From 2686849118217ba692439407adb53ec3849d48ac Mon Sep 17 00:00:00 2001 From: Sadik Armagan Date: Fri, 22 Jan 2021 14:25:31 +0000 Subject: MLCE-335 'DEPTH_TO_SPACE and GATHER operator support in TfLiteParser' * Added GATHER operator support to TfLiteParser * Added DEPTH_TO_SPACE operator support to TfLiteParser Signed-off-by: Sadik Armagan Change-Id: Id5d3b54e2d850eb9f19417029efbeb73a3029e69 --- CMakeLists.txt | 2 + src/armnnTfLiteParser/TensorFlowLiteSupport.md | 4 + src/armnnTfLiteParser/TfLiteParser.cpp | 91 ++++++++++++++++ src/armnnTfLiteParser/TfLiteParser.hpp | 2 + src/armnnTfLiteParser/test/DepthToSpace.cpp | 98 +++++++++++++++++ src/armnnTfLiteParser/test/Gather.cpp | 121 +++++++++++++++++++++ .../test/ParserFlatbuffersFixture.hpp | 102 ++++++++++++++--- 7 files changed, 407 insertions(+), 13 deletions(-) create mode 100644 src/armnnTfLiteParser/test/DepthToSpace.cpp create mode 100644 src/armnnTfLiteParser/test/Gather.cpp diff --git a/CMakeLists.txt b/CMakeLists.txt index 2eb0263beb..b071bf0865 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -753,6 +753,7 @@ if(BUILD_UNIT_TESTS) src/armnnTfParser/test/Convolution2d.cpp src/armnnTfParser/test/Concat.cpp src/armnnTfParser/test/ConcatOfConcats.cpp + src/armnnTfLiteParser/test/DepthToSpace.cpp src/armnnTfParser/test/DepthwiseConvolution2d.cpp src/armnnTfParser/test/Equal.cpp src/armnnTfParser/test/ExpandDims.cpp @@ -805,6 +806,7 @@ if(BUILD_UNIT_TESTS) src/armnnTfLiteParser/test/Div.cpp src/armnnTfLiteParser/test/Exp.cpp src/armnnTfLiteParser/test/FullyConnected.cpp + src/armnnTfLiteParser/test/Gather.cpp src/armnnTfLiteParser/test/L2Normalization.cpp src/armnnTfLiteParser/test/LeakyRelu.cpp src/armnnTfLiteParser/test/LoadScopeDynamicTensor.cpp diff --git a/src/armnnTfLiteParser/TensorFlowLiteSupport.md b/src/armnnTfLiteParser/TensorFlowLiteSupport.md index 118fed7f7c..16663c986c 100644 --- a/src/armnnTfLiteParser/TensorFlowLiteSupport.md +++ b/src/armnnTfLiteParser/TensorFlowLiteSupport.md @@ -16,6 +16,8 @@ The Arm NN SDK TensorFlow Lite parser currently supports the following operators * CONV_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE +* DEPTH_TO_SPACE + * DEPTHWISE_CONV_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE * DEQUANTIZE @@ -28,6 +30,8 @@ The Arm NN SDK TensorFlow Lite parser currently supports the following operators * FULLY_CONNECTED, Supported Fused Activation: RELU , RELU6 , TANH, NONE +* GATHER + * HARD_SWISH * LEAKY_RELU diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp index a18471a71e..1a1e854395 100644 --- a/src/armnnTfLiteParser/TfLiteParser.cpp +++ b/src/armnnTfLiteParser/TfLiteParser.cpp @@ -547,11 +547,13 @@ TfLiteParser::TfLiteParser(const Optional& o m_ParserFunctions[tflite::BuiltinOperator_CONCATENATION] = &TfLiteParser::ParseConcatenation; m_ParserFunctions[tflite::BuiltinOperator_CONV_2D] = &TfLiteParser::ParseConv2D; m_ParserFunctions[tflite::BuiltinOperator_CUSTOM] = &TfLiteParser::ParseCustomOperator; + m_ParserFunctions[tflite::BuiltinOperator_DEPTH_TO_SPACE] = &TfLiteParser::ParseDepthToSpace; m_ParserFunctions[tflite::BuiltinOperator_DEPTHWISE_CONV_2D] = &TfLiteParser::ParseDepthwiseConv2D; m_ParserFunctions[tflite::BuiltinOperator_DEQUANTIZE] = &TfLiteParser::ParseDequantize; m_ParserFunctions[tflite::BuiltinOperator_ELU] = &TfLiteParser::ParseElu; m_ParserFunctions[tflite::BuiltinOperator_EXP] = &TfLiteParser::ParseExp; m_ParserFunctions[tflite::BuiltinOperator_FULLY_CONNECTED] = &TfLiteParser::ParseFullyConnected; + m_ParserFunctions[tflite::BuiltinOperator_GATHER] = &TfLiteParser::ParseGather; m_ParserFunctions[tflite::BuiltinOperator_HARD_SWISH] = &TfLiteParser::ParseHardSwish; m_ParserFunctions[tflite::BuiltinOperator_LEAKY_RELU] = &TfLiteParser::ParseLeakyRelu; m_ParserFunctions[tflite::BuiltinOperator_LOGISTIC] = &TfLiteParser::ParseLogistic; @@ -2903,6 +2905,95 @@ void TfLiteParser::ParseArgMax(size_t subgraphIndex, size_t operatorIndex) RegisterOutputSlots(subgraphIndex, operatorIndex, layer, outputTensorIndexes); } +void TfLiteParser::ParseGather(size_t subgraphIndex, size_t operatorIndex) +{ + CHECK_MODEL(m_Model, subgraphIndex, operatorIndex); + + TfLiteParser::TensorRawPtrVector inputs = GetInputs(m_Model, subgraphIndex, operatorIndex); + CHECK_VALID_SIZE(inputs.size(), 2); + TfLiteParser::TensorRawPtrVector outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex); + CHECK_VALID_SIZE(outputs.size(), 1); + + armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[0]); + armnn::TensorInfo indicesTensorInfo = ToTensorInfo(inputs[1]); + TensorInfo outputTensorInfo = ToTensorInfo(outputs[0], true); + + armnn::GatherDescriptor gatherDescriptor; + + const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex]; + const auto * options = operatorPtr->builtin_options.AsGatherOptions(); + auto axis = options->axis; + + auto inputDimensions = static_cast(inputTensorInfo.GetNumDimensions()); + auto indicesDimensions = indicesTensorInfo.GetNumDimensions(); + auto outputDimensions = outputTensorInfo.GetNumDimensions(); + if (((axis < -inputDimensions) && (axis < 0)) || ((axis >= inputDimensions) && (axis > 0))) + { + throw ParseException( + fmt::format("Operation has invalid axis: {} It is out of bounds [ -{}, {} ) {}", + axis, + inputDimensions, inputDimensions, + CHECK_LOCATION().AsString())); + } + if (outputDimensions != static_cast(inputDimensions) + indicesDimensions - 1) + { + throw ParseException( + fmt::format("Operation has invalid output dimensions: {} Output must be an ({} + {} - 1) -D tensor {}", + outputDimensions, + inputDimensions, indicesDimensions, + CHECK_LOCATION().AsString())); + } + + gatherDescriptor.m_Axis = axis; + + auto layerName = fmt::format("Gather:{}:{}", subgraphIndex, operatorIndex); + IConnectableLayer* layer = m_Network->AddGatherLayer(gatherDescriptor, layerName.c_str()); + ARMNN_ASSERT(layer != nullptr); + layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); + + auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex)); + RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]}); + + auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex)); + RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]}); +} + +void TfLiteParser::ParseDepthToSpace(size_t subgraphIndex, size_t operatorIndex) +{ + CHECK_MODEL(m_Model, subgraphIndex, operatorIndex); + + TfLiteParser::TensorRawPtrVector inputs = GetInputs(m_Model, subgraphIndex, operatorIndex); + CHECK_VALID_SIZE(inputs.size(), 1); + TfLiteParser::TensorRawPtrVector outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex); + CHECK_VALID_SIZE(outputs.size(), 1); + + armnn::DepthToSpaceDescriptor descriptor; + + const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex]; + const auto * options = operatorPtr->builtin_options.AsDepthToSpaceOptions(); + auto blockSize = options->block_size; + if (blockSize < 2) + { + throw ParseException( + fmt::format("Operation has invalid block size: {} Block size should be >= 2 {}", + blockSize, + CHECK_LOCATION().AsString())); + } + descriptor.m_BlockSize = armnn::numeric_cast(blockSize); + + auto layerName = fmt::format("DepthToSpace:{}:{}", subgraphIndex, operatorIndex); + IConnectableLayer* layer = m_Network->AddDepthToSpaceLayer(descriptor, layerName.c_str()); + ARMNN_ASSERT(layer != nullptr); + TensorInfo outputTensorInfo = ToTensorInfo(outputs[0], true); + layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); + + auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex)); + RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]}); + + auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex)); + RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]}); +} + armnn::IConnectableLayer* TfLiteParser::AddFusedActivationLayer(armnn::IConnectableLayer* prevLayer, unsigned int outputSlot, tflite::ActivationFunctionType activationType) diff --git a/src/armnnTfLiteParser/TfLiteParser.hpp b/src/armnnTfLiteParser/TfLiteParser.hpp index a8ddc69df8..418180fd25 100644 --- a/src/armnnTfLiteParser/TfLiteParser.hpp +++ b/src/armnnTfLiteParser/TfLiteParser.hpp @@ -99,12 +99,14 @@ private: void ParseBatchToSpaceND(size_t subgraphIndex, size_t operatorIndex); void ParseConcatenation(size_t subgraphIndex, size_t operatorIndex); void ParseConv2D(size_t subgraphIndex, size_t operatorIndex); + void ParseDepthToSpace(size_t subgraphIndex, size_t operatorIndex); void ParseDepthwiseConv2D(size_t subgraphIndex, size_t operatorIndex); void ParseDequantize(size_t subgraphIndex, size_t operatorIndex); void ParseDetectionPostProcess(size_t subgraphIndex, size_t operatorIndex); void ParseElu(size_t subgraphIndex, size_t operatorIndex); void ParseExp(size_t subgraphIndex, size_t operatorIndex); void ParseFullyConnected(size_t subgraphIndex, size_t operatorIndex); + void ParseGather(size_t subgraphIndex, size_t operatorIndex); void ParseHardSwish(size_t subgraphIndex, size_t operatorIndex); void ParseLeakyRelu(size_t subgraphIndex, size_t operatorIndex); void ParseLogistic(size_t subgraphIndex, size_t operatorIndex); diff --git a/src/armnnTfLiteParser/test/DepthToSpace.cpp b/src/armnnTfLiteParser/test/DepthToSpace.cpp new file mode 100644 index 0000000000..efd1207297 --- /dev/null +++ b/src/armnnTfLiteParser/test/DepthToSpace.cpp @@ -0,0 +1,98 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include +#include "ParserFlatbuffersFixture.hpp" +#include "../TfLiteParser.hpp" + +#include +#include + +BOOST_AUTO_TEST_SUITE(TensorflowLiteParser) + +struct DepthToSpaceFixture : public ParserFlatbuffersFixture +{ + explicit DepthToSpaceFixture(const std::string& inputShape, + const std::string& outputShape, + const std::string& dataType = "FLOAT32", + const std::string& scale = "1.0", + const std::string& offset = "0") + { + m_JsonString = R"( + { + "version": 3, + "operator_codes": [ { "builtin_code": "DEPTH_TO_SPACE" } ], + "subgraphs": [ { + "tensors": [ + { + "shape": )" + inputShape + R"(, + "type": )" + dataType + R"(, + "buffer": 0, + "name": "inputTensor", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ )" + scale + R"( ], + "zero_point": [ )" + offset + R"( ], + } + }, + { + "shape": )" + outputShape + R"(, + "type": )" + dataType + R"(, + "buffer": 1, + "name": "outputTensor", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ )" + scale + R"( ], + "zero_point": [ )" + offset + R"( ], + } + } + ], + "inputs": [ 0 ], + "outputs": [ 1 ], + "operators": [ + { + "opcode_index": 0, + "inputs": [ 0 ], + "outputs": [ 1 ], + "builtin_options_type": "DepthToSpaceOptions", + "builtin_options": { + "block_size": 2 + }, + "custom_options_format": "FLEXBUFFERS" + } + ], + } ], + "buffers" : [ + { }, + { }, + ] + } + )"; + SetupSingleInputSingleOutput("inputTensor", "outputTensor"); + } +}; + +struct SimpleDepthToSpaceFixture : public DepthToSpaceFixture +{ + SimpleDepthToSpaceFixture() : DepthToSpaceFixture("[ 1, 2, 2, 4 ]", "[ 1, 4, 4, 1 ]") {} +}; + +BOOST_FIXTURE_TEST_CASE(ParseDepthToSpace, SimpleDepthToSpaceFixture) +{ + RunTest<4, armnn::DataType::Float32> + (0, + {{ "inputTensor", { 1.f, 2.f, 3.f, 4.f, + 5.f, 6.f, 7.f, 8.f, + 9.f, 10.f, 11.f, 12.f, + 13.f, 14.f, 15.f, 16.f }}}, + {{ "outputTensor", { 1.f, 2.f, 5.f, 6.f, + 3.f, 4.f, 7.f, 8.f, + 9.f, 10.f, 13.f, 14.f, + 11.f, 12.f, 15.f, 16.f }}}); +} + +BOOST_AUTO_TEST_SUITE_END() diff --git a/src/armnnTfLiteParser/test/Gather.cpp b/src/armnnTfLiteParser/test/Gather.cpp new file mode 100644 index 0000000000..498d56d254 --- /dev/null +++ b/src/armnnTfLiteParser/test/Gather.cpp @@ -0,0 +1,121 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include +#include "ParserFlatbuffersFixture.hpp" +#include "../TfLiteParser.hpp" + +#include +#include + +BOOST_AUTO_TEST_SUITE(TensorflowLiteParser) + +struct GatherFixture : public ParserFlatbuffersFixture +{ + explicit GatherFixture(const std::string& paramsShape, + const std::string& outputShape, + const std::string& indicesShape, + const std::string& dataType = "FLOAT32", + const std::string& scale = "1.0", + const std::string& offset = "0") + { + m_JsonString = R"( + { + "version": 3, + "operator_codes": [ { "builtin_code": "GATHER" } ], + "subgraphs": [ { + "tensors": [ + { + "shape": )" + paramsShape + R"(, + "type": )" + dataType + R"(, + "buffer": 0, + "name": "inputTensor", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ )" + scale + R"( ], + "zero_point": [ )" + offset + R"( ], + } + }, + { + "shape": )" + indicesShape + R"( , + "type": "INT32", + "buffer": 1, + "name": "indices", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ 1.0 ], + "zero_point": [ 0 ], + } + }, + { + "shape": )" + outputShape + R"(, + "type": )" + dataType + R"(, + "buffer": 2, + "name": "outputTensor", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ )" + scale + R"( ], + "zero_point": [ )" + offset + R"( ], + } + } + ], + "inputs": [ 0, 1 ], + "outputs": [ 2 ], + "operators": [ + { + "opcode_index": 0, + "inputs": [ 0, 1 ], + "outputs": [ 2 ], + "builtin_options_type": "GatherOptions", + "builtin_options": { + "axis": 0 + }, + "custom_options_format": "FLEXBUFFERS" + } + ], + } ], + "buffers" : [ + { }, + { }, + { }, + ] + } + )"; + Setup(); + } +}; + +struct SimpleGatherFixture : public GatherFixture +{ + SimpleGatherFixture() : GatherFixture("[ 5, 2 ]", "[ 3, 2 ]", "[ 3 ]") {} +}; + +BOOST_FIXTURE_TEST_CASE(ParseGather, SimpleGatherFixture) +{ + RunTest<2, armnn::DataType::Float32, armnn::DataType::Signed32, armnn::DataType::Float32> + (0, + {{ "inputTensor", { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 }}}, + {{ "indices", { 1, 3, 4 }}}, + {{ "outputTensor", { 3, 4, 7, 8, 9, 10 }}}); +} + +struct GatherUint8Fixture : public GatherFixture +{ + GatherUint8Fixture() : GatherFixture("[ 8 ]", "[ 3 ]", "[ 3 ]", "UINT8") {} +}; + +BOOST_FIXTURE_TEST_CASE(ParseGatherUint8, GatherUint8Fixture) +{ + RunTest<1, armnn::DataType::QAsymmU8, armnn::DataType::Signed32, armnn::DataType::QAsymmU8> + (0, + {{ "inputTensor", { 1, 2, 3, 4, 5, 6, 7, 8 }}}, + {{ "indices", { 7, 6, 5 }}}, + {{ "outputTensor", { 8, 7, 6 }}}); +} + +BOOST_AUTO_TEST_SUITE_END() diff --git a/src/armnnTfLiteParser/test/ParserFlatbuffersFixture.hpp b/src/armnnTfLiteParser/test/ParserFlatbuffersFixture.hpp index 50a312fcf6..fc1d94e21f 100644 --- a/src/armnnTfLiteParser/test/ParserFlatbuffersFixture.hpp +++ b/src/armnnTfLiteParser/test/ParserFlatbuffersFixture.hpp @@ -152,6 +152,18 @@ struct ParserFlatbuffersFixture const std::map>>& expectedOutputData, bool isDynamic = false); + /// Multiple Inputs with different DataTypes, Multiple Outputs w/ Variable DataTypes + /// Executes the network with the given input tensors and checks the results against the given output tensors. + /// This overload supports multiple inputs and multiple outputs, identified by name along with the allowance for + /// the input datatype to be different to the output + template + void RunTest(size_t subgraphId, + const std::map>>& input1Data, + const std::map>>& input2Data, + const std::map>>& expectedOutputData); /// Multiple Inputs, Multiple Outputs w/ Variable Datatypes and different dimension sizes. /// Executes the network with the given input tensors and checks the results against the given output tensors. @@ -212,8 +224,30 @@ struct ParserFlatbuffersFixture tensors->quantization.get()->zero_point.begin(), tensors->quantization.get()->zero_point.end()); } + +private: + /// Fills the InputTensors with given input data + template + void FillInputTensors(armnn::InputTensors& inputTensors, + const std::map>>& inputData, + size_t subgraphId); }; +/// Fills the InputTensors with given input data +template +void ParserFlatbuffersFixture::FillInputTensors( + armnn::InputTensors& inputTensors, + const std::map>>& inputData, + size_t subgraphId) +{ + for (auto&& it : inputData) + { + armnn::BindingPointInfo bindingInfo = m_Parser->GetNetworkInputBindingInfo(subgraphId, it.first); + armnn::VerifyTensorInfoDataType(bindingInfo.second, dataType); + inputTensors.push_back({ bindingInfo.first, armnn::ConstTensor(bindingInfo.second, it.second.data()) }); + } +} + /// Single Input, Single Output /// Executes the network with the given input tensor and checks the result against the given output tensor. /// This overload assumes the network has a single input and a single output. @@ -256,12 +290,7 @@ void ParserFlatbuffersFixture::RunTest(size_t subgraphId, // Setup the armnn input tensors from the given vectors. armnn::InputTensors inputTensors; - for (auto&& it : inputData) - { - armnn::BindingPointInfo bindingInfo = m_Parser->GetNetworkInputBindingInfo(subgraphId, it.first); - armnn::VerifyTensorInfoDataType(bindingInfo.second, armnnType1); - inputTensors.push_back({ bindingInfo.first, armnn::ConstTensor(bindingInfo.second, it.second.data()) }); - } + FillInputTensors(inputTensors, inputData, subgraphId); // Allocate storage for the output tensors to be written to and setup the armnn output tensors. std::map> outputStorage; @@ -310,13 +339,7 @@ void ParserFlatbuffersFixture::RunTest(std::size_t subgraphId, // Setup the armnn input tensors from the given vectors. armnn::InputTensors inputTensors; - for (auto&& it : inputData) - { - armnn::BindingPointInfo bindingInfo = m_Parser->GetNetworkInputBindingInfo(subgraphId, it.first); - armnn::VerifyTensorInfoDataType(bindingInfo.second, armnnType1); - - inputTensors.push_back({ bindingInfo.first, armnn::ConstTensor(bindingInfo.second, it.second.data()) }); - } + FillInputTensors(inputTensors, inputData, subgraphId); armnn::OutputTensors outputTensors; outputTensors.reserve(expectedOutputData.size()); @@ -347,3 +370,56 @@ void ParserFlatbuffersFixture::RunTest(std::size_t subgraphId, } } } + +/// Multiple Inputs with different DataTypes, Multiple Outputs w/ Variable DataTypes +/// Executes the network with the given input tensors and checks the results against the given output tensors. +/// This overload supports multiple inputs and multiple outputs, identified by name along with the allowance for +/// the input datatype to be different to the output +template +void ParserFlatbuffersFixture::RunTest(size_t subgraphId, + const std::map>>& input1Data, + const std::map>>& input2Data, + const std::map>>& expectedOutputData) +{ + using DataType2 = armnn::ResolveType; + + // Setup the armnn input tensors from the given vectors. + armnn::InputTensors inputTensors; + FillInputTensors(inputTensors, input1Data, subgraphId); + FillInputTensors(inputTensors, input2Data, subgraphId); + + // Allocate storage for the output tensors to be written to and setup the armnn output tensors. + std::map> outputStorage; + armnn::OutputTensors outputTensors; + for (auto&& it : expectedOutputData) + { + armnn::LayerBindingId outputBindingId = m_Parser->GetNetworkOutputBindingInfo(subgraphId, it.first).first; + armnn::TensorInfo outputTensorInfo = m_Runtime->GetOutputTensorInfo(m_NetworkIdentifier, outputBindingId); + + // Check that output tensors have correct number of dimensions (NumOutputDimensions specified in test) + auto outputNumDimensions = outputTensorInfo.GetNumDimensions(); + BOOST_CHECK_MESSAGE((outputNumDimensions == NumOutputDimensions), + fmt::format("Number of dimensions expected {}, but got {} for output layer {}", + NumOutputDimensions, + outputNumDimensions, + it.first)); + + armnn::VerifyTensorInfoDataType(outputTensorInfo, outputType); + outputStorage.emplace(it.first, MakeTensor(outputTensorInfo)); + outputTensors.push_back( + { outputBindingId, armnn::Tensor(outputTensorInfo, outputStorage.at(it.first).data()) }); + } + + m_Runtime->EnqueueWorkload(m_NetworkIdentifier, inputTensors, outputTensors); + + // Compare each output tensor to the expected values + for (auto&& it : expectedOutputData) + { + armnn::BindingPointInfo bindingInfo = m_Parser->GetNetworkOutputBindingInfo(subgraphId, it.first); + auto outputExpected = MakeTensor(bindingInfo.second, it.second); + BOOST_TEST(CompareTensors(outputExpected, outputStorage[it.first], false)); + } +} \ No newline at end of file -- cgit v1.2.1