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

1 files changed, 128 insertions, 0 deletions

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 <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()