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 26 of file TfLiteParser.hpp.

Member Typedef Documentation

BufferPtr

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

Definition at line 39 of file TfLiteParser.hpp.

BufferRawPtr

using BufferRawPtr = const tflite::BufferT *

Definition at line 40 of file TfLiteParser.hpp.

ModelPtr

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

Definition at line 30 of file TfLiteParser.hpp.

OperatorCodePtr

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

Definition at line 33 of file TfLiteParser.hpp.

OperatorPtr

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

Definition at line 32 of file TfLiteParser.hpp.

SubgraphPtr

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

Definition at line 31 of file TfLiteParser.hpp.

TensorIdRawPtr

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

Definition at line 37 of file TfLiteParser.hpp.

TensorIdRawPtrVector

using TensorIdRawPtrVector = std::vector<TensorIdRawPtr>

Definition at line 38 of file TfLiteParser.hpp.

TensorPtr

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

Definition at line 34 of file TfLiteParser.hpp.

TensorRawPtr

using TensorRawPtr = const tflite::TensorT *

Definition at line 35 of file TfLiteParser.hpp.

TensorRawPtrVector

using TensorRawPtrVector = std::vector<TensorRawPtr>

Definition at line 36 of file TfLiteParser.hpp.

Constructor & Destructor Documentation

TfLiteParserImpl()

TfLiteParserImpl

(

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

options = armnn::EmptyOptional()

)

Definition at line 744 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_BATCH_MATMUL]            = &TfLiteParserImpl::ParseBatchMatMul;
    m_ParserFunctions[tflite::BuiltinOperator_BROADCAST_TO]            = &TfLiteParserImpl::ParseBroadcastTo;
    m_ParserFunctions[tflite::BuiltinOperator_CEIL]                    = &TfLiteParserImpl::ParseCeil;
    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_4)
    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_GELU]                    = &TfLiteParserImpl::ParseGelu;
    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_LOG]                     = &TfLiteParserImpl::ParseLog;
    m_ParserFunctions[tflite::BuiltinOperator_LOGICAL_NOT]             = &TfLiteParserImpl::ParseLogicalNot;
    m_ParserFunctions[tflite::BuiltinOperator_LOGISTIC]                = &TfLiteParserImpl::ParseLogistic;
    m_ParserFunctions[tflite::BuiltinOperator_LOG_SOFTMAX]             = &TfLiteParserImpl::ParseLogSoftmax;
    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_POW]                     = &TfLiteParserImpl::ParsePower;
    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_REVERSE_V2]              = &TfLiteParserImpl::ParseReverseV2;
    m_ParserFunctions[tflite::BuiltinOperator_RSQRT]                   = &TfLiteParserImpl::ParseRsqrt;
    m_ParserFunctions[tflite::BuiltinOperator_SCATTER_ND]              = &TfLiteParserImpl::ParseScatterNd;
    m_ParserFunctions[tflite::BuiltinOperator_SQRT]                    = &TfLiteParserImpl::ParseSqrt;
    m_ParserFunctions[tflite::BuiltinOperator_SHAPE]                   = &TfLiteParserImpl::ParseShape;
    m_ParserFunctions[tflite::BuiltinOperator_SIN]                     = &TfLiteParserImpl::ParseSin;
    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_SPACE_TO_DEPTH]          = &TfLiteParserImpl::ParseSpaceToDepth;
    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_SQUARE]                  = &TfLiteParserImpl::ParseSquare;
    m_ParserFunctions[tflite::BuiltinOperator_SQUARED_DIFFERENCE]      = &TfLiteParserImpl::ParseSquaredDifference;
    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_TILE]                    = &TfLiteParserImpl::ParseTile;
    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 964 of file TfLiteParser.cpp.

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

References TfLiteParserImpl::LoadModelFromBinary().

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 957 of file TfLiteParser.cpp.

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

References TfLiteParserImpl::LoadModelFromFile().

GetBuffer()

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

static

Definition at line 5764 of file TfLiteParser.cpp.

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

References CHECK_BUFFER.

GetInputs()

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

static

Definition at line 5452 of file TfLiteParser.cpp.

{
    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;
}

References CHECK_MODEL, and CHECKED_NON_NEGATIVE.

GetInputTensorIds()

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

static

Definition at line 5532 of file TfLiteParser.cpp.

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

References CHECK_MODEL.

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 5942 of file TfLiteParser.cpp.

{
    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()));
}

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

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 5974 of file TfLiteParser.cpp.

{
    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_OverriddenOutputShapes.size() > 0 ?
                                                m_OverriddenOutputShapes[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()));
}

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

GetOutputs()

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

static

Definition at line 5479 of file TfLiteParser.cpp.

{
    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;
}

References CHECK_MODEL, CHECK_TENSOR, and CHECKED_NON_NEGATIVE.

GetOutputTensorIds()

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

static

Definition at line 5542 of file TfLiteParser.cpp.

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

References CHECK_MODEL.

GetSubgraphCount()

size_t GetSubgraphCount

(

)

const

Return the number of subgraphs in the parsed model.

Definition at line 6006 of file TfLiteParser.cpp.

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

GetSubgraphInputs()

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

static

Definition at line 5499 of file TfLiteParser.cpp.

{
    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;
}

References CHECK_SUBGRAPH, CHECK_TENSOR, and CHECKED_NON_NEGATIVE.

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

GetSubgraphInputTensorNames()

std::vector< std::string > GetSubgraphInputTensorNames

(

size_t

subgraphId

)

const

Return the input tensor names for a given subgraph.

Definition at line 6011 of file TfLiteParser.cpp.

{
    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;
}

References CHECK_SUBGRAPH, and TfLiteParserImpl::GetSubgraphInputs().

GetSubgraphOutputs()

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

static

Definition at line 5516 of file TfLiteParser.cpp.

{
    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;
}

References CHECK_SUBGRAPH, and CHECKED_NON_NEGATIVE.

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

GetSubgraphOutputTensorNames()

std::vector< std::string > GetSubgraphOutputTensorNames

(

size_t

subgraphId

)

const

Return the output tensor names for a given subgraph.

Definition at line 6024 of file TfLiteParser.cpp.

{
    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;
}

References CHECK_SUBGRAPH, and TfLiteParserImpl::GetSubgraphOutputs().

GetVersion()

const std::string GetVersion ( )

static

Retrieve version in X.Y.Z form.

Definition at line 6037 of file TfLiteParser.cpp.

{
    return TFLITE_PARSER_VERSION;
}

References TFLITE_PARSER_VERSION.

LoadModel()

armnn::INetworkPtr LoadModel

(

std::unique_ptr< tflite::ModelT >

model

)

Definition at line 972 of file TfLiteParser.cpp.

{
    ResetParser();
    m_Model = std::move(model);
 
    return CreateNetworkFromModel();
}

LoadModelFromBinary()

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

static

Definition at line 5433 of file TfLiteParser.cpp.

{
    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);
}

References CHECK_LOCATION.

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

LoadModelFromFile()

TfLiteParserImpl::ModelPtr LoadModelFromFile ( const char *  fileName )

static

Definition at line 5403 of file TfLiteParser.cpp.

{
    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());
    }
    if (!fs::is_regular_file(pathToFile))
    {
        // Exclude non regular files.
        throw InvalidArgumentException(fmt::format("File \"{}\" is not a regular file and cannot be loaded.",
                                                   pathToFile.c_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());
}

References CHECK_LOCATION, and TfLiteParserImpl::LoadModelFromBinary().

Referenced by TfLiteParserImpl::CreateNetworkFromBinaryFile().

OutputShapeOfReshape()

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

static

Definition at line 3311 of file TfLiteParser.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());
 
    TensorInfo reshapeInfo = inputTensorInfo;
    reshapeInfo.SetShape(outputShape);
 
    return reshapeInfo;
}

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

OutputShapeOfSqueeze()

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

static

Definition at line 2430 of file TfLiteParser.cpp.

{
    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;
}

References CHECK_LOCATION, CHECK_VALID_SIZE, TensorInfo::GetNumDimensions(), TensorInfo::GetShape(), and TensorInfo::SetShape().

---

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

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