TfLiteParserImpl Class Reference

#include <TfLiteParser.hpp>

Public Types
using	ModelPtr = std::unique_ptr< tflite::ModelT >
using	SubgraphPtr = std::unique_ptr< tflite::SubGraphT >
using	OperatorPtr = std::unique_ptr< tflite::OperatorT >
using	OperatorCodePtr = std::unique_ptr< tflite::OperatorCodeT >
using	TensorPtr = std::unique_ptr< tflite::TensorT >
using	TensorRawPtr = const tflite::TensorT *
using	TensorRawPtrVector = std::vector< TensorRawPtr >
using	TensorIdRawPtr = std::pair< size_t, TensorRawPtr >
using	TensorIdRawPtrVector = std::vector< TensorIdRawPtr >
using	BufferPtr = std::unique_ptr< tflite::BufferT >
using	BufferRawPtr = const tflite::BufferT *

Public Member Functions
armnn::INetworkPtr	CreateNetworkFromBinaryFile (const char *graphFile)
	Create the network from a flatbuffers binary file on disk. More...
armnn::INetworkPtr	CreateNetworkFromBinary (const std::vector< uint8_t > &binaryContent)
	Create the network from a flatbuffers binary. More...
BindingPointInfo	GetNetworkInputBindingInfo (size_t subgraphId, const std::string &name) const
	Retrieve binding info (layer id and tensor info) for the network input identified by the given layer name and subgraph id. More...
BindingPointInfo	GetNetworkOutputBindingInfo (size_t subgraphId, const std::string &name) const
	Retrieve binding info (layer id and tensor info) for the network output identified by the given layer name and subgraph id. More...
size_t	GetSubgraphCount () const
	Return the number of subgraphs in the parsed model. More...
std::vector< std::string >	GetSubgraphInputTensorNames (size_t subgraphId) const
	Return the input tensor names for a given subgraph. More...
std::vector< std::string >	GetSubgraphOutputTensorNames (size_t subgraphId) const
	Return the output tensor names for a given subgraph. More...
	TfLiteParserImpl (const armnn::Optional< ITfLiteParser::TfLiteParserOptions > &options=armnn::EmptyOptional())
	~TfLiteParserImpl ()=default
armnn::INetworkPtr	CreateNetworkFromBinaryAsDynamic (const std::vector< uint8_t > &binaryContent)
armnn::INetworkPtr	LoadModel (std::unique_ptr< tflite::ModelT > model)

Static Public Member Functions
static ModelPtr	LoadModelFromFile (const char *fileName)
static ModelPtr	LoadModelFromBinary (const uint8_t *binaryContent, size_t len)
static TensorRawPtrVector	GetInputs (const ModelPtr &model, size_t subgraphIndex, size_t operatorIndex)
static TensorRawPtrVector	GetOutputs (const ModelPtr &model, size_t subgraphIndex, size_t operatorIndex)
static TensorIdRawPtrVector	GetSubgraphInputs (const ModelPtr &model, size_t subgraphIndex)
static TensorIdRawPtrVector	GetSubgraphOutputs (const ModelPtr &model, size_t subgraphIndex)
static std::vector< int32_t > &	GetInputTensorIds (const ModelPtr &model, size_t subgraphIndex, size_t operatorIndex)
static std::vector< int32_t > &	GetOutputTensorIds (const ModelPtr &model, size_t subgraphIndex, size_t operatorIndex)
static BufferRawPtr	GetBuffer (const ModelPtr &model, size_t bufferIndex)
static armnn::TensorInfo	OutputShapeOfSqueeze (std::vector< uint32_t > squeezeDims, const armnn::TensorInfo &inputTensorInfo)
static armnn::TensorInfo	OutputShapeOfReshape (const armnn::TensorInfo &inputTensorInfo, const std::vector< int32_t > &targetDimsIn)
static const std::string	GetVersion ()
	Retrieve version in X.Y.Z form. More...

Detailed Description

Definition at line 25 of file TfLiteParser.hpp.

Member Typedef Documentation

BufferPtr

using BufferPtr = std::unique_ptr<tflite::BufferT>

Definition at line 38 of file TfLiteParser.hpp.

BufferRawPtr

using BufferRawPtr = const tflite::BufferT *

Definition at line 39 of file TfLiteParser.hpp.

ModelPtr

using ModelPtr = std::unique_ptr<tflite::ModelT>

Definition at line 29 of file TfLiteParser.hpp.

OperatorCodePtr

using OperatorCodePtr = std::unique_ptr<tflite::OperatorCodeT>

Definition at line 32 of file TfLiteParser.hpp.

OperatorPtr

using OperatorPtr = std::unique_ptr<tflite::OperatorT>

Definition at line 31 of file TfLiteParser.hpp.

SubgraphPtr

using SubgraphPtr = std::unique_ptr<tflite::SubGraphT>

Definition at line 30 of file TfLiteParser.hpp.

TensorIdRawPtr

using TensorIdRawPtr = std::pair<size_t, TensorRawPtr>

Definition at line 36 of file TfLiteParser.hpp.

TensorIdRawPtrVector

using TensorIdRawPtrVector = std::vector<TensorIdRawPtr>

Definition at line 37 of file TfLiteParser.hpp.

TensorPtr

using TensorPtr = std::unique_ptr<tflite::TensorT>

Definition at line 33 of file TfLiteParser.hpp.

TensorRawPtr

using TensorRawPtr = const tflite::TensorT *

Definition at line 34 of file TfLiteParser.hpp.

TensorRawPtrVector

using TensorRawPtrVector = std::vector<TensorRawPtr>

Definition at line 35 of file TfLiteParser.hpp.

Constructor & Destructor Documentation

TfLiteParserImpl()

TfLiteParserImpl

(

const armnn::Optional< ITfLiteParser::TfLiteParserOptions > &

options = armnn::EmptyOptional()

)

Definition at line 671 of file TfLiteParser.cpp.

: m_Options(options)
, m_Network(nullptr, nullptr)
, m_ParserFunctions(tflite::BuiltinOperator_MAX+1, &TfLiteParserImpl::ParseUnsupportedOperator)
{
    // register supported operators
    m_ParserFunctions[tflite::BuiltinOperator_ABS]                     = &TfLiteParserImpl::ParseAbs;
    m_ParserFunctions[tflite::BuiltinOperator_ADD]                     = &TfLiteParserImpl::ParseAdd;
    m_ParserFunctions[tflite::BuiltinOperator_ARG_MIN]                 = &TfLiteParserImpl::ParseArgMin;
    m_ParserFunctions[tflite::BuiltinOperator_ARG_MAX]                 = &TfLiteParserImpl::ParseArgMax;
    m_ParserFunctions[tflite::BuiltinOperator_AVERAGE_POOL_2D]         = &TfLiteParserImpl::ParseAveragePool2D;
    m_ParserFunctions[tflite::BuiltinOperator_BATCH_TO_SPACE_ND]       = &TfLiteParserImpl::ParseBatchToSpaceND;
    m_ParserFunctions[tflite::BuiltinOperator_CAST]                    = &TfLiteParserImpl::ParseCast;
    m_ParserFunctions[tflite::BuiltinOperator_CONCATENATION]           = &TfLiteParserImpl::ParseConcatenation;
    m_ParserFunctions[tflite::BuiltinOperator_CONV_2D]                 = &TfLiteParserImpl::ParseConv2D;
    // Conv3D support was added in TF 2.5, so for backwards compatibility a hash define is needed.
    #if defined(ARMNN_POST_TFLITE_2_3)
    m_ParserFunctions[tflite::BuiltinOperator_CONV_3D]                 = &TfLiteParserImpl::ParseConv3D;
    #endif
    m_ParserFunctions[tflite::BuiltinOperator_CUSTOM]                  = &TfLiteParserImpl::ParseCustomOperator;
    m_ParserFunctions[tflite::BuiltinOperator_DEPTH_TO_SPACE]          = &TfLiteParserImpl::ParseDepthToSpace;
    m_ParserFunctions[tflite::BuiltinOperator_DEPTHWISE_CONV_2D]       = &TfLiteParserImpl::ParseDepthwiseConv2D;
    m_ParserFunctions[tflite::BuiltinOperator_DEQUANTIZE]              = &TfLiteParserImpl::ParseDequantize;
    m_ParserFunctions[tflite::BuiltinOperator_DIV]                     = &TfLiteParserImpl::ParseDiv;
    m_ParserFunctions[tflite::BuiltinOperator_ELU]                     = &TfLiteParserImpl::ParseElu;
    m_ParserFunctions[tflite::BuiltinOperator_EQUAL]                   = &TfLiteParserImpl::ParseEqual;
    m_ParserFunctions[tflite::BuiltinOperator_EXP]                     = &TfLiteParserImpl::ParseExp;
    m_ParserFunctions[tflite::BuiltinOperator_EXPAND_DIMS]             = &TfLiteParserImpl::ParseExpandDims;
    m_ParserFunctions[tflite::BuiltinOperator_FLOOR_DIV]               = &TfLiteParserImpl::ParseFloorDiv;
    m_ParserFunctions[tflite::BuiltinOperator_FULLY_CONNECTED]         = &TfLiteParserImpl::ParseFullyConnected;
    m_ParserFunctions[tflite::BuiltinOperator_GATHER]                  = &TfLiteParserImpl::ParseGather;
    m_ParserFunctions[tflite::BuiltinOperator_GATHER_ND]               = &TfLiteParserImpl::ParseGatherNd;
    m_ParserFunctions[tflite::BuiltinOperator_GREATER]                 = &TfLiteParserImpl::ParseGreater;
    m_ParserFunctions[tflite::BuiltinOperator_GREATER_EQUAL]           = &TfLiteParserImpl::ParseGreaterOrEqual;
    m_ParserFunctions[tflite::BuiltinOperator_HARD_SWISH]              = &TfLiteParserImpl::ParseHardSwish;
    m_ParserFunctions[tflite::BuiltinOperator_LEAKY_RELU]              = &TfLiteParserImpl::ParseLeakyRelu;
    m_ParserFunctions[tflite::BuiltinOperator_LESS]                    = &TfLiteParserImpl::ParseLess;
    m_ParserFunctions[tflite::BuiltinOperator_LESS_EQUAL]              = &TfLiteParserImpl::ParseLessOrEqual;
    m_ParserFunctions[tflite::BuiltinOperator_LOCAL_RESPONSE_NORMALIZATION]
            = &TfLiteParserImpl::ParseLocalResponseNormalization;
    m_ParserFunctions[tflite::BuiltinOperator_LOGICAL_NOT]             = &TfLiteParserImpl::ParseLogicalNot;
    m_ParserFunctions[tflite::BuiltinOperator_LOGISTIC]                = &TfLiteParserImpl::ParseLogistic;
    m_ParserFunctions[tflite::BuiltinOperator_L2_NORMALIZATION]        = &TfLiteParserImpl::ParseL2Normalization;
    m_ParserFunctions[tflite::BuiltinOperator_MAX_POOL_2D]             = &TfLiteParserImpl::ParseMaxPool2D;
    m_ParserFunctions[tflite::BuiltinOperator_MAXIMUM]                 = &TfLiteParserImpl::ParseMaximum;
    m_ParserFunctions[tflite::BuiltinOperator_MEAN]                    = &TfLiteParserImpl::ParseMean;
    m_ParserFunctions[tflite::BuiltinOperator_MINIMUM]                 = &TfLiteParserImpl::ParseMinimum;
    m_ParserFunctions[tflite::BuiltinOperator_MIRROR_PAD]              = &TfLiteParserImpl::ParseMirrorPad;
    m_ParserFunctions[tflite::BuiltinOperator_MUL]                     = &TfLiteParserImpl::ParseMul;
    m_ParserFunctions[tflite::BuiltinOperator_NEG]                     = &TfLiteParserImpl::ParseNeg;
    m_ParserFunctions[tflite::BuiltinOperator_NOT_EQUAL]               = &TfLiteParserImpl::ParseNotEqual;
    m_ParserFunctions[tflite::BuiltinOperator_PACK]                    = &TfLiteParserImpl::ParsePack;
    m_ParserFunctions[tflite::BuiltinOperator_PAD]                     = &TfLiteParserImpl::ParsePad;
    m_ParserFunctions[tflite::BuiltinOperator_PADV2]                   = &TfLiteParserImpl::ParsePad;
    m_ParserFunctions[tflite::BuiltinOperator_PRELU]                   = &TfLiteParserImpl::ParsePrelu;
    m_ParserFunctions[tflite::BuiltinOperator_QUANTIZE]                = &TfLiteParserImpl::ParseQuantize;
    m_ParserFunctions[tflite::BuiltinOperator_RELU]                    = &TfLiteParserImpl::ParseRelu;
    m_ParserFunctions[tflite::BuiltinOperator_RELU6]                   = &TfLiteParserImpl::ParseRelu6;
    m_ParserFunctions[tflite::BuiltinOperator_REDUCE_MAX]              = &TfLiteParserImpl::ParseReduceMax;
    m_ParserFunctions[tflite::BuiltinOperator_REDUCE_MIN]              = &TfLiteParserImpl::ParseReduceMin;
    m_ParserFunctions[tflite::BuiltinOperator_REDUCE_PROD]             = &TfLiteParserImpl::ParseReduceProd;
    m_ParserFunctions[tflite::BuiltinOperator_RESHAPE]                 = &TfLiteParserImpl::ParseReshape;
    m_ParserFunctions[tflite::BuiltinOperator_RESIZE_BILINEAR]         = &TfLiteParserImpl::ParseResizeBilinear;
    m_ParserFunctions[tflite::BuiltinOperator_RESIZE_NEAREST_NEIGHBOR] = &TfLiteParserImpl::ParseResizeNearestNeighbor;
    m_ParserFunctions[tflite::BuiltinOperator_RSQRT]                   = &TfLiteParserImpl::ParseRsqrt;
    m_ParserFunctions[tflite::BuiltinOperator_SQRT]                    = &TfLiteParserImpl::ParseSqrt;
    m_ParserFunctions[tflite::BuiltinOperator_SHAPE]                   = &TfLiteParserImpl::ParseShape;
    m_ParserFunctions[tflite::BuiltinOperator_SLICE]                   = &TfLiteParserImpl::ParseSlice;
    m_ParserFunctions[tflite::BuiltinOperator_SOFTMAX]                 = &TfLiteParserImpl::ParseSoftmax;
    m_ParserFunctions[tflite::BuiltinOperator_SPACE_TO_BATCH_ND]       = &TfLiteParserImpl::ParseSpaceToBatchND;
    m_ParserFunctions[tflite::BuiltinOperator_SPLIT]                   = &TfLiteParserImpl::ParseSplit;
    m_ParserFunctions[tflite::BuiltinOperator_SPLIT_V]                 = &TfLiteParserImpl::ParseSplitV;
    m_ParserFunctions[tflite::BuiltinOperator_SQUEEZE]                 = &TfLiteParserImpl::ParseSqueeze;
    m_ParserFunctions[tflite::BuiltinOperator_STRIDED_SLICE]           = &TfLiteParserImpl::ParseStridedSlice;
    m_ParserFunctions[tflite::BuiltinOperator_SUB]                     = &TfLiteParserImpl::ParseSub;
    m_ParserFunctions[tflite::BuiltinOperator_SUM]                     = &TfLiteParserImpl::ParseSum;
    m_ParserFunctions[tflite::BuiltinOperator_TANH]                    = &TfLiteParserImpl::ParseTanH;
    m_ParserFunctions[tflite::BuiltinOperator_TRANSPOSE]               = &TfLiteParserImpl::ParseTranspose;
    m_ParserFunctions[tflite::BuiltinOperator_TRANSPOSE_CONV]          = &TfLiteParserImpl::ParseTransposeConv;
    m_ParserFunctions[tflite::BuiltinOperator_UNIDIRECTIONAL_SEQUENCE_LSTM]
            = &TfLiteParserImpl::ParseUnidirectionalSequenceLSTM;
    m_ParserFunctions[tflite::BuiltinOperator_UNPACK]                  = &TfLiteParserImpl::ParseUnpack;

    // register supported custom operators
    m_CustomParserFunctions["TFLite_Detection_PostProcess"]      = &TfLiteParserImpl::ParseDetectionPostProcess;
}

~TfLiteParserImpl()

~TfLiteParserImpl ( )

default

Member Function Documentation

CreateNetworkFromBinary()

INetworkPtr CreateNetworkFromBinary

(

const std::vector< uint8_t > &

binaryContent

)

Create the network from a flatbuffers binary.

Definition at line 775 of file TfLiteParser.cpp.

References TfLiteParserImpl::LoadModelFromBinary().

{
    ResetParser();
    m_Model = LoadModelFromBinary(binaryContent.data(), binaryContent.size());
    return CreateNetworkFromModel();
}

CreateNetworkFromBinaryAsDynamic()

armnn::INetworkPtr CreateNetworkFromBinaryAsDynamic

(

const std::vector< uint8_t > &

binaryContent

)

CreateNetworkFromBinaryFile()

INetworkPtr CreateNetworkFromBinaryFile

(

const char *

graphFile

)

Create the network from a flatbuffers binary file on disk.

Definition at line 768 of file TfLiteParser.cpp.

References TfLiteParserImpl::LoadModelFromFile().

{
    ResetParser();
    m_Model = LoadModelFromFile(graphFile);
    return CreateNetworkFromModel();
}

GetBuffer()

TfLiteParserImpl::BufferRawPtr GetBuffer ( const ModelPtr &  model, size_t  bufferIndex  )

static

Definition at line 4690 of file TfLiteParser.cpp.

References armnnTfLiteParser::AsFloatArray(), CHECK_BUFFER, CHECK_BUFFER_SIZE, CHECK_LOCATION, CHECK_TENSOR_PTR, armnn::Float32, TensorInfo::GetDataType(), armnn::GetDataTypeName(), TensorInfo::GetShape(), armnn::QAsymmS8, armnn::QAsymmU8, armnn::QSymmS8, TensorInfo::SetConstant(), armnn::Signed32, and armnnDeserializer::ToTensorInfo().

Referenced by armnnTfLiteParser::AsFloatArray(), armnnTfLiteParser::ComputeWrappedIndex(), TfLiteParserImpl::OutputShapeOfReshape(), and TfLiteParserImpl::OutputShapeOfSqueeze().

{
    CHECK_BUFFER(model, bufferIndex);
    return model->buffers[bufferIndex].get();
}

GetInputs()

TfLiteParserImpl::TensorRawPtrVector GetInputs ( const ModelPtr &  model, size_t  subgraphIndex, size_t  operatorIndex  )

static

Definition at line 4423 of file TfLiteParser.cpp.

References CHECK_MODEL, and CHECKED_NON_NEGATIVE.

Referenced by armnnTfLiteParser::AsFloatArray(), armnnTfLiteParser::ComputeWrappedIndex(), TfLiteParserImpl::OutputShapeOfReshape(), and TfLiteParserImpl::OutputShapeOfSqueeze().

{
    CHECK_MODEL(model, subgraphIndex, operatorIndex);

    const auto& subgraphPtr = model->subgraphs[subgraphIndex];
    const auto& operatorPtr = subgraphPtr->operators[operatorIndex];

    size_t inputCount = operatorPtr->inputs.size();
    TensorRawPtrVector result;
    for (size_t i = 0; i < inputCount; ++i)
    {
        // If the input location is -1 then assume input is turned off.
        if (operatorPtr->inputs[i] == -1)
        {
            continue;
        }
        else
        {
            uint32_t inputId = CHECKED_NON_NEGATIVE(operatorPtr->inputs[i]);
            result.push_back(subgraphPtr->tensors[inputId].get());
        }
    }
    return result;
}

GetInputTensorIds()

std::vector< int32_t > & GetInputTensorIds ( const ModelPtr &  model, size_t  subgraphIndex, size_t  operatorIndex  )

static

Definition at line 4503 of file TfLiteParser.cpp.

References CHECK_MODEL.

Referenced by armnnTfLiteParser::AsFloatArray(), armnnTfLiteParser::ComputeWrappedIndex(), TfLiteParserImpl::OutputShapeOfReshape(), and TfLiteParserImpl::OutputShapeOfSqueeze().

{
    CHECK_MODEL(model, subgraphIndex, operatorIndex);
    const auto& subgraphPtr = model->subgraphs[subgraphIndex];
    const auto& operatorPtr = subgraphPtr->operators[operatorIndex];
    return operatorPtr->inputs;
}

GetNetworkInputBindingInfo()

BindingPointInfo GetNetworkInputBindingInfo	(	size_t	subgraphId,
		const std::string &	name
	)		const

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

Definition at line 4846 of file TfLiteParser.cpp.

References CHECK_LOCATION, CHECK_SUBGRAPH, TfLiteParserImpl::GetSubgraphInputs(), TensorInfo::SetConstant(), and armnnDeserializer::ToTensorInfo().

{
    CHECK_SUBGRAPH(m_Model, subgraphId);
    auto inputs = GetSubgraphInputs(m_Model, subgraphId);
    for (auto const& input : inputs)
    {
        if (input.second->name == name)
        {
            auto bindingId = GenerateLayerBindingId(subgraphId, input.first);
            auto inputTensorInfo = ToTensorInfo(input.second);
            // Input tensors are always treated as constant tensors during network execution.
            inputTensorInfo.SetConstant(true);
            return std::make_pair(bindingId, inputTensorInfo);
        }
    }

    std::stringstream bindings;
    for (auto const& input : inputs)
    {
        bindings << "'" << input.second->name << "' ";
    }

    throw ParseException(
        fmt::format("No input binding found for subgraph:{} and name:{}. "
                    "Possible inputs are: [{}] {}",
                    subgraphId,
                    name,
                    bindings.str(),
                    CHECK_LOCATION().AsString()));
}

GetNetworkOutputBindingInfo()

BindingPointInfo GetNetworkOutputBindingInfo	(	size_t	subgraphId,
		const std::string &	name
	)		const

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

Definition at line 4878 of file TfLiteParser.cpp.

References CHECK_LOCATION, CHECK_SUBGRAPH, TfLiteParserImpl::GetSubgraphOutputs(), and armnnDeserializer::ToTensorInfo().

{
    CHECK_SUBGRAPH(m_Model, subgraphId);
    auto outputs = GetSubgraphOutputs(m_Model, subgraphId);
    for (unsigned int i = 0; i < outputs.size(); ++i)
    {
        auto const output = outputs[i];
        if (output.second->name == name)
        {
            auto bindingId = GenerateLayerBindingId(subgraphId, output.first);
            std::vector<unsigned int> shape = m_OverridenOutputShapes.size() > 0 ?
                                                m_OverridenOutputShapes[i] : AsUnsignedVector(output.second->shape);
            return std::make_pair(bindingId, ToTensorInfo(output.second, shape));
        }
    }

    std::stringstream bindings;
    for (auto const& output : outputs)
    {
        bindings << "'" << output.second->name << "' ";
    }

    throw ParseException(
        fmt::format("No output binding found for subgraph:{} and name:{}. "
                    "Possible outputs are: [{}] {}",
                    subgraphId,
                    name,
                    bindings.str(),
                    CHECK_LOCATION().AsString()));
}

GetOutputs()

TfLiteParserImpl::TensorRawPtrVector GetOutputs ( const ModelPtr &  model, size_t  subgraphIndex, size_t  operatorIndex  )

static

Definition at line 4450 of file TfLiteParser.cpp.

References CHECK_MODEL, CHECK_TENSOR, and CHECKED_NON_NEGATIVE.

Referenced by armnnTfLiteParser::AsFloatArray(), armnnTfLiteParser::ComputeWrappedIndex(), TfLiteParserImpl::OutputShapeOfReshape(), and TfLiteParserImpl::OutputShapeOfSqueeze().

{
    CHECK_MODEL(model, subgraphIndex, operatorIndex);

    const auto& subgraphPtr = model->subgraphs[subgraphIndex];
    const auto& operatorPtr = subgraphPtr->operators[operatorIndex];

    size_t outputCount = operatorPtr->outputs.size();
    TensorRawPtrVector result(outputCount);
    for (size_t i = 0; i < outputCount; ++i)
    {
        uint32_t outputId = CHECKED_NON_NEGATIVE(operatorPtr->outputs[i]);
        CHECK_TENSOR(model, subgraphIndex, outputId);
        result[i] = subgraphPtr->tensors[outputId].get();
    }
    return result;
}

GetOutputTensorIds()

std::vector< int32_t > & GetOutputTensorIds ( const ModelPtr &  model, size_t  subgraphIndex, size_t  operatorIndex  )

static

Definition at line 4513 of file TfLiteParser.cpp.

References ARMNN_ASSERT, CHECK_LOCATION, CHECK_MODEL, CHECK_SUBGRAPH, TensorInfo::GetDataType(), IConnectableLayer::GetInputSlot(), TensorInfo::GetNumBytes(), IConnectableLayer::GetNumInputSlots(), IConnectableLayer::GetNumOutputSlots(), IConnectableLayer::GetOutputSlot(), TfLiteParserImpl::GetSubgraphInputs(), TfLiteParserImpl::GetSubgraphOutputs(), TensorInfo::SetConstant(), TensorInfo::SetDataType(), IOutputSlot::SetTensorInfo(), and armnnDeserializer::ToTensorInfo().

Referenced by armnnTfLiteParser::AsFloatArray(), armnnTfLiteParser::ComputeWrappedIndex(), TfLiteParserImpl::OutputShapeOfReshape(), and TfLiteParserImpl::OutputShapeOfSqueeze().

{
    CHECK_MODEL(model, subgraphIndex, operatorIndex);
    const auto& subgraphPtr = model->subgraphs[subgraphIndex];
    const auto& operatorPtr = subgraphPtr->operators[operatorIndex];
    return operatorPtr->outputs;
}

GetSubgraphCount()

size_t GetSubgraphCount

(

)

const

Return the number of subgraphs in the parsed model.

Definition at line 4910 of file TfLiteParser.cpp.

{
    return m_Model->subgraphs.size();
}

GetSubgraphInputs()

TfLiteParserImpl::TensorIdRawPtrVector GetSubgraphInputs ( const ModelPtr &  model, size_t  subgraphIndex  )

static

Definition at line 4470 of file TfLiteParser.cpp.

References CHECK_SUBGRAPH, CHECK_TENSOR, and CHECKED_NON_NEGATIVE.

Referenced by TfLiteParserImpl::GetNetworkInputBindingInfo(), TfLiteParserImpl::GetOutputTensorIds(), and TfLiteParserImpl::GetSubgraphInputTensorNames().

{
    CHECK_SUBGRAPH(model, subgraphIndex);
    const auto& subgraphPtr = model->subgraphs[subgraphIndex];

    size_t inputCount = subgraphPtr->inputs.size();
    TensorIdRawPtrVector result(inputCount);
    for (size_t i = 0; i < inputCount; ++i)
    {
        uint32_t inputId = CHECKED_NON_NEGATIVE(subgraphPtr->inputs[i]);
        CHECK_TENSOR(model, subgraphIndex, inputId);
        result[i] = std::make_pair(inputId, subgraphPtr->tensors[inputId].get());
    }
    return result;
}

GetSubgraphInputTensorNames()

std::vector< std::string > GetSubgraphInputTensorNames

(

size_t

subgraphId

)

const

Return the input tensor names for a given subgraph.

Definition at line 4915 of file TfLiteParser.cpp.

References CHECK_SUBGRAPH, and TfLiteParserImpl::GetSubgraphInputs().

{
    CHECK_SUBGRAPH(m_Model, subgraphId);
    auto inputs = GetSubgraphInputs(m_Model, subgraphId);
    std::vector<std::string> result;
    result.reserve(inputs.size());
    for (auto const& input : inputs)
    {
        result.push_back(input.second->name);
    }
    return result;
}

GetSubgraphOutputs()

TfLiteParserImpl::TensorIdRawPtrVector GetSubgraphOutputs ( const ModelPtr &  model, size_t  subgraphIndex  )

static

Definition at line 4487 of file TfLiteParser.cpp.

References CHECK_SUBGRAPH, and CHECKED_NON_NEGATIVE.

Referenced by TfLiteParserImpl::GetNetworkOutputBindingInfo(), TfLiteParserImpl::GetOutputTensorIds(), and TfLiteParserImpl::GetSubgraphOutputTensorNames().

{
    CHECK_SUBGRAPH(model, subgraphIndex);
    const auto& subgraphPtr = model->subgraphs[subgraphIndex];

    size_t outputCount = subgraphPtr->outputs.size();
    TensorIdRawPtrVector result(outputCount);
    for (size_t i = 0; i < outputCount; ++i)
    {
        uint32_t outputId = CHECKED_NON_NEGATIVE(subgraphPtr->outputs[i]);
        result[i] = std::make_pair(outputId, subgraphPtr->tensors[outputId].get());
    }
    return result;
}

GetSubgraphOutputTensorNames()

std::vector< std::string > GetSubgraphOutputTensorNames

(

size_t

subgraphId

)

const

Return the output tensor names for a given subgraph.

Definition at line 4928 of file TfLiteParser.cpp.

References CHECK_SUBGRAPH, and TfLiteParserImpl::GetSubgraphOutputs().

{
    CHECK_SUBGRAPH(m_Model, subgraphId);
    auto outputs = GetSubgraphOutputs(m_Model, subgraphId);
    std::vector<std::string> result;
    result.reserve(outputs.size());
    for (auto const& output : outputs)
    {
        result.push_back(output.second->name);
    }
    return result;
}

GetVersion()

const std::string GetVersion ( )

static

Retrieve version in X.Y.Z form.

Definition at line 4941 of file TfLiteParser.cpp.

References TFLITE_PARSER_VERSION.

{
    return TFLITE_PARSER_VERSION;
}

LoadModel()

armnn::INetworkPtr LoadModel

(

std::unique_ptr< tflite::ModelT >

model

)

Definition at line 783 of file TfLiteParser.cpp.

References ARMNN_ASSERT, ARMNN_LOG, CHECK_LOCATION, armnn::error, and Exception::what().

{
    ResetParser();
    m_Model = std::move(model);

    return CreateNetworkFromModel();
}

LoadModelFromBinary()

TfLiteParserImpl::ModelPtr LoadModelFromBinary ( const uint8_t *  binaryContent, size_t  len  )

static

Definition at line 4404 of file TfLiteParser.cpp.

References CHECK_LOCATION.

Referenced by TfLiteParserImpl::CreateNetworkFromBinary(), and TfLiteParserImpl::LoadModelFromFile().

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

LoadModelFromFile()

TfLiteParserImpl::ModelPtr LoadModelFromFile ( const char *  fileName )

static

Definition at line 4380 of file TfLiteParser.cpp.

References CHECK_LOCATION, and TfLiteParserImpl::LoadModelFromBinary().

Referenced by TfLiteParserImpl::CreateNetworkFromBinaryFile().

{
    if (fileName == nullptr)
    {
        throw InvalidArgumentException(fmt::format("Invalid (null) file name {}",
                                       CHECK_LOCATION().AsString()));
    }
    std::error_code errorCode;
    fs::path pathToFile(fileName);
    if (!fs::exists(pathToFile, errorCode))
    {
        //fmt::format() could not be used here (format error)
        std::stringstream msg;
        msg << "Cannot find the file (" << fileName << ") errorCode: " << errorCode
            << " " << CHECK_LOCATION().AsString();

        throw FileNotFoundException(msg.str());
    }
    std::ifstream file(fileName, std::ios::binary);
    std::string fileContent((std::istreambuf_iterator<char>(file)), std::istreambuf_iterator<char>());
    return LoadModelFromBinary(reinterpret_cast<const uint8_t *>(fileContent.c_str()),
                               fileContent.size());
}

OutputShapeOfReshape()

armnn::TensorInfo OutputShapeOfReshape ( const armnn::TensorInfo &  inputTensorInfo, const std::vector< int32_t > &  targetDimsIn  )

static

Definition at line 2671 of file TfLiteParser.cpp.

References ARMNN_ASSERT, ARMNN_THROW_PARSE_EXCEPTION, CHECK_LOCATION, CHECK_MODEL, CHECK_SUPPORTED_FUSED_ACTIVATION, CHECK_VALID_SIZE, CHECKED_NON_NEGATIVE, armnnDeserializer::CheckShape(), IOutputSlot::Connect(), TfLiteParserImpl::GetBuffer(), TensorInfo::GetDataType(), BaseTensor< MemoryType >::GetInfo(), TfLiteParserImpl::GetInputs(), IConnectableLayer::GetInputSlot(), TfLiteParserImpl::GetInputTensorIds(), IConnectableLayer::GetName(), TensorInfo::GetNumBytes(), TensorShape::GetNumDimensions(), TensorInfo::GetNumDimensions(), TensorInfo::GetNumElements(), IConnectableLayer::GetNumOutputSlots(), TfLiteParserImpl::GetOutputs(), IConnectableLayer::GetOutputSlot(), TfLiteParserImpl::GetOutputTensorIds(), TensorInfo::GetQuantizationOffset(), TensorInfo::GetQuantizationScale(), TensorInfo::GetShape(), armnnUtils::GetUnsignedAxis(), LstmDescriptor::m_ActivationFunc, StackDescriptor::m_Axis, FullyConnectedDescriptor::m_BiasEnabled, LstmInputParams::m_CellBias, LstmInputParams::m_CellLayerNormWeights, LstmInputParams::m_CellToForgetWeights, LstmInputParams::m_CellToInputWeights, LstmInputParams::m_CellToOutputWeights, FullyConnectedDescriptor::m_ConstantWeights, DetectionPostProcessDescriptor::m_DetectionsPerClass, LstmInputParams::m_ForgetGateBias, LstmInputParams::m_ForgetLayerNormWeights, LstmInputParams::m_InputGateBias, LstmInputParams::m_InputLayerNormWeights, StackDescriptor::m_InputShape, LstmInputParams::m_InputToCellWeights, LstmInputParams::m_InputToForgetWeights, LstmInputParamsInfo::m_InputToForgetWeights, LstmInputParams::m_InputToInputWeights, LstmInputParams::m_InputToOutputWeights, DetectionPostProcessDescriptor::m_MaxClassesPerDetection, DetectionPostProcessDescriptor::m_MaxDetections, ResizeDescriptor::m_Method, DetectionPostProcessDescriptor::m_NmsIouThreshold, DetectionPostProcessDescriptor::m_NmsScoreThreshold, DetectionPostProcessDescriptor::m_NumClasses, StackDescriptor::m_NumInputs, LstmInputParams::m_OutputGateBias, LstmInputParams::m_OutputLayerNormWeights, LstmInputParams::m_ProjectionBias, LstmInputParams::m_ProjectionWeights, LstmInputParams::m_RecurrentToCellWeights, LstmInputParams::m_RecurrentToForgetWeights, LstmInputParams::m_RecurrentToInputWeights, LstmInputParams::m_RecurrentToOutputWeights, DetectionPostProcessDescriptor::m_ScaleH, DetectionPostProcessDescriptor::m_ScaleW, DetectionPostProcessDescriptor::m_ScaleX, DetectionPostProcessDescriptor::m_ScaleY, ReshapeDescriptor::m_TargetShape, FullyConnectedDescriptor::m_TransposeWeightMatrix, DetectionPostProcessDescriptor::m_UseRegularNms, armnn::MaxNumOfTensorDimensions, armnn::NHWC, armnn::numeric_cast(), armnnUtils::ProcessConcatInputTensorInfo(), OriginsDescriptor::SetConcatAxis(), TensorInfo::SetShape(), IOutputSlot::SetTensorInfo(), ViewsDescriptor::SetViewOriginCoord(), ViewsDescriptor::SetViewSize(), and armnnDeserializer::ToTensorInfo().

{
    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));
        outputDims[stretchIndex] = inputTensorInfo.GetNumElements() / targetNumElements;
    }

    TensorShape outputShape = TensorShape(static_cast<unsigned int>(outputDims.size()), outputDims.data());

    TensorInfo reshapeInfo = inputTensorInfo;
    reshapeInfo.SetShape(outputShape);

    return reshapeInfo;
}

OutputShapeOfSqueeze()

armnn::TensorInfo OutputShapeOfSqueeze ( std::vector< uint32_t >  squeezeDims, const armnn::TensorInfo &  inputTensorInfo  )

static

Definition at line 1928 of file TfLiteParser.cpp.

References ARMNN_ASSERT, ARMNN_THROW_PARSE_EXCEPTION, CHECK_LOCATION, CHECK_MODEL, CHECK_VALID_SIZE, IOutputSlot::Connect(), armnn::Float32, TfLiteParserImpl::GetBuffer(), TensorInfo::GetDataType(), TfLiteParserImpl::GetInputs(), IConnectableLayer::GetInputSlot(), TfLiteParserImpl::GetInputTensorIds(), TensorInfo::GetNumBytes(), TensorShape::GetNumDimensions(), TensorInfo::GetNumDimensions(), TensorInfo::GetNumElements(), TfLiteParserImpl::GetOutputs(), IConnectableLayer::GetOutputSlot(), TfLiteParserImpl::GetOutputTensorIds(), TensorInfo::GetShape(), armnn::IgnoreUnused(), ActivationDescriptor::m_A, MeanDescriptor::m_Axis, ActivationDescriptor::m_B, StridedSliceDescriptor::m_Begin, StridedSliceDescriptor::m_BeginMask, StridedSliceDescriptor::m_DataLayout, StridedSliceDescriptor::m_EllipsisMask, StridedSliceDescriptor::m_End, StridedSliceDescriptor::m_EndMask, ActivationDescriptor::m_Function, MeanDescriptor::m_KeepDims, StridedSliceDescriptor::m_NewAxisMask, PadDescriptor::m_PaddingMode, PadDescriptor::m_PadList, PadDescriptor::m_PadValue, StridedSliceDescriptor::m_ShrinkAxisMask, StridedSliceDescriptor::m_Stride, ReshapeDescriptor::m_TargetShape, armnn::NHWC, armnn::QAsymmS8, armnn::QAsymmU8, armnn::QSymmS8, TensorInfo::SetShape(), IOutputSlot::SetTensorInfo(), armnn::Signed32, armnn::Signed64, and armnnDeserializer::ToTensorInfo().

{
    CHECK_VALID_SIZE(squeezeDims.size(), 0, 1, 2, 3, 4);
    static const uint32_t dimensionSequence[] = { 0, 1, 2, 3 };

    if (inputTensorInfo.GetNumDimensions() > 4)
    {
        std::stringstream ss;
        ss << "Input tensor has unexpected number of dimensions:" << inputTensorInfo.GetNumDimensions()
           << " shape:" << inputTensorInfo.GetShape() << " "
           << CHECK_LOCATION().AsString();
        throw ParseException(ss.str());
    }

    if (squeezeDims.empty())
    {
        squeezeDims.assign(dimensionSequence,
                           dimensionSequence+inputTensorInfo.GetNumDimensions());
    }

    std::vector<uint32_t> outputDims;
    for(unsigned int i = 0; i < inputTensorInfo.GetNumDimensions(); i++)
    {
        bool skipSqueeze = (std::find(squeezeDims.begin(), squeezeDims.end(), i) == squeezeDims.end());
        auto currentDimension = inputTensorInfo.GetShape()[i];
        if (skipSqueeze || currentDimension != 1)
        {
            outputDims.push_back(currentDimension);
        }
    }

    if (outputDims.size() > 4)
    {
        std::stringstream ss;
        ss << "Output tensor has unexpected number of dimensions:" << inputTensorInfo.GetNumDimensions()
           << " shape:" << inputTensorInfo.GetShape() << " "
           << CHECK_LOCATION().AsString();
        throw ParseException(ss.str());
    }

    TensorShape outShape = TensorShape(static_cast<unsigned int>(outputDims.size()),
                                       outputDims.data());

    // we need to preserve the tensor type and the quantization data as well
    TensorInfo outTensorInfo = inputTensorInfo;
    outTensorInfo.SetShape(outShape);

    return outTensorInfo;
}

---

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

• src/armnnTfLiteParser/TfLiteParser.hpp
• src/armnnTfLiteParser/TfLiteParser.cpp