From 28c94573013d7caf429601f529c6f690cd4994e2 Mon Sep 17 00:00:00 2001 From: Matthew Jackson Date: Thu, 18 Jul 2019 10:47:03 +0100 Subject: IVGCVSW-3383 - Add TfLite Parser support for L2 Normalization layer * Added ParseL2Normalization in TfLiteParser * Added new unit tests L2Normalization.cpp * Added documentation for supported L2 Normalization to TensorflorLiteSupport.md Signed-off-by: Matthew Jackson Change-Id: I83ea75d1791ac8a00390aed3e5d0a7b337fcd46d --- CMakeLists.txt | 1 + src/armnnTfLiteParser/TensorFlowLiteSupport.md | 2 + src/armnnTfLiteParser/TfLiteParser.cpp | 28 ++++++ src/armnnTfLiteParser/TfLiteParser.hpp | 1 + src/armnnTfLiteParser/test/L2Normalization.cpp | 128 +++++++++++++++++++++++++ 5 files changed, 160 insertions(+) create mode 100644 src/armnnTfLiteParser/test/L2Normalization.cpp diff --git a/CMakeLists.txt b/CMakeLists.txt index 9bc4201a5e..aa462fb999 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -565,6 +565,7 @@ if(BUILD_UNIT_TESTS) src/armnnTfLiteParser/test/DepthwiseConvolution2D.cpp src/armnnTfLiteParser/test/DetectionPostProcess.cpp src/armnnTfLiteParser/test/FullyConnected.cpp + src/armnnTfLiteParser/test/L2Normalization.cpp src/armnnTfLiteParser/test/Maximum.cpp src/armnnTfLiteParser/test/MaxPool2D.cpp src/armnnTfLiteParser/test/Mean.cpp diff --git a/src/armnnTfLiteParser/TensorFlowLiteSupport.md b/src/armnnTfLiteParser/TensorFlowLiteSupport.md index 8a8b7bed6d..7acbf28397 100644 --- a/src/armnnTfLiteParser/TensorFlowLiteSupport.md +++ b/src/armnnTfLiteParser/TensorFlowLiteSupport.md @@ -22,6 +22,8 @@ The Arm NN SDK TensorFlow Lite parser currently supports the following operators * LOGISTIC +* L2_NORMALIZATION + * MAX_POOL_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE * MAXIMUM diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp index 21c17155b5..04fa6b1947 100644 --- a/src/armnnTfLiteParser/TfLiteParser.cpp +++ b/src/armnnTfLiteParser/TfLiteParser.cpp @@ -440,6 +440,7 @@ TfLiteParser::TfLiteParser() m_ParserFunctions[tflite::BuiltinOperator_CUSTOM] = &TfLiteParser::ParseDetectionPostProcess; m_ParserFunctions[tflite::BuiltinOperator_FULLY_CONNECTED] = &TfLiteParser::ParseFullyConnected; m_ParserFunctions[tflite::BuiltinOperator_LOGISTIC] = &TfLiteParser::ParseLogistic; + m_ParserFunctions[tflite::BuiltinOperator_L2_NORMALIZATION] = &TfLiteParser::ParseL2Normalization; m_ParserFunctions[tflite::BuiltinOperator_MAX_POOL_2D] = &TfLiteParser::ParseMaxPool2D; m_ParserFunctions[tflite::BuiltinOperator_MAXIMUM] = &TfLiteParser::ParseMaximum; m_ParserFunctions[tflite::BuiltinOperator_MINIMUM] = &TfLiteParser::ParseMinimum; @@ -917,6 +918,33 @@ void TfLiteParser::ParseBatchToSpaceND(size_t subgraphIndex, size_t operatorInde RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]}); } +void TfLiteParser::ParseL2Normalization(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); + + L2NormalizationDescriptor desc; + desc.m_DataLayout = armnn::DataLayout::NHWC; + auto layerName = boost::str(boost::format("L2Normalization:%1%:%2%") % subgraphIndex % operatorIndex); + IConnectableLayer* layer = m_Network->AddL2NormalizationLayer(desc, layerName.c_str()); + + BOOST_ASSERT(layer != nullptr); + + armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]); + 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 TfLiteParser::ParseMaxPool2D(size_t subgraphIndex, size_t operatorIndex) { ParsePool(subgraphIndex, operatorIndex, PoolingAlgorithm::Max); diff --git a/src/armnnTfLiteParser/TfLiteParser.hpp b/src/armnnTfLiteParser/TfLiteParser.hpp index 437e459732..90b800d56d 100644 --- a/src/armnnTfLiteParser/TfLiteParser.hpp +++ b/src/armnnTfLiteParser/TfLiteParser.hpp @@ -100,6 +100,7 @@ private: void ParseDetectionPostProcess(size_t subgraphIndex, size_t operatorIndex); void ParseFullyConnected(size_t subgraphIndex, size_t operatorIndex); void ParseLogistic(size_t subgraphIndex, size_t operatorIndex); + void ParseL2Normalization(size_t subgraphIndex, size_t operatorIndex); void ParseMaxPool2D(size_t subgraphIndex, size_t operatorIndex); void ParseMaximum(size_t subgraphIndex, size_t operatorIndex); void ParseMean(size_t subgraphIndex, size_t operatorIndex); diff --git a/src/armnnTfLiteParser/test/L2Normalization.cpp b/src/armnnTfLiteParser/test/L2Normalization.cpp new file mode 100644 index 0000000000..0dd5eeffac --- /dev/null +++ b/src/armnnTfLiteParser/test/L2Normalization.cpp @@ -0,0 +1,128 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include +#include "ParserFlatbuffersFixture.hpp" +#include "../TfLiteParser.hpp" + +#include +#include + +BOOST_AUTO_TEST_SUITE(TensorflowLiteParser) + +struct L2NormalizationFixture : public ParserFlatbuffersFixture +{ + explicit L2NormalizationFixture(const std::string & inputOutputShape) + { + m_JsonString = R"( + { + "version": 3, + "operator_codes": [ { "builtin_code": "L2_NORMALIZATION" } ], + "subgraphs": [ { + "tensors": [ + { + "shape": )" + inputOutputShape + R"(, + "type": "FLOAT32", + "buffer": 0, + "name": "inputTensor", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ 1.0 ], + "zero_point": [ 0 ], + } + }, + { + "shape": )" + inputOutputShape + R"(, + "type": "FLOAT32", + "buffer": 1, + "name": "outputTensor", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ 1.0 ], + "zero_point": [ 0 ], + } + } + ], + "inputs": [ 0 ], + "outputs": [ 1 ], + "operators": [ + { + "opcode_index": 0, + "inputs": [ 0 ], + "outputs": [ 1 ], + "custom_options_format": "FLEXBUFFERS" + } + ], + } ], + "buffers" : [ + { } + ] + } + )"; + Setup(); + } +}; + +float CalcL2Norm(std::initializer_list elements) +{ + const float reduction = std::accumulate(elements.begin(), elements.end(), 0.0f, + [](float acc, float element) { return acc + element * element; }); + const float eps = 1e-12f; + const float max = reduction < eps ? eps : reduction; + return sqrtf(max); +} + +struct L2NormalizationFixture4D : L2NormalizationFixture +{ + // TfLite uses NHWC shape + L2NormalizationFixture4D() : L2NormalizationFixture("[ 1, 1, 4, 3 ]") {} +}; + +BOOST_FIXTURE_TEST_CASE(ParseL2Normalization4D, L2NormalizationFixture4D) +{ + RunTest<4, armnn::DataType::Float32>( + 0, + {{"inputTensor", { 1.0f, 2.0f, 3.0f, + 4.0f, 5.0f, 6.0f, + 7.0f, 8.0f, 9.0f, + 10.0f, 11.0f, 12.0f }}}, + + {{"outputTensor", { 1.0f / CalcL2Norm({ 1.0f, 2.0f, 3.0f }), + 2.0f / CalcL2Norm({ 1.0f, 2.0f, 3.0f }), + 3.0f / CalcL2Norm({ 1.0f, 2.0f, 3.0f }), + + 4.0f / CalcL2Norm({ 4.0f, 5.0f, 6.0f }), + 5.0f / CalcL2Norm({ 4.0f, 5.0f, 6.0f }), + 6.0f / CalcL2Norm({ 4.0f, 5.0f, 6.0f }), + + 7.0f / CalcL2Norm({ 7.0f, 8.0f, 9.0f }), + 8.0f / CalcL2Norm({ 7.0f, 8.0f, 9.0f }), + 9.0f / CalcL2Norm({ 7.0f, 8.0f, 9.0f }), + + 10.0f / CalcL2Norm({ 10.0f, 11.0f, 12.0f }), + 11.0f / CalcL2Norm({ 10.0f, 11.0f, 12.0f }), + 12.0f / CalcL2Norm({ 10.0f, 11.0f, 12.0f }) }}}); +} + +struct L2NormalizationSimpleFixture4D : L2NormalizationFixture +{ + L2NormalizationSimpleFixture4D() : L2NormalizationFixture("[ 1, 1, 1, 4 ]") {} +}; + +BOOST_FIXTURE_TEST_CASE(ParseL2NormalizationEps4D, L2NormalizationSimpleFixture4D) +{ + RunTest<4, armnn::DataType::Float32>( + 0, + {{"inputTensor", { 0.00000001f, 0.00000002f, 0.00000003f, 0.00000004f }}}, + + {{"outputTensor", { 0.00000001f / CalcL2Norm({ 0.00000001f, 0.00000002f, 0.00000003f, 0.00000004f }), + 0.00000002f / CalcL2Norm({ 0.00000001f, 0.00000002f, 0.00000003f, 0.00000004f }), + 0.00000003f / CalcL2Norm({ 0.00000001f, 0.00000002f, 0.00000003f, 0.00000004f }), + 0.00000004f / CalcL2Norm({ 0.00000001f, 0.00000002f, 0.00000003f, 0.00000004f }) }}}); +} + +BOOST_AUTO_TEST_SUITE_END() -- cgit v1.2.1