IDeserializer::DeserializerImpl Class Reference

#include <Deserializer.hpp>

Public Member Functions
armnn::INetworkPtr	CreateNetworkFromBinary (const std::vector< uint8_t > &binaryContent)
	Create an input network from binary file contents. More...
armnn::INetworkPtr	CreateNetworkFromBinary (std::istream &binaryContent)
	Create an input network from a binary input stream. More...
BindingPointInfo	GetNetworkInputBindingInfo (unsigned int layerId, const std::string &name) const
	Retrieve binding info (layer id and tensor info) for the network input identified by the given layer name. More...
BindingPointInfo	GetNetworkOutputBindingInfo (unsigned int layerId, const std::string &name) const
	Retrieve binding info (layer id and tensor info) for the network output identified by the given layer name. More...
	DeserializerImpl ()
	~DeserializerImpl ()=default
	DeserializerImpl (const DeserializerImpl &)=delete
DeserializerImpl &	operator= (const DeserializerImpl &)=delete

Static Public Member Functions
static GraphPtr	LoadGraphFromBinary (const uint8_t *binaryContent, size_t len)
static TensorRawPtrVector	GetInputs (const GraphPtr &graph, unsigned int layerIndex)
static TensorRawPtrVector	GetOutputs (const GraphPtr &graph, unsigned int layerIndex)
static LayerBaseRawPtr	GetBaseLayer (const GraphPtr &graphPtr, unsigned int layerIndex)
static int32_t	GetBindingLayerInfo (const GraphPtr &graphPtr, unsigned int layerIndex)
static std::string	GetLayerName (const GraphPtr &graph, unsigned int index)
static armnn::Pooling2dDescriptor	GetPooling2dDescriptor (Pooling2dDescriptor pooling2dDescriptor, unsigned int layerIndex)
static armnn::Pooling3dDescriptor	GetPooling3dDescriptor (Pooling3dDescriptor pooling3dDescriptor, unsigned int layerIndex)
static armnn::NormalizationDescriptor	GetNormalizationDescriptor (NormalizationDescriptorPtr normalizationDescriptor, unsigned int layerIndex)
static armnn::LstmDescriptor	GetLstmDescriptor (LstmDescriptorPtr lstmDescriptor)
static armnn::LstmInputParams	GetLstmInputParams (LstmDescriptorPtr lstmDescriptor, LstmInputParamsPtr lstmInputParams)
static armnn::QLstmDescriptor	GetQLstmDescriptor (QLstmDescriptorPtr qLstmDescriptorPtr)
static armnn::UnidirectionalSequenceLstmDescriptor	GetUnidirectionalSequenceLstmDescriptor (UnidirectionalSequenceLstmDescriptorPtr descriptor)
static armnn::TensorInfo	OutputShapeOfReshape (const armnn::TensorInfo &inputTensorInfo, const std::vector< uint32_t > &targetDimsIn)

Detailed Description

Definition at line 34 of file Deserializer.hpp.

Constructor & Destructor Documentation

DeserializerImpl() [1/2]

DeserializerImpl

(

)

Definition at line 207 of file Deserializer.cpp.

: m_Network(nullptr, nullptr),
//May require LayerType_Max to be included
m_ParserFunctions(Layer_MAX+1, &IDeserializer::DeserializerImpl::ParseUnsupportedLayer)
{
    // register supported layers
    m_ParserFunctions[Layer_AbsLayer]                    = &DeserializerImpl::ParseAbs;
    m_ParserFunctions[Layer_ActivationLayer]             = &DeserializerImpl::ParseActivation;
    m_ParserFunctions[Layer_AdditionLayer]               = &DeserializerImpl::ParseAdd;
    m_ParserFunctions[Layer_ArgMinMaxLayer]              = &DeserializerImpl::ParseArgMinMax;
    m_ParserFunctions[Layer_BatchMatMulLayer]            = &DeserializerImpl::ParseBatchMatMul;
    m_ParserFunctions[Layer_BatchToSpaceNdLayer]         = &DeserializerImpl::ParseBatchToSpaceNd;
    m_ParserFunctions[Layer_BatchNormalizationLayer]     = &DeserializerImpl::ParseBatchNormalization;
    m_ParserFunctions[Layer_CastLayer]                   = &DeserializerImpl::ParseCast;
    m_ParserFunctions[Layer_ChannelShuffleLayer]         = &DeserializerImpl::ParseChannelShuffle;
    m_ParserFunctions[Layer_ComparisonLayer]             = &DeserializerImpl::ParseComparison;
    m_ParserFunctions[Layer_ConcatLayer]                 = &DeserializerImpl::ParseConcat;
    m_ParserFunctions[Layer_ConstantLayer]               = &DeserializerImpl::ParseConstant;
    m_ParserFunctions[Layer_Convolution2dLayer]          = &DeserializerImpl::ParseConvolution2d;
    m_ParserFunctions[Layer_Convolution3dLayer]          = &DeserializerImpl::ParseConvolution3d;
    m_ParserFunctions[Layer_DepthToSpaceLayer]           = &DeserializerImpl::ParseDepthToSpace;
    m_ParserFunctions[Layer_DepthwiseConvolution2dLayer] = &DeserializerImpl::ParseDepthwiseConvolution2d;
    m_ParserFunctions[Layer_DequantizeLayer]             = &DeserializerImpl::ParseDequantize;
    m_ParserFunctions[Layer_DetectionPostProcessLayer]   = &DeserializerImpl::ParseDetectionPostProcess;
    m_ParserFunctions[Layer_DivisionLayer]               = &DeserializerImpl::ParseDivision;
    m_ParserFunctions[Layer_ElementwiseBinaryLayer]      = &DeserializerImpl::ParseElementwiseBinary;
    m_ParserFunctions[Layer_ElementwiseUnaryLayer]       = &DeserializerImpl::ParseElementwiseUnary;
    m_ParserFunctions[Layer_EqualLayer]                  = &DeserializerImpl::ParseEqual;
    m_ParserFunctions[Layer_FullyConnectedLayer]         = &DeserializerImpl::ParseFullyConnected;
    m_ParserFunctions[Layer_FillLayer]                   = &DeserializerImpl::ParseFill;
    m_ParserFunctions[Layer_FloorLayer]                  = &DeserializerImpl::ParseFloor;
    m_ParserFunctions[Layer_GatherLayer]                 = &DeserializerImpl::ParseGather;
    m_ParserFunctions[Layer_GatherNdLayer]               = &DeserializerImpl::ParseGatherNd;
    m_ParserFunctions[Layer_GreaterLayer]                = &DeserializerImpl::ParseGreater;
    m_ParserFunctions[Layer_InstanceNormalizationLayer]  = &DeserializerImpl::ParseInstanceNormalization;
    m_ParserFunctions[Layer_L2NormalizationLayer]        = &DeserializerImpl::ParseL2Normalization;
    m_ParserFunctions[Layer_LogicalBinaryLayer]          = &DeserializerImpl::ParseLogicalBinary;
    m_ParserFunctions[Layer_LogSoftmaxLayer]             = &DeserializerImpl::ParseLogSoftmax;
    m_ParserFunctions[Layer_LstmLayer]                   = &DeserializerImpl::ParseLstm;
    m_ParserFunctions[Layer_MaximumLayer]                = &DeserializerImpl::ParseMaximum;
    m_ParserFunctions[Layer_MeanLayer]                   = &DeserializerImpl::ParseMean;
    m_ParserFunctions[Layer_MinimumLayer]                = &DeserializerImpl::ParseMinimum;
    m_ParserFunctions[Layer_MergeLayer]                  = &DeserializerImpl::ParseMerge;
    m_ParserFunctions[Layer_MergerLayer]                 = &DeserializerImpl::ParseConcat;
    m_ParserFunctions[Layer_MultiplicationLayer]         = &DeserializerImpl::ParseMultiplication;
    m_ParserFunctions[Layer_NormalizationLayer]          = &DeserializerImpl::ParseNormalization;
    m_ParserFunctions[Layer_PadLayer]                    = &DeserializerImpl::ParsePad;
    m_ParserFunctions[Layer_PermuteLayer]                = &DeserializerImpl::ParsePermute;
    m_ParserFunctions[Layer_Pooling2dLayer]              = &DeserializerImpl::ParsePooling2d;
    m_ParserFunctions[Layer_Pooling3dLayer]              = &DeserializerImpl::ParsePooling3d;
    m_ParserFunctions[Layer_PreluLayer]                  = &DeserializerImpl::ParsePrelu;
    m_ParserFunctions[Layer_QLstmLayer]                  = &DeserializerImpl::ParseQLstm;
    m_ParserFunctions[Layer_QuantizeLayer]               = &DeserializerImpl::ParseQuantize;
    m_ParserFunctions[Layer_QuantizedLstmLayer]          = &DeserializerImpl::ParseQuantizedLstm;
    m_ParserFunctions[Layer_RankLayer]                   = &DeserializerImpl::ParseRank;
    m_ParserFunctions[Layer_ReduceLayer]                 = &DeserializerImpl::ParseReduce;
    m_ParserFunctions[Layer_ReshapeLayer]                = &DeserializerImpl::ParseReshape;
    m_ParserFunctions[Layer_ResizeBilinearLayer]         = &DeserializerImpl::ParseResizeBilinear;
    m_ParserFunctions[Layer_ResizeLayer]                 = &DeserializerImpl::ParseResize;
    m_ParserFunctions[Layer_ReverseV2Layer]              = &DeserializerImpl::ParseReverseV2;
    m_ParserFunctions[Layer_RsqrtLayer]                  = &DeserializerImpl::ParseRsqrt;
    m_ParserFunctions[Layer_ShapeLayer]                  = &DeserializerImpl::ParseShape;
    m_ParserFunctions[Layer_SliceLayer]                  = &DeserializerImpl::ParseSlice;
    m_ParserFunctions[Layer_SoftmaxLayer]                = &DeserializerImpl::ParseSoftmax;
    m_ParserFunctions[Layer_SpaceToBatchNdLayer]         = &DeserializerImpl::ParseSpaceToBatchNd;
    m_ParserFunctions[Layer_SpaceToDepthLayer]           = &DeserializerImpl::ParseSpaceToDepth;
    m_ParserFunctions[Layer_SplitterLayer]               = &DeserializerImpl::ParseSplitter;
    m_ParserFunctions[Layer_StackLayer]                  = &DeserializerImpl::ParseStack;
    m_ParserFunctions[Layer_StandInLayer]                = &DeserializerImpl::ParseStandIn;
    m_ParserFunctions[Layer_StridedSliceLayer]           = &DeserializerImpl::ParseStridedSlice;
    m_ParserFunctions[Layer_SubtractionLayer]            = &DeserializerImpl::ParseSubtraction;
    m_ParserFunctions[Layer_SwitchLayer]                 = &DeserializerImpl::ParseSwitch;
    m_ParserFunctions[Layer_TileLayer]                   = &DeserializerImpl::ParseTile;
    m_ParserFunctions[Layer_TransposeConvolution2dLayer] = &DeserializerImpl::ParseTransposeConvolution2d;
    m_ParserFunctions[Layer_TransposeLayer]              = &DeserializerImpl::ParseTranspose;
    m_ParserFunctions[Layer_UnidirectionalSequenceLstmLayer] = &DeserializerImpl::ParseUnidirectionalSequenceLstm;
}

~DeserializerImpl()

~DeserializerImpl ( )

default

DeserializerImpl() [2/2]

DeserializerImpl ( const DeserializerImpl &  )

delete

Member Function Documentation

CreateNetworkFromBinary() [1/2]

INetworkPtr CreateNetworkFromBinary

(

const std::vector< uint8_t > &

binaryContent

)

Create an input network from binary file contents.

Definition at line 854 of file Deserializer.cpp.

{
     ResetParser();
     GraphPtr graph = LoadGraphFromBinary(binaryContent.data(), binaryContent.size());
     return CreateNetworkFromGraph(graph);
}

CreateNetworkFromBinary() [2/2]

armnn::INetworkPtr CreateNetworkFromBinary

(

std::istream &

binaryContent

)

Create an input network from a binary input stream.

Definition at line 861 of file Deserializer.cpp.

{
    ResetParser();
    if (binaryContent.fail()) {
        ARMNN_LOG(error) << (std::string("Cannot read input"));
        throw ParseException("Unable to read Input stream data");
    }
    binaryContent.seekg(0, std::ios::end);
    const std::streamoff size = binaryContent.tellg();
    std::vector<char> content(static_cast<size_t>(size));
    binaryContent.seekg(0);
    binaryContent.read(content.data(), static_cast<std::streamsize>(size));
    GraphPtr graph = LoadGraphFromBinary(reinterpret_cast<uint8_t*>(content.data()), static_cast<size_t>(size));
    return CreateNetworkFromGraph(graph);
}

References ARMNN_LOG, and armnn::error.

GetBaseLayer()

LayerBaseRawPtr GetBaseLayer ( const GraphPtr &  graphPtr, unsigned int  layerIndex  )

static

Definition at line 285 of file Deserializer.cpp.

{
    auto layerType = graphPtr->layers()->Get(layerIndex)->layer_type();
 
    switch(layerType)
    {
        case Layer::Layer_AbsLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_AbsLayer()->base();
        case Layer::Layer_ActivationLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_ActivationLayer()->base();
        case Layer::Layer_AdditionLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_AdditionLayer()->base();
        case Layer::Layer_ArgMinMaxLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_ArgMinMaxLayer()->base();
        case Layer::Layer_BatchMatMulLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_BatchMatMulLayer()->base();
        case Layer::Layer_BatchToSpaceNdLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_BatchToSpaceNdLayer()->base();
        case Layer::Layer_BatchNormalizationLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_BatchNormalizationLayer()->base();
        case Layer::Layer_CastLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_CastLayer()->base();
        case Layer::Layer_ChannelShuffleLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_ChannelShuffleLayer()->base();
        case Layer::Layer_ComparisonLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_ComparisonLayer()->base();
        case Layer::Layer_ConcatLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_ConcatLayer()->base();
        case Layer::Layer_ConstantLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_ConstantLayer()->base();
        case Layer::Layer_Convolution2dLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_Convolution2dLayer()->base();
        case Layer::Layer_Convolution3dLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_Convolution3dLayer()->base();
        case Layer::Layer_DepthToSpaceLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_DepthToSpaceLayer()->base();
        case Layer::Layer_DepthwiseConvolution2dLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_DepthwiseConvolution2dLayer()->base();
        case Layer::Layer_DequantizeLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_DequantizeLayer()->base();
        case Layer::Layer_DetectionPostProcessLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_DetectionPostProcessLayer()->base();
        case Layer::Layer_DivisionLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_DivisionLayer()->base();
        case Layer::Layer_EqualLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_EqualLayer()->base();
        case Layer::Layer_ElementwiseBinaryLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_ElementwiseBinaryLayer()->base();
        case Layer::Layer_ElementwiseUnaryLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_ElementwiseUnaryLayer()->base();
        case Layer::Layer_FullyConnectedLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_FullyConnectedLayer()->base();
        case Layer::Layer_FillLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_FillLayer()->base();
        case Layer::Layer_FloorLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_FloorLayer()->base();
        case Layer::Layer_GatherLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_GatherLayer()->base();
        case Layer::Layer_GatherNdLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_GatherNdLayer()->base();
        case Layer::Layer_GreaterLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_GreaterLayer()->base();
        case Layer::Layer_InputLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_InputLayer()->base()->base();
        case Layer::Layer_InstanceNormalizationLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_InstanceNormalizationLayer()->base();
        case Layer::Layer_L2NormalizationLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_L2NormalizationLayer()->base();
        case Layer::Layer_LogicalBinaryLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_LogicalBinaryLayer()->base();
        case Layer::Layer_LogSoftmaxLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_LogSoftmaxLayer()->base();
        case Layer::Layer_LstmLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_LstmLayer()->base();
        case Layer::Layer_MeanLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_MeanLayer()->base();
        case Layer::Layer_MinimumLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_MinimumLayer()->base();
        case Layer::Layer_MaximumLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_MaximumLayer()->base();
        case Layer::Layer_MergeLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_MergeLayer()->base();
        case Layer::Layer_MergerLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_MergerLayer()->base();
        case Layer::Layer_MultiplicationLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_MultiplicationLayer()->base();
        case Layer::Layer_NormalizationLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_NormalizationLayer()->base();
        case Layer::Layer_OutputLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_OutputLayer()->base()->base();
        case Layer::Layer_PadLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_PadLayer()->base();
        case Layer::Layer_PermuteLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_PermuteLayer()->base();
        case Layer::Layer_Pooling2dLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_Pooling2dLayer()->base();
        case Layer::Layer_Pooling3dLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_Pooling3dLayer()->base();
        case Layer::Layer_PreluLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_PreluLayer()->base();
        case Layer::Layer_QLstmLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_QLstmLayer()->base();
        case Layer::Layer_QuantizeLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_QuantizeLayer()->base();
        case Layer::Layer_QuantizedLstmLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_QuantizedLstmLayer()->base();
        case Layer::Layer_RankLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_RankLayer()->base();
        case Layer::Layer_ReduceLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_ReduceLayer()->base();
        case Layer::Layer_ReshapeLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_ReshapeLayer()->base();
        case Layer::Layer_ResizeBilinearLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_ResizeBilinearLayer()->base();
        case Layer::Layer_ResizeLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_ResizeLayer()->base();
        case Layer::Layer_ReverseV2Layer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_ReverseV2Layer()->base();
        case Layer::Layer_RsqrtLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_RsqrtLayer()->base();
        case Layer::Layer_ShapeLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_ShapeLayer()->base();
        case Layer::Layer_SliceLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_SliceLayer()->base();
        case Layer::Layer_SoftmaxLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->base();
        case Layer::Layer_SpaceToBatchNdLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_SpaceToBatchNdLayer()->base();
        case Layer::Layer_SpaceToDepthLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_SpaceToDepthLayer()->base();
        case Layer::Layer_SplitterLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_SplitterLayer()->base();
        case Layer::Layer_StackLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_StackLayer()->base();
        case Layer::Layer_StandInLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_StandInLayer()->base();
        case Layer::Layer_StridedSliceLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_StridedSliceLayer()->base();
        case Layer::Layer_SubtractionLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_SubtractionLayer()->base();
        case Layer::Layer_SwitchLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_SwitchLayer()->base();
        case Layer::Layer_TileLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_TileLayer()->base();
        case Layer::Layer_TransposeConvolution2dLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_TransposeConvolution2dLayer()->base();
        case Layer::Layer_TransposeLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_TransposeLayer()->base();
        case Layer::Layer_UnidirectionalSequenceLstmLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_UnidirectionalSequenceLstmLayer()->base();
        case Layer::Layer_NONE:
        default:
            throw ParseException(fmt::format("Layer type {} not recognized", layerType));
    }
}

GetBindingLayerInfo()

int32_t GetBindingLayerInfo ( const GraphPtr &  graphPtr, unsigned int  layerIndex  )

static

Definition at line 448 of file Deserializer.cpp.

{
    auto layerType = graphPtr->layers()->Get(layerIndex)->layer_type();
 
    if (layerType == Layer::Layer_InputLayer)
    {
        return graphPtr->layers()->Get(layerIndex)->layer_as_InputLayer()->base()->layerBindingId();
    }
    else if ( layerType == Layer::Layer_OutputLayer )
    {
        return graphPtr->layers()->Get(layerIndex)->layer_as_OutputLayer()->base()->layerBindingId();
    }
    return 0;
}

GetInputs()

TensorRawPtrVector GetInputs ( const GraphPtr &  graph, unsigned int  layerIndex  )

static

Definition at line 803 of file Deserializer.cpp.

{
    CHECK_LAYERS(graphPtr, 0, layerIndex);
    auto layer = GetBaseLayer(graphPtr, layerIndex);
    const auto& numInputs = layer->inputSlots()->size();
 
    TensorRawPtrVector result(numInputs);
 
   for (unsigned int i=0; i<numInputs; ++i)
   {
       auto inputId = CHECKED_NON_NEGATIVE(static_cast<int32_t>
                                          (layer->inputSlots()->Get(i)->connection()->sourceLayerIndex()));
       result[i] = GetBaseLayer(graphPtr, inputId)->outputSlots()->Get(0)->tensorInfo();
   }
   return result;
}

References CHECK_LAYERS, and CHECKED_NON_NEGATIVE.

GetLayerName()

std::string GetLayerName ( const GraphPtr &  graph, unsigned int  index  )

static

Definition at line 441 of file Deserializer.cpp.

{
    auto layer = GetBaseLayer(graph, index);
    assert(layer);
    return layer->layerName()->str();
}

GetLstmDescriptor()

armnn::LstmDescriptor GetLstmDescriptor ( LstmDescriptorPtr  lstmDescriptor )

static

Definition at line 3285 of file Deserializer.cpp.

{
    armnn::LstmDescriptor desc;
 
    desc.m_ActivationFunc = lstmDescriptor->activationFunc();
    desc.m_ClippingThresCell = lstmDescriptor->clippingThresCell();
    desc.m_ClippingThresProj = lstmDescriptor->clippingThresProj();
    desc.m_CifgEnabled = lstmDescriptor->cifgEnabled();
    desc.m_PeepholeEnabled = lstmDescriptor->peepholeEnabled();
    desc.m_ProjectionEnabled = lstmDescriptor->projectionEnabled();
    desc.m_LayerNormEnabled = lstmDescriptor->layerNormEnabled();
 
    return desc;
}

References LstmDescriptor::m_ActivationFunc, LstmDescriptor::m_CifgEnabled, LstmDescriptor::m_ClippingThresCell, LstmDescriptor::m_ClippingThresProj, LstmDescriptor::m_LayerNormEnabled, LstmDescriptor::m_PeepholeEnabled, and LstmDescriptor::m_ProjectionEnabled.

GetLstmInputParams()

static armnn::LstmInputParams GetLstmInputParams ( LstmDescriptorPtr  lstmDescriptor, LstmInputParamsPtr  lstmInputParams  )

static

GetNetworkInputBindingInfo()

BindingPointInfo GetNetworkInputBindingInfo	(	unsigned int	layerId,
		const std::string &	name
	)		const

Retrieve binding info (layer id and tensor info) for the network input identified by the given layer name.

Definition at line 939 of file Deserializer.cpp.

{
    IgnoreUnused(layerIndex);
    for (auto inputBinding : m_InputBindings)
    {
        if (inputBinding.first == name)
        {
            return inputBinding.second;
        }
    }
    throw ParseException(fmt::format("No input binding found for layer:{0} / {1}",
                                     name,
                                     CHECK_LOCATION().AsString()));
}

References CHECK_LOCATION, and armnn::IgnoreUnused().

GetNetworkOutputBindingInfo()

BindingPointInfo GetNetworkOutputBindingInfo	(	unsigned int	layerId,
		const std::string &	name
	)		const

Retrieve binding info (layer id and tensor info) for the network output identified by the given layer name.

Definition at line 955 of file Deserializer.cpp.

{
    IgnoreUnused(layerIndex);
    for (auto outputBinding : m_OutputBindings)
    {
        if (outputBinding.first == name)
        {
            return outputBinding.second;
        }
    }
    throw ParseException(fmt::format("No output binding found for layer:{0} / {1}",
                                     name,
                                     CHECK_LOCATION().AsString()));
}

References CHECK_LOCATION, and armnn::IgnoreUnused().

GetNormalizationDescriptor()

armnn::NormalizationDescriptor GetNormalizationDescriptor ( NormalizationDescriptorPtr  normalizationDescriptor, unsigned int  layerIndex  )

static

Definition at line 2950 of file Deserializer.cpp.

{
    IgnoreUnused(layerIndex);
    armnn::NormalizationDescriptor desc;
 
    switch (normalizationDescriptor->normChannelType())
    {
        case NormalizationAlgorithmChannel_Across:
        {
            desc.m_NormChannelType = armnn::NormalizationAlgorithmChannel::Across;
            break;
        }
        case NormalizationAlgorithmChannel_Within:
        {
            desc.m_NormChannelType = armnn::NormalizationAlgorithmChannel::Within;
            break;
        }
        default:
        {
            throw ParseException("Unsupported normalization channel type");
        }
    }
 
    switch (normalizationDescriptor->normMethodType())
    {
        case NormalizationAlgorithmMethod_LocalBrightness:
        {
            desc.m_NormMethodType = armnn::NormalizationAlgorithmMethod::LocalBrightness;
            break;
        }
        case NormalizationAlgorithmMethod_LocalContrast:
        {
            desc.m_NormMethodType = armnn::NormalizationAlgorithmMethod::LocalContrast;
            break;
        }
        default:
        {
            throw ParseException("Unsupported normalization method type");
        }
    }
 
    switch (normalizationDescriptor->dataLayout())
    {
        case DataLayout_NCHW:
        {
            desc.m_DataLayout = armnn::DataLayout::NCHW;
            break;
        }
        case DataLayout_NHWC:
        {
            desc.m_DataLayout = armnn::DataLayout::NHWC;
            break;
        }
        default:
        {
            throw ParseException("Unsupported data layout");
        }
    }
 
    desc.m_Alpha    = normalizationDescriptor->alpha();
    desc.m_Beta     = normalizationDescriptor->beta();
    desc.m_K        = normalizationDescriptor->k();
    desc.m_NormSize = normalizationDescriptor->normSize();
 
    return desc;
}

References armnn::Across, armnn::IgnoreUnused(), armnn::LocalBrightness, armnn::LocalContrast, NormalizationDescriptor::m_Alpha, NormalizationDescriptor::m_Beta, NormalizationDescriptor::m_DataLayout, NormalizationDescriptor::m_K, NormalizationDescriptor::m_NormChannelType, NormalizationDescriptor::m_NormMethodType, NormalizationDescriptor::m_NormSize, armnn::NCHW, armnn::NHWC, and armnn::Within.

GetOutputs()

TensorRawPtrVector GetOutputs ( const GraphPtr &  graph, unsigned int  layerIndex  )

static

Definition at line 820 of file Deserializer.cpp.

{
    CHECK_LAYERS(graphPtr, 0, layerIndex);
    auto layer = GetBaseLayer(graphPtr, layerIndex);
    const auto& numOutputs = layer->outputSlots()->size();
 
    TensorRawPtrVector result(numOutputs);
 
    for (unsigned int i=0; i<numOutputs; ++i)
    {
        result[i] = layer->outputSlots()->Get(i)->tensorInfo();
    }
    return result;
}

References CHECK_LAYERS.

GetPooling2dDescriptor()

armnn::Pooling2dDescriptor GetPooling2dDescriptor ( Pooling2dDescriptor  pooling2dDescriptor, unsigned int  layerIndex  )

static

Definition at line 2361 of file Deserializer.cpp.

{
    IgnoreUnused(layerIndex);
    armnn::Pooling2dDescriptor desc;
 
    switch (pooling2dDesc->poolType())
    {
        case PoolingAlgorithm_Average:
        {
            desc.m_PoolType = armnn::PoolingAlgorithm::Average;
            break;
        }
        case PoolingAlgorithm_Max:
        {
            desc.m_PoolType = armnn::PoolingAlgorithm::Max;
            break;
        }
        case PoolingAlgorithm_L2:
        {
            desc.m_PoolType = armnn::PoolingAlgorithm::L2;
            break;
        }
        default:
        {
            throw ParseException("Unsupported pooling algorithm");
        }
    }
 
    switch (pooling2dDesc->outputShapeRounding())
    {
        case OutputShapeRounding_Floor:
        {
            desc.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor;
            break;
        }
        case OutputShapeRounding_Ceiling:
        {
            desc.m_OutputShapeRounding = armnn::OutputShapeRounding::Ceiling;
            break;
        }
        default:
        {
            throw ParseException("Unsupported output shape rounding");
        }
    }
 
    switch (pooling2dDesc->paddingMethod())
    {
        case PaddingMethod_Exclude:
        {
            desc.m_PaddingMethod = armnn::PaddingMethod::Exclude;
            break;
        }
        case PaddingMethod_IgnoreValue:
        {
            desc.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue;
            break;
        }
        default:
        {
            throw ParseException("Unsupported padding method");
        }
    }
 
    switch (pooling2dDesc->dataLayout())
    {
        case DataLayout_NCHW:
        {
            desc.m_DataLayout = armnn::DataLayout::NCHW;
            break;
        }
        case DataLayout_NHWC:
        {
            desc.m_DataLayout = armnn::DataLayout::NHWC;
            break;
        }
        default:
        {
            throw ParseException("Unsupported data layout");
        }
    }
 
    desc.m_PadRight   = pooling2dDesc->padRight();
    desc.m_PadLeft    = pooling2dDesc->padLeft();
    desc.m_PadBottom  = pooling2dDesc->padBottom();
    desc.m_PadTop     = pooling2dDesc->padTop();
    desc.m_StrideX    = pooling2dDesc->strideX();
    desc.m_StrideY    = pooling2dDesc->strideY();
    desc.m_PoolWidth  = pooling2dDesc->poolWidth();
    desc.m_PoolHeight = pooling2dDesc->poolHeight();
 
    return desc;
}

References armnn::Average, armnn::Ceiling, armnn::Exclude, armnn::Floor, armnn::IgnoreUnused(), armnn::IgnoreValue, armnn::L2, Pooling2dDescriptor::m_DataLayout, Pooling2dDescriptor::m_OutputShapeRounding, Pooling2dDescriptor::m_PadBottom, Pooling2dDescriptor::m_PaddingMethod, Pooling2dDescriptor::m_PadLeft, Pooling2dDescriptor::m_PadRight, Pooling2dDescriptor::m_PadTop, Pooling2dDescriptor::m_PoolHeight, Pooling2dDescriptor::m_PoolType, Pooling2dDescriptor::m_PoolWidth, Pooling2dDescriptor::m_StrideX, Pooling2dDescriptor::m_StrideY, armnn::Max, armnn::NCHW, and armnn::NHWC.

GetPooling3dDescriptor()

armnn::Pooling3dDescriptor GetPooling3dDescriptor ( Pooling3dDescriptor  pooling3dDescriptor, unsigned int  layerIndex  )

static

Definition at line 2456 of file Deserializer.cpp.

{
    IgnoreUnused(layerIndex);
    armnn::Pooling3dDescriptor desc;
 
    switch (pooling3dDesc->poolType())
    {
        case PoolingAlgorithm_Average:
        {
            desc.m_PoolType = armnn::PoolingAlgorithm::Average;
            break;
        }
        case PoolingAlgorithm_Max:
        {
            desc.m_PoolType = armnn::PoolingAlgorithm::Max;
            break;
        }
        case PoolingAlgorithm_L2:
        {
            desc.m_PoolType = armnn::PoolingAlgorithm::L2;
            break;
        }
        default:
        {
            throw ParseException("Unsupported pooling algorithm");
        }
    }
 
    switch (pooling3dDesc->outputShapeRounding())
    {
        case OutputShapeRounding_Floor:
        {
            desc.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor;
            break;
        }
        case OutputShapeRounding_Ceiling:
        {
            desc.m_OutputShapeRounding = armnn::OutputShapeRounding::Ceiling;
            break;
        }
        default:
        {
            throw ParseException("Unsupported output shape rounding");
        }
    }
 
    switch (pooling3dDesc->paddingMethod())
    {
        case PaddingMethod_Exclude:
        {
            desc.m_PaddingMethod = armnn::PaddingMethod::Exclude;
            break;
        }
        case PaddingMethod_IgnoreValue:
        {
            desc.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue;
            break;
        }
        default:
        {
            throw ParseException("Unsupported padding method");
        }
    }
 
    switch (pooling3dDesc->dataLayout())
    {
        case DataLayout_NCDHW:
        {
            desc.m_DataLayout = armnn::DataLayout::NCDHW;
            break;
        }
        case DataLayout_NDHWC:
        {
            desc.m_DataLayout = armnn::DataLayout::NDHWC;
            break;
        }
        default:
        {
            throw ParseException("Unsupported data layout");
        }
    }
 
    desc.m_PadRight   = pooling3dDesc->padRight();
    desc.m_PadLeft    = pooling3dDesc->padLeft();
    desc.m_PadBottom  = pooling3dDesc->padBottom();
    desc.m_PadTop     = pooling3dDesc->padTop();
    desc.m_PadFront   = pooling3dDesc->padFront();
    desc.m_PadBack    = pooling3dDesc->padBack();
    desc.m_StrideX    = pooling3dDesc->strideX();
    desc.m_StrideY    = pooling3dDesc->strideY();
    desc.m_StrideZ    = pooling3dDesc->strideZ();
    desc.m_PoolWidth  = pooling3dDesc->poolWidth();
    desc.m_PoolHeight = pooling3dDesc->poolHeight();
    desc.m_PoolDepth  = pooling3dDesc->poolDepth();
 
    return desc;
}

References armnn::Average, armnn::Ceiling, armnn::Exclude, armnn::Floor, armnn::IgnoreUnused(), armnn::IgnoreValue, armnn::L2, Pooling3dDescriptor::m_DataLayout, Pooling3dDescriptor::m_OutputShapeRounding, Pooling3dDescriptor::m_PadBack, Pooling3dDescriptor::m_PadBottom, Pooling3dDescriptor::m_PaddingMethod, Pooling3dDescriptor::m_PadFront, Pooling3dDescriptor::m_PadLeft, Pooling3dDescriptor::m_PadRight, Pooling3dDescriptor::m_PadTop, Pooling3dDescriptor::m_PoolDepth, Pooling3dDescriptor::m_PoolHeight, Pooling3dDescriptor::m_PoolType, Pooling3dDescriptor::m_PoolWidth, Pooling3dDescriptor::m_StrideX, Pooling3dDescriptor::m_StrideY, Pooling3dDescriptor::m_StrideZ, armnn::Max, armnn::NCDHW, and armnn::NDHWC.

GetQLstmDescriptor()

armnn::QLstmDescriptor GetQLstmDescriptor ( QLstmDescriptorPtr  qLstmDescriptorPtr )

static

Definition at line 3416 of file Deserializer.cpp.

{
    armnn::QLstmDescriptor desc;
 
    desc.m_CifgEnabled       = qLstmDescriptor->cifgEnabled();
    desc.m_PeepholeEnabled   = qLstmDescriptor->peepholeEnabled();
    desc.m_ProjectionEnabled = qLstmDescriptor->projectionEnabled();
    desc.m_LayerNormEnabled  = qLstmDescriptor->layerNormEnabled();
 
    desc.m_CellClip       = qLstmDescriptor->cellClip();
    desc.m_ProjectionClip = qLstmDescriptor->projectionClip();
 
    desc.m_InputIntermediateScale  = qLstmDescriptor->inputIntermediateScale();
    desc.m_ForgetIntermediateScale = qLstmDescriptor->forgetIntermediateScale();
    desc.m_CellIntermediateScale   = qLstmDescriptor->cellIntermediateScale();
    desc.m_OutputIntermediateScale = qLstmDescriptor->outputIntermediateScale();
 
    desc.m_HiddenStateScale     = qLstmDescriptor->hiddenStateScale();
    desc.m_HiddenStateZeroPoint = qLstmDescriptor->hiddenStateZeroPoint();
 
    return desc;
}

References QLstmDescriptor::m_CellClip, QLstmDescriptor::m_CellIntermediateScale, QLstmDescriptor::m_CifgEnabled, QLstmDescriptor::m_ForgetIntermediateScale, QLstmDescriptor::m_HiddenStateScale, QLstmDescriptor::m_HiddenStateZeroPoint, QLstmDescriptor::m_InputIntermediateScale, QLstmDescriptor::m_LayerNormEnabled, QLstmDescriptor::m_OutputIntermediateScale, QLstmDescriptor::m_PeepholeEnabled, QLstmDescriptor::m_ProjectionClip, and QLstmDescriptor::m_ProjectionEnabled.

GetUnidirectionalSequenceLstmDescriptor()

armnn::UnidirectionalSequenceLstmDescriptor GetUnidirectionalSequenceLstmDescriptor ( UnidirectionalSequenceLstmDescriptorPtr  descriptor )

static

Definition at line 3875 of file Deserializer.cpp.

{
    armnn::UnidirectionalSequenceLstmDescriptor desc;
 
    desc.m_ActivationFunc = descriptor->activationFunc();
    desc.m_ClippingThresCell = descriptor->clippingThresCell();
    desc.m_ClippingThresProj = descriptor->clippingThresProj();
    desc.m_CifgEnabled = descriptor->cifgEnabled();
    desc.m_PeepholeEnabled = descriptor->peepholeEnabled();
    desc.m_ProjectionEnabled = descriptor->projectionEnabled();
    desc.m_LayerNormEnabled = descriptor->layerNormEnabled();
    desc.m_TimeMajor = descriptor->timeMajor();
 
    return desc;
}

References LstmDescriptor::m_ActivationFunc, LstmDescriptor::m_CifgEnabled, LstmDescriptor::m_ClippingThresCell, LstmDescriptor::m_ClippingThresProj, LstmDescriptor::m_LayerNormEnabled, LstmDescriptor::m_PeepholeEnabled, LstmDescriptor::m_ProjectionEnabled, and LstmDescriptor::m_TimeMajor.

LoadGraphFromBinary()

GraphPtr LoadGraphFromBinary ( const uint8_t *  binaryContent, size_t  len  )

static

Definition at line 877 of file Deserializer.cpp.

{
    if (binaryContent == nullptr)
    {
        throw InvalidArgumentException(fmt::format("Invalid (null) binary content {}",
                                                   CHECK_LOCATION().AsString()));
    }
    flatbuffers::Verifier verifier(binaryContent, len);
    if (verifier.VerifyBuffer<SerializedGraph>() == false)
    {
        throw ParseException(fmt::format("Buffer doesn't conform to the expected Armnn "
                                         "flatbuffers format. size:{0} {1}",
                                         len,
                                         CHECK_LOCATION().AsString()));
    }
    return GetSerializedGraph(binaryContent);
}

References CHECK_LOCATION.

operator=()

DeserializerImpl& operator= ( const DeserializerImpl &  )

delete

OutputShapeOfReshape()

armnn::TensorInfo OutputShapeOfReshape ( const armnn::TensorInfo &  inputTensorInfo, const std::vector< uint32_t > &  targetDimsIn  )

static

Definition at line 2616 of file Deserializer.cpp.

{
    std::vector<unsigned int> outputDims(targetDimsIn.begin(), targetDimsIn.end());
    const auto stretchDim = std::find(targetDimsIn.begin(), targetDimsIn.end(), -1);
 
    if (stretchDim != targetDimsIn.end())
    {
        if (std::find(std::next(stretchDim), targetDimsIn.end(), -1) != targetDimsIn.end())
        {
            throw ParseException(fmt::format("At most one component of shape can be -1 {}",
                                             CHECK_LOCATION().AsString()));
        }
 
        auto targetNumElements =
           armnn::numeric_cast<unsigned int>(
               std::accumulate(targetDimsIn.begin(), targetDimsIn.end(), -1, std::multiplies<int32_t>()));
 
        auto stretchIndex = static_cast<size_t>(std::distance(targetDimsIn.begin(), stretchDim));
        if (targetNumElements == 0)
        {
            if (inputTensorInfo.GetNumElements() == 0)
            {
                outputDims[stretchIndex] = 0;
            }
            else
            {
                throw ParseException(
                        fmt::format("Input to reshape is a tensor with elements, but the requested shape has 0. {}",
                                    CHECK_LOCATION().AsString()));
            }
        }
        else
        {
            outputDims[stretchIndex] = inputTensorInfo.GetNumElements() / targetNumElements;
        }
    }
 
    TensorShape outputShape = TensorShape(static_cast<unsigned int>(outputDims.size()), outputDims.data());
 
    armnn::TensorInfo reshapeInfo = inputTensorInfo;
    reshapeInfo.SetShape(outputShape);
 
    return reshapeInfo;
}

References CHECK_LOCATION, TensorInfo::GetNumElements(), and TensorInfo::SetShape().

---

The documentation for this class was generated from the following files:

• src/armnnDeserializer/Deserializer.hpp
• src/armnnDeserializer/Deserializer.cpp