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author | Mike Kelly <mike.kelly@arm.com> | 2021-09-01 21:22:37 +0100 |
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committer | Jim Flynn <jim.flynn@arm.com> | 2021-09-02 08:37:02 +0000 |
commit | 31dce2b3fa19781836a9a295b514b2ab37f5d928 (patch) | |
tree | 852770e21c4251c91ed80eddc49d2dcbc6047d61 | |
parent | 00e9ebf026b1e2f6dbbed201ce1abe0091d6453b (diff) | |
download | armnn-31dce2b3fa19781836a9a295b514b2ab37f5d928.tar.gz |
IVGCVSW-6294 Added support for LRN to TfLiteParser
* Added support for LRN to TfLiteParser
Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Change-Id: Ia34441a4adeecd1f17c65af047d6c207729703ec
-rw-r--r-- | CMakeLists.txt | 1 | ||||
-rw-r--r-- | src/armnnTfLiteParser/TfLiteParser.cpp | 46 | ||||
-rw-r--r-- | src/armnnTfLiteParser/TfLiteParser.hpp | 1 | ||||
-rw-r--r-- | src/armnnTfLiteParser/test/LocalResponseNormalization.cpp | 107 |
4 files changed, 155 insertions, 0 deletions
diff --git a/CMakeLists.txt b/CMakeLists.txt index 2b0c952547..60753bed3a 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -682,6 +682,7 @@ if(BUILD_UNIT_TESTS) src/armnnTfLiteParser/test/L2Normalization.cpp src/armnnTfLiteParser/test/LeakyRelu.cpp src/armnnTfLiteParser/test/LoadScopeDynamicTensor.cpp + src/armnnTfLiteParser/test/LocalResponseNormalization.cpp src/armnnTfLiteParser/test/Maximum.cpp src/armnnTfLiteParser/test/MaxPool2D.cpp src/armnnTfLiteParser/test/Mean.cpp diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp index 2ac325c08c..5c7cb9b0b8 100644 --- a/src/armnnTfLiteParser/TfLiteParser.cpp +++ b/src/armnnTfLiteParser/TfLiteParser.cpp @@ -657,6 +657,8 @@ TfLiteParserImpl::TfLiteParserImpl(const Optional<ITfLiteParser::TfLiteParserOpt 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; @@ -3401,6 +3403,50 @@ void TfLiteParserImpl::ParseExp(size_t subgraphIndex, size_t operatorIndex) ParseElementwiseUnary(subgraphIndex, operatorIndex, armnn::UnaryOperation::Exp); } +void TfLiteParserImpl::ParseLocalResponseNormalization(size_t subgraphIndex, size_t operatorIndex) +{ + CHECK_MODEL(m_Model, subgraphIndex, operatorIndex); + + auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex); + CHECK_VALID_SIZE(inputs.size(), 1); + + auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex); + CHECK_VALID_SIZE(outputs.size(), 1); + + auto layerName = fmt::format("LRN:{}:{}", subgraphIndex, operatorIndex); + std::string layerNameFormatted = fmt::format(layerName, subgraphIndex, operatorIndex); + + armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[0]); + + const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex]; + const auto* options = operatorPtr->builtin_options.AsLocalResponseNormalizationOptions(); + + armnn::NormalizationDescriptor descriptor; + descriptor.m_DataLayout = armnn::DataLayout::NHWC; + descriptor.m_NormChannelType = armnn::NormalizationAlgorithmChannel::Across; + descriptor.m_NormMethodType = armnn::NormalizationAlgorithmMethod::LocalBrightness; + descriptor.m_NormSize = static_cast<uint32_t>(options->radius); + descriptor.m_K = options->bias; + descriptor.m_Alpha = options->alpha; + descriptor.m_Beta = options->beta; + + // ArmNN expects normSize to be the full size of the normalization + // window rather than the radius as in TfLite. + descriptor.m_NormSize = 1 + (2 * descriptor.m_NormSize); + + IConnectableLayer* layer = m_Network->AddNormalizationLayer(descriptor, layerNameFormatted.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]}); +} + void TfLiteParserImpl::ParseLogicalNot(size_t subgraphIndex, size_t operatorIndex) { ParseElementwiseUnary(subgraphIndex, operatorIndex, armnn::UnaryOperation::LogicalNot); diff --git a/src/armnnTfLiteParser/TfLiteParser.hpp b/src/armnnTfLiteParser/TfLiteParser.hpp index 0f11e41d37..dcd00d887d 100644 --- a/src/armnnTfLiteParser/TfLiteParser.hpp +++ b/src/armnnTfLiteParser/TfLiteParser.hpp @@ -131,6 +131,7 @@ private: void ParseLeakyRelu(size_t subgraphIndex, size_t operatorIndex); void ParseLess(size_t subgraphIndex, size_t operatorIndex); void ParseLessOrEqual(size_t subgraphIndex, size_t operatorIndex); + void ParseLocalResponseNormalization(size_t subgraphIndex, size_t operatorIndex); void ParseLogicalNot(size_t subgraphIndex, size_t operatorIndex); void ParseLogistic(size_t subgraphIndex, size_t operatorIndex); void ParseL2Normalization(size_t subgraphIndex, size_t operatorIndex); diff --git a/src/armnnTfLiteParser/test/LocalResponseNormalization.cpp b/src/armnnTfLiteParser/test/LocalResponseNormalization.cpp new file mode 100644 index 0000000000..5fe6daa582 --- /dev/null +++ b/src/armnnTfLiteParser/test/LocalResponseNormalization.cpp @@ -0,0 +1,107 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "ParserFlatbuffersFixture.hpp" + +TEST_SUITE("TensorflowLiteParser_LRN") +{ +struct LRNFixture : public ParserFlatbuffersFixture +{ + explicit LRNFixture(std::string inputdim, std::string outputdim, std::string dataType) + { + m_JsonString = R"( + { + "version": 3, + "operator_codes": [ { "builtin_code": "LOCAL_RESPONSE_NORMALIZATION" } ], + "subgraphs": [ + { + "tensors": [ + { + "shape": )" + + outputdim + + R"(, + "type": )" + + dataType + + R"(, + "buffer": 0, + "name": "OutputTensor", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ 1.0 ], + "zero_point": [ 0 ] + } + }, + { + "shape": )" + + inputdim + + R"(, + "type": )" + + dataType + + R"(, + "buffer": 1, + "name": "InputTensor", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ 1.0 ], + "zero_point": [ 0 ] + } + } + ], + "inputs": [ 1 ], + "outputs": [ 0 ], + "operators": [ { + "opcode_index": 0, + "inputs": [ 1 ], + "outputs": [ 0 ], + "builtin_options_type": "LocalResponseNormalizationOptions", + "builtin_options": + { + "radius": 2, + "bias": 1.0, + "alpha": 1.0, + "beta": 0.5 + }, + "custom_options_format": "FLEXBUFFERS" + } ] + } + ], + "description": "MaxPool2D test.", + "buffers" : [ {}, {} ] + })"; + + SetupSingleInputSingleOutput("InputTensor", "OutputTensor"); + } +}; + +struct LRNLiteFixtureFloat4DOutput : LRNFixture +{ + LRNLiteFixtureFloat4DOutput() : LRNFixture("[ 1, 1, 4, 4 ]", "[ 1, 1, 4, 4 ]", "FLOAT32") {} +}; + +TEST_CASE_FIXTURE(LRNLiteFixtureFloat4DOutput, "LRNLiteFloat4DOutput") +{ + RunTest<4, armnn::DataType::Float32>(0, + { + 2.0f, 3.0f, 5.0f, 2.0f, + 2.0f, 3.0f, 5.0f, 2.0f, + 2.0f, 3.0f, 5.0f, 2.0f, + 2.0f, 3.0f, 5.0f, 2.0f + }, + { + 0.320256f, 0.457496f, 0.762493f, 0.320256f, + 0.320256f, 0.457496f, 0.762493f, 0.320256f, + 0.320256f, 0.457496f, 0.762493f, 0.320256f, + 0.320256f, 0.457496f, 0.762493f, 0.320256f + }); +} + +TEST_CASE_FIXTURE(LRNLiteFixtureFloat4DOutput, "LRNIncorrectDataTypeError") +{ + CHECK_THROWS_AS((RunTest<4, armnn::DataType::QAsymmU8>(0, { 2, 3, 5, 2 }, { 5 })), armnn::Exception); +} + +} |