14 #include <boost/numeric/conversion/cast.hpp> 15 #include <flatbuffers/util.h> 19 using namespace armnn;
20 namespace fb = flatbuffers;
31 return serializer::ActivationFunction::ActivationFunction_Sigmoid;
33 return serializer::ActivationFunction::ActivationFunction_TanH;
35 return serializer::ActivationFunction::ActivationFunction_Linear;
37 return serializer::ActivationFunction::ActivationFunction_ReLu;
39 return serializer::ActivationFunction::ActivationFunction_BoundedReLu;
41 return serializer::ActivationFunction::ActivationFunction_LeakyReLu;
43 return serializer::ActivationFunction::ActivationFunction_Abs;
45 return serializer::ActivationFunction::ActivationFunction_Sqrt;
47 return serializer::ActivationFunction::ActivationFunction_Square;
49 return serializer::ActivationFunction::ActivationFunction_Elu;
51 return serializer::ActivationFunction::ActivationFunction_HardSwish;
53 return serializer::ActivationFunction::ActivationFunction_Sigmoid;
62 return serializer::ArgMinMaxFunction::ArgMinMaxFunction_Max;
65 return serializer::ArgMinMaxFunction::ArgMinMaxFunction_Min;
71 if (m_guidMap.empty())
73 m_guidMap.insert(std::make_pair(guid, m_layerId));
75 else if (m_guidMap.find(guid) == m_guidMap.end())
78 m_guidMap.insert(std::make_pair(guid, m_layerId));
82 return m_guidMap[guid];
91 auto flatBufferInputBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Input);
94 auto flatBufferInputBindableBaseLayer = serializer::CreateBindableLayerBase(m_flatBufferBuilder,
95 flatBufferInputBaseLayer,
98 m_inputIds.push_back(
id);
101 auto flatBufferInputLayer = serializer::CreateInputLayer(m_flatBufferBuilder, flatBufferInputBindableBaseLayer);
104 CreateAnyLayer(flatBufferInputLayer.o, serializer::Layer::Layer_InputLayer);
113 auto flatBufferOutputBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Output);
116 auto flatBufferOutputBindableBaseLayer = serializer::CreateBindableLayerBase(m_flatBufferBuilder,
117 flatBufferOutputBaseLayer,
120 m_outputIds.push_back(
id);
123 auto flatBufferOutputLayer = serializer::CreateOutputLayer(m_flatBufferBuilder, flatBufferOutputBindableBaseLayer);
125 CreateAnyLayer(flatBufferOutputLayer.o, serializer::Layer::Layer_OutputLayer);
131 auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Abs);
132 auto flatBufferAbsLayer = serializer::CreateAbsLayer(m_flatBufferBuilder, flatBufferBaseLayer);
134 CreateAnyLayer(flatBufferAbsLayer.o, serializer::Layer::Layer_AbsLayer);
145 auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Activation);
148 auto flatBufferDescriptor = CreateActivationDescriptor(m_flatBufferBuilder,
154 auto flatBufferAdditionLayer = CreateActivationLayer(m_flatBufferBuilder,
156 flatBufferDescriptor);
159 CreateAnyLayer(flatBufferAdditionLayer.o, serializer::Layer::Layer_ActivationLayer);
168 auto flatBufferAdditionBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Addition);
171 auto flatBufferAdditionLayer = serializer::CreateAdditionLayer(m_flatBufferBuilder, flatBufferAdditionBaseLayer);
174 CreateAnyLayer(flatBufferAdditionLayer.o, serializer::Layer::Layer_AdditionLayer);
185 auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_ArgMinMax);
188 auto flatBufferDescriptor = CreateArgMinMaxDescriptor(m_flatBufferBuilder,
193 auto flatBufferLayer = CreateArgMinMaxLayer(m_flatBufferBuilder,
195 flatBufferDescriptor);
197 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_ArgMinMaxLayer);
208 auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_BatchToSpaceNd);
210 std::vector<unsigned int> crops;
211 crops.reserve(descriptor.
m_Crops.size() * 2);
212 for (
auto& crop : descriptor.
m_Crops)
214 crops.push_back(crop.first);
215 crops.push_back(crop.second);
218 auto flatBufferDescriptor =
219 CreateBatchToSpaceNdDescriptor(m_flatBufferBuilder,
220 m_flatBufferBuilder.CreateVector(descriptor.
m_BlockShape),
221 m_flatBufferBuilder.CreateVector(crops),
224 auto flatBufferLayer = serializer::CreateBatchToSpaceNdLayer(m_flatBufferBuilder,
226 flatBufferDescriptor);
228 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_BatchToSpaceNdLayer);
241 auto fbBatchNormalizationBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_BatchNormalization);
242 auto fbBatchNormalizationDescriptor = serializer::CreateBatchNormalizationDescriptor(
244 batchNormDescriptor.
m_Eps,
247 auto fbMeanConstTensorInfo = CreateConstTensorInfo(mean);
248 auto fbVarianceConstTensorInfo = CreateConstTensorInfo(variance);
249 auto fbBetaConstTensorInfo = CreateConstTensorInfo(beta);
250 auto fbGammaConstTensorInfo = CreateConstTensorInfo(gamma);
251 auto fbBatchNormalizationLayer = serializer::CreateBatchNormalizationLayer(m_flatBufferBuilder,
252 fbBatchNormalizationBaseLayer,
253 fbBatchNormalizationDescriptor,
254 fbMeanConstTensorInfo,
255 fbVarianceConstTensorInfo,
256 fbBetaConstTensorInfo,
257 fbGammaConstTensorInfo);
259 CreateAnyLayer(fbBatchNormalizationLayer.o, serializer::Layer::Layer_BatchNormalizationLayer);
268 auto fbBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Comparison);
269 auto fbDescriptor = serializer::CreateComparisonDescriptor(
273 auto fbLayer = serializer::CreateComparisonLayer(m_flatBufferBuilder, fbBaseLayer, fbDescriptor);
274 CreateAnyLayer(fbLayer.o, serializer::Layer::Layer_ComparisonLayer);
285 auto flatBufferConstantBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Constant);
287 auto flatBufferConstTensorInfo = CreateConstTensorInfo(input);
290 auto flatBufferLayer = CreateConstantLayer(m_flatBufferBuilder,
291 flatBufferConstantBaseLayer,
292 flatBufferConstTensorInfo);
295 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_ConstantLayer);
308 auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Convolution2d);
310 auto flatBufferDescriptor = CreateConvolution2dDescriptor(m_flatBufferBuilder,
321 auto flatBufferWeightsConstTensorInfo = CreateConstTensorInfo(weights);
322 flatbuffers::Offset<serializer::ConstTensor> flatBufferBiasesConstTensorInfo;
326 flatBufferBiasesConstTensorInfo = CreateConstTensorInfo(biases.
value());
330 auto flatBufferLayer = CreateConvolution2dLayer(m_flatBufferBuilder,
332 flatBufferDescriptor,
333 flatBufferWeightsConstTensorInfo,
334 flatBufferBiasesConstTensorInfo);
337 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_Convolution2dLayer);
346 auto fbBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_DepthToSpace);
347 auto fbDescriptor = CreateDepthToSpaceDescriptor(m_flatBufferBuilder,
351 auto fbLayer = serializer::CreateDepthToSpaceLayer(m_flatBufferBuilder, fbBaseLayer, fbDescriptor);
353 CreateAnyLayer(fbLayer.o, serializer::Layer::Layer_DepthToSpaceLayer);
364 auto fbBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_DepthwiseConvolution2d);
365 auto fbDescriptor = CreateDepthwiseConvolution2dDescriptor(m_flatBufferBuilder,
377 flatbuffers::Offset<serializer::ConstTensor> fbWeightsConstTensorInfo = CreateConstTensorInfo(weights);
378 flatbuffers::Offset<serializer::ConstTensor> fbBiasesConstTensorInfo;
381 fbBiasesConstTensorInfo = CreateConstTensorInfo(biases.
value());
384 auto flatBufferLayer = CreateDepthwiseConvolution2dLayer(m_flatBufferBuilder,
387 fbWeightsConstTensorInfo,
388 fbBiasesConstTensorInfo);
390 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_DepthwiseConvolution2dLayer);
398 auto fbDequantizeBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Dequantize);
399 auto fbDequantizeLayer = serializer::CreateDequantizeLayer(m_flatBufferBuilder, fbDequantizeBaseLayer);
401 CreateAnyLayer(fbDequantizeLayer.o, serializer::Layer::Layer_DequantizeLayer);
411 auto fbBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_DetectionPostProcess);
412 auto fbDescriptor = CreateDetectionPostProcessDescriptor(m_flatBufferBuilder,
425 flatbuffers::Offset<serializer::ConstTensor> fbAnchorsConstTensorInfo = CreateConstTensorInfo(anchors);
427 auto flatBufferLayer = CreateDetectionPostProcessLayer(m_flatBufferBuilder,
430 fbAnchorsConstTensorInfo);
432 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_DetectionPostProcessLayer);
439 auto fbDivisionBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Division);
440 auto fbDivisionLayer = serializer::CreateDivisionLayer(m_flatBufferBuilder, fbDivisionBaseLayer);
442 CreateAnyLayer(fbDivisionLayer.o, serializer::Layer::Layer_DivisionLayer);
451 auto fbBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_ElementwiseUnary);
452 auto fbDescriptor = serializer::CreateElementwiseUnaryDescriptor(
456 auto fbLayer = serializer::CreateElementwiseUnaryLayer(m_flatBufferBuilder, fbBaseLayer, fbDescriptor);
457 CreateAnyLayer(fbLayer.o, serializer::Layer::Layer_ElementwiseUnaryLayer);
464 auto fbBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Equal);
465 auto fbEqualLayer = serializer::CreateEqualLayer(m_flatBufferBuilder, fbBaseLayer);
467 CreateAnyLayer(fbEqualLayer.o, serializer::Layer::Layer_EqualLayer);
476 auto fbFillBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Fill);
478 auto fbDescriptor = serializer::CreateFillDescriptor(m_flatBufferBuilder, fillDescriptor.
m_Value);
480 auto fbFillLayer = serializer::CreateFillLayer(m_flatBufferBuilder, fbFillBaseLayer, fbDescriptor);
482 CreateAnyLayer(fbFillLayer.o, serializer::Layer::Layer_FillLayer);
489 auto flatBufferFloorBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Floor);
490 auto flatBufferFloorLayer = serializer::CreateFloorLayer(m_flatBufferBuilder, flatBufferFloorBaseLayer);
492 CreateAnyLayer(flatBufferFloorLayer.o, serializer::Layer::Layer_FloorLayer);
499 VisitGatherLayer(layer, gatherDescriptor, name);
508 auto fbGatherDescriptor = CreateGatherDescriptor(m_flatBufferBuilder,
510 auto fbGatherBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Gather);
511 auto flatBufferLayer = serializer::CreateGatherLayer(m_flatBufferBuilder, fbGatherBaseLayer, fbGatherDescriptor);
513 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_GatherLayer);
520 auto fbGreaterBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Greater);
521 auto fbGreaterLayer = serializer::CreateGreaterLayer(m_flatBufferBuilder, fbGreaterBaseLayer);
523 CreateAnyLayer(fbGreaterLayer.o, serializer::Layer::Layer_GreaterLayer);
526 void SerializerVisitor::VisitInstanceNormalizationLayer(
533 auto fbDescriptor = serializer::CreateInstanceNormalizationDescriptor(
535 instanceNormalizationDescriptor.
m_Gamma,
536 instanceNormalizationDescriptor.
m_Beta,
537 instanceNormalizationDescriptor.
m_Eps,
540 auto fbBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_InstanceNormalization);
541 auto fbLayer = serializer::CreateInstanceNormalizationLayer(m_flatBufferBuilder, fbBaseLayer, fbDescriptor);
543 CreateAnyLayer(fbLayer.o, serializer::Layer::Layer_InstanceNormalizationLayer);
553 auto fbBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_L2Normalization);
556 auto fbDescriptor = serializer::CreateL2NormalizationDescriptor(
559 l2NormalizationDescriptor.
m_Eps);
562 auto fbLayer = serializer::CreateL2NormalizationLayer(m_flatBufferBuilder, fbBaseLayer, fbDescriptor);
564 CreateAnyLayer(fbLayer.o, serializer::Layer::Layer_L2NormalizationLayer);
574 auto flatBufferLogSoftmaxBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_LogSoftmax);
577 auto flatBufferLogSoftmaxDesc =
578 serializer::CreateLogSoftmaxDescriptor(m_flatBufferBuilder,
579 logSoftmaxDescriptor.
m_Beta,
580 logSoftmaxDescriptor.
m_Axis);
583 auto flatBufferLogSoftmaxLayer =
584 serializer::CreateLogSoftmaxLayer(m_flatBufferBuilder,
585 flatBufferLogSoftmaxBaseLayer,
586 flatBufferLogSoftmaxDesc);
588 CreateAnyLayer(flatBufferLogSoftmaxLayer.o, serializer::Layer::Layer_LogSoftmaxLayer);
598 auto fbLstmBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Lstm);
600 auto fbLstmDescriptor = serializer::CreateLstmDescriptor(
618 auto cellBias = CreateConstTensorInfo(*params.
m_CellBias);
622 flatbuffers::Offset<serializer::ConstTensor> inputToInputWeights;
623 flatbuffers::Offset<serializer::ConstTensor> recurrentToInputWeights;
624 flatbuffers::Offset<serializer::ConstTensor> cellToInputWeights;
625 flatbuffers::Offset<serializer::ConstTensor> inputGateBias;
626 flatbuffers::Offset<serializer::ConstTensor> projectionWeights;
627 flatbuffers::Offset<serializer::ConstTensor> projectionBias;
628 flatbuffers::Offset<serializer::ConstTensor> cellToForgetWeights;
629 flatbuffers::Offset<serializer::ConstTensor> cellToOutputWeights;
630 flatbuffers::Offset<serializer::ConstTensor> inputLayerNormWeights;
631 flatbuffers::Offset<serializer::ConstTensor> forgetLayerNormWeights;
632 flatbuffers::Offset<serializer::ConstTensor> cellLayerNormWeights;
633 flatbuffers::Offset<serializer::ConstTensor> outputLayerNormWeights;
666 auto fbLstmParams = serializer::CreateLstmInputParams(
668 inputToForgetWeights,
670 inputToOutputWeights,
671 recurrentToForgetWeights,
672 recurrentToCellWeights,
673 recurrentToOutputWeights,
678 recurrentToInputWeights,
685 inputLayerNormWeights,
686 forgetLayerNormWeights,
687 cellLayerNormWeights,
688 outputLayerNormWeights);
690 auto fbLstmLayer = serializer::CreateLstmLayer(
696 CreateAnyLayer(fbLstmLayer.o, serializer::Layer::Layer_LstmLayer);
703 auto fbMaximumBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Maximum);
704 auto fbMaximumLayer = serializer::CreateMaximumLayer(m_flatBufferBuilder, fbMaximumBaseLayer);
706 CreateAnyLayer(fbMaximumLayer.o, serializer::Layer::Layer_MaximumLayer);
715 auto fbMeanBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Mean);
716 auto fbMeanDescriptor = serializer::CreateMeanDescriptor(m_flatBufferBuilder,
717 m_flatBufferBuilder.CreateVector(descriptor.
m_Axis),
720 auto fbMeanLayer = serializer::CreateMeanLayer(m_flatBufferBuilder,
724 CreateAnyLayer(fbMeanLayer.o, serializer::Layer::Layer_MeanLayer);
731 auto fbMinimumBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Minimum);
732 auto fbMinimumLayer = serializer::CreateMinimumLayer(m_flatBufferBuilder, fbMinimumBaseLayer);
734 CreateAnyLayer(fbMinimumLayer.o, serializer::Layer::Layer_MinimumLayer);
741 auto fbMergeBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Merge);
742 auto fbMergeLayer = serializer::CreateMergeLayer(m_flatBufferBuilder, fbMergeBaseLayer);
744 CreateAnyLayer(fbMergeLayer.o, serializer::Layer::Layer_MergeLayer);
751 VisitConcatLayer(layer, mergerDescriptor, name);
760 auto flatBufferConcatBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Concat);
762 std::vector<flatbuffers::Offset<UintVector>> views;
763 for (
unsigned int v = 0; v < concatDescriptor.
GetNumViews(); ++v)
766 std::vector<uint32_t> origins;
769 origins.push_back(origin[d]);
771 auto view = m_flatBufferBuilder.CreateVector(origins);
772 auto uintVector = CreateUintVector(m_flatBufferBuilder, view);
773 views.push_back(uintVector);
776 auto flatBufferConcatDescriptor = CreateOriginsDescriptor(m_flatBufferBuilder,
780 m_flatBufferBuilder.CreateVector(views));
782 auto flatBufferLayer = CreateConcatLayer(m_flatBufferBuilder,
783 flatBufferConcatBaseLayer,
784 flatBufferConcatDescriptor);
786 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_ConcatLayer);
793 auto fbMultiplicationBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Multiplication);
794 auto fbMultiplicationLayer = serializer::CreateMultiplicationLayer(m_flatBufferBuilder,
795 fbMultiplicationBaseLayer);
797 CreateAnyLayer(fbMultiplicationLayer.o, serializer::Layer::Layer_MultiplicationLayer);
806 auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Pad);
808 std::vector<unsigned int> padList;
811 padList.push_back(p.first);
812 padList.push_back(p.second);
815 auto flatBufferPadDesc = serializer::CreatePadDescriptor(m_flatBufferBuilder,
816 m_flatBufferBuilder.CreateVector(padList),
819 auto flatBufferPadLayer = serializer::CreatePadLayer(m_flatBufferBuilder,
823 CreateAnyLayer(flatBufferPadLayer.o, serializer::Layer::Layer_PadLayer);
833 auto flatBufferPermuteBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Permute);
835 std::vector<unsigned int> dimMappings;
841 auto flatBufferPermuteDesc = serializer::CreatePermuteDescriptor(m_flatBufferBuilder,
842 m_flatBufferBuilder.CreateVector(dimMappings));
845 auto flatBufferPermuteLayer = serializer::CreatePermuteLayer(m_flatBufferBuilder,
846 flatBufferPermuteBaseLayer,
847 flatBufferPermuteDesc);
850 CreateAnyLayer(flatBufferPermuteLayer.o, serializer::Layer::Layer_PermuteLayer);
858 auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Rank);
859 auto flatBufferRankLayer = serializer::CreateRankLayer(m_flatBufferBuilder, flatBufferBaseLayer);
861 CreateAnyLayer(flatBufferRankLayer.o, serializer::Layer::Layer_RankLayer);
871 auto flatBufferReshapeBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Reshape);
873 std::vector<unsigned int> targetShape;
879 auto flatBufferReshapeDesc = serializer::CreateReshapeDescriptor(m_flatBufferBuilder,
880 m_flatBufferBuilder.CreateVector(targetShape));
883 auto flatBufferReshapeLayer = serializer::CreateReshapeLayer(m_flatBufferBuilder, flatBufferReshapeBaseLayer,
884 flatBufferReshapeDesc);
887 CreateAnyLayer(flatBufferReshapeLayer.o, serializer::Layer::Layer_ReshapeLayer);
896 auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_ResizeBilinear);
898 auto flatBufferDescriptor =
899 CreateResizeBilinearDescriptor(m_flatBufferBuilder,
906 auto flatBufferLayer = serializer::CreateResizeBilinearLayer(m_flatBufferBuilder,
908 flatBufferDescriptor);
910 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_ResizeBilinearLayer);
919 auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Resize);
921 auto flatBufferDescriptor =
922 CreateResizeDescriptor(m_flatBufferBuilder,
930 auto flatBufferLayer = serializer::CreateResizeLayer(m_flatBufferBuilder,
932 flatBufferDescriptor);
934 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_ResizeLayer);
941 auto fbRsqrtBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Rsqrt);
942 auto fbRsqrtLayer = serializer::CreateRsqrtLayer(m_flatBufferBuilder, fbRsqrtBaseLayer);
944 CreateAnyLayer(fbRsqrtLayer.o, serializer::Layer::Layer_RsqrtLayer);
953 auto fbSliceBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Slice);
954 auto fbSliceDescriptor = CreateSliceDescriptor(m_flatBufferBuilder,
955 m_flatBufferBuilder.CreateVector(sliceDescriptor.
m_Begin),
956 m_flatBufferBuilder.CreateVector(sliceDescriptor.
m_Size));
958 auto fbSliceLayer = serializer::CreateSliceLayer(m_flatBufferBuilder, fbSliceBaseLayer, fbSliceDescriptor);
960 CreateAnyLayer(fbSliceLayer.o, serializer::Layer::Layer_SliceLayer);
971 auto flatBufferSoftmaxBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Softmax);
974 auto flatBufferSoftmaxDesc =
975 serializer::CreateSoftmaxDescriptor(m_flatBufferBuilder, softmaxDescriptor.
m_Beta);
978 auto flatBufferSoftmaxLayer =
979 serializer::CreateSoftmaxLayer(m_flatBufferBuilder,
980 flatBufferSoftmaxBaseLayer,
981 flatBufferSoftmaxDesc);
983 CreateAnyLayer(flatBufferSoftmaxLayer.o, serializer::Layer::Layer_SoftmaxLayer);
992 auto fbPooling2dBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Pooling2d);
993 auto fbPooling2dDescriptor = serializer::CreatePooling2dDescriptor(
1008 auto fbPooling2dLayer = serializer::CreatePooling2dLayer(m_flatBufferBuilder,
1009 fbPooling2dBaseLayer,
1010 fbPooling2dDescriptor);
1012 CreateAnyLayer(fbPooling2dLayer.o, serializer::Layer::Layer_Pooling2dLayer);
1021 auto flatBufferPreluBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Prelu);
1024 auto flatBufferPreluLayer = serializer::CreatePreluLayer(m_flatBufferBuilder, flatBufferPreluBaseLayer);
1027 CreateAnyLayer(flatBufferPreluLayer.o, serializer::Layer::Layer_PreluLayer);
1034 auto fbQuantizeBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Quantize);
1035 auto fbQuantizeLayer = serializer::CreateQuantizeLayer(m_flatBufferBuilder,
1036 fbQuantizeBaseLayer);
1037 CreateAnyLayer(fbQuantizeLayer.o, serializer::Layer::Layer_QuantizeLayer);
1050 auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_FullyConnected);
1053 auto flatBufferDescriptor =
1054 serializer::CreateFullyConnectedDescriptor(m_flatBufferBuilder,
1059 auto flatBufferWeights = CreateConstTensorInfo(weights);
1062 flatbuffers::Offset<serializer::ConstTensor> flatBufferBiases;
1065 flatBufferBiases = CreateConstTensorInfo(biases.
value());
1069 auto flatBufferLayer = serializer::CreateFullyConnectedLayer(m_flatBufferBuilder,
1070 flatBufferBaseLayer,
1071 flatBufferDescriptor,
1076 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_FullyConnectedLayer);
1087 auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_SpaceToBatchNd);
1089 std::vector<unsigned int> padList;
1090 padList.reserve(spaceToBatchNdDescriptor.
m_PadList.size()*2);
1091 for (
auto& pad : spaceToBatchNdDescriptor.
m_PadList)
1093 padList.push_back(pad.first);
1094 padList.push_back(pad.second);
1097 auto flatBufferDescriptor =
1098 CreateSpaceToBatchNdDescriptor(m_flatBufferBuilder,
1099 m_flatBufferBuilder.CreateVector(spaceToBatchNdDescriptor.
m_BlockShape),
1100 m_flatBufferBuilder.CreateVector(padList),
1103 auto flatBufferLayer = serializer::CreateSpaceToBatchNdLayer(m_flatBufferBuilder,
1104 flatBufferBaseLayer,
1105 flatBufferDescriptor);
1107 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_SpaceToBatchNdLayer);
1117 auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_SpaceToDepth);
1118 auto flatBufferDescriptor =
1119 CreateSpaceToDepthDescriptor(m_flatBufferBuilder,
1123 auto flatBufferLayer = serializer::CreateSpaceToDepthLayer(m_flatBufferBuilder,
1124 flatBufferBaseLayer,
1125 flatBufferDescriptor);
1127 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_SpaceToDepthLayer);
1138 std::vector<flatbuffers::Offset<UintVector>> flatBufferViewOrigins;
1139 flatBufferViewOrigins.reserve(viewsDescriptor.
GetNumViews());
1141 for(
unsigned int vIdx = 0; vIdx < viewsDescriptor.
GetNumViews(); ++vIdx)
1143 std::vector<uint32_t> viewOrigin;
1147 for(
unsigned int dIdx = 0; dIdx < viewsDescriptor.
GetNumDimensions(); ++dIdx)
1149 viewOrigin.push_back(viewsDescriptor.
GetViewOrigin(vIdx)[dIdx]);
1152 flatBufferViewOrigins.push_back(CreateUintVector(m_flatBufferBuilder,
1153 m_flatBufferBuilder.CreateVector(viewOrigin)));
1157 auto flatBufferOriginDescriptor = CreateOriginsDescriptor(m_flatBufferBuilder,
1161 m_flatBufferBuilder.CreateVector(flatBufferViewOrigins));
1164 std::vector<flatbuffers::Offset<UintVector>> flatBufferViewSizes;
1165 flatBufferViewSizes.reserve(viewsDescriptor.
GetNumViews());
1167 for(
unsigned int vIdx = 0; vIdx < viewsDescriptor.
GetNumViews(); ++vIdx)
1169 std::vector<uint32_t> viewSize;
1173 for(
unsigned int dIdx = 0; dIdx < viewsDescriptor.
GetNumDimensions(); ++dIdx)
1175 viewSize.push_back(viewsDescriptor.
GetViewSizes(vIdx)[dIdx]);
1178 flatBufferViewSizes.push_back(CreateUintVector(m_flatBufferBuilder,
1179 m_flatBufferBuilder.CreateVector(viewSize)));
1183 auto flatBufferViewsDescriptor = CreateViewsDescriptor(m_flatBufferBuilder,
1184 flatBufferOriginDescriptor,
1185 m_flatBufferBuilder.CreateVector(flatBufferViewSizes));
1188 auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Splitter);
1190 auto flatBufferSplitterLayer = serializer::CreateSplitterLayer(m_flatBufferBuilder,
1191 flatBufferBaseLayer,
1192 flatBufferViewsDescriptor);
1194 CreateAnyLayer(flatBufferSplitterLayer.o, serializer::Layer::Layer_SplitterLayer);
1203 auto fbNormalizationBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Normalization);
1205 auto fbNormalizationDescriptor = serializer::CreateNormalizationDescriptor(
1206 m_flatBufferBuilder,
1215 auto flatBufferLayer = serializer::CreateNormalizationLayer(m_flatBufferBuilder,
1216 fbNormalizationBaseLayer,
1217 fbNormalizationDescriptor);
1219 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_NormalizationLayer);
1228 auto stackBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Stack);
1230 std::vector<unsigned int> inputShape;
1236 auto flatBufferStackDescriptor = CreateStackDescriptor(m_flatBufferBuilder,
1239 m_flatBufferBuilder.CreateVector(inputShape));
1241 auto stackLayer = serializer::CreateStackLayer(m_flatBufferBuilder, stackBaseLayer, flatBufferStackDescriptor);
1242 CreateAnyLayer(stackLayer.o, serializer::Layer::Layer_StackLayer);
1251 auto fbDescriptor = serializer::CreateStandInDescriptor(m_flatBufferBuilder,
1255 auto fbBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_StandIn);
1256 auto fbLayer = serializer::CreateStandInLayer(m_flatBufferBuilder, fbBaseLayer, fbDescriptor);
1258 CreateAnyLayer(fbLayer.o, serializer::Layer::Layer_StandInLayer);
1267 auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_StridedSlice);
1269 auto flatBufferDescriptor =
1270 CreateStridedSliceDescriptor(m_flatBufferBuilder,
1271 m_flatBufferBuilder.CreateVector(stridedSliceDescriptor.
m_Begin),
1272 m_flatBufferBuilder.CreateVector(stridedSliceDescriptor.
m_End),
1273 m_flatBufferBuilder.CreateVector(stridedSliceDescriptor.
m_Stride),
1281 auto flatBufferLayer = serializer::CreateStridedSliceLayer(m_flatBufferBuilder,
1282 flatBufferBaseLayer,
1283 flatBufferDescriptor);
1285 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_StridedSliceLayer);
1292 auto fbSubtractionBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Subtraction);
1293 auto fbSubtractionLayer = serializer::CreateSubtractionLayer(m_flatBufferBuilder, fbSubtractionBaseLayer);
1295 CreateAnyLayer(fbSubtractionLayer.o, serializer::Layer::Layer_SubtractionLayer);
1302 auto fbSwitchBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Switch);
1303 auto fbSwitchLayer = serializer::CreateSwitchLayer(m_flatBufferBuilder, fbSwitchBaseLayer);
1305 CreateAnyLayer(fbSwitchLayer.o, serializer::Layer::Layer_SwitchLayer);
1308 void SerializerVisitor::VisitTransposeConvolution2dLayer(
1317 auto fbBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Convolution2d);
1318 auto fbDescriptor = CreateTransposeConvolution2dDescriptor(m_flatBufferBuilder,
1329 auto fbWeightsConstTensorInfo = CreateConstTensorInfo(weights);
1330 flatbuffers::Offset<serializer::ConstTensor> fbBiasesConstTensorInfo;
1333 fbBiasesConstTensorInfo = CreateConstTensorInfo(biases.
value());
1336 auto fbLayer = CreateTransposeConvolution2dLayer(m_flatBufferBuilder,
1339 fbWeightsConstTensorInfo,
1340 fbBiasesConstTensorInfo);
1342 CreateAnyLayer(fbLayer.o, serializer::Layer::Layer_TransposeConvolution2dLayer);
1352 auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Transpose);
1354 std::vector<unsigned int> dimMappings;
1360 auto flatBufferDesc = serializer::CreateTransposeDescriptor(m_flatBufferBuilder,
1361 m_flatBufferBuilder.CreateVector(dimMappings));
1364 auto flatBufferLayer = serializer::CreateTransposeLayer(m_flatBufferBuilder,
1365 flatBufferBaseLayer,
1369 CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_TransposeLayer);
1379 auto fbQLstmBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_QLstm);
1381 auto fbQLstmDescriptor = serializer::CreateQLstmDescriptor(
1382 m_flatBufferBuilder,
1405 auto cellBias = CreateConstTensorInfo(*params.
m_CellBias);
1409 flatbuffers::Offset<serializer::ConstTensor> inputToInputWeights;
1410 flatbuffers::Offset<serializer::ConstTensor> recurrentToInputWeights;
1411 flatbuffers::Offset<serializer::ConstTensor> inputGateBias;
1421 flatbuffers::Offset<serializer::ConstTensor> projectionWeights;
1422 flatbuffers::Offset<serializer::ConstTensor> projectionBias;
1431 flatbuffers::Offset<serializer::ConstTensor> cellToInputWeights;
1432 flatbuffers::Offset<serializer::ConstTensor> cellToForgetWeights;
1433 flatbuffers::Offset<serializer::ConstTensor> cellToOutputWeights;
1447 flatbuffers::Offset<serializer::ConstTensor> inputLayerNormWeights;
1448 flatbuffers::Offset<serializer::ConstTensor> forgetLayerNormWeights;
1449 flatbuffers::Offset<serializer::ConstTensor> cellLayerNormWeights;
1450 flatbuffers::Offset<serializer::ConstTensor> outputLayerNormWeights;
1464 auto fbQLstmParams = serializer::CreateQLstmInputParams(
1465 m_flatBufferBuilder,
1466 inputToForgetWeights,
1468 inputToOutputWeights,
1469 recurrentToForgetWeights,
1470 recurrentToCellWeights,
1471 recurrentToOutputWeights,
1475 inputToInputWeights,
1476 recurrentToInputWeights,
1481 cellToForgetWeights,
1482 cellToOutputWeights,
1483 inputLayerNormWeights,
1484 forgetLayerNormWeights,
1485 cellLayerNormWeights,
1486 outputLayerNormWeights);
1488 auto fbQLstmLayer = serializer::CreateQLstmLayer(
1489 m_flatBufferBuilder,
1494 CreateAnyLayer(fbQLstmLayer.o, serializer::Layer::Layer_QLstmLayer);
1503 auto fbQuantizedLstmBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_QuantizedLstm);
1518 auto cellBias = CreateConstTensorInfo(params.
GetCellBias());
1521 auto fbQuantizedLstmParams = serializer::CreateQuantizedLstmInputParams(
1522 m_flatBufferBuilder,
1523 inputToInputWeights,
1524 inputToForgetWeights,
1526 inputToOutputWeights,
1527 recurrentToInputWeights,
1528 recurrentToForgetWeights,
1529 recurrentToCellWeights,
1530 recurrentToOutputWeights,
1536 auto fbQuantizedLstmLayer = serializer::CreateQuantizedLstmLayer(
1537 m_flatBufferBuilder,
1538 fbQuantizedLstmBaseLayer,
1539 fbQuantizedLstmParams);
1541 CreateAnyLayer(fbQuantizedLstmLayer.o, serializer::Layer::Layer_QuantizedLstmLayer);
1544 fb::Offset<serializer::LayerBase> SerializerVisitor::CreateLayerBase(
const IConnectableLayer* layer,
1548 uint32_t fbIndex = GetSerializedId(layer->
GetGuid());
1550 std::vector<fb::Offset<serializer::InputSlot>> inputSlots = CreateInputSlots(layer);
1551 std::vector<fb::Offset<serializer::OutputSlot>> outputSlots = CreateOutputSlots(layer);
1553 return serializer::CreateLayerBase(m_flatBufferBuilder,
1555 m_flatBufferBuilder.CreateString(layer->
GetName()),
1557 m_flatBufferBuilder.CreateVector(inputSlots),
1558 m_flatBufferBuilder.CreateVector(outputSlots));
1561 void SerializerVisitor::CreateAnyLayer(
const flatbuffers::Offset<void>& layer,
const serializer::Layer serializerLayer)
1564 auto anyLayer = armnnSerializer::CreateAnyLayer(m_flatBufferBuilder, serializerLayer, layer);
1565 m_serializedLayers.push_back(anyLayer);
1568 template <
typename T>
1569 flatbuffers::Offset<flatbuffers::Vector<T>> SerializerVisitor::CreateDataVector(
const void* memory,
unsigned int size)
1571 const T* buffer =
reinterpret_cast<const T*
>(memory);
1572 std::vector<T> vector(buffer, buffer + (size /
sizeof(T)));
1573 auto fbVector = m_flatBufferBuilder.CreateVector(vector);
1577 flatbuffers::Offset<TensorInfo> SerializerVisitor::CreateTensorInfo(
const armnn::TensorInfo& tensorInfo)
1580 std::vector<unsigned int> shape;
1583 shape.push_back(tensorInfo.
GetShape()[dim]);
1589 auto flatBufferTensorInfo =
1590 serializer::CreateTensorInfo(m_flatBufferBuilder,
1591 m_flatBufferBuilder.CreateVector(shape),
1597 static_cast<unsigned int> 1599 return flatBufferTensorInfo;
1603 auto flatBufferTensorInfo = serializer::CreateTensorInfo(m_flatBufferBuilder,
1604 m_flatBufferBuilder.CreateVector(shape),
1610 static_cast<unsigned int> 1612 return flatBufferTensorInfo;
1615 flatbuffers::Offset<serializer::ConstTensor>
1620 flatbuffers::Offset<void> fbPayload;
1628 flatbuffers::Offset<serializer::IntData> flatBuffersData = serializer::CreateIntData(
1629 m_flatBufferBuilder,
1631 fbPayload = flatBuffersData.o;
1639 flatbuffers::Offset<serializer::ShortData> flatBuffersData = serializer::CreateShortData(
1640 m_flatBufferBuilder,
1642 fbPayload = flatBuffersData.o;
1652 flatbuffers::Offset<serializer::ByteData> flatBuffersData = serializer::CreateByteData(
1653 m_flatBufferBuilder,
1655 fbPayload = flatBuffersData.o;
1658 flatbuffers::Offset<serializer::ConstTensor> flatBufferConstTensor = serializer::CreateConstTensor(
1659 m_flatBufferBuilder,
1660 CreateTensorInfo(tensorInfo),
1663 return flatBufferConstTensor;
1666 flatbuffers::Offset<armnnSerializer::FeatureCompatibilityVersions> SerializerVisitor::GetVersionTable()
1668 flatbuffers::Offset<armnnSerializer::FeatureCompatibilityVersions> versionsTable =
1669 serializer::CreateFeatureCompatibilityVersions(
1670 m_flatBufferBuilder,
1673 return versionsTable;
1676 std::vector<fb::Offset<serializer::InputSlot>>
1679 std::vector<fb::Offset<serializer::InputSlot>> inputSlots;
1682 for (
unsigned int slotIndex = 0; slotIndex<layer->
GetNumInputSlots(); ++slotIndex)
1693 inputSlots.push_back(serializer::CreateInputSlot(m_flatBufferBuilder, slotIndex, &conn));
1698 std::vector<fb::Offset<serializer::OutputSlot>>
1701 std::vector<fb::Offset<serializer::OutputSlot>> outputSlots;
1704 for (
unsigned int slotIndex = 0; slotIndex < layer->
GetNumOutputSlots(); ++slotIndex)
1710 outputSlots.push_back(serializer::CreateOutputSlot(m_flatBufferBuilder,
1712 CreateTensorInfo(tensorInfo)));
1736 inNetwork.
Accept(m_SerializerVisitor);
1737 flatbuffers::FlatBufferBuilder& fbBuilder = m_SerializerVisitor.GetFlatBufferBuilder();
1740 auto serializedGraph = serializer::CreateSerializedGraph(
1742 fbBuilder.CreateVector(m_SerializerVisitor.GetSerializedLayers()),
1743 fbBuilder.CreateVector(m_SerializerVisitor.GetInputIds()),
1744 fbBuilder.CreateVector(m_SerializerVisitor.GetOutputIds()),
1745 m_SerializerVisitor.GetVersionTable());
1748 fbBuilder.Finish(serializedGraph);
1751 bool Serializer::SaveSerializedToStream(std::ostream& stream)
1753 flatbuffers::FlatBufferBuilder& fbBuilder = m_SerializerVisitor.GetFlatBufferBuilder();
1756 stream.write(reinterpret_cast<const char*>(fbBuilder.GetBufferPointer()), bytesToWrite);
1757 return !stream.bad();
uint32_t m_PadBottom
Padding bottom value in the height dimension.
bool m_BiasEnabled
Enable/disable bias.
float m_Eps
Used to avoid dividing by zero.
virtual unsigned int GetNumOutputSlots() const =0
Returns the number of connectable output slots.
bool m_HalfPixelCenters
Half Pixel Centers.
armnnSerializer::UnaryOperation GetFlatBufferUnaryOperation(armnn::UnaryOperation comparisonOperation)
bool m_ProjectionEnabled
Enable/disable the projection layer.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
bool m_AlignCorners
Aligned corners.
UnaryOperation m_Operation
Specifies the elementwiseUnary operation to execute.
uint32_t m_Axis
0-based axis along which to stack the input tensors.
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.
uint32_t m_PadBottom
Padding bottom value in the height dimension.
bool m_BiasEnabled
Enable/disable bias.
virtual unsigned int GetNumInputSlots() const =0
Returns the number of connectable input slots.
float m_K
Kappa value used for the across channel normalization equation.
int m_Axis
Scalar, defaulted to the last index (-1), specifying the dimension the activation will be performed o...
A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer.
const TensorShape & GetShape() const
uint32_t m_PadBottom
Padding bottom value in the height dimension.
uint32_t m_PadLeft
Padding left value in the width dimension.
float m_ClippingThresProj
Clipping threshold value for the projection.
int32_t m_ShrinkAxisMask
Shrink axis mask value. If set, the nth specification shrinks the dimensionality by 1...
A ReshapeDescriptor for the ReshapeLayer.
std::vector< int > m_Begin
Begin values for the input that will be sliced.
float m_PadValue
Optional value to use for padding, defaults to 0.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
uint32_t GetNumDimensions() const
Get the number of dimensions.
A ComparisonDescriptor for the ComparisonLayer.
float m_ScaleX
Center size encoding scale x.
TensorShape m_InputShape
Required shape of all input tensors.
uint32_t m_TargetWidth
Target width value.
bool m_TransposeWeightMatrix
Enable/disable transpose weight matrix.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Dimensionality GetDimensionality() const
Function that returns the tensor type.
bool HasPerAxisQuantization() const
uint32_t m_PoolWidth
Pooling width value.
bool m_PeepholeEnabled
Enable/disable peephole.
armnnSerializer::OutputShapeRounding GetFlatBufferOutputShapeRounding(armnn::OutputShapeRounding outputShapeRounding)
A Convolution2dDescriptor for the Convolution2dLayer.
float m_Alpha
Alpha value for the normalization equation.
uint32_t m_PadLeft
Padding left value in the width dimension.
float m_HiddenStateScale
Hidden State quantization scale.
bool m_BiasEnabled
Enable/disable bias.
Optional< unsigned int > GetQuantizationDim() 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.
std::vector< unsigned int > m_Size
Size of the slice in each dimension.
float m_Eps
Value to add to the variance. Used to avoid dividing by zero.
PaddingMethod m_PaddingMethod
The padding method to be used. (Exclude, IgnoreValue).
ArgMinMaxFunction m_Function
Specify if the function is to find Min or Max.
uint32_t m_DetectionsPerClass
Detections per classes, used in Regular NMS.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
serializer::ActivationFunction GetFlatBufferActivationFunction(armnn::ActivationFunction function)
Main network class which provides the interface for building up a neural network. ...
armnnSerializer::NormalizationAlgorithmMethod GetFlatBufferNormalizationAlgorithmMethod(armnn::NormalizationAlgorithmMethod normalizationAlgorithmMethod)
uint32_t m_PadTop
Padding top value in the height dimension.
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
std::vector< std::pair< unsigned int, unsigned int > > m_PadList
Specifies the padding for input dimension.
uint32_t GetNumViews() const
Get the number of views.
Copyright (c) 2020 ARM Limited.
void IgnoreUnused(Ts &&...)
uint32_t m_PadBottom
Padding bottom value in the height dimension.
int32_t m_BeginMask
Begin mask value.
uint32_t m_DilationY
Dilation along y axis.
int32_t m_EndMask
End mask value.
A SpaceToDepthDescriptor for the SpaceToDepthLayer.
std::vector< std::pair< unsigned int, unsigned int > > m_PadList
Specifies the padding values for the input dimension: heightPad{top, bottom} widthPad{left, right}.
std::vector< float > GetQuantizationScales() const
uint32_t m_DilationY
Dilation factor value for height dimension.
armnnSerializer::ConstTensorData GetFlatBufferConstTensorData(armnn::DataType dataType)
A BatchToSpaceNdDescriptor for the BatchToSpaceNdLayer.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
PermutationVector m_DimMappings
Indicates how to translate tensor elements from a given source into the target destination, when source and target potentially have different memory layouts e.g.
int LayerBindingId
Type of identifiers for bindable layers (inputs, outputs).
armnnSerializer::DataType GetFlatBufferDataType(armnn::DataType dataType)
uint32_t m_NumOutputs
Number of output tensors.
NormalizationAlgorithmMethod m_NormMethodType
Normalization method algorithm to use (LocalBrightness, LocalContrast).
A ResizeDescriptor for the ResizeLayer.
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).
serializer::ArgMinMaxFunction GetFlatBufferArgMinMaxFunction(armnn::ArgMinMaxFunction function)
TensorShape m_TargetShape
Target shape value.
uint32_t m_PoolHeight
Pooling height value.
uint32_t m_PadTop
Padding top value in the height dimension.
uint32_t m_MaxDetections
Maximum numbers of detections.
A PadDescriptor for the PadLayer.
const uint32_t * GetViewOrigin(uint32_t idx) const
Return the view origin at the int value idx.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
armnnSerializer::NormalizationAlgorithmChannel GetFlatBufferNormalizationAlgorithmChannel(armnn::NormalizationAlgorithmChannel normalizationAlgorithmChannel)
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.
uint32_t m_PadRight
Padding right value in the width dimension.
uint32_t m_DilationX
Dilation factor value for width dimension.
uint32_t m_PadTop
Padding top value in the height dimension.
std::vector< unsigned int > m_Begin
Beginning indices of the slice in each dimension.
int32_t m_NewAxisMask
New axis mask value.
bool m_KeepDims
Enable/disable keep dimensions. If true, then the reduced dimensions that are of length 1 are kept...
std::vector< unsigned int > m_BlockShape
Block shape values.
float m_Eps
Epsilon, small scalar value added to variance to avoid dividing by zero. Defaults to 1e-12f...
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.
int32_t m_EllipsisMask
Ellipsis mask value.
virtual LayerGuid GetGuid() const =0
Returns the unique id of the layer.
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.
virtual unsigned int CalculateIndexOnOwner() const =0
std::enable_if_t< std::is_unsigned< Source >::value &&std::is_unsigned< Dest >::value, Dest > numeric_cast(Source source)
bool m_UseRegularNms
Use Regular NMS.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
std::vector< unsigned int > m_BlockShape
Block shape value.
std::vector< int > m_Stride
Stride values for the input that will be sliced.
An ActivationDescriptor for the ActivationLayer.
const TensorInfo & GetInfo() const
min(a, max(b, input)) ReLu1 & ReLu6.
uint32_t m_TargetHeight
Target height value.
uint32_t m_NumInputs
Number of input tensors.
uint32_t m_TargetHeight
Target height value.
uint32_t m_ActivationFunc
The activation function to use.
A SliceDescriptor for the SliceLayer.
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
float m_ClippingThresCell
Clipping threshold value for the cell state.
unsigned int m_BlockSize
Scalar specifying the input block size. It must be >= 1.
const uint32_t * GetViewOrigin(uint32_t idx) const
Get the view origin at the int value idx.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
float m_ForgetIntermediateScale
Forget intermediate quantization scale.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
float m_Beta
Beta, the offset scalar value applied for the normalized tensor. Defaults to 1.0. ...
armnnSerializer::DataLayout GetFlatBufferDataLayout(armnn::DataLayout dataLayout)
float m_ScaleH
Center size encoding scale height.
ComparisonOperation m_Operation
Specifies the comparison operation to execute.
std::vector< int > m_End
End values for the input that will be sliced.
A SpaceToBatchNdDescriptor for the SpaceToBatchNdLayer.
NormalizationAlgorithmChannel m_NormChannelType
Normalization channel algorithm to use (Across, Within).
const uint32_t * GetViewSizes(uint32_t idx) const
Get the view sizes at the int value idx.
float m_CellClip
Clipping threshold value for the cell state.
float m_A
Alpha upper bound value used by the activation functions. (BoundedReLu, Linear, TanH, Elu).
uint32_t m_DilationX
Dilation along x axis.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).
std::unique_ptr< ISerializer, void(*)(ISerializer *serializer)> ISerializerPtr
uint32_t m_PadLeft
Padding left value in the width dimension.
armnnSerializer::ComparisonOperation GetFlatBufferComparisonOperation(armnn::ComparisonOperation comparisonOperation)
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.
virtual void Accept(ILayerVisitor &visitor) const =0
A ElementwiseUnaryDescriptor for the ElementwiseUnaryLayer.
PoolingAlgorithm m_PoolType
The pooling algorithm to use (Max. Average, L2).
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.
std::vector< std::pair< unsigned int, unsigned int > > m_Crops
The values to crop from the input dimension.
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
bool m_ProjectionEnabled
Enable/disable the projection layer.
OutputShapeRounding m_OutputShapeRounding
The rounding method for the output shape. (Floor, Ceiling).
armnnSerializer::ResizeMethod GetFlatBufferResizeMethod(armnn::ResizeMethod method)
uint32_t m_NumInputs
Number of input tensors.
uint32_t GetNumDimensions() const
Get the number of dimensions.
virtual const IInputSlot & GetInputSlot(unsigned int index) const =0
Get a const input slot handle by slot index.
A MeanDescriptor for the MeanLayer.
armnnSerializer::PaddingMethod GetFlatBufferPaddingMethod(armnn::PaddingMethod paddingMethod)
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.
int m_Axis
Axis to reduce across the input tensor.
virtual const char * GetName() const =0
Returns the name of the layer.
float m_ScaleY
Center size encoding scale y.
uint32_t GetNumViews() const
Get the number of views.
float m_NmsScoreThreshold
NMS score threshold.
virtual LayerGuid GetOwningLayerGuid() const =0
A Pooling2dDescriptor for the Pooling2dLayer.
A NormalizationDescriptor for the NormalizationLayer.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
An InstanceNormalizationDescriptor for InstanceNormalizationLayer.
unsigned int GetConcatAxis() const
Get the concatenation axis value.
A ResizeBilinearDescriptor for the ResizeBilinearLayer.
float m_CellIntermediateScale
Cell intermediate quantization scale.
float m_B
Beta lower bound value used by the activation functions. (BoundedReLu, Linear, TanH).
A SoftmaxDescriptor for the SoftmaxLayer.
float m_Beta
Beta value for the normalization equation.
const OriginsDescriptor & GetOrigins() const
Get the View Origins.
bool m_CifgEnabled
Enable/disable CIFG (coupled input & forget gate).
PermutationVector m_DimMappings
Indicates how to translate tensor elements from a given source into the target destination, when source and target potentially have different memory layouts e.g.
uint32_t m_NormSize
Depth radius value.
ActivationFunction m_Function
The activation function to use (Sigmoid, TanH, Linear, ReLu, BoundedReLu, SoftReLu, LeakyReLu, Abs, Sqrt, Square, Elu).
armnnSerializer::PoolingAlgorithm GetFlatBufferPoolingAlgorithm(armnn::PoolingAlgorithm poolingAlgorithm)
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
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 })