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 <matthew.jackson@arm.com>
Change-Id: I83ea75d1791ac8a00390aed3e5d0a7b337fcd46d
diff --git a/CMakeLists.txt b/CMakeLists.txt
index 9bc4201..aa462fb 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -565,6 +565,7 @@
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 8a8b7be..7acbf28 100644
--- a/src/armnnTfLiteParser/TensorFlowLiteSupport.md
+++ b/src/armnnTfLiteParser/TensorFlowLiteSupport.md
@@ -22,6 +22,8 @@
* 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 21c1715..04fa6b1 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -440,6 +440,7 @@
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 @@
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 437e459..90b800d 100644
--- a/src/armnnTfLiteParser/TfLiteParser.hpp
+++ b/src/armnnTfLiteParser/TfLiteParser.hpp
@@ -100,6 +100,7 @@
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 0000000..0dd5eef
--- /dev/null
+++ b/src/armnnTfLiteParser/test/L2Normalization.cpp
@@ -0,0 +1,128 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <boost/test/unit_test.hpp>
+#include "ParserFlatbuffersFixture.hpp"
+#include "../TfLiteParser.hpp"
+
+#include <string>
+#include <iostream>
+
+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<float> 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()