14 #include <fmt/format.h> 17 using namespace armnn;
18 namespace fb = flatbuffers;
24 ISerializer::ISerializer() : pSerializerImpl(new SerializerImpl())
28 ISerializer::~ISerializer() =
default;
47 pSerializerImpl->Serialize(inNetwork);
52 return pSerializerImpl->SaveSerializedToStream(stream);
98 uint32_t SerializerStrategy::GetSerializedId(
LayerGuid guid)
100 if (m_guidMap.empty())
102 m_guidMap.insert(std::make_pair(guid, m_layerId));
104 else if (m_guidMap.find(guid) == m_guidMap.end())
107 m_guidMap.insert(std::make_pair(guid, m_layerId));
111 return m_guidMap[guid];
124 flatBufferInputBaseLayer,
127 m_inputIds.push_back(
id);
147 flatBufferOutputBaseLayer,
150 m_outputIds.push_back(
id);
177 flatBufferDescriptor);
216 flatBufferDescriptor);
231 std::vector<unsigned int> crops;
232 crops.reserve(descriptor.
m_Crops.size() * 2);
233 for (
auto& crop : descriptor.
m_Crops)
235 crops.push_back(crop.first);
236 crops.push_back(crop.second);
239 auto flatBufferDescriptor =
241 m_flatBufferBuilder.CreateVector(descriptor.
m_BlockShape),
242 m_flatBufferBuilder.CreateVector(crops),
247 flatBufferDescriptor);
252 void SerializerStrategy::SerializeBatchNormalizationLayer(
255 const std::vector<armnn::ConstTensor>& constants,
268 batchNormDescriptor.
m_Eps,
271 auto fbMeanConstTensorInfo = CreateConstTensorInfo(mean);
272 auto fbVarianceConstTensorInfo = CreateConstTensorInfo(variance);
273 auto fbBetaConstTensorInfo = CreateConstTensorInfo(beta);
274 auto fbGammaConstTensorInfo = CreateConstTensorInfo(gamma);
276 fbBatchNormalizationBaseLayer,
277 fbBatchNormalizationDescriptor,
278 fbMeanConstTensorInfo,
279 fbVarianceConstTensorInfo,
280 fbBetaConstTensorInfo,
281 fbGammaConstTensorInfo);
326 const std::vector<armnn::ConstTensor>& constants,
336 auto flatBufferConstTensorInfo = CreateConstTensorInfo(input);
340 flatBufferConstantBaseLayer,
341 flatBufferConstTensorInfo);
372 flatBufferDescriptor);
407 flatBufferDescriptor);
468 const std::vector<armnn::ConstTensor>& constants,
489 flatbuffers::Offset<serializer::ConstTensor> fbAnchorsConstTensorInfo = CreateConstTensorInfo(anchors);
494 fbAnchorsConstTensorInfo);
574 void SerializerStrategy::SerializeInstanceNormalizationLayer(
583 instanceNormalizationDescriptor.
m_Gamma,
584 instanceNormalizationDescriptor.
m_Beta,
585 instanceNormalizationDescriptor.
m_Eps,
607 l2NormalizationDescriptor.
m_Eps);
640 auto flatBufferLogSoftmaxDesc =
642 logSoftmaxDescriptor.
m_Beta,
643 logSoftmaxDescriptor.
m_Axis);
646 auto flatBufferLogSoftmaxLayer =
648 flatBufferLogSoftmaxBaseLayer,
649 flatBufferLogSoftmaxDesc);
656 const std::vector<armnn::ConstTensor>& constants,
677 auto inputToForgetWeights = CreateConstTensorInfo(constants[i++]);
678 auto inputToCellWeights = CreateConstTensorInfo(constants[i++]);
679 auto inputToOutputWeights = CreateConstTensorInfo(constants[i++]);
680 auto recurrentToForgetWeights = CreateConstTensorInfo(constants[i++]);
681 auto recurrentToCellWeights = CreateConstTensorInfo(constants[i++]);
682 auto recurrentToOutputWeights = CreateConstTensorInfo(constants[i++]);
683 auto forgetGateBias = CreateConstTensorInfo(constants[i++]);
684 auto cellBias = CreateConstTensorInfo(constants[i++]);
685 auto outputGateBias = CreateConstTensorInfo(constants[i++]);
690 flatbuffers::Offset<serializer::ConstTensor> inputToInputWeights;
691 flatbuffers::Offset<serializer::ConstTensor> recurrentToInputWeights;
692 flatbuffers::Offset<serializer::ConstTensor> cellToInputWeights;
693 flatbuffers::Offset<serializer::ConstTensor> inputGateBias;
694 flatbuffers::Offset<serializer::ConstTensor> projectionWeights;
695 flatbuffers::Offset<serializer::ConstTensor> projectionBias;
696 flatbuffers::Offset<serializer::ConstTensor> cellToForgetWeights;
697 flatbuffers::Offset<serializer::ConstTensor> cellToOutputWeights;
698 flatbuffers::Offset<serializer::ConstTensor> inputLayerNormWeights;
699 flatbuffers::Offset<serializer::ConstTensor> forgetLayerNormWeights;
700 flatbuffers::Offset<serializer::ConstTensor> cellLayerNormWeights;
701 flatbuffers::Offset<serializer::ConstTensor> outputLayerNormWeights;
705 inputToInputWeights = CreateConstTensorInfo(constants[i++]);
706 recurrentToInputWeights = CreateConstTensorInfo(constants[i++]);
707 inputGateBias = CreateConstTensorInfo(constants[i++]);
714 cellToInputWeights = CreateConstTensorInfo(constants[i++]);
716 cellToForgetWeights = CreateConstTensorInfo(constants[i++]);
717 cellToOutputWeights = CreateConstTensorInfo(constants[i++]);
722 projectionWeights = CreateConstTensorInfo(constants[i++]);
723 projectionBias = CreateConstTensorInfo(constants[i++]);
730 inputLayerNormWeights = CreateConstTensorInfo(constants[i++]);
732 forgetLayerNormWeights = CreateConstTensorInfo(constants[i++]);
733 cellLayerNormWeights = CreateConstTensorInfo(constants[i++]);
734 outputLayerNormWeights = CreateConstTensorInfo(constants[i++]);
739 inputToForgetWeights,
741 inputToOutputWeights,
742 recurrentToForgetWeights,
743 recurrentToCellWeights,
744 recurrentToOutputWeights,
749 recurrentToInputWeights,
756 inputLayerNormWeights,
757 forgetLayerNormWeights,
758 cellLayerNormWeights,
759 outputLayerNormWeights);
788 m_flatBufferBuilder.CreateVector(descriptor.
m_Axis),
826 std::vector<flatbuffers::Offset<UintVector>> views;
827 for (
unsigned int v = 0; v < concatDescriptor.
GetNumViews(); ++v)
830 std::vector<uint32_t> origins;
833 origins.push_back(origin[d]);
835 auto view = m_flatBufferBuilder.CreateVector(origins);
837 views.push_back(uintVector);
844 m_flatBufferBuilder.CreateVector(views));
847 flatBufferConcatBaseLayer,
848 flatBufferConcatDescriptor);
859 fbMultiplicationBaseLayer);
872 std::vector<unsigned int> padList;
875 padList.push_back(p.first);
876 padList.push_back(p.second);
880 m_flatBufferBuilder.CreateVector(padList),
900 std::vector<unsigned int> dimMappings;
907 m_flatBufferBuilder.CreateVector(dimMappings));
911 flatBufferPermuteBaseLayer,
912 flatBufferPermuteDesc);
936 m_flatBufferBuilder.CreateVector(reduceDescriptor.
m_vAxis),
955 std::vector<unsigned int> targetShape;
962 m_flatBufferBuilder.CreateVector(targetShape));
966 flatBufferReshapeDesc);
980 auto flatBufferDescriptor =
991 flatBufferDescriptor);
1004 m_flatBufferBuilder.CreateVector(sliceDescriptor.
m_Begin),
1005 m_flatBufferBuilder.CreateVector(sliceDescriptor.
m_Size));
1023 auto flatBufferSoftmaxDesc =
1025 softmaxDescriptor.
m_Beta,
1026 softmaxDescriptor.
m_Axis);
1029 auto flatBufferSoftmaxLayer =
1031 flatBufferSoftmaxBaseLayer,
1032 flatBufferSoftmaxDesc);
1045 m_flatBufferBuilder,
1060 fbPooling2dBaseLayer,
1061 fbPooling2dDescriptor);
1074 m_flatBufferBuilder,
1093 fbPooling3dBaseLayer,
1094 fbPooling3dDescriptor);
1120 fbQuantizeBaseLayer);
1133 auto flatBufferDescriptor =
1141 flatBufferBaseLayer,
1142 flatBufferDescriptor);
1158 std::vector<unsigned int> padList;
1159 padList.reserve(spaceToBatchNdDescriptor.
m_PadList.size()*2);
1160 for (
auto& pad : spaceToBatchNdDescriptor.
m_PadList)
1162 padList.push_back(pad.first);
1163 padList.push_back(pad.second);
1166 auto flatBufferDescriptor =
1168 m_flatBufferBuilder.CreateVector(spaceToBatchNdDescriptor.
m_BlockShape),
1169 m_flatBufferBuilder.CreateVector(padList),
1173 flatBufferBaseLayer,
1174 flatBufferDescriptor);
1187 auto flatBufferDescriptor =
1193 flatBufferBaseLayer,
1194 flatBufferDescriptor);
1207 std::vector<flatbuffers::Offset<UintVector>> flatBufferViewOrigins;
1208 flatBufferViewOrigins.reserve(viewsDescriptor.
GetNumViews());
1210 for(
unsigned int vIdx = 0; vIdx < viewsDescriptor.
GetNumViews(); ++vIdx)
1212 std::vector<uint32_t> viewOrigin;
1216 for(
unsigned int dIdx = 0; dIdx < viewsDescriptor.
GetNumDimensions(); ++dIdx)
1218 viewOrigin.push_back(viewsDescriptor.
GetViewOrigin(vIdx)[dIdx]);
1222 m_flatBufferBuilder.CreateVector(viewOrigin)));
1230 m_flatBufferBuilder.CreateVector(flatBufferViewOrigins));
1233 std::vector<flatbuffers::Offset<UintVector>> flatBufferViewSizes;
1234 flatBufferViewSizes.reserve(viewsDescriptor.
GetNumViews());
1236 for(
unsigned int vIdx = 0; vIdx < viewsDescriptor.
GetNumViews(); ++vIdx)
1238 std::vector<uint32_t> viewSize;
1242 for(
unsigned int dIdx = 0; dIdx < viewsDescriptor.
GetNumDimensions(); ++dIdx)
1244 viewSize.push_back(viewsDescriptor.
GetViewSizes(vIdx)[dIdx]);
1248 m_flatBufferBuilder.CreateVector(viewSize)));
1253 flatBufferOriginDescriptor,
1254 m_flatBufferBuilder.CreateVector(flatBufferViewSizes));
1260 flatBufferBaseLayer,
1261 flatBufferViewsDescriptor);
1275 m_flatBufferBuilder,
1285 fbNormalizationBaseLayer,
1286 fbNormalizationDescriptor);
1310 std::vector<unsigned int> inputShape;
1319 m_flatBufferBuilder.CreateVector(inputShape));
1349 auto flatBufferDescriptor =
1351 m_flatBufferBuilder.CreateVector(stridedSliceDescriptor.
m_Begin),
1352 m_flatBufferBuilder.CreateVector(stridedSliceDescriptor.
m_End),
1353 m_flatBufferBuilder.CreateVector(stridedSliceDescriptor.
m_Stride),
1362 flatBufferBaseLayer,
1363 flatBufferDescriptor);
1388 void SerializerStrategy::SerializeTransposeConvolution2dLayer(
1391 const std::vector<armnn::ConstTensor>& constants,
1410 auto fbWeightsConstTensorInfo = CreateConstTensorInfo(weights);
1411 flatbuffers::Offset<serializer::ConstTensor> fbBiasesConstTensorInfo;
1412 if (constants.size() > 1)
1415 fbBiasesConstTensorInfo = CreateConstTensorInfo(biases);
1421 fbWeightsConstTensorInfo,
1422 fbBiasesConstTensorInfo);
1436 std::vector<unsigned int> dimMappings;
1443 m_flatBufferBuilder.CreateVector(dimMappings));
1447 flatBufferBaseLayer,
1456 const std::vector<armnn::ConstTensor>& constants,
1464 m_flatBufferBuilder,
1483 auto inputToForgetWeights = CreateConstTensorInfo(constants[i++]);
1484 auto inputToCellWeights = CreateConstTensorInfo(constants[i++]);
1485 auto inputToOutputWeights = CreateConstTensorInfo(constants[i++]);
1486 auto recurrentToForgetWeights = CreateConstTensorInfo(constants[i++]);
1487 auto recurrentToCellWeights = CreateConstTensorInfo(constants[i++]);
1488 auto recurrentToOutputWeights = CreateConstTensorInfo(constants[i++]);
1489 auto forgetGateBias = CreateConstTensorInfo(constants[i++]);
1490 auto cellBias = CreateConstTensorInfo(constants[i++]);
1491 auto outputGateBias = CreateConstTensorInfo(constants[i++]);
1494 flatbuffers::Offset<serializer::ConstTensor> inputToInputWeights;
1495 flatbuffers::Offset<serializer::ConstTensor> recurrentToInputWeights;
1496 flatbuffers::Offset<serializer::ConstTensor> inputGateBias;
1500 inputToInputWeights = CreateConstTensorInfo(constants[i++]);
1501 recurrentToInputWeights = CreateConstTensorInfo(constants[i++]);
1502 inputGateBias = CreateConstTensorInfo(constants[i++]);
1506 flatbuffers::Offset<serializer::ConstTensor> cellToInputWeights;
1507 flatbuffers::Offset<serializer::ConstTensor> cellToForgetWeights;
1508 flatbuffers::Offset<serializer::ConstTensor> cellToOutputWeights;
1514 cellToInputWeights = CreateConstTensorInfo(constants[i++]);
1516 cellToForgetWeights = CreateConstTensorInfo(constants[i++]);
1517 cellToOutputWeights = CreateConstTensorInfo(constants[i++]);
1521 flatbuffers::Offset<serializer::ConstTensor> projectionWeights;
1522 flatbuffers::Offset<serializer::ConstTensor> projectionBias;
1526 projectionWeights = CreateConstTensorInfo(constants[i++]);
1527 projectionBias = CreateConstTensorInfo(constants[i++]);
1531 flatbuffers::Offset<serializer::ConstTensor> inputLayerNormWeights;
1532 flatbuffers::Offset<serializer::ConstTensor> forgetLayerNormWeights;
1533 flatbuffers::Offset<serializer::ConstTensor> cellLayerNormWeights;
1534 flatbuffers::Offset<serializer::ConstTensor> outputLayerNormWeights;
1540 inputLayerNormWeights = CreateConstTensorInfo(constants[i++]);
1542 forgetLayerNormWeights = CreateConstTensorInfo(constants[i++]);
1543 cellLayerNormWeights = CreateConstTensorInfo(constants[i++]);
1544 outputLayerNormWeights = CreateConstTensorInfo(constants[i++]);
1548 m_flatBufferBuilder,
1549 inputToForgetWeights,
1551 inputToOutputWeights,
1552 recurrentToForgetWeights,
1553 recurrentToCellWeights,
1554 recurrentToOutputWeights,
1558 inputToInputWeights,
1559 recurrentToInputWeights,
1564 cellToForgetWeights,
1565 cellToOutputWeights,
1566 inputLayerNormWeights,
1567 forgetLayerNormWeights,
1568 cellLayerNormWeights,
1569 outputLayerNormWeights);
1572 m_flatBufferBuilder,
1581 const std::vector<armnn::ConstTensor>& constants,
1592 auto inputToInputWeights = CreateConstTensorInfo(constants[i++]);
1593 auto inputToForgetWeights = CreateConstTensorInfo(constants[i++]);
1594 auto inputToCellWeights = CreateConstTensorInfo(constants[i++]);
1595 auto inputToOutputWeights = CreateConstTensorInfo(constants[i++]);
1597 auto recurrentToInputWeights = CreateConstTensorInfo(constants[i++]);
1598 auto recurrentToForgetWeights = CreateConstTensorInfo(constants[i++]);
1599 auto recurrentToCellWeights = CreateConstTensorInfo(constants[i++]);
1600 auto recurrentToOutputWeights = CreateConstTensorInfo(constants[i++]);
1602 auto inputGateBias = CreateConstTensorInfo(constants[i++]);
1603 auto forgetGateBias = CreateConstTensorInfo(constants[i++]);
1604 auto cellBias = CreateConstTensorInfo(constants[i++]);
1605 auto outputGateBias = CreateConstTensorInfo(constants[i++]);
1608 m_flatBufferBuilder,
1609 inputToInputWeights,
1610 inputToForgetWeights,
1612 inputToOutputWeights,
1613 recurrentToInputWeights,
1614 recurrentToForgetWeights,
1615 recurrentToCellWeights,
1616 recurrentToOutputWeights,
1623 m_flatBufferBuilder,
1624 fbQuantizedLstmBaseLayer,
1625 fbQuantizedLstmParams);
1630 void SerializerStrategy::SerializeUnidirectionalSequenceLstmLayer(
1633 const std::vector<armnn::ConstTensor>& constants,
1638 auto fbUnidirectionalSequenceLstmBaseLayer =
1642 m_flatBufferBuilder,
1656 auto inputToForgetWeights = CreateConstTensorInfo(constants[i++]);
1657 auto inputToCellWeights = CreateConstTensorInfo(constants[i++]);
1658 auto inputToOutputWeights = CreateConstTensorInfo(constants[i++]);
1659 auto recurrentToForgetWeights = CreateConstTensorInfo(constants[i++]);
1660 auto recurrentToCellWeights = CreateConstTensorInfo(constants[i++]);
1661 auto recurrentToOutputWeights = CreateConstTensorInfo(constants[i++]);
1662 auto forgetGateBias = CreateConstTensorInfo(constants[i++]);
1663 auto cellBias = CreateConstTensorInfo(constants[i++]);
1664 auto outputGateBias = CreateConstTensorInfo(constants[i++]);
1667 flatbuffers::Offset<serializer::ConstTensor> inputToInputWeights;
1668 flatbuffers::Offset<serializer::ConstTensor> recurrentToInputWeights;
1669 flatbuffers::Offset<serializer::ConstTensor> cellToInputWeights;
1670 flatbuffers::Offset<serializer::ConstTensor> inputGateBias;
1671 flatbuffers::Offset<serializer::ConstTensor> projectionWeights;
1672 flatbuffers::Offset<serializer::ConstTensor> projectionBias;
1673 flatbuffers::Offset<serializer::ConstTensor> cellToForgetWeights;
1674 flatbuffers::Offset<serializer::ConstTensor> cellToOutputWeights;
1675 flatbuffers::Offset<serializer::ConstTensor> inputLayerNormWeights;
1676 flatbuffers::Offset<serializer::ConstTensor> forgetLayerNormWeights;
1677 flatbuffers::Offset<serializer::ConstTensor> cellLayerNormWeights;
1678 flatbuffers::Offset<serializer::ConstTensor> outputLayerNormWeights;
1682 inputToInputWeights = CreateConstTensorInfo(constants[i++]);
1683 recurrentToInputWeights = CreateConstTensorInfo(constants[i++]);
1684 inputGateBias = CreateConstTensorInfo(constants[i++]);
1691 cellToInputWeights = CreateConstTensorInfo(constants[i++]);
1693 cellToForgetWeights = CreateConstTensorInfo(constants[i++]);
1694 cellToOutputWeights = CreateConstTensorInfo(constants[i++]);
1699 projectionWeights = CreateConstTensorInfo(constants[i++]);
1700 projectionBias = CreateConstTensorInfo(constants[i++]);
1707 inputLayerNormWeights = CreateConstTensorInfo(constants[i++]);
1709 forgetLayerNormWeights = CreateConstTensorInfo(constants[i++]);
1710 cellLayerNormWeights = CreateConstTensorInfo(constants[i++]);
1711 outputLayerNormWeights = CreateConstTensorInfo(constants[i++]);
1715 m_flatBufferBuilder,
1716 inputToForgetWeights,
1718 inputToOutputWeights,
1719 recurrentToForgetWeights,
1720 recurrentToCellWeights,
1721 recurrentToOutputWeights,
1725 inputToInputWeights,
1726 recurrentToInputWeights,
1731 cellToForgetWeights,
1732 cellToOutputWeights,
1733 inputLayerNormWeights,
1734 forgetLayerNormWeights,
1735 cellLayerNormWeights,
1736 outputLayerNormWeights);
1739 m_flatBufferBuilder,
1740 fbUnidirectionalSequenceLstmBaseLayer,
1741 fbUnidirectionalSequenceLstmDescriptor,
1742 fbUnidirectionalSequenceLstmParams);
1747 fb::Offset<serializer::LayerBase> SerializerStrategy::CreateLayerBase(
const IConnectableLayer* layer,
1751 uint32_t fbIndex = GetSerializedId(layer->
GetGuid());
1753 std::vector<fb::Offset<serializer::InputSlot>> inputSlots = CreateInputSlots(layer);
1754 std::vector<fb::Offset<serializer::OutputSlot>> outputSlots = CreateOutputSlots(layer);
1758 m_flatBufferBuilder.CreateString(layer->
GetName()),
1760 m_flatBufferBuilder.CreateVector(inputSlots),
1761 m_flatBufferBuilder.CreateVector(outputSlots));
1764 void SerializerStrategy::CreateAnyLayer(
const flatbuffers::Offset<void>& layer,
const serializer::Layer serializerLayer)
1768 m_serializedLayers.push_back(anyLayer);
1771 template <
typename T>
1772 flatbuffers::Offset<flatbuffers::Vector<T>> SerializerStrategy::CreateDataVector(
const void* memory,
unsigned int size)
1774 const T* buffer =
reinterpret_cast<const T*
>(memory);
1775 std::vector<T> vector(buffer, buffer + (size /
sizeof(T)));
1776 auto fbVector = m_flatBufferBuilder.CreateVector(vector);
1780 flatbuffers::Offset<TensorInfo> SerializerStrategy::CreateTensorInfo(
const armnn::TensorInfo& tensorInfo)
1783 std::vector<unsigned int> shape;
1784 std::vector<bool> specificity;
1793 shape.push_back(tensorInfo.
GetShape()[dim]);
1804 auto flatBufferTensorInfo =
1806 m_flatBufferBuilder.CreateVector(shape),
1812 static_cast<unsigned int> 1814 m_flatBufferBuilder.CreateVector(specificity));
1815 return flatBufferTensorInfo;
1820 m_flatBufferBuilder.CreateVector(shape),
1826 static_cast<unsigned int> 1828 m_flatBufferBuilder.CreateVector(specificity));
1829 return flatBufferTensorInfo;
1832 flatbuffers::Offset<serializer::ConstTensor>
1837 flatbuffers::Offset<void> fbPayload;
1845 m_flatBufferBuilder,
1847 fbPayload = flatBuffersData.o;
1855 m_flatBufferBuilder,
1857 fbPayload = flatBuffersData.o;
1866 m_flatBufferBuilder,
1868 fbPayload = flatBuffersData.o;
1879 m_flatBufferBuilder,
1881 fbPayload = flatBuffersData.o;
1885 m_flatBufferBuilder,
1889 return flatBufferConstTensor;
1894 flatbuffers::Offset<armnnSerializer::FeatureCompatibilityVersions> versionsTable =
1896 m_flatBufferBuilder,
1901 return versionsTable;
1904 std::vector<fb::Offset<serializer::InputSlot>>
1907 std::vector<fb::Offset<serializer::InputSlot>> inputSlots;
1910 for (
unsigned int slotIndex = 0; slotIndex<layer->
GetNumInputSlots(); ++slotIndex)
1926 std::vector<fb::Offset<serializer::OutputSlot>>
1929 std::vector<fb::Offset<serializer::OutputSlot>> outputSlots;
1932 for (
unsigned int slotIndex = 0; slotIndex < layer->
GetNumOutputSlots(); ++slotIndex)
1947 const std::vector<armnn::ConstTensor>& constants,
1959 SerializeActivationLayer(layer, layerDescriptor, name);
1964 SerializeAdditionLayer(layer, name);
1971 SerializeArgMinMaxLayer(layer, layerDescriptor, name);
1978 SerializeBatchNormalizationLayer(layer,
1988 SerializeBatchToSpaceNdLayer(layer,
1995 SerializeCastLayer(layer, name);
2002 SerializeChannelShuffleLayer(layer,
2011 SerializeComparisonLayer(layer,
2020 SerializeConcatLayer(layer,
2027 SerializeConstantLayer(layer,
2036 SerializeConvolution2dLayer(layer,
2045 SerializeConvolution3dLayer(layer,
2054 SerializeDepthToSpaceLayer(layer,
2063 SerializeDepthwiseConvolution2dLayer(layer,
2070 SerializeDequantizeLayer(layer,
2078 SerializeDetectionPostProcessLayer(layer, layerDescriptor, constants, name);
2083 SerializeDivisionLayer(layer, name);
2090 SerializeElementwiseUnaryLayer(layer, layerDescriptor, name);
2097 SerializeFillLayer(layer, layerDescriptor, name);
2102 SerializeFloorLayer(layer, name);
2109 SerializeFullyConnectedLayer(layer, layerDescriptor, name);
2116 SerializeGatherLayer(layer, layerDescriptor, name);
2121 SerializeGatherNdLayer(layer, name);
2126 SerializeInputLayer(layer,
id, name);
2133 SerializeInstanceNormalizationLayer(layer, layerDescriptor, name);
2140 SerializeL2NormalizationLayer(layer, layerDescriptor, name);
2147 SerializeLogicalBinaryLayer(layer, layerDescriptor, name);
2154 SerializeLogSoftmaxLayer(layer, layerDescriptor, name);
2161 SerializeLstmLayer(layer, layerDescriptor, constants, name);
2168 SerializeQLstmLayer(layer, layerDescriptor, constants, name);
2173 SerializeMaximumLayer(layer, name);
2180 SerializeMeanLayer(layer, layerDescriptor, name);
2185 SerializeMergeLayer(layer, name);
2190 SerializeMinimumLayer(layer, name);
2195 SerializeMultiplicationLayer(layer, name);
2202 SerializeNormalizationLayer(layer, layerDescriptor, name);
2207 SerializeOutputLayer(layer,
id, name);
2214 SerializePadLayer(layer, layerDescriptor, name);
2221 SerializePermuteLayer(layer, layerDescriptor, name);
2228 SerializePooling2dLayer(layer, layerDescriptor, name);
2235 SerializePooling3dLayer(layer, layerDescriptor, name);
2240 SerializePreluLayer(layer, name);
2245 SerializeQuantizeLayer(layer, name);
2249 SerializeQuantizedLstmLayer(layer, constants, name);
2255 SerializeReshapeLayer(layer, layerDescriptor, name);
2260 SerializeRankLayer(layer, name);
2267 SerializeReduceLayer(layer, layerDescriptor, name);
2274 SerializeResizeLayer(layer, layerDescriptor, name);
2279 SerializeShapeLayer(layer, name);
2286 SerializeSliceLayer(layer, layerDescriptor, name);
2293 SerializeSoftmaxLayer(layer, layerDescriptor, name);
2300 SerializeSpaceToBatchNdLayer(layer, layerDescriptor, name);
2307 SerializeSpaceToDepthLayer(layer, layerDescriptor, name);
2314 SerializeSplitterLayer(layer, layerDescriptor, name);
2321 SerializeStackLayer(layer, layerDescriptor, name);
2328 SerializeStandInLayer(layer, layerDescriptor, name);
2335 SerializeStridedSliceLayer(layer, layerDescriptor, name);
2340 SerializeSubtractionLayer(layer, name);
2345 SerializeSwitchLayer(layer, name);
2352 SerializeTransposeLayer(layer, layerDescriptor, name);
2359 SerializeTransposeConvolution2dLayer(layer, layerDescriptor, constants, name);
2366 SerializeUnidirectionalSequenceLstmLayer(layer, layerDescriptor, constants, name);
2372 fmt::format(
"A layer of unknown type was given to the serializer. Layer name: {}; Layer Id: {}",
2383 flatbuffers::FlatBufferBuilder& fbBuilder = m_SerializerStrategy.GetFlatBufferBuilder();
2388 fbBuilder.CreateVector(m_SerializerStrategy.GetSerializedLayers()),
2389 fbBuilder.CreateVector(m_SerializerStrategy.GetInputIds()),
2390 fbBuilder.CreateVector(m_SerializerStrategy.GetOutputIds()),
2391 m_SerializerStrategy.GetVersionTable());
2394 fbBuilder.Finish(serializedGraph);
2400 flatbuffers::FlatBufferBuilder& fbBuilder = m_SerializerStrategy.GetFlatBufferBuilder();
2403 stream.write(reinterpret_cast<const char*>(fbBuilder.GetBufferPointer()), bytesToWrite);
2404 return !stream.bad();
uint32_t m_PadBottom
Padding bottom value in the height dimension.
bool m_BiasEnabled
Enable/disable bias.
flatbuffers::Offset< Convolution3dDescriptor > CreateConvolution3dDescriptor(flatbuffers::FlatBufferBuilder &_fbb, uint32_t padLeft=0, uint32_t padRight=0, uint32_t padTop=0, uint32_t padBottom=0, uint32_t padFront=0, uint32_t padBack=0, uint32_t strideX=0, uint32_t strideY=0, uint32_t strideZ=0, uint32_t dilationX=1, uint32_t dilationY=1, uint32_t dilationZ=1, bool biasEnabled=false, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NDHWC)
PoolingAlgorithm m_PoolType
The pooling algorithm to use (Max. Average, L2).
flatbuffers::Offset< LongData > CreateLongData(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< int64_t >> data=0)
float m_Eps
Used to avoid dividing by zero.
virtual unsigned int GetNumOutputSlots() const =0
Returns the number of connectable output slots.
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).
flatbuffers::Offset< ReshapeDescriptor > CreateReshapeDescriptor(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< uint32_t >> targetShape=0)
ARMNN_NO_DEPRECATE_WARN_END void ExecuteStrategy(IStrategy &strategy) const
flatbuffers::Offset< ReduceLayer > CreateReduceLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::ReduceDescriptor > descriptor=0)
UnaryOperation m_Operation
Specifies the elementwiseUnary operation to execute.
uint32_t m_Axis
0-based axis along which to stack the input tensors.
flatbuffers::Offset< OutputSlot > CreateOutputSlot(flatbuffers::FlatBufferBuilder &_fbb, uint32_t index=0, flatbuffers::Offset< armnnSerializer::TensorInfo > tensorInfo=0)
A ViewsDescriptor for the SplitterLayer.
Interface for a layer that is connectable to other layers via InputSlots and OutputSlots.
flatbuffers::Offset< DepthwiseConvolution2dDescriptor > CreateDepthwiseConvolution2dDescriptor(flatbuffers::FlatBufferBuilder &_fbb, uint32_t padLeft=0, uint32_t padRight=0, uint32_t padTop=0, uint32_t padBottom=0, uint32_t strideX=0, uint32_t strideY=0, uint32_t dilationX=1, uint32_t dilationY=1, bool biasEnabled=false, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NCHW)
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.
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
flatbuffers::Offset< LstmLayer > CreateLstmLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::LstmDescriptor > descriptor=0, flatbuffers::Offset< armnnSerializer::LstmInputParams > inputParams=0)
const TensorShape & GetShape() const
uint32_t m_PoolWidth
Pooling width value.
flatbuffers::Offset< L2NormalizationLayer > CreateL2NormalizationLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::L2NormalizationDescriptor > descriptor=0)
uint32_t m_PadBottom
Padding bottom value in the height dimension.
uint32_t m_PadLeft
Padding left value in the width dimension.
flatbuffers::Offset< TransposeConvolution2dDescriptor > CreateTransposeConvolution2dDescriptor(flatbuffers::FlatBufferBuilder &_fbb, uint32_t padLeft=0, uint32_t padRight=0, uint32_t padTop=0, uint32_t padBottom=0, uint32_t strideX=0, uint32_t strideY=0, bool biasEnabled=false, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NCHW)
float m_ClippingThresProj
Clipping threshold value for the projection.
uint32_t m_PoolDepth
Pooling depth value.
int32_t m_ShrinkAxisMask
Shrink axis mask value. If set, the nth specification shrinks the dimensionality by 1...
A ReshapeDescriptor for the ReshapeLayer.
flatbuffers::Offset< ResizeDescriptor > CreateResizeDescriptor(flatbuffers::FlatBufferBuilder &_fbb, uint32_t targetHeight=0, uint32_t targetWidth=0, armnnSerializer::ResizeMethod method=armnnSerializer::ResizeMethod_NearestNeighbor, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NHWC, bool alignCorners=false, bool halfPixelCenters=false)
flatbuffers::Offset< FillLayer > CreateFillLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::FillDescriptor > descriptor=0)
std::vector< int > m_Begin
Begin values for the input that will be sliced.
uint32_t m_PadBack
Padding back value in the depth dimension.
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.
void Serialize(const armnn::INetwork &inNetwork)
Serializes the network to ArmNN SerializedGraph.
float m_ScaleX
Center size encoding scale x.
TensorShape m_InputShape
Required shape of all input tensors.
bool m_TransposeWeightMatrix
Enable/disable transpose weight matrix.
Dimensionality GetDimensionality() const
Function that returns the tensor type.
flatbuffers::Offset< GatherLayer > CreateGatherLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::GatherDescriptor > descriptor=0)
flatbuffers::Offset< RankLayer > CreateRankLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
bool HasPerAxisQuantization() const
uint32_t m_PoolWidth
Pooling width value.
bool m_PeepholeEnabled
Enable/disable peephole.
armnnSerializer::OutputShapeRounding GetFlatBufferOutputShapeRounding(armnn::OutputShapeRounding outputShapeRounding)
flatbuffers::Offset< TransposeLayer > CreateTransposeLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::TransposeDescriptor > descriptor=0)
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
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.
flatbuffers::Offset< ComparisonLayer > CreateComparisonLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::ComparisonDescriptor > descriptor=0)
bool m_KeepDims
if true then output shape has no change.
float m_HiddenStateScale
Hidden State quantization scale.
bool m_BiasEnabled
Enable/disable bias.
flatbuffers::Offset< ConstTensor > CreateConstTensor(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::TensorInfo > info=0, armnnSerializer::ConstTensorData data_type=armnnSerializer::ConstTensorData_NONE, flatbuffers::Offset< void > data=0)
Optional< unsigned int > GetQuantizationDim() const
flatbuffers::Offset< QuantizeLayer > CreateQuantizeLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
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.
flatbuffers::Offset< InputSlot > CreateInputSlot(flatbuffers::FlatBufferBuilder &_fbb, uint32_t index=0, const armnnSerializer::Connection *connection=0)
std::vector< unsigned int > m_Size
Size of the slice in each dimension.
static ISerializer * CreateRaw()
flatbuffers::Offset< SpaceToDepthDescriptor > CreateSpaceToDepthDescriptor(flatbuffers::FlatBufferBuilder &_fbb, uint32_t blockSize=0, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NHWC)
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).
flatbuffers::Offset< GatherNdLayer > CreateGatherNdLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
flatbuffers::Offset< QuantizedLstmLayer > CreateQuantizedLstmLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::QuantizedLstmInputParams > inputParams=0)
flatbuffers::Offset< TransposeDescriptor > CreateTransposeDescriptor(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< uint32_t >> dimMappings=0)
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. ...
uint32_t m_PadRight
Padding right value in the width dimension.
flatbuffers::Offset< DetectionPostProcessDescriptor > CreateDetectionPostProcessDescriptor(flatbuffers::FlatBufferBuilder &_fbb, uint32_t maxDetections=0, uint32_t maxClassesPerDetection=0, uint32_t detectionsPerClass=0, float nmsScoreThreshold=0.0f, float nmsIouThreshold=0.0f, uint32_t numClasses=0, bool useRegularNms=false, float scaleX=0.0f, float scaleY=0.0f, float scaleW=0.0f, float scaleH=0.0f)
flatbuffers::Offset< Pooling3dLayer > CreatePooling3dLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::Pooling3dDescriptor > descriptor=0)
armnnSerializer::NormalizationAlgorithmMethod GetFlatBufferNormalizationAlgorithmMethod(armnn::NormalizationAlgorithmMethod normalizationAlgorithmMethod)
uint32_t m_PadTop
Padding top value in the height dimension.
flatbuffers::Offset< AnyLayer > CreateAnyLayer(flatbuffers::FlatBufferBuilder &_fbb, armnnSerializer::Layer layer_type=armnnSerializer::Layer_NONE, flatbuffers::Offset< void > layer=0)
uint32_t m_PadBottom
Padding bottom value in the height dimension.
flatbuffers::Offset< DepthwiseConvolution2dLayer > CreateDepthwiseConvolution2dLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::DepthwiseConvolution2dDescriptor > descriptor=0, flatbuffers::Offset< armnnSerializer::ConstTensor > weights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > biases=0)
bool m_BiasEnabled
Enable/disable bias.
A LogicalBinaryDescriptor for the LogicalBinaryLayer.
flatbuffers::Offset< MergeLayer > CreateMergeLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
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.
ReduceOperation m_ReduceOperation
Specifies the reduction operation to execute.
flatbuffers::Offset< QLstmInputParams > CreateQLstmInputParams(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::ConstTensor > inputToForgetWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > inputToCellWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > inputToOutputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > recurrentToForgetWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > recurrentToCellWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > recurrentToOutputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > forgetGateBias=0, flatbuffers::Offset< armnnSerializer::ConstTensor > cellBias=0, flatbuffers::Offset< armnnSerializer::ConstTensor > outputGateBias=0, flatbuffers::Offset< armnnSerializer::ConstTensor > inputToInputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > recurrentToInputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > inputGateBias=0, flatbuffers::Offset< armnnSerializer::ConstTensor > projectionWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > projectionBias=0, flatbuffers::Offset< armnnSerializer::ConstTensor > cellToInputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > cellToForgetWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > cellToOutputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > inputLayerNormWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > forgetLayerNormWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > cellLayerNormWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > outputLayerNormWeights=0)
bool m_TimeMajor
Enable/disable time major.
Copyright (c) 2021 ARM Limited and Contributors.
DataLayout m_DataLayout
The data layout to be used (NCDHW, NDHWC).
void IgnoreUnused(Ts &&...)
flatbuffers::Offset< TensorInfo > CreateTensorInfo(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< uint32_t >> dimensions=0, armnnSerializer::DataType dataType=armnnSerializer::DataType_Float16, float quantizationScale=1.0f, int32_t quantizationOffset=0, flatbuffers::Offset< flatbuffers::Vector< float >> quantizationScales=0, uint32_t quantizationDim=0, uint32_t dimensionality=1, flatbuffers::Offset< flatbuffers::Vector< uint8_t >> dimensionSpecificity=0, bool isConstant=false)
uint32_t m_PadBottom
Padding bottom value in the height dimension.
int32_t m_BeginMask
Begin mask value.
uint32_t m_PadFront
Padding front value in the depth dimension.
flatbuffers::Offset< FullyConnectedDescriptor > CreateFullyConnectedDescriptor(flatbuffers::FlatBufferBuilder &_fbb, bool biasEnabled=false, bool transposeWeightsMatrix=false, bool constantWeights=true)
flatbuffers::Offset< TransposeConvolution2dLayer > CreateTransposeConvolution2dLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::TransposeConvolution2dDescriptor > descriptor=0, flatbuffers::Offset< armnnSerializer::ConstTensor > weights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > biases=0)
uint32_t m_DilationY
Dilation along y axis.
int32_t m_EndMask
End mask value.
A SpaceToDepthDescriptor for the SpaceToDepthLayer.
flatbuffers::Offset< PreluLayer > CreatePreluLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
std::vector< std::pair< unsigned int, unsigned int > > m_PadList
Specifies the padding values for the input dimension: heightPad{top, bottom} widthPad{left, right}.
uint32_t m_PoolHeight
Pooling height value.
std::vector< float > GetQuantizationScales() const
uint32_t m_DilationX
Dilation along x axis.
flatbuffers::Offset< StandInDescriptor > CreateStandInDescriptor(flatbuffers::FlatBufferBuilder &_fbb, uint32_t numInputs=0, uint32_t numOutputs=0)
bool SaveSerializedToStream(std::ostream &stream)
Serializes the SerializedGraph to the stream.
uint32_t m_DilationY
Dilation factor value for height dimension.
armnnSerializer::ConstTensorData GetFlatBufferConstTensorData(armnn::DataType dataType)
bool GetDimensionSpecificity(unsigned int i) const
Gets information about if the dimension size has been specified or not.
LogicalBinaryOperation m_Operation
Specifies the logical operation to execute.
A BatchToSpaceNdDescriptor for the BatchToSpaceNdLayer.
void ExecuteStrategy(const armnn::IConnectableLayer *layer, const armnn::BaseDescriptor &descriptor, const std::vector< armnn::ConstTensor > &constants, const char *name, const armnn::LayerBindingId id) override
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.
flatbuffers::Offset< MultiplicationLayer > CreateMultiplicationLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
flatbuffers::Offset< DepthToSpaceLayer > CreateDepthToSpaceLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::DepthToSpaceDescriptor > descriptor=0)
flatbuffers::Offset< InstanceNormalizationLayer > CreateInstanceNormalizationLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::InstanceNormalizationDescriptor > descriptor=0)
armnnSerializer::ReduceOperation GetFlatBufferReduceOperation(armnn::ReduceOperation reduceOperation)
int LayerBindingId
Type of identifiers for bindable layers (inputs, outputs).
flatbuffers::Offset< SliceLayer > CreateSliceLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::SliceDescriptor > descriptor=0)
armnnSerializer::DataType GetFlatBufferDataType(armnn::DataType dataType)
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
uint32_t m_NumOutputs
Number of output tensors.
NormalizationAlgorithmMethod m_NormMethodType
Normalization method algorithm to use (LocalBrightness, LocalContrast).
flatbuffers::Offset< Convolution2dDescriptor > CreateConvolution2dDescriptor(flatbuffers::FlatBufferBuilder &_fbb, uint32_t padLeft=0, uint32_t padRight=0, uint32_t padTop=0, uint32_t padBottom=0, uint32_t strideX=0, uint32_t strideY=0, uint32_t dilationX=1, uint32_t dilationY=1, bool biasEnabled=false, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NCHW)
flatbuffers::Offset< Pooling3dDescriptor > CreatePooling3dDescriptor(flatbuffers::FlatBufferBuilder &_fbb, armnnSerializer::PoolingAlgorithm poolType=armnnSerializer::PoolingAlgorithm_Max, uint32_t padLeft=0, uint32_t padRight=0, uint32_t padTop=0, uint32_t padBottom=0, uint32_t padFront=0, uint32_t padBack=0, uint32_t poolWidth=0, uint32_t poolHeight=0, uint32_t poolDepth=0, uint32_t strideX=0, uint32_t strideY=0, uint32_t strideZ=0, armnnSerializer::OutputShapeRounding outputShapeRounding=armnnSerializer::OutputShapeRounding_Floor, armnnSerializer::PaddingMethod paddingMethod=armnnSerializer::PaddingMethod_IgnoreValue, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NHWC)
flatbuffers::Offset< InputLayer > CreateInputLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::BindableLayerBase > base=0)
A ResizeBilinearDescriptor for the ResizeBilinearLayer.
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.
Base class for all descriptors.
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).
flatbuffers::Offset< ShortData > CreateShortData(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< int16_t >> data=0)
serializer::ArgMinMaxFunction GetFlatBufferArgMinMaxFunction(armnn::ArgMinMaxFunction function)
TensorShape m_TargetShape
Target shape value.
bool SaveSerializedToStream(std::ostream &stream)
Serializes the SerializedGraph to the stream.
flatbuffers::Offset< ConcatLayer > CreateConcatLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::OriginsDescriptor > descriptor=0)
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.
flatbuffers::Offset< SubtractionLayer > CreateSubtractionLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
flatbuffers::Offset< BindableLayerBase > CreateBindableLayerBase(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, int32_t layerBindingId=0)
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.
uint32_t m_PadBack
Padding back value in the depth dimension.
flatbuffers::Offset< ArgMinMaxLayer > CreateArgMinMaxLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::ArgMinMaxDescriptor > descriptor=0)
armnnSerializer::NormalizationAlgorithmChannel GetFlatBufferNormalizationAlgorithmChannel(armnn::NormalizationAlgorithmChannel normalizationAlgorithmChannel)
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
flatbuffers::Offset< QLstmDescriptor > CreateQLstmDescriptor(flatbuffers::FlatBufferBuilder &_fbb, bool cifgEnabled=true, bool peepholeEnabled=false, bool projectionEnabled=false, bool layerNormEnabled=false, float cellClip=0.0f, float projectionClip=0.0f, float inputIntermediateScale=0.0f, float forgetIntermediateScale=0.0f, float cellIntermediateScale=0.0f, float outputIntermediateScale=0.0f, int32_t hiddenStateZeroPoint=0, float hiddenStateScale=0.0f)
bool m_LayerNormEnabled
Enable/disable layer normalization.
float m_NmsIouThreshold
Intersection over union threshold.
flatbuffers::Offset< ReshapeLayer > CreateReshapeLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::ReshapeDescriptor > descriptor=0)
armnnSerializer::LogicalBinaryOperation GetFlatBufferLogicalBinaryOperation(armnn::LogicalBinaryOperation logicalBinaryOperation)
flatbuffers::Offset< ArgMinMaxDescriptor > CreateArgMinMaxDescriptor(flatbuffers::FlatBufferBuilder &_fbb, armnnSerializer::ArgMinMaxFunction argMinMaxFunction=armnnSerializer::ArgMinMaxFunction_Min, int32_t axis=0)
flatbuffers::Offset< SoftmaxDescriptor > CreateSoftmaxDescriptor(flatbuffers::FlatBufferBuilder &_fbb, float beta=0.0f, int32_t axis=-1)
An LstmDescriptor for the LstmLayer.
uint32_t m_PadRight
Padding right value in the width dimension.
flatbuffers::Offset< AdditionLayer > CreateAdditionLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
uint32_t m_DilationX
Dilation factor value for width dimension.
uint32_t m_PadTop
Padding top value in the height dimension.
flatbuffers::Offset< L2NormalizationDescriptor > CreateL2NormalizationDescriptor(flatbuffers::FlatBufferBuilder &_fbb, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NCHW, float eps=1e-12f)
std::vector< unsigned int > m_Begin
Beginning indices of the slice in each dimension.
int32_t m_NewAxisMask
New axis mask value.
flatbuffers::Offset< MinimumLayer > CreateMinimumLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
bool m_KeepDims
Enable/disable keep dimensions. If true, then the reduced dimensions that are of length 1 are kept...
flatbuffers::Offset< ByteData > CreateByteData(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< int8_t >> data=0)
std::vector< unsigned int > m_BlockShape
Block shape values.
flatbuffers::Offset< FeatureCompatibilityVersions > CreateFeatureCompatibilityVersions(flatbuffers::FlatBufferBuilder &_fbb, uint32_t bindingIdsScheme=0, uint32_t weightsLayoutScheme=0, uint32_t constantTensorsAsInputs=0)
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.
flatbuffers::Offset< DepthToSpaceDescriptor > CreateDepthToSpaceDescriptor(flatbuffers::FlatBufferBuilder &_fbb, uint32_t blockSize=0, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NHWC)
A L2NormalizationDescriptor for the L2NormalizationLayer.
int32_t GetQuantizationOffset() const
An ArgMinMaxDescriptor for ArgMinMaxLayer.
armnnSerializer::PaddingMode GetFlatBufferPaddingMode(armnn::PaddingMode paddingMode)
float GetQuantizationScale() const
flatbuffers::Offset< LstmInputParams > CreateLstmInputParams(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::ConstTensor > inputToForgetWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > inputToCellWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > inputToOutputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > recurrentToForgetWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > recurrentToCellWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > recurrentToOutputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > forgetGateBias=0, flatbuffers::Offset< armnnSerializer::ConstTensor > cellBias=0, flatbuffers::Offset< armnnSerializer::ConstTensor > outputGateBias=0, flatbuffers::Offset< armnnSerializer::ConstTensor > inputToInputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > recurrentToInputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > cellToInputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > inputGateBias=0, flatbuffers::Offset< armnnSerializer::ConstTensor > projectionWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > projectionBias=0, flatbuffers::Offset< armnnSerializer::ConstTensor > cellToForgetWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > cellToOutputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > inputLayerNormWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > forgetLayerNormWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > cellLayerNormWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > outputLayerNormWeights=0)
DataType GetDataType() const
An OriginsDescriptor for the ConcatLayer.
A ReduceDescriptor for the REDUCE operators.
float m_ProjectionClip
Clipping threshold value for the projection.
flatbuffers::Offset< CastLayer > CreateCastLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
flatbuffers::Offset< LayerBase > CreateLayerBase(flatbuffers::FlatBufferBuilder &_fbb, uint32_t index=0, flatbuffers::Offset< flatbuffers::String > layerName=0, armnnSerializer::LayerType layerType=armnnSerializer::LayerType_Addition, flatbuffers::Offset< flatbuffers::Vector< flatbuffers::Offset< armnnSerializer::InputSlot >>> inputSlots=0, flatbuffers::Offset< flatbuffers::Vector< flatbuffers::Offset< armnnSerializer::OutputSlot >>> outputSlots=0)
flatbuffers::Offset< ShapeLayer > CreateShapeLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
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.
flatbuffers::Offset< QuantizedLstmInputParams > CreateQuantizedLstmInputParams(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::ConstTensor > inputToInputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > inputToForgetWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > inputToCellWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > inputToOutputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > recurrentToInputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > recurrentToForgetWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > recurrentToCellWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > recurrentToOutputWeights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > inputGateBias=0, flatbuffers::Offset< armnnSerializer::ConstTensor > forgetGateBias=0, flatbuffers::Offset< armnnSerializer::ConstTensor > cellBias=0, flatbuffers::Offset< armnnSerializer::ConstTensor > outputGateBias=0)
flatbuffers::Offset< ReduceDescriptor > CreateReduceDescriptor(flatbuffers::FlatBufferBuilder &_fbb, bool keepDims=false, flatbuffers::Offset< flatbuffers::Vector< uint32_t >> axis=0, armnnSerializer::ReduceOperation reduceOperation=armnnSerializer::ReduceOperation_Sum)
flatbuffers::Offset< StackDescriptor > CreateStackDescriptor(flatbuffers::FlatBufferBuilder &_fbb, uint32_t axis=0, uint32_t numInputs=0, flatbuffers::Offset< flatbuffers::Vector< uint32_t >> inputShape=0)
flatbuffers::Offset< BatchToSpaceNdDescriptor > CreateBatchToSpaceNdDescriptor(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< uint32_t >> blockShape=0, flatbuffers::Offset< flatbuffers::Vector< uint32_t >> crops=0, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NHWC)
float m_InputIntermediateScale
Input intermediate quantization scale.
OutputShapeRounding m_OutputShapeRounding
The rounding method for the output shape. (Floor, Ceiling).
uint32_t m_TargetWidth
Target width value.
flatbuffers::Offset< SplitterLayer > CreateSplitterLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::ViewsDescriptor > descriptor=0)
A GatherDescriptor for the GatherLayer.
uint32_t m_PadBottom
Padding bottom value in the height dimension.
bool m_PeepholeEnabled
Enable/disable peephole.
uint32_t m_NumClasses
Number of classes.
bool m_HalfPixelCenters
Half Pixel Centers.
flatbuffers::Offset< OutputLayer > CreateOutputLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::BindableLayerBase > base=0)
void Serialize(const armnn::INetwork &inNetwork)
Serializes the network to ArmNN SerializedGraph.
flatbuffers::Offset< SoftmaxLayer > CreateSoftmaxLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::SoftmaxDescriptor > descriptor=0)
flatbuffers::Offset< FillDescriptor > CreateFillDescriptor(flatbuffers::FlatBufferBuilder &_fbb, float value=0.0f)
uint32_t m_PadTop
Padding top value in the height dimension.
A StandInDescriptor for the StandIn layer.
A QLstmDescriptor for the QLstmLayer.
flatbuffers::Offset< StridedSliceLayer > CreateStridedSliceLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::StridedSliceDescriptor > descriptor=0)
virtual unsigned int CalculateIndexOnOwner() const =0
flatbuffers::Offset< LogSoftmaxDescriptor > CreateLogSoftmaxDescriptor(flatbuffers::FlatBufferBuilder &_fbb, float beta=1.0f, int32_t axis=-1)
bool m_UseRegularNms
Use Regular NMS.
uint32_t m_PadFront
Padding front value in the depth dimension.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
flatbuffers::Offset< MeanLayer > CreateMeanLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::MeanDescriptor > descriptor=0)
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.
flatbuffers::Offset< ActivationLayer > CreateActivationLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::ActivationDescriptor > descriptor=0)
flatbuffers::Offset< SpaceToDepthLayer > CreateSpaceToDepthLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::SpaceToDepthDescriptor > descriptor=0)
flatbuffers::Offset< SliceDescriptor > CreateSliceDescriptor(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< uint32_t >> begin=0, flatbuffers::Offset< flatbuffers::Vector< uint32_t >> size=0)
const TensorInfo & GetInfo() const
min(a, max(b, input)) ReLu1 & ReLu6.
flatbuffers::Offset< BatchNormalizationLayer > CreateBatchNormalizationLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::BatchNormalizationDescriptor > descriptor=0, flatbuffers::Offset< armnnSerializer::ConstTensor > mean=0, flatbuffers::Offset< armnnSerializer::ConstTensor > variance=0, flatbuffers::Offset< armnnSerializer::ConstTensor > beta=0, flatbuffers::Offset< armnnSerializer::ConstTensor > gamma=0)
flatbuffers::Offset< BatchNormalizationDescriptor > CreateBatchNormalizationDescriptor(flatbuffers::FlatBufferBuilder &_fbb, float eps=0.0f, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NHWC)
uint32_t m_NumInputs
Number of input tensors.
flatbuffers::Offset< GatherDescriptor > CreateGatherDescriptor(flatbuffers::FlatBufferBuilder &_fbb, int32_t axis=0)
flatbuffers::Offset< Convolution3dLayer > CreateConvolution3dLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::Convolution3dDescriptor > descriptor=0)
uint32_t m_PadLeft
Padding left value in the width dimension.
flatbuffers::Offset< ActivationDescriptor > CreateActivationDescriptor(flatbuffers::FlatBufferBuilder &_fbb, armnnSerializer::ActivationFunction activationFunction=armnnSerializer::ActivationFunction_Sigmoid, float a=0.0f, float b=0.0f)
uint32_t m_TargetHeight
Target height value.
uint32_t m_ActivationFunc
The activation function to use.
A SliceDescriptor for the SliceLayer.
flatbuffers::Offset< NormalizationLayer > CreateNormalizationLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::NormalizationDescriptor > descriptor=0)
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
A Convolution3dDescriptor for the Convolution3dLayer.
uint32_t m_PadRight
Padding right value in the width dimension.
flatbuffers::Offset< ViewsDescriptor > CreateViewsDescriptor(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::OriginsDescriptor > origins=0, flatbuffers::Offset< flatbuffers::Vector< flatbuffers::Offset< armnnSerializer::UintVector >>> viewSizes=0)
virtual LayerType GetType() const =0
Returns the armnn::LayerType of this layer.
flatbuffers::Offset< PermuteDescriptor > CreatePermuteDescriptor(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< uint32_t >> dimMappings=0)
float m_ClippingThresCell
Clipping threshold value for the cell state.
unsigned int m_BlockSize
Scalar specifying the input block size. It must be >= 1.
uint32_t m_NumGroups
Number of groups for the channel shuffle operation.
flatbuffers::Offset< MeanDescriptor > CreateMeanDescriptor(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< uint32_t >> axis=0, bool keepDims=false)
const uint32_t * GetViewOrigin(uint32_t idx) const
Get the view origin at the int value idx.
PaddingMode m_PaddingMode
Specifies the Padding mode (Constant, Reflect or Symmetric)
flatbuffers::Offset< StandInLayer > CreateStandInLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::StandInDescriptor > descriptor=0)
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)
A Pooling3dDescriptor for the Pooling3dLayer.
uint32_t m_StrideZ
Stride value when proceeding through input for the depth dimension.
std::vector< uint32_t > m_vAxis
The indices of the dimensions to reduce.
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.
flatbuffers::Offset< SwitchLayer > CreateSwitchLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
A SpaceToBatchNdDescriptor for the SpaceToBatchNdLayer.
DataLayout m_DataLayout
The data layout to be used (NDHWC, NCDHW).
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.
flatbuffers::Offset< ElementwiseUnaryDescriptor > CreateElementwiseUnaryDescriptor(flatbuffers::FlatBufferBuilder &_fbb, armnnSerializer::UnaryOperation operation=armnnSerializer::UnaryOperation_Abs)
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).
arm::pipe::ProfilingGuid LayerGuid
Define LayerGuid type.
flatbuffers::Offset< PadDescriptor > CreatePadDescriptor(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< uint32_t >> padList=0, float padValue=0.0f, armnnSerializer::PaddingMode paddingMode=armnnSerializer::PaddingMode_Constant)
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).
flatbuffers::Offset< PadLayer > CreatePadLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::PadDescriptor > descriptor=0)
flatbuffers::Offset< FloorLayer > CreateFloorLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
std::unique_ptr< ISerializer, void(*)(ISerializer *serializer)> ISerializerPtr
flatbuffers::Offset< NormalizationDescriptor > CreateNormalizationDescriptor(flatbuffers::FlatBufferBuilder &_fbb, armnnSerializer::NormalizationAlgorithmChannel normChannelType=armnnSerializer::NormalizationAlgorithmChannel_Across, armnnSerializer::NormalizationAlgorithmMethod normMethodType=armnnSerializer::NormalizationAlgorithmMethod_LocalBrightness, uint32_t normSize=0, float alpha=0.0f, float beta=0.0f, float k=0.0f, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NCHW)
uint32_t m_PadLeft
Padding left value in the width dimension.
armnnSerializer::ComparisonOperation GetFlatBufferComparisonOperation(armnn::ComparisonOperation comparisonOperation)
flatbuffers::Offset< Pooling2dDescriptor > CreatePooling2dDescriptor(flatbuffers::FlatBufferBuilder &_fbb, armnnSerializer::PoolingAlgorithm poolType=armnnSerializer::PoolingAlgorithm_Max, uint32_t padLeft=0, uint32_t padRight=0, uint32_t padTop=0, uint32_t padBottom=0, uint32_t poolWidth=0, uint32_t poolHeight=0, uint32_t strideX=0, uint32_t strideY=0, armnnSerializer::OutputShapeRounding outputShapeRounding=armnnSerializer::OutputShapeRounding_Floor, armnnSerializer::PaddingMethod paddingMethod=armnnSerializer::PaddingMethod_IgnoreValue, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NHWC)
bool m_AlignCorners
Aligned corners.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
flatbuffers::Offset< ConstantLayer > CreateConstantLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::ConstTensor > input=0)
int32_t m_Axis
The axis in params to gather indices from.
A ElementwiseUnaryDescriptor for the ElementwiseUnaryLayer.
flatbuffers::Offset< ChannelShuffleLayer > CreateChannelShuffleLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::ChannelShuffleDescriptor > descriptor=0)
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.
flatbuffers::Offset< UintVector > CreateUintVector(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< uint32_t >> data=0)
flatbuffers::Offset< StackLayer > CreateStackLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::StackDescriptor > descriptor=0)
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
uint32_t m_PadLeft
Padding left value in the width dimension.
std::vector< std::pair< unsigned int, unsigned int > > m_Crops
The values to crop from the input dimension.
flatbuffers::Offset< Convolution2dLayer > CreateConvolution2dLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::Convolution2dDescriptor > descriptor=0, flatbuffers::Offset< armnnSerializer::ConstTensor > weights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > biases=0)
flatbuffers::Offset< UnidirectionalSequenceLstmLayer > CreateUnidirectionalSequenceLstmLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::UnidirectionalSequenceLstmDescriptor > descriptor=0, flatbuffers::Offset< armnnSerializer::LstmInputParams > inputParams=0)
uint32_t m_PadTop
Padding top value in the height dimension.
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
flatbuffers::Offset< Pooling2dLayer > CreatePooling2dLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::Pooling2dDescriptor > descriptor=0)
uint32_t m_PadTop
Padding top value in the height dimension.
bool m_ProjectionEnabled
Enable/disable the projection layer.
flatbuffers::Offset< SpaceToBatchNdLayer > CreateSpaceToBatchNdLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::SpaceToBatchNdDescriptor > descriptor=0)
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.
flatbuffers::Offset< UnidirectionalSequenceLstmDescriptor > CreateUnidirectionalSequenceLstmDescriptor(flatbuffers::FlatBufferBuilder &_fbb, uint32_t activationFunc=0, float clippingThresCell=0.0f, float clippingThresProj=0.0f, bool cifgEnabled=true, bool peepholeEnabled=false, bool projectionEnabled=false, bool layerNormEnabled=false, bool timeMajor=false)
uint32_t GetNumDimensions() const
Get the number of dimensions.
flatbuffers::Offset< ComparisonDescriptor > CreateComparisonDescriptor(flatbuffers::FlatBufferBuilder &_fbb, armnnSerializer::ComparisonOperation operation=armnnSerializer::ComparisonOperation_Equal)
virtual const IInputSlot & GetInputSlot(unsigned int index) const =0
Get a const input slot handle by slot index.
A MeanDescriptor for the MeanLayer.
flatbuffers::Offset< MaximumLayer > CreateMaximumLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
static ISerializerPtr Create()
armnnSerializer::PaddingMethod GetFlatBufferPaddingMethod(armnn::PaddingMethod paddingMethod)
bool m_LayerNormEnabled
Enable/disable layer normalization.
std::enable_if_t< std::is_unsigned< Source >::value &&std::is_unsigned< Dest >::value, Dest > numeric_cast(Source source)
uint32_t m_PadRight
Padding right value in the width dimension.
flatbuffers::Offset< InstanceNormalizationDescriptor > CreateInstanceNormalizationDescriptor(flatbuffers::FlatBufferBuilder &_fbb, float gamma=0.0f, float beta=0.0f, float eps=0.0f, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NHWC)
A TransposeDescriptor for the TransposeLayer.
A StridedSliceDescriptor for the StridedSliceLayer.
virtual const TensorInfo & GetTensorInfo() const =0
uint32_t m_Axis
Axis to apply channel shuffle operation on.
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.
flatbuffers::Offset< IntData > CreateIntData(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< int32_t >> data=0)
virtual const char * GetName() const =0
Returns the name of the layer.
float m_ScaleY
Center size encoding scale y.
flatbuffers::Offset< ResizeLayer > CreateResizeLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::ResizeDescriptor > descriptor=0)
uint32_t GetNumViews() const
Get the number of views.
flatbuffers::Offset< FullyConnectedLayer > CreateFullyConnectedLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::FullyConnectedDescriptor > descriptor=0, flatbuffers::Offset< armnnSerializer::ConstTensor > weights=0, flatbuffers::Offset< armnnSerializer::ConstTensor > biases=0)
float m_NmsScoreThreshold
NMS score threshold.
flatbuffers::Offset< DequantizeLayer > CreateDequantizeLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
flatbuffers::Offset< ChannelShuffleDescriptor > CreateChannelShuffleDescriptor(flatbuffers::FlatBufferBuilder &_fbb, uint32_t axis=0, uint32_t numGroups=0)
virtual LayerGuid GetOwningLayerGuid() const =0
A Pooling2dDescriptor for the Pooling2dLayer.
flatbuffers::Offset< DetectionPostProcessLayer > CreateDetectionPostProcessLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::DetectionPostProcessDescriptor > descriptor=0, flatbuffers::Offset< armnnSerializer::ConstTensor > anchors=0)
A NormalizationDescriptor for the NormalizationLayer.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
flatbuffers::Offset< BatchToSpaceNdLayer > CreateBatchToSpaceNdLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::BatchToSpaceNdDescriptor > descriptor=0)
flatbuffers::Offset< armnnSerializer::FeatureCompatibilityVersions > GetVersionTable()
An InstanceNormalizationDescriptor for InstanceNormalizationLayer.
PaddingMethod m_PaddingMethod
The padding method to be used. (Exclude, IgnoreValue).
unsigned int GetConcatAxis() const
Get the concatenation axis value.
A ChannelShuffleDescriptor for the ChannelShuffle operator.
flatbuffers::Offset< LogSoftmaxLayer > CreateLogSoftmaxLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::LogSoftmaxDescriptor > descriptor=0)
float m_CellIntermediateScale
Cell intermediate quantization scale.
flatbuffers::Offset< StridedSliceDescriptor > CreateStridedSliceDescriptor(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< int32_t >> begin=0, flatbuffers::Offset< flatbuffers::Vector< int32_t >> end=0, flatbuffers::Offset< flatbuffers::Vector< int32_t >> stride=0, int32_t beginMask=0, int32_t endMask=0, int32_t shrinkAxisMask=0, int32_t ellipsisMask=0, int32_t newAxisMask=0, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NHWC)
flatbuffers::Offset< OriginsDescriptor > CreateOriginsDescriptor(flatbuffers::FlatBufferBuilder &_fbb, uint32_t concatAxis=0, uint32_t numViews=0, uint32_t numDimensions=0, flatbuffers::Offset< flatbuffers::Vector< flatbuffers::Offset< armnnSerializer::UintVector >>> viewOrigins=0)
flatbuffers::Offset< QLstmLayer > CreateQLstmLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::QLstmDescriptor > descriptor=0, flatbuffers::Offset< armnnSerializer::QLstmInputParams > inputParams=0)
uint32_t m_DilationZ
Dilation along z axis.
flatbuffers::Offset< LstmDescriptor > CreateLstmDescriptor(flatbuffers::FlatBufferBuilder &_fbb, uint32_t activationFunc=0, float clippingThresCell=0.0f, float clippingThresProj=0.0f, bool cifgEnabled=true, bool peepholeEnabled=false, bool projectionEnabled=false, bool layerNormEnabled=false)
float m_B
Beta lower bound value used by the activation functions. (BoundedReLu, Linear, TanH).
static void Destroy(ISerializer *serializer)
A SoftmaxDescriptor for the SoftmaxLayer.
float m_Beta
Beta value for the normalization equation.
flatbuffers::Offset< ElementwiseUnaryLayer > CreateElementwiseUnaryLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::ElementwiseUnaryDescriptor > descriptor=0)
flatbuffers::Offset< PermuteLayer > CreatePermuteLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::PermuteDescriptor > descriptor=0)
uint32_t m_StrideZ
Stride value when proceeding through input for the depth dimension.
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.
flatbuffers::Offset< SpaceToBatchNdDescriptor > CreateSpaceToBatchNdDescriptor(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< uint32_t >> blockShape=0, flatbuffers::Offset< flatbuffers::Vector< uint32_t >> padList=0, armnnSerializer::DataLayout dataLayout=armnnSerializer::DataLayout_NHWC)
ActivationFunction m_Function
The activation function to use (Sigmoid, TanH, Linear, ReLu, BoundedReLu, SoftReLu, LeakyReLu, Abs, Sqrt, Square, Elu).
flatbuffers::Offset< SerializedGraph > CreateSerializedGraph(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< flatbuffers::Vector< flatbuffers::Offset< armnnSerializer::AnyLayer >>> layers=0, flatbuffers::Offset< flatbuffers::Vector< int32_t >> inputIds=0, flatbuffers::Offset< flatbuffers::Vector< int32_t >> outputIds=0, flatbuffers::Offset< armnnSerializer::FeatureCompatibilityVersions > featureVersions=0)
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.
uint32_t m_DilationY
Dilation along y axis.
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
flatbuffers::Offset< LogicalBinaryDescriptor > CreateLogicalBinaryDescriptor(flatbuffers::FlatBufferBuilder &_fbb, armnnSerializer::LogicalBinaryOperation operation=armnnSerializer::LogicalBinaryOperation_LogicalAnd)
flatbuffers::Offset< DivisionLayer > CreateDivisionLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0)
A PermuteDescriptor for the PermuteLayer.
flatbuffers::Offset< LogicalBinaryLayer > CreateLogicalBinaryLayer(flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset< armnnSerializer::LayerBase > base=0, flatbuffers::Offset< armnnSerializer::LogicalBinaryDescriptor > descriptor=0)
uint32_t m_PadRight
Padding right value in the width dimension.
int32_t m_HiddenStateZeroPoint
Hidden State zero point.
bool m_ConstantWeights
Enable/disable constant weights and biases.