayerVerifier verifier(layerName, {
info}, {
info});
1253 deserializedNetwork->Accept(verifier);
1259 class FullyConnectedLayerVerifier :
public LayerVerifierBaseWithDescriptor<Descriptor>
1262 FullyConnectedLayerVerifier(
const std::string& layerName,
1263 const std::vector<armnn::TensorInfo>& inputInfos,
1264 const std::vector<armnn::TensorInfo>& outputInfos,
1265 const Descriptor& descriptor,
1268 : LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor)
1273 const Descriptor& descriptor,
1276 const char* name)
override 1278 VerifyNameAndConnections(layer, name);
1279 VerifyDescriptor(descriptor);
1281 CompareConstTensor(weight, m_Weight);
1283 BOOST_TEST(bias.
has_value() == descriptor.m_BiasEnabled);
1284 BOOST_TEST(bias.
has_value() == m_Bias.has_value());
1286 if (bias.
has_value() && m_Bias.has_value())
1288 CompareConstTensor(bias.
value(), m_Bias.value());
1297 const std::string layerName(
"fullyConnected");
1303 std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements());
1304 std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements());
1315 network->AddFullyConnectedLayer(descriptor,
1327 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1328 BOOST_CHECK(deserializedNetwork);
1330 FullyConnectedLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases);
1331 deserializedNetwork->Accept(verifier);
1337 class GatherLayerVerifier :
public LayerVerifierBaseWithDescriptor<GatherDescriptor>
1340 GatherLayerVerifier(
const std::string& layerName,
1341 const std::vector<armnn::TensorInfo>& inputInfos,
1342 const std::vector<armnn::TensorInfo>& outputInfos,
1344 : LayerVerifierBaseWithDescriptor<GatherDescriptor>(layerName, inputInfos, outputInfos, descriptor) {}
1348 const char *name)
override 1350 VerifyNameAndConnections(layer, name);
1351 BOOST_CHECK(descriptor.
m_Axis == m_Descriptor.m_Axis);
1356 const char*)
override {}
1359 const std::string layerName(
"gather");
1366 paramsInfo.SetQuantizationScale(1.0f);
1367 paramsInfo.SetQuantizationOffset(0);
1368 outputInfo.SetQuantizationScale(1.0f);
1369 outputInfo.SetQuantizationOffset(0);
1371 const std::vector<int32_t>& indicesData = {7, 6, 5};
1388 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1389 BOOST_CHECK(deserializedNetwork);
1391 GatherLayerVerifier verifier(layerName, {paramsInfo, indicesInfo}, {outputInfo}, descriptor);
1392 deserializedNetwork->Accept(verifier);
1395 class GreaterLayerVerifier :
public LayerVerifierBase
1398 GreaterLayerVerifier(
const std::string& layerName,
1399 const std::vector<armnn::TensorInfo>& inputInfos,
1400 const std::vector<armnn::TensorInfo>& outputInfos)
1401 : LayerVerifierBase(layerName, inputInfos, outputInfos) {}
1405 const char* name)
override 1407 VerifyNameAndConnections(layer, name);
1413 throw armnn::Exception(
"GreaterLayer should have translated to ComparisonLayer");
1422 const std::string layerName(
"greater");
1439 equalLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
1443 equalLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
1445 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1446 BOOST_CHECK(deserializedNetwork);
1448 GreaterLayerVerifier verifier(layerName, { inputInfo, inputInfo }, { outputInfo });
1449 deserializedNetwork->Accept(verifier);
1459 const std::vector<uint8_t> greaterModel =
1461 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00,
1462 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
1463 0xCC, 0x01, 0x00, 0x00, 0x20, 0x01, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x02, 0x00,
1464 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,
1465 0x60, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B, 0x04, 0x00, 0x00, 0x00, 0xFE, 0xFE, 0xFF, 0xFF, 0x04, 0x00,
1466 0x00, 0x00, 0x06, 0xFF, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0xEA, 0xFE, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00,
1467 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00,
1468 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1469 0x64, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xB4, 0xFE, 0xFF, 0xFF, 0x00, 0x00,
1470 0x00, 0x19, 0x04, 0x00, 0x00, 0x00, 0x52, 0xFF, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x36, 0xFF, 0xFF, 0xFF,
1471 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x1C, 0x00,
1472 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x67, 0x72, 0x65, 0x61, 0x74, 0x65, 0x72, 0x00, 0x02, 0x00, 0x00, 0x00,
1473 0x5C, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x34, 0xFF,
1474 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x92, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x04, 0x08, 0x00, 0x00, 0x00,
1475 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00,
1476 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x08, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00,
1477 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x00, 0x00,
1478 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0E, 0x00,
1479 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00,
1480 0x06, 0x00, 0x08, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0E, 0x00,
1481 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00,
1482 0x0E, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x14, 0x00, 0x0E, 0x00, 0x00, 0x00,
1483 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00,
1484 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
1485 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00,
1486 0x00, 0x00, 0x66, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1487 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00,
1488 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09,
1489 0x04, 0x00, 0x00, 0x00, 0xF6, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x0A, 0x00,
1490 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x14, 0x00, 0x00, 0x00,
1491 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x0E, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00,
1492 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1493 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0A, 0x00, 0x00, 0x00,
1494 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x08, 0x00,
1495 0x07, 0x00, 0x0C, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00,
1496 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
1497 0x02, 0x00, 0x00, 0x00
1500 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(std::string(greaterModel.begin(), greaterModel.end()));
1501 BOOST_CHECK(deserializedNetwork);
1508 GreaterLayerVerifier verifier(
"greater", { inputInfo, inputInfo }, { outputInfo });
1509 deserializedNetwork->Accept(verifier);
1516 const std::string layerName(
"instanceNormalization");
1521 descriptor.m_Beta = 0.1f;
1522 descriptor.m_Eps = 0.0001f;
1528 network->AddInstanceNormalizationLayer(descriptor, layerName.c_str());
1537 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1538 BOOST_CHECK(deserializedNetwork);
1540 InstanceNormalizationLayerVerifier verifier(layerName, {
info}, {
info}, descriptor);
1541 deserializedNetwork->Accept(verifier);
1548 const std::string l2NormLayerName(
"l2Normalization");
1553 desc.m_Eps = 0.0001f;
1566 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1567 BOOST_CHECK(deserializedNetwork);
1569 L2NormalizationLayerVerifier verifier(l2NormLayerName, {
info}, {
info}, desc);
1570 deserializedNetwork->Accept(verifier);
1580 const std::vector<uint8_t> l2NormalizationModel =
1582 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00,
1583 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,
1584 0x3C, 0x01, 0x00, 0x00, 0x74, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00,
1585 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0xE8, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B,
1586 0x04, 0x00, 0x00, 0x00, 0xD6, 0xFE, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x08, 0x00,
1587 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x9E, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00,
1588 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00,
1589 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1590 0x4C, 0xFF, 0xFF, 0xFF, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x44, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
1591 0x00, 0x20, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00,
1592 0x20, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x06, 0x00, 0x04, 0x00, 0x00, 0x00, 0x00, 0x00,
1593 0x0E, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x14, 0x00, 0x0E, 0x00, 0x00, 0x00,
1594 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x1F, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00, 0x20, 0x00,
1595 0x00, 0x00, 0x0F, 0x00, 0x00, 0x00, 0x6C, 0x32, 0x4E, 0x6F, 0x72, 0x6D, 0x61, 0x6C, 0x69, 0x7A, 0x61, 0x74,
1596 0x69, 0x6F, 0x6E, 0x00, 0x01, 0x00, 0x00, 0x00, 0x48, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00,
1597 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
1598 0x52, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x04, 0x00,
1599 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00,
1600 0x08, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1601 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09,
1602 0x04, 0x00, 0x00, 0x00, 0xF6, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x0A, 0x00,
1603 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x14, 0x00, 0x00, 0x00,
1604 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x0E, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00,
1605 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1606 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0A, 0x00, 0x00, 0x00,
1607 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x08, 0x00,
1608 0x07, 0x00, 0x0C, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00,
1609 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
1610 0x05, 0x00, 0x00, 0x00, 0x00
1614 DeserializeNetwork(std::string(l2NormalizationModel.begin(), l2NormalizationModel.end()));
1615 BOOST_CHECK(deserializedNetwork);
1617 const std::string layerName(
"l2Normalization");
1623 desc.m_Eps = 1e-12f;
1625 L2NormalizationLayerVerifier verifier(layerName, {inputInfo}, {inputInfo}, desc);
1626 deserializedNetwork->Accept(verifier);
1633 const std::string layerName(
"log_softmax");
1637 descriptor.
m_Beta = 1.0f;
1638 descriptor.m_Axis = -1;
1651 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1652 BOOST_CHECK(deserializedNetwork);
1654 LogSoftmaxLayerVerifier verifier(layerName, {
info}, {
info}, descriptor);
1655 deserializedNetwork->Accept(verifier);
1662 const std::string layerName(
"maximum");
1679 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1680 BOOST_CHECK(deserializedNetwork);
1682 MaximumLayerVerifier verifier(layerName, {
info,
info}, {info});
1683 deserializedNetwork->Accept(verifier);
1690 const std::string layerName(
"mean");
1695 descriptor.
m_Axis = { 2 };
1696 descriptor.m_KeepDims =
true;
1709 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1710 BOOST_CHECK(deserializedNetwork);
1712 MeanLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor);
1713 deserializedNetwork->Accept(verifier);
1720 const std::string layerName(
"merge");
1737 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1738 BOOST_CHECK(deserializedNetwork);
1740 MergeLayerVerifier verifier(layerName, {
info,
info}, {info});
1741 deserializedNetwork->Accept(verifier);
1744 class MergerLayerVerifier :
public LayerVerifierBaseWithDescriptor<armnn::OriginsDescriptor>
1747 MergerLayerVerifier(
const std::string& layerName,
1748 const std::vector<armnn::TensorInfo>& inputInfos,
1749 const std::vector<armnn::TensorInfo>& outputInfos,
1751 : LayerVerifierBaseWithDescriptor<armnn::OriginsDescriptor>(layerName, inputInfos, outputInfos, descriptor) {}
1755 const char*)
override 1757 throw armnn::Exception(
"MergerLayer should have translated to ConcatLayer");
1762 const char* name)
override 1764 VerifyNameAndConnections(layer, name);
1765 VerifyDescriptor(descriptor);
1774 const std::string layerName(
"merger");
1778 const std::vector<armnn::TensorShape> shapes({inputInfo.
GetShape(), inputInfo.
GetShape()});
1793 mergerLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
1797 mergerLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
1799 std::string mergerLayerNetwork = SerializeNetwork(*network);
1801 BOOST_CHECK(deserializedNetwork);
1803 MergerLayerVerifier verifier(layerName, {inputInfo, inputInfo}, {outputInfo}, descriptor);
1804 deserializedNetwork->Accept(verifier);
1814 const std::vector<uint8_t> mergerModel =
1816 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00,
1817 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
1818 0x38, 0x02, 0x00, 0x00, 0x8C, 0x01, 0x00, 0x00, 0x70, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x02, 0x00,
1819 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,
1820 0xF4, 0xFD, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B, 0x04, 0x00, 0x00, 0x00, 0x92, 0xFE, 0xFF, 0xFF, 0x04, 0x00,
1821 0x00, 0x00, 0x9A, 0xFE, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x7E, 0xFE, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00,
1822 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00,
1823 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1824 0xF8, 0xFE, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x48, 0xFE, 0xFF, 0xFF, 0x00, 0x00,
1825 0x00, 0x1F, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00,
1826 0x68, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00,
1827 0x0C, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
1828 0x02, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x22, 0xFF, 0xFF, 0xFF, 0x04, 0x00,
1829 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1830 0x00, 0x00, 0x00, 0x00, 0x3E, 0xFF, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x00, 0x00,
1831 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x36, 0xFF, 0xFF, 0xFF,
1832 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x1E, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x1C, 0x00,
1833 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x6D, 0x65, 0x72, 0x67, 0x65, 0x72, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
1834 0x5C, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x34, 0xFF,
1835 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x92, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00,
1836 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x02, 0x00,
1837 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x08, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00,
1838 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x00, 0x00,
1839 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0E, 0x00,
1840 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00,
1841 0x06, 0x00, 0x08, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0E, 0x00,
1842 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00,
1843 0x0E, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x14, 0x00, 0x0E, 0x00, 0x00, 0x00,
1844 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00,
1845 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
1846 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00,
1847 0x00, 0x00, 0x66, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1848 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00,
1849 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09,
1850 0x04, 0x00, 0x00, 0x00, 0xF6, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x0A, 0x00,
1851 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x14, 0x00, 0x00, 0x00,
1852 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x0E, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00,
1853 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1854 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0A, 0x00, 0x00, 0x00,
1855 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x08, 0x00,
1856 0x07, 0x00, 0x0C, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00,
1857 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
1858 0x02, 0x00, 0x00, 0x00
1861 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(std::string(mergerModel.begin(), mergerModel.end()));
1862 BOOST_CHECK(deserializedNetwork);
1867 const std::vector<armnn::TensorShape> shapes({inputInfo.
GetShape(), inputInfo.
GetShape()});
1872 MergerLayerVerifier verifier(
"merger", { inputInfo, inputInfo }, { outputInfo }, descriptor);
1873 deserializedNetwork->Accept(verifier);
1878 const std::string layerName(
"concat");
1882 const std::vector<armnn::TensorShape> shapes({inputInfo.
GetShape(), inputInfo.
GetShape()});
1901 std::string concatLayerNetwork = SerializeNetwork(*network);
1903 BOOST_CHECK(deserializedNetwork);
1907 MergerLayerVerifier verifier(layerName, {inputInfo, inputInfo}, {outputInfo}, descriptor);
1908 deserializedNetwork->Accept(verifier);
1915 const std::string layerName(
"minimum");
1932 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1933 BOOST_CHECK(deserializedNetwork);
1935 MinimumLayerVerifier verifier(layerName, {
info,
info}, {info});
1936 deserializedNetwork->Accept(verifier);
1943 const std::string layerName(
"multiplication");
1960 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1961 BOOST_CHECK(deserializedNetwork);
1963 MultiplicationLayerVerifier verifier(layerName, {
info,
info}, {info});
1964 deserializedNetwork->Accept(verifier);
1971 const std::string layerName(
"prelu");
1991 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1992 BOOST_CHECK(deserializedNetwork);
1994 PreluLayerVerifier verifier(layerName, {inputTensorInfo, alphaTensorInfo}, {outputTensorInfo});
1995 deserializedNetwork->Accept(verifier);
2002 const std::string layerName(
"normalization");
2007 desc.m_NormSize = 3;
2023 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2024 BOOST_CHECK(deserializedNetwork);
2026 NormalizationLayerVerifier verifier(layerName, {
info}, {
info}, desc);
2027 deserializedNetwork->Accept(verifier);
2034 const std::string layerName(
"pad");
2051 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2052 BOOST_CHECK(deserializedNetwork);
2054 PadLayerVerifier verifier(layerName, {inputTensorInfo}, {outputTensorInfo}, desc);
2055 deserializedNetwork->Accept(verifier);
2066 const std::vector<uint8_t> padModel =
2068 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00,
2069 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,
2070 0x54, 0x01, 0x00, 0x00, 0x6C, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00,
2071 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0xD0, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B,
2072 0x04, 0x00, 0x00, 0x00, 0x96, 0xFF, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x9E, 0xFF, 0xFF, 0xFF, 0x04, 0x00,
2073 0x00, 0x00, 0x72, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,
2074 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00,
2075 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x2C, 0xFF, 0xFF, 0xFF, 0x01, 0x00, 0x00, 0x00,
2076 0x00, 0x00, 0x00, 0x00, 0x24, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x16, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00,
2077 0x0E, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x4C, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00,
2078 0x00, 0x00, 0x06, 0x00, 0x08, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x08, 0x00,
2079 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
2080 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00,
2081 0x0E, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x14, 0x00, 0x0E, 0x00, 0x00, 0x00,
2082 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00,
2083 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x70, 0x61, 0x64, 0x00, 0x01, 0x00, 0x00, 0x00, 0x48, 0x00, 0x00, 0x00,
2084 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00,
2085 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x52, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00,
2086 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x05, 0x00,
2087 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00,
2088 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00,
2089 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x04, 0x00, 0x00, 0x00, 0xF6, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00,
2090 0x00, 0x00, 0x06, 0x00, 0x0A, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00,
2091 0x0E, 0x00, 0x14, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x0E, 0x00, 0x00, 0x00,
2092 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00,
2093 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00,
2094 0x08, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00,
2095 0x0A, 0x00, 0x10, 0x00, 0x08, 0x00, 0x07, 0x00, 0x0C, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01,
2096 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00,
2097 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x00
2100 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(std::string(padModel.begin(), padModel.end()));
2101 BOOST_CHECK(deserializedNetwork);
2108 PadLayerVerifier verifier(
"pad", { inputInfo }, { outputInfo }, descriptor);
2109 deserializedNetwork->Accept(verifier);
2116 const std::string layerName(
"permute");
2133 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2134 BOOST_CHECK(deserializedNetwork);
2136 PermuteLayerVerifier verifier(layerName, {inputTensorInfo}, {outputTensorInfo}, descriptor);
2137 deserializedNetwork->Accept(verifier);
2144 const std::string layerName(
"pooling2d");
2151 desc.m_PadBottom = 0;
2153 desc.m_PadRight = 0;
2157 desc.m_PoolHeight = 2;
2158 desc.m_PoolWidth = 2;
2173 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2174 BOOST_CHECK(deserializedNetwork);
2176 Pooling2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc);
2177 deserializedNetwork->Accept(verifier);
2184 const std::string layerName(
"quantize");
2198 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2199 BOOST_CHECK(deserializedNetwork);
2201 QuantizeLayerVerifier verifier(layerName, {
info}, {
info});
2202 deserializedNetwork->Accept(verifier);
2209 const std::string layerName(
"rank");
2224 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2225 BOOST_CHECK(deserializedNetwork);
2227 RankLayerVerifier verifier(layerName, {inputInfo}, {outputInfo});
2228 deserializedNetwork->Accept(verifier);
2235 const std::string layerName(
"reshape");
2252 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2253 BOOST_CHECK(deserializedNetwork);
2255 ReshapeLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor);
2256 deserializedNetwork->Accept(verifier);
2263 const std::string layerName(
"resize");
2269 desc.m_TargetHeight = 2;
2271 desc.m_AlignCorners =
true;
2272 desc.m_HalfPixelCenters =
true;
2285 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2286 BOOST_CHECK(deserializedNetwork);
2288 ResizeLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc);
2289 deserializedNetwork->Accept(verifier);
2292 class ResizeBilinearLayerVerifier :
public LayerVerifierBaseWithDescriptor<armnn::ResizeBilinearDescriptor>
2295 ResizeBilinearLayerVerifier(
const std::string& layerName,
2296 const std::vector<armnn::TensorInfo>& inputInfos,
2297 const std::vector<armnn::TensorInfo>& outputInfos,
2299 : LayerVerifierBaseWithDescriptor<armnn::ResizeBilinearDescriptor>(
2300 layerName, inputInfos, outputInfos, descriptor) {}
2304 const char* name)
override 2306 VerifyNameAndConnections(layer, name);
2309 BOOST_CHECK(descriptor.
m_TargetWidth == m_Descriptor.m_TargetWidth);
2310 BOOST_CHECK(descriptor.
m_TargetHeight == m_Descriptor.m_TargetHeight);
2311 BOOST_CHECK(descriptor.
m_DataLayout == m_Descriptor.m_DataLayout);
2312 BOOST_CHECK(descriptor.
m_AlignCorners == m_Descriptor.m_AlignCorners);
2318 const char*)
override 2320 throw armnn::Exception(
"ResizeBilinearLayer should have translated to ResizeLayer");
2329 const std::string layerName(
"resizeBilinear");
2335 desc.m_TargetHeight = 2u;
2336 desc.m_AlignCorners =
true;
2337 desc.m_HalfPixelCenters =
true;
2347 resizeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
2350 resizeLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
2352 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2353 BOOST_CHECK(deserializedNetwork);
2355 ResizeBilinearLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc);
2356 deserializedNetwork->Accept(verifier);
2366 const std::vector<uint8_t> resizeBilinearModel =
2368 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00,
2369 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,
2370 0x50, 0x01, 0x00, 0x00, 0x74, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00,
2371 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0xD4, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B,
2372 0x04, 0x00, 0x00, 0x00, 0xC2, 0xFE, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x08, 0x00,
2373 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x8A, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00,
2374 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00,
2375 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
2376 0x38, 0xFF, 0xFF, 0xFF, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x30, 0xFF, 0xFF, 0xFF, 0x00, 0x00,
2377 0x00, 0x1A, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0E, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00,
2378 0x34, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x12, 0x00, 0x08, 0x00, 0x0C, 0x00,
2379 0x07, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x04, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
2380 0x00, 0x00, 0x0E, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x14, 0x00, 0x0E, 0x00,
2381 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x19, 0x00, 0x00, 0x00, 0x1C, 0x00, 0x00, 0x00,
2382 0x20, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x00, 0x00, 0x72, 0x65, 0x73, 0x69, 0x7A, 0x65, 0x42, 0x69, 0x6C, 0x69,
2383 0x6E, 0x65, 0x61, 0x72, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x48, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
2384 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00,
2385 0x00, 0x00, 0x52, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
2386 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x04, 0x00,
2387 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
2388 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00,
2389 0x00, 0x09, 0x04, 0x00, 0x00, 0x00, 0xF6, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00,
2390 0x0A, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x14, 0x00,
2391 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x0E, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
2392 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
2393 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0A, 0x00,
2394 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00,
2395 0x08, 0x00, 0x07, 0x00, 0x0C, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00,
2396 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x05, 0x00,
2397 0x00, 0x00, 0x05, 0x00, 0x00, 0x00
2401 DeserializeNetwork(std::string(resizeBilinearModel.begin(), resizeBilinearModel.end()));
2402 BOOST_CHECK(deserializedNetwork);
2409 descriptor.m_TargetHeight = 2u;
2411 ResizeBilinearLayerVerifier verifier(
"resizeBilinear", { inputInfo }, { outputInfo }, descriptor);
2412 deserializedNetwork->Accept(verifier);
2419 const std::string layerName{
"slice"};
2438 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2439 BOOST_CHECK(deserializedNetwork);
2441 SliceLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor);
2442 deserializedNetwork->Accept(verifier);
2449 const std::string layerName(
"softmax");
2453 descriptor.
m_Beta = 1.0f;
2466 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2467 BOOST_CHECK(deserializedNetwork);
2469 SoftmaxLayerVerifier verifier(layerName, {
info}, {
info}, descriptor);
2470 deserializedNetwork->Accept(verifier);
2477 const std::string layerName(
"spaceToBatchNd");
2483 desc.m_BlockShape = {2, 2};
2484 desc.m_PadList = {{0, 0}, {2, 0}};
2497 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2498 BOOST_CHECK(deserializedNetwork);
2500 SpaceToBatchNdLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc);
2501 deserializedNetwork->Accept(verifier);
2508 const std::string layerName(
"spaceToDepth");
2528 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2529 BOOST_CHECK(deserializedNetwork);
2531 SpaceToDepthLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc);
2532 deserializedNetwork->Accept(verifier);
2539 const unsigned int numViews = 3;
2540 const unsigned int numDimensions = 4;
2541 const unsigned int inputShape[] = {1, 18, 4, 4};
2542 const unsigned int outputShape[] = {1, 6, 4, 4};
2545 unsigned int splitterDimSizes[4] = {
static_cast<unsigned int>(inputShape[0]),
2546 static_cast<unsigned int>(inputShape[1]),
2547 static_cast<unsigned int>(inputShape[2]),
2548 static_cast<unsigned int>(inputShape[3])};
2549 splitterDimSizes[1] /= numViews;
2552 for (
unsigned int g = 0; g < numViews; ++g)
2556 for (
unsigned int dimIdx=0; dimIdx < 4; dimIdx++)
2558 desc.
SetViewSize(g, dimIdx, splitterDimSizes[dimIdx]);
2562 const std::string layerName(
"splitter");
2583 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2584 BOOST_CHECK(deserializedNetwork);
2586 SplitterLayerVerifier verifier(layerName, {inputInfo}, {outputInfo, outputInfo, outputInfo}, desc);
2587 deserializedNetwork->Accept(verifier);
2594 const std::string layerName(
"stack");
2615 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2616 BOOST_CHECK(deserializedNetwork);
2618 StackLayerVerifier verifier(layerName, {inputTensorInfo, inputTensorInfo}, {outputTensorInfo}, descriptor);
2619 deserializedNetwork->Accept(verifier);
2626 const std::string layerName(
"standIn");
2650 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2651 BOOST_CHECK(deserializedNetwork);
2653 StandInLayerVerifier verifier(layerName, { tensorInfo, tensorInfo }, { tensorInfo, tensorInfo }, descriptor);
2654 deserializedNetwork->Accept(verifier);
2661 const std::string layerName(
"stridedSlice");
2665 armnn::StridedSliceDescriptor desc({0, 0, 1, 0}, {1, 1, 1, 1}, {1, 1, 1, 1});
2667 desc.m_ShrinkAxisMask = (1 << 1) | (1 << 2);
2681 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2682 BOOST_CHECK(deserializedNetwork);
2684 StridedSliceLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc);
2685 deserializedNetwork->Accept(verifier);
2692 const std::string layerName(
"subtraction");
2709 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2710 BOOST_CHECK(deserializedNetwork);
2712 SubtractionLayerVerifier verifier(layerName, {
info,
info}, {info});
2713 deserializedNetwork->Accept(verifier);
2718 class SwitchLayerVerifier :
public LayerVerifierBase
2721 SwitchLayerVerifier(
const std::string& layerName,
2722 const std::vector<armnn::TensorInfo>& inputInfos,
2723 const std::vector<armnn::TensorInfo>& outputInfos)
2724 : LayerVerifierBase(layerName, inputInfos, outputInfos) {}
2728 VerifyNameAndConnections(layer, name);
2733 const char*)
override {}
2736 const std::string layerName(
"switch");
2739 std::vector<float> constantData = GenerateRandomData<float>(
info.GetNumElements());
2759 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2760 BOOST_CHECK(deserializedNetwork);
2762 SwitchLayerVerifier verifier(layerName, {
info,
info}, {info, info});
2763 deserializedNetwork->Accept(verifier);
2770 const std::string layerName(
"transpose");
2787 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2788 BOOST_CHECK(deserializedNetwork);
2790 TransposeLayerVerifier verifier(layerName, {inputTensorInfo}, {outputTensorInfo}, descriptor);
2791 deserializedNetwork->Accept(verifier);
2797 class TransposeConvolution2dLayerVerifier :
public LayerVerifierBaseWithDescriptor<Descriptor>
2800 TransposeConvolution2dLayerVerifier(
const std::string& layerName,
2801 const std::vector<armnn::TensorInfo>& inputInfos,
2802 const std::vector<armnn::TensorInfo>& outputInfos,
2803 const Descriptor& descriptor,
2806 : LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor)
2807 , m_Weights(weights)
2812 const Descriptor& descriptor,
2815 const char* name)
override 2817 VerifyNameAndConnections(layer, name);
2818 VerifyDescriptor(descriptor);
2821 CompareConstTensor(weights, m_Weights);
2824 BOOST_CHECK(biases.
has_value() == descriptor.m_BiasEnabled);
2825 BOOST_CHECK(biases.
has_value() == m_Biases.has_value());
2827 if (biases.
has_value() && m_Biases.has_value())
2829 CompareConstTensor(biases.
value(), m_Biases.value());
2838 const std::string layerName(
"transposeConvolution2d");
2845 std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements());
2848 std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements());
2864 network->AddTransposeConvolution2dLayer(descriptor,
2876 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2877 BOOST_CHECK(deserializedNetwork);
2879 TransposeConvolution2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases);
2880 deserializedNetwork->Accept(verifier);
2885 class ConstantLayerVerifier :
public LayerVerifierBase
2888 ConstantLayerVerifier(
const std::string& layerName,
2889 const std::vector<armnn::TensorInfo>& inputInfos,
2890 const std::vector<armnn::TensorInfo>& outputInfos,
2892 : LayerVerifierBase(layerName, inputInfos, outputInfos)
2893 , m_LayerInput(layerInput) {}
2897 const char* name)
override 2899 VerifyNameAndConnections(layer, name);
2900 CompareConstTensor(input, m_LayerInput);
2909 const std::string layerName(
"constant");
2912 std::vector<float> constantData = GenerateRandomData<float>(
info.GetNumElements());
2929 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2930 BOOST_CHECK(deserializedNetwork);
2932 ConstantLayerVerifier verifier(layerName, {}, {
info}, constTensor);
2933 deserializedNetwork->Accept(verifier);
2936 class VerifyLstmLayer :
public LayerVerifierBaseWithDescriptor<armnn::LstmDescriptor>
2939 VerifyLstmLayer(
const std::string& layerName,
2940 const std::vector<armnn::TensorInfo>& inputInfos,
2941 const std::vector<armnn::TensorInfo>& outputInfos,
2944 : LayerVerifierBaseWithDescriptor<armnn::LstmDescriptor>(layerName, inputInfos, outputInfos, descriptor)
2945 , m_InputParams(inputParams) {}
2952 VerifyNameAndConnections(layer, name);
2953 VerifyDescriptor(descriptor);
2954 VerifyInputParameters(params);
2983 "m_InputGateBias", m_InputParams.m_InputGateBias, params.
m_InputGateBias);
2985 "m_ForgetGateBias", m_InputParams.m_ForgetGateBias, params.
m_ForgetGateBias);
2987 "m_CellBias", m_InputParams.m_CellBias, params.
m_CellBias);
2989 "m_OutputGateBias", m_InputParams.m_OutputGateBias, params.
m_OutputGateBias);
2993 "m_ProjectionBias", m_InputParams.m_ProjectionBias, params.
m_ProjectionBias);
3018 const uint32_t batchSize = 1;
3019 const uint32_t inputSize = 2;
3020 const uint32_t numUnits = 4;
3021 const uint32_t outputSize = numUnits;
3024 std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements());
3025 armnn::ConstTensor inputToForgetWeights(inputWeightsInfo1, inputToForgetWeightsData);
3027 std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements());
3030 std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements());
3031 armnn::ConstTensor inputToOutputWeights(inputWeightsInfo1, inputToOutputWeightsData);
3034 std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements());
3035 armnn::ConstTensor recurrentToForgetWeights(inputWeightsInfo2, recurrentToForgetWeightsData);
3037 std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements());
3038 armnn::ConstTensor recurrentToCellWeights(inputWeightsInfo2, recurrentToCellWeightsData);
3040 std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements());
3041 armnn::ConstTensor recurrentToOutputWeights(inputWeightsInfo2, recurrentToOutputWeightsData);
3044 std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo3.GetNumElements());
3047 std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo3.GetNumElements());
3050 std::vector<float> forgetGateBiasData(numUnits, 1.0f);
3053 std::vector<float> cellBiasData(numUnits, 0.0f);
3056 std::vector<float> outputGateBiasData(numUnits, 0.0f);
3076 const std::string layerName(
"lstm");
3110 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
3111 BOOST_CHECK(deserializedNetwork);
3113 VerifyLstmLayer checker(
3115 {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo},
3116 {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo},
3119 deserializedNetwork->Accept(checker);
3132 const uint32_t batchSize = 2;
3133 const uint32_t inputSize = 5;
3134 const uint32_t numUnits = 20;
3135 const uint32_t outputSize = 16;
3138 std::vector<float> inputToInputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
3141 std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
3144 std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
3147 std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
3151 std::vector<float> inputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3154 std::vector<float> forgetGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3157 std::vector<float> cellBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3160 std::vector<float> outputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3164 std::vector<float> recurrentToInputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
3165 armnn::ConstTensor recurrentToInputWeights(tensorInfo20x16, recurrentToInputWeightsData);
3167 std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
3168 armnn::ConstTensor recurrentToForgetWeights(tensorInfo20x16, recurrentToForgetWeightsData);
3170 std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
3171 armnn::ConstTensor recurrentToCellWeights(tensorInfo20x16, recurrentToCellWeightsData);
3173 std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
3174 armnn::ConstTensor recurrentToOutputWeights(tensorInfo20x16, recurrentToOutputWeightsData);
3176 std::vector<float> cellToInputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3179 std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3182 std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3186 std::vector<float> projectionWeightsData = GenerateRandomData<float>(tensorInfo16x20.GetNumElements());
3190 std::vector<float> projectionBiasData(outputSize, 0.f);
3222 const std::string layerName(
"lstm");
3256 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
3257 BOOST_CHECK(deserializedNetwork);
3259 VerifyLstmLayer checker(
3261 {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo},
3262 {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo},
3265 deserializedNetwork->Accept(checker);
3279 const uint32_t batchSize = 2;
3280 const uint32_t inputSize = 5;
3281 const uint32_t numUnits = 20;
3282 const uint32_t outputSize = 16;
3285 std::vector<float> inputToInputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
3288 std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
3291 std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
3294 std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
3298 std::vector<float> inputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3301 std::vector<float> forgetGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3304 std::vector<float> cellBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3307 std::vector<float> outputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3311 std::vector<float> recurrentToInputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
3312 armnn::ConstTensor recurrentToInputWeights(tensorInfo20x16, recurrentToInputWeightsData);
3314 std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
3315 armnn::ConstTensor recurrentToForgetWeights(tensorInfo20x16, recurrentToForgetWeightsData);
3317 std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
3318 armnn::ConstTensor recurrentToCellWeights(tensorInfo20x16, recurrentToCellWeightsData);
3320 std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
3321 armnn::ConstTensor recurrentToOutputWeights(tensorInfo20x16, recurrentToOutputWeightsData);
3323 std::vector<float> cellToInputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3326 std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3329 std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3333 std::vector<float> projectionWeightsData = GenerateRandomData<float>(tensorInfo16x20.GetNumElements());
3337 std::vector<float> projectionBiasData(outputSize, 0.f);
3340 std::vector<float> inputLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3343 std::vector<float> forgetLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3346 std::vector<float> cellLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3349 std::vector<float> outLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
3387 const std::string layerName(
"lstm");
3421 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
3422 BOOST_CHECK(deserializedNetwork);
3424 VerifyLstmLayer checker(
3426 {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo},
3427 {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo},
3430 deserializedNetwork->Accept(checker);
3439 const std::vector<uint8_t> lstmNoCifgWithPeepholeAndProjectionModel =
3441 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00,
3442 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x2C, 0x00, 0x00, 0x00, 0x38, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00,
3443 0xDC, 0x29, 0x00, 0x00, 0x38, 0x29, 0x00, 0x00, 0xB4, 0x28, 0x00, 0x00, 0x94, 0x01, 0x00, 0x00, 0x3C, 0x01,
3444 0x00, 0x00, 0xE0, 0x00, 0x00, 0x00, 0x84, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,
3445 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x04, 0x00,
3446 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x70, 0xD6, 0xFF, 0xFF,
3447 0x00, 0x00, 0x00, 0x0B, 0x04, 0x00, 0x00, 0x00, 0x06, 0xD7, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x88, 0xD7,
3448 0xFF, 0xFF, 0x08, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0xF6, 0xD6, 0xFF, 0xFF, 0x07, 0x00, 0x00, 0x00,
3449 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00,
3450 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
3451 0xE8, 0xD7, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0xC8, 0xD6, 0xFF, 0xFF, 0x00, 0x00,
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3980 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x7E, 0xFC, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x64, 0x00, 0x00, 0x00,
3981 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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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, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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3999 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
4000 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
4001 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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4003 0x00, 0x00, 0x00, 0x00, 0x1A, 0xFD, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00,
4004 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x10, 0x00, 0x0C, 0x00,
4005 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x06, 0x00, 0x07, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00,
4006 0x01, 0x01, 0x04, 0x00, 0x00, 0x00, 0x2E, 0xFE, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
4007 0x22, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6C, 0x73,
4008 0x74, 0x6D, 0x00, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0xEC, 0x00, 0x00, 0x00, 0xD0, 0x00, 0x00, 0x00,
4009 0xB4, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x88, 0x00, 0x00, 0x00, 0x5C, 0x00, 0x00, 0x00, 0x30, 0x00,
4010 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x14, 0xFF, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
4011 0xA6, 0xFD, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00,
4012 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x3C, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00,
4013 0x04, 0x00, 0x00, 0x00, 0xCE, 0xFD, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00,
4014 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x64, 0xFF, 0xFF, 0xFF,
4015 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xF6, 0xFD, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00,
4016 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
4017 0xB4, 0xFE, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x1A, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00,
4018 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x50, 0x00, 0x00, 0x00,
4019 0xF0, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00,
4020 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
4021 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00,
4022 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xE8, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x09, 0x04, 0x00, 0x00, 0x00,
4023 0x7E, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00,
4024 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x76, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00,
4025 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00,
4026 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
4027 0x68, 0xFF, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0xCE, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00,
4028 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
4029 0x08, 0x00, 0x0E, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x0C, 0x00,
4030 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x08, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00,
4031 0x08, 0x00, 0x0E, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x01, 0x00,
4032 0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x14, 0x00,
4033 0x0E, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00,
4034 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
4035 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00,
4036 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6E, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00,
4037 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x08, 0x00,
4038 0x0C, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x04, 0x00, 0x00, 0x00,
4039 0xF6, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x0A, 0x00, 0x04, 0x00, 0x06, 0x00,
4040 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x14, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00,
4041 0x0C, 0x00, 0x10, 0x00, 0x0E, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00,
4042 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
4043 0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00,
4044 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x08, 0x00, 0x07, 0x00, 0x0C, 0x00,
4045 0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00,
4046 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x00
4050 DeserializeNetwork(std::string(lstmNoCifgWithPeepholeAndProjectionModel.begin(),
4051 lstmNoCifgWithPeepholeAndProjectionModel.end()));
4053 BOOST_CHECK(deserializedNetwork);
4064 const uint32_t batchSize = 2u;
4065 const uint32_t inputSize = 5u;
4066 const uint32_t numUnits = 20u;
4067 const uint32_t outputSize = 16u;
4070 std::vector<float> inputToInputWeightsData(tensorInfo20x5.GetNumElements(), 0.0f);
4073 std::vector<float> inputToForgetWeightsData(tensorInfo20x5.GetNumElements(), 0.0f);
4076 std::vector<float> inputToCellWeightsData(tensorInfo20x5.GetNumElements(), 0.0f);
4079 std::vector<float> inputToOutputWeightsData(tensorInfo20x5.GetNumElements(), 0.0f);
4083 std::vector<float> inputGateBiasData(tensorInfo20.GetNumElements(), 0.0f);
4086 std::vector<float> forgetGateBiasData(tensorInfo20.GetNumElements(), 0.0f);
4089 std::vector<float> cellBiasData(tensorInfo20.GetNumElements(), 0.0f);
4092 std::vector<float> outputGateBiasData(tensorInfo20.GetNumElements(), 0.0f);
4096 std::vector<float> recurrentToInputWeightsData(tensorInfo20x16.GetNumElements(), 0.0f);
4097 armnn::ConstTensor recurrentToInputWeights(tensorInfo20x16, recurrentToInputWeightsData);
4099 std::vector<float> recurrentToForgetWeightsData(tensorInfo20x16.GetNumElements(), 0.0f);
4100 armnn::ConstTensor recurrentToForgetWeights(tensorInfo20x16, recurrentToForgetWeightsData);
4102 std::vector<float> recurrentToCellWeightsData(tensorInfo20x16.GetNumElements(), 0.0f);
4103 armnn::ConstTensor recurrentToCellWeights(tensorInfo20x16, recurrentToCellWeightsData);
4105 std::vector<float> recurrentToOutputWeightsData(tensorInfo20x16.GetNumElements(), 0.0f);
4106 armnn::ConstTensor recurrentToOutputWeights(tensorInfo20x16, recurrentToOutputWeightsData);
4108 std::vector<float> cellToInputWeightsData(tensorInfo20.GetNumElements(), 0.0f);
4111 std::vector<float> cellToForgetWeightsData(tensorInfo20.GetNumElements(), 0.0f);
4114 std::vector<float> cellToOutputWeightsData(tensorInfo20.GetNumElements(), 0.0f);
4118 std::vector<float> projectionWeightsData(tensorInfo16x20.GetNumElements(), 0.0f);
4122 std::vector<float> projectionBiasData(outputSize, 0.0f);
4150 const std::string layerName(
"lstm");
4156 VerifyLstmLayer checker(
4158 {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo},
4159 {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo},
4162 deserializedNetwork->Accept(checker);
4164 class VerifyQuantizedLstmLayer :
public LayerVerifierBase
4168 VerifyQuantizedLstmLayer(
const std::string& layerName,
4169 const std::vector<armnn::TensorInfo>& inputInfos,
4170 const std::vector<armnn::TensorInfo>& outputInfos,
4172 : LayerVerifierBase(layerName, inputInfos, outputInfos), m_InputParams(inputParams) {}
4178 VerifyNameAndConnections(layer, name);
4179 VerifyInputParameters(params);
4185 VerifyConstTensors(
"m_InputToInputWeights",
4187 VerifyConstTensors(
"m_InputToForgetWeights",
4189 VerifyConstTensors(
"m_InputToCellWeights",
4191 VerifyConstTensors(
"m_InputToOutputWeights",
4193 VerifyConstTensors(
"m_RecurrentToInputWeights",
4195 VerifyConstTensors(
"m_RecurrentToForgetWeights",
4197 VerifyConstTensors(
"m_RecurrentToCellWeights",
4199 VerifyConstTensors(
"m_RecurrentToOutputWeights",
4201 VerifyConstTensors(
"m_InputGateBias",
4203 VerifyConstTensors(
"m_ForgetGateBias",
4205 VerifyConstTensors(
"m_CellBias",
4206 m_InputParams.m_CellBias, params.
m_CellBias);
4207 VerifyConstTensors(
"m_OutputGateBias",
4217 const uint32_t batchSize = 1;
4218 const uint32_t inputSize = 2;
4219 const uint32_t numUnits = 4;
4220 const uint32_t outputSize = numUnits;
4223 float inputOutputScale = 0.0078125f;
4224 int32_t inputOutputOffset = 128;
4226 float cellStateScale = 0.00048828125f;
4227 int32_t cellStateOffset = 0;
4229 float weightsScale = 0.00408021f;
4230 int32_t weightsOffset = 100;
4232 float biasScale = 3.1876640625e-05f;
4233 int32_t biasOffset = 0;
4237 std::vector<uint8_t> inputToInputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8};
4242 armnn::ConstTensor inputToInputWeights(inputToInputWeightsInfo, inputToInputWeightsData);
4245 std::vector<uint8_t> inputToForgetWeightsData = {1, 2, 3, 4, 5, 6, 7, 8};
4250 armnn::ConstTensor inputToForgetWeights(inputToForgetWeightsInfo, inputToForgetWeightsData);
4253 std::vector<uint8_t> inputToCellWeightsData = {1, 2, 3, 4, 5, 6, 7, 8};
4258 armnn::ConstTensor inputToCellWeights(inputToCellWeightsInfo, inputToCellWeightsData);
4261 std::vector<uint8_t> inputToOutputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8};
4266 armnn::ConstTensor inputToOutputWeights(inputToOutputWeightsInfo, inputToOutputWeightsData);
4270 std::vector<uint8_t> recurrentToInputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16};
4275 armnn::ConstTensor recurrentToInputWeights(recurrentToInputWeightsInfo, recurrentToInputWeightsData);
4278 std::vector<uint8_t> recurrentToForgetWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16};
4283 armnn::ConstTensor recurrentToForgetWeights(recurrentToForgetWeightsInfo, recurrentToForgetWeightsData);
4286 std::vector<uint8_t> recurrentToCellWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16};
4291 armnn::ConstTensor recurrentToCellWeights(recurrentToCellWeightsInfo, recurrentToCellWeightsData);
4294 std::vector<uint8_t> recurrentToOutputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16};
4299 armnn::ConstTensor recurrentToOutputWeights(recurrentToOutputWeightsInfo, recurrentToOutputWeightsData);
4303 std::vector<int32_t> inputGateBiasData = {1, 2, 3, 4};
4311 std::vector<int32_t> forgetGateBiasData = {1, 2, 3, 4};
4319 std::vector<int32_t> cellBiasData = {1, 2, 3, 4};
4327 std::vector<int32_t> outputGateBiasData = {1, 2, 3, 4};
4352 const std::string layerName(
"QuantizedLstm");
4386 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
4387 BOOST_CHECK(deserializedNetwork);
4389 VerifyQuantizedLstmLayer checker(layerName,
4390 {inputTensorInfo, cellStateTensorInfo, outputStateTensorInfo},
4391 {cellStateTensorInfo, outputStateTensorInfo},
4394 deserializedNetwork->Accept(checker);
4397 class VerifyQLstmLayer :
public LayerVerifierBaseWithDescriptor<armnn::QLstmDescriptor>
4400 VerifyQLstmLayer(
const std::string& layerName,
4401 const std::vector<armnn::TensorInfo>& inputInfos,
4402 const std::vector<armnn::TensorInfo>& outputInfos,
4405 : LayerVerifierBaseWithDescriptor<armnn::QLstmDescriptor>(layerName, inputInfos, outputInfos, descriptor)
4406 , m_InputParams(inputParams) {}
4413 VerifyNameAndConnections(layer, name);
4414 VerifyDescriptor(descriptor);
4415 VerifyInputParameters(params);
4444 "m_InputGateBias", m_InputParams.m_InputGateBias, params.
m_InputGateBias);
4446 "m_ForgetGateBias", m_InputParams.m_ForgetGateBias, params.
m_ForgetGateBias);
4448 "m_CellBias", m_InputParams.m_CellBias, params.
m_CellBias);
4450 "m_OutputGateBias", m_InputParams.m_OutputGateBias, params.
m_OutputGateBias);
4454 "m_ProjectionBias", m_InputParams.m_ProjectionBias, params.
m_ProjectionBias);
4489 const unsigned int numBatches = 2;
4490 const unsigned int inputSize = 5;
4491 const unsigned int outputSize = 4;
4492 const unsigned int numUnits = 4;
4495 float inputScale = 0.0078f;
4496 int32_t inputOffset = 0;
4498 float outputScale = 0.0078f;
4499 int32_t outputOffset = 0;
4501 float cellStateScale = 3.5002e-05f;
4502 int32_t cellStateOffset = 0;
4504 float weightsScale = 0.007f;
4505 int32_t weightsOffset = 0;
4507 float biasScale = 3.5002e-05f / 1024;
4508 int32_t biasOffset = 0;
4523 std::vector<int8_t> inputToForgetWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
4524 std::vector<int8_t> inputToCellWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
4525 std::vector<int8_t> inputToOutputWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
4531 std::vector<int8_t> recurrentToForgetWeightsData =
4532 GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
4533 std::vector<int8_t> recurrentToCellWeightsData =
4534 GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
4535 std::vector<int8_t> recurrentToOutputWeightsData =
4536 GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
4538 armnn::ConstTensor recurrentToForgetWeights(recurrentWeightsInfo, recurrentToForgetWeightsData);
4539 armnn::ConstTensor recurrentToCellWeights(recurrentWeightsInfo, recurrentToCellWeightsData);
4540 armnn::ConstTensor recurrentToOutputWeights(recurrentWeightsInfo, recurrentToOutputWeightsData);
4542 std::vector<int32_t> forgetGateBiasData(numUnits, 1);
4543 std::vector<int32_t> cellBiasData(numUnits, 0);
4544 std::vector<int32_t> outputGateBiasData(numUnits, 0);
4566 const std::string layerName(
"qLstm");
4613 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
4614 BOOST_CHECK(deserializedNetwork);
4616 VerifyQLstmLayer checker(layerName,
4617 {inputInfo, cellStateInfo, outputStateInfo},
4618 {outputStateInfo, cellStateInfo, outputStateInfo},
4622 deserializedNetwork->Accept(checker);
4646 const unsigned int numBatches = 2;
4647 const unsigned int inputSize = 5;
4648 const unsigned int outputSize = 4;
4649 const unsigned int numUnits = 4;
4652 float inputScale = 0.0078f;
4653 int32_t inputOffset = 0;
4655 float outputScale = 0.0078f;
4656 int32_t outputOffset = 0;
4658 float cellStateScale = 3.5002e-05f;
4659 int32_t cellStateOffset = 0;
4661 float weightsScale = 0.007f;
4662 int32_t weightsOffset = 0;
4664 float layerNormScale = 3.5002e-05f;
4665 int32_t layerNormOffset = 0;
4667 float biasScale = layerNormScale / 1024;
4668 int32_t biasOffset = 0;
4692 std::vector<int8_t> inputToForgetWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
4693 std::vector<int8_t> inputToCellWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
4694 std::vector<int8_t> inputToOutputWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
4700 std::vector<int8_t> recurrentToForgetWeightsData =
4701 GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
4702 std::vector<int8_t> recurrentToCellWeightsData =
4703 GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
4704 std::vector<int8_t> recurrentToOutputWeightsData =
4705 GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
4707 armnn::ConstTensor recurrentToForgetWeights(recurrentWeightsInfo, recurrentToForgetWeightsData);
4708 armnn::ConstTensor recurrentToCellWeights(recurrentWeightsInfo, recurrentToCellWeightsData);
4709 armnn::ConstTensor recurrentToOutputWeights(recurrentWeightsInfo, recurrentToOutputWeightsData);
4711 std::vector<int32_t> forgetGateBiasData(numUnits, 1);
4712 std::vector<int32_t> cellBiasData(numUnits, 0);
4713 std::vector<int32_t> outputGateBiasData(numUnits, 0);
4720 std::vector<int16_t> forgetLayerNormWeightsData =
4721 GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements());
4722 std::vector<int16_t> cellLayerNormWeightsData =
4723 GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements());
4724 std::vector<int16_t> outputLayerNormWeightsData =
4725 GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements());
4727 armnn::ConstTensor forgetLayerNormWeights(layerNormWeightsInfo, forgetLayerNormWeightsData);
4728 armnn::ConstTensor cellLayerNormWeights(layerNormWeightsInfo, cellLayerNormWeightsData);
4729 armnn::ConstTensor outputLayerNormWeights(layerNormWeightsInfo, outputLayerNormWeightsData);
4754 const std::string layerName(
"qLstm");
4801 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
4802 BOOST_CHECK(deserializedNetwork);
4804 VerifyQLstmLayer checker(layerName,
4805 {inputInfo, cellStateInfo, outputStateInfo},
4806 {outputStateInfo, cellStateInfo, outputStateInfo},
4810 deserializedNetwork->Accept(checker);
4833 const unsigned int numBatches = 2;
4834 const unsigned int inputSize = 5;
4835 const unsigned int outputSize = 4;
4836 const unsigned int numUnits = 4;
4839 float inputScale = 0.0078f;
4840 int32_t inputOffset = 0;
4842 float outputScale = 0.0078f;
4843 int32_t outputOffset = 0;
4845 float cellStateScale = 3.5002e-05f;
4846 int32_t cellStateOffset = 0;
4848 float weightsScale = 0.007f;
4849 int32_t weightsOffset = 0;
4851 float layerNormScale = 3.5002e-05f;
4852 int32_t layerNormOffset = 0;
4854 float biasScale = layerNormScale / 1024;
4855 int32_t biasOffset = 0;
4889 std::vector<int8_t> inputToForgetWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
4890 std::vector<int8_t> inputToCellWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
4891 std::vector<int8_t> inputToOutputWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
4897 std::vector<int8_t> recurrentToForgetWeightsData =
4898 GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
4899 std::vector<int8_t> recurrentToCellWeightsData =
4900 GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
4901 std::vector<int8_t> recurrentToOutputWeightsData =
4902 GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
4904 armnn::ConstTensor recurrentToForgetWeights(recurrentWeightsInfo, recurrentToForgetWeightsData);
4905 armnn::ConstTensor recurrentToCellWeights(recurrentWeightsInfo, recurrentToCellWeightsData);
4906 armnn::ConstTensor recurrentToOutputWeights(recurrentWeightsInfo, recurrentToOutputWeightsData);
4908 std::vector<int32_t> forgetGateBiasData(numUnits, 1);
4909 std::vector<int32_t> cellBiasData(numUnits, 0);
4910 std::vector<int32_t> outputGateBiasData(numUnits, 0);
4917 std::vector<int8_t> inputToInputWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
4918 std::vector<int8_t> recurrentToInputWeightsData =
4919 GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
4920 std::vector<int32_t> inputGateBiasData(numUnits, 1);
4923 armnn::ConstTensor recurrentToInputWeights(recurrentWeightsInfo, recurrentToInputWeightsData);
4927 std::vector<int16_t> cellToInputWeightsData = GenerateRandomData<int16_t>(peepholeWeightsInfo.GetNumElements());
4928 std::vector<int16_t> cellToForgetWeightsData = GenerateRandomData<int16_t>(peepholeWeightsInfo.GetNumElements());
4929 std::vector<int16_t> cellToOutputWeightsData = GenerateRandomData<int16_t>(peepholeWeightsInfo.GetNumElements());
4932 armnn::ConstTensor cellToForgetWeights(peepholeWeightsInfo, cellToForgetWeightsData);
4933 armnn::ConstTensor cellToOutputWeights(peepholeWeightsInfo, cellToOutputWeightsData);
4936 std::vector<int8_t> projectionWeightsData = GenerateRandomData<int8_t>(projectionWeightsInfo.GetNumElements());
4937 std::vector<int32_t> projectionBiasData(outputSize, 1);
4943 std::vector<int16_t> inputLayerNormWeightsData =
4944 GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements());
4945 std::vector<int16_t> forgetLayerNormWeightsData =
4946 GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements());
4947 std::vector<int16_t> cellLayerNormWeightsData =
4948 GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements());
4949 std::vector<int16_t> outputLayerNormWeightsData =
4950 GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements());
4952 armnn::ConstTensor inputLayerNormWeights(layerNormWeightsInfo, inputLayerNormWeightsData);
4953 armnn::ConstTensor forgetLayerNormWeights(layerNormWeightsInfo, forgetLayerNormWeightsData);
4954 armnn::ConstTensor cellLayerNormWeights(layerNormWeightsInfo, cellLayerNormWeightsData);
4955 armnn::ConstTensor outputLayerNormWeights(layerNormWeightsInfo, outputLayerNormWeightsData);
4995 const std::string layerName(
"qLstm");
5042 armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
5043 BOOST_CHECK(deserializedNetwork);
5045 VerifyQLstmLayer checker(layerName,
5046 {inputInfo, cellStateInfo, outputStateInfo},
5047 {outputStateInfo, cellStateInfo, outputStateInfo},
5051 deserializedNetwork->Accept(checker);
BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)
uint32_t m_PadBottom
Padding bottom value in the height dimension.
bool m_BiasEnabled
Enable/disable bias.
virtual unsigned int GetNumOutputSlots() const =0
Returns the number of connectable output slots.
bool m_ProjectionEnabled
Enable/disable the projection layer.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
float Dequantize(QuantizedType value, float scale, int32_t offset)
Dequantize an 8-bit data type into a floating point data type.
A ViewsDescriptor for the SplitterLayer.
Interface for a layer that is connectable to other layers via InputSlots and OutputSlots.
float m_ScaleW
Center size encoding scale weight.
bool m_BiasEnabled
Enable/disable bias.
virtual unsigned int GetNumInputSlots() const =0
Returns the number of connectable input slots.
void Slice(const TensorInfo &inputInfo, const SliceDescriptor &descriptor, const void *inputData, void *outputData, unsigned int dataTypeSize)
A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer.
const TensorShape & GetShape() const
uint32_t m_PadBottom
Padding bottom value in the height dimension.
float m_ClippingThresProj
Clipping threshold value for the projection.
A ReshapeDescriptor for the ReshapeLayer.
void ArgMinMax(Decoder< float > &in, int32_t *out, const TensorInfo &inputTensorInfo, const TensorInfo &outputTensorInfo, ArgMinMaxFunction function, int axis)
#define ARMNN_NO_DEPRECATE_WARN_BEGIN
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
void Fill(Encoder< float > &output, const TensorShape &desiredOutputShape, const float value)
Creates a tensor and fills it with a scalar value.
A ComparisonDescriptor for the ComparisonLayer.
float m_ScaleX
Center size encoding scale x.
uint32_t m_TargetWidth
Target width value.
bool m_TransposeWeightMatrix
Enable/disable transpose weight matrix.
bool m_PeepholeEnabled
Enable/disable peephole.
A Convolution2dDescriptor for the Convolution2dLayer.
uint32_t m_PadLeft
Padding left value in the width dimension.
float m_HiddenStateScale
Hidden State quantization scale.
bool m_BiasEnabled
Enable/disable bias.
const TensorShape & GetShape() const
float m_OutputIntermediateScale
Output intermediate quantization scale.
ResizeMethod m_Method
The Interpolation method to use (Bilinear, NearestNeighbor).
float m_Gamma
Gamma, the scale scalar value applied for the normalized tensor. Defaults to 1.0. ...
float m_Beta
Exponentiation value.
The padding fields don't count and are ignored.
float m_Eps
Value to add to the variance. Used to avoid dividing by zero.
ArgMinMaxFunction m_Function
Specify if the function is to find Min or Max.
uint32_t m_DetectionsPerClass
Detections per classes, used in Regular NMS.
armnn::TensorInfo anchorsInfo({ 6, 4 }, armnn::DataType::Float32)
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Main network class which provides the interface for building up a neural network. ...
unsigned int GetNumElements() const
void Serialize(const armnn::INetwork &inNetwork) override
Serializes the network to ArmNN SerializedGraph.
void Transpose(const armnn::TensorShape &dstShape, const armnn::PermutationVector &mappings, const void *src, void *dst, size_t dataTypeSize)
void DepthToSpace(const TensorInfo &inputInfo, const DepthToSpaceDescriptor &descriptor, const void *inputData, void *outputData, unsigned int dataTypeSize)
uint32_t m_PadRight
Padding right value in the width dimension.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
MemoryType GetMemoryArea() const
Copyright (c) 2020 ARM Limited.
uint32_t m_PadBottom
Padding bottom value in the height dimension.
uint32_t m_DilationY
Dilation along y axis.
int32_t m_EndMask
End mask value.
A SpaceToDepthDescriptor for the SpaceToDepthLayer.
uint32_t m_DilationY
Dilation factor value for height dimension.
#define DECLARE_LAYER_VERIFIER_CLASS(name)
A BatchToSpaceNdDescriptor for the BatchToSpaceNdLayer.
int LayerBindingId
Type of identifiers for bindable layers (inputs, outputs).
void Stack(const StackQueueDescriptor &data, std::vector< std::unique_ptr< Decoder< float >>> &inputs, Encoder< float > &output)
virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0
constexpr const char * GetDataTypeName(DataType dataType)
A ResizeDescriptor for the ResizeLayer.
BOOST_AUTO_TEST_CASE(SerializeAddition)
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
uint32_t m_MaxClassesPerDetection
Maximum numbers of classes per detection, used in Fast NMS.
std::vector< unsigned int > m_Axis
Values for the dimensions to reduce.
A StackDescriptor for the StackLayer.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
uint32_t m_PadTop
Padding top value in the height dimension.
uint32_t m_MaxDetections
Maximum numbers of detections.
A PadDescriptor for the PadLayer.
void Permute(const armnn::TensorShape &dstShape, const armnn::PermutationVector &mappings, const void *src, void *dst, size_t dataTypeSize)
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
bool m_LayerNormEnabled
Enable/disable layer normalization.
float m_NmsIouThreshold
Intersection over union threshold.
An LstmDescriptor for the LstmLayer.
#define ARMNN_NO_DEPRECATE_WARN_END
uint32_t m_DilationX
Dilation factor value for width dimension.
uint32_t m_PadTop
Padding top value in the height dimension.
Status SetViewSize(uint32_t view, uint32_t coord, uint32_t value)
Set the size of the views.
An output connection slot for a layer.
A L2NormalizationDescriptor for the L2NormalizationLayer.
int32_t GetQuantizationOffset() const
An ArgMinMaxDescriptor for ArgMinMaxLayer.
float GetQuantizationScale() const
DataType GetDataType() const
An OriginsDescriptor for the ConcatLayer.
float m_ProjectionClip
Clipping threshold value for the projection.
bool has_value() const noexcept
A FullyConnectedDescriptor for the FullyConnectedLayer.
bool m_BiasEnabled
Enable/disable bias.
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
float m_InputIntermediateScale
Input intermediate quantization scale.
uint32_t m_TargetWidth
Target width value.
A GatherDescriptor for the GatherLayer.
bool m_PeepholeEnabled
Enable/disable peephole.
uint32_t m_NumClasses
Number of classes.
bool m_HalfPixelCenters
Half Pixel Centers.
uint32_t m_PadTop
Padding top value in the height dimension.
A StandInDescriptor for the StandIn layer.
A QLstmDescriptor for the QLstmLayer.
QuantizedType Quantize(float value, float scale, int32_t offset)
Quantize a floating point data type into an 8-bit data type.
bool m_UseRegularNms
Use Regular NMS.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
void LogSoftmax(Decoder< float > &input, Encoder< float > &output, const TensorInfo &inputInfo, const LogSoftmaxDescriptor &descriptor)
const TensorInfo & GetInfo() const
uint32_t m_TargetHeight
Target height value.
uint32_t m_ActivationFunc
The activation function to use.
A SliceDescriptor for the SliceLayer.
Visitor base class with empty implementations.
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
void SpaceToBatchNd(const TensorInfo &inputInfo, const TensorInfo &outputInfo, const SpaceToBatchNdDescriptor ¶ms, Decoder< float > &inputData, Encoder< float > &outputData)
bool SaveSerializedToStream(std::ostream &stream) override
Serializes the SerializedGraph to the stream.
float m_ClippingThresCell
Clipping threshold value for the cell state.
unsigned int m_BlockSize
Scalar specifying the input block size. It must be >= 1.
float m_ForgetIntermediateScale
Forget intermediate quantization scale.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
float m_ScaleH
Center size encoding scale height.
ComparisonOperation m_Operation
Specifies the comparison operation to execute.
A SpaceToBatchNdDescriptor for the SpaceToBatchNdLayer.
float m_CellClip
Clipping threshold value for the cell state.
uint32_t m_DilationX
Dilation along x axis.
BOOST_AUTO_TEST_SUITE_END()
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).
uint32_t m_PadLeft
Padding left value in the width dimension.
void StridedSlice(const TensorInfo &inputInfo, const StridedSliceDescriptor ¶ms, const void *inputData, void *outputData, unsigned int dataTypeSize)
bool m_AlignCorners
Aligned corners.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
int32_t m_Axis
The axis in params to gather indices from.
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
Base class for all ArmNN exceptions so that users can filter to just those.
bool m_ProjectionEnabled
Enable/disable the projection layer.
virtual const IInputSlot & GetInputSlot(unsigned int index) const =0
Get a const input slot handle by slot index.
A MeanDescriptor for the MeanLayer.
void Mean(const armnn::TensorInfo &inputInfo, const armnn::TensorInfo &outputInfo, const std::vector< unsigned int > &axis, Decoder< float > &input, Encoder< float > &output)
bool m_LayerNormEnabled
Enable/disable layer normalization.
uint32_t m_PadRight
Padding right value in the width dimension.
A TransposeDescriptor for the TransposeLayer.
A StridedSliceDescriptor for the StridedSliceLayer.
virtual const TensorInfo & GetTensorInfo() const =0
virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0
Get the const output slot handle by slot index.
void SpaceToDepth(const TensorInfo &inputInfo, const TensorInfo &outputInfo, const SpaceToDepthDescriptor ¶ms, Decoder< float > &inputData, Encoder< float > &outputData)
float m_ScaleY
Center size encoding scale y.
OriginsDescriptor CreateDescriptorForConcatenation(TensorShapeIt first, TensorShapeIt last, unsigned int concatenationDimension)
Convenience template to create an OriginsDescriptor to use when creating a ConcatLayer for performing...
#define DECLARE_LAYER_VERIFIER_CLASS_WITH_DESCRIPTOR(name)
float m_NmsScoreThreshold
NMS score threshold.
std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr
void BatchToSpaceNd(const DataLayoutIndexed &dataLayout, const TensorInfo &inputTensorInfo, const TensorInfo &outputTensorInfo, const std::vector< unsigned int > &blockShape, const std::vector< std::pair< unsigned int, unsigned int >> &cropsData, Decoder< float > &inputDecoder, Encoder< float > &outputEncoder)
void Pad(const TensorInfo &inputInfo, const TensorInfo &outputInfo, const PadQueueDescriptor &data)
virtual int Connect(IInputSlot &destination)=0
DataType GetDataType() const
A Pooling2dDescriptor for the Pooling2dLayer.
A NormalizationDescriptor for the NormalizationLayer.
void Pooling2d(Decoder< float > &rInputDecoder, Encoder< float > &rOutputEncoder, const TensorInfo &inputInfo, const TensorInfo &outputInfo, const Pooling2dDescriptor ¶ms)
Computes the Pooling2d operation.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
An InstanceNormalizationDescriptor for InstanceNormalizationLayer.
A ResizeBilinearDescriptor for the ResizeBilinearLayer.
void Splitter(const SplitterQueueDescriptor &data)
float m_CellIntermediateScale
Cell intermediate quantization scale.
void Softmax(Decoder< float > &in, Encoder< float > &out, const TensorInfo &inputTensorInfo, float beta, int axis)
Computes the softmax function on some inputs, into outputs, with a shape given by tensorInfo...
static INetworkPtr Create(NetworkOptions networkOptions={})
A SoftmaxDescriptor for the SoftmaxLayer.
bool m_CifgEnabled
Enable/disable CIFG (coupled input & forget gate).
Status SetViewOriginCoord(uint32_t view, uint32_t coord, uint32_t value)
Set the view origin coordinates.
void Resize(Decoder< float > &in, const TensorInfo &inputInfo, Encoder< float > &out, const TensorInfo &outputInfo, DataLayoutIndexed dataLayout, armnn::ResizeMethod resizeMethod, bool alignCorners, bool halfPixelCenters)
A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer.
A FillDescriptor for the FillLayer.
A BatchNormalizationDescriptor for the BatchNormalizationLayer.
uint32_t m_PadLeft
Padding left value in the width dimension.
unsigned int GetNumBytes() const
A PermuteDescriptor for the PermuteLayer.
uint32_t m_PadRight
Padding right value in the width dimension.
int32_t m_HiddenStateZeroPoint
Hidden State zero point.
std::vector< float > anchors({ 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 10.5f, 1.0f, 1.0f, 0.5f, 10.5f, 1.0f, 1.0f, 0.5f, 100.5f, 1.0f, 1.0f })