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-rw-r--r--src/armnnDeserializer/test/DeserializeL2Normalization.cpp142
1 files changed, 142 insertions, 0 deletions
diff --git a/src/armnnDeserializer/test/DeserializeL2Normalization.cpp b/src/armnnDeserializer/test/DeserializeL2Normalization.cpp
new file mode 100644
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+++ b/src/armnnDeserializer/test/DeserializeL2Normalization.cpp
@@ -0,0 +1,142 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <boost/test/unit_test.hpp>
+#include "ParserFlatbuffersSerializeFixture.hpp"
+#include "../Deserializer.hpp"
+
+#include <string>
+#include <iostream>
+
+BOOST_AUTO_TEST_SUITE(Deserializer)
+
+struct L2NormalizationFixture : public ParserFlatbuffersSerializeFixture
+{
+ explicit L2NormalizationFixture(const std::string &inputShape,
+ const std::string &outputShape,
+ const std::string &dataType,
+ const std::string &dataLayout,
+ const std::string epsilon)
+ {
+ m_JsonString = R"(
+ {
+ inputIds: [0],
+ outputIds: [2],
+ layers: [
+ {
+ layer_type: "InputLayer",
+ layer: {
+ base: {
+ layerBindingId: 0,
+ base: {
+ index: 0,
+ layerName: "InputLayer",
+ layerType: "Input",
+ inputSlots: [{
+ index: 0,
+ connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+ }],
+ outputSlots: [{
+ index: 0,
+ tensorInfo: {
+ dimensions: )" + inputShape + R"(,
+ dataType: ")" + dataType + R"(",
+ quantizationScale: 0.5,
+ quantizationOffset: 0
+ },
+ }]
+ },
+ }
+ },
+ },
+ {
+ layer_type: "L2NormalizationLayer",
+ layer : {
+ base: {
+ index:1,
+ layerName: "L2NormalizationLayer",
+ layerType: "L2Normalization",
+ inputSlots: [{
+ index: 0,
+ connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+ }],
+ outputSlots: [{
+ index: 0,
+ tensorInfo: {
+ dimensions: )" + outputShape + R"(,
+ dataType: ")" + dataType + R"("
+ },
+ }],
+ },
+ descriptor: {
+ dataLayout: ")" + dataLayout + R"(",
+ eps: )" + epsilon + R"(
+ },
+ },
+ },
+ {
+ layer_type: "OutputLayer",
+ layer: {
+ base:{
+ layerBindingId: 0,
+ base: {
+ index: 2,
+ layerName: "OutputLayer",
+ layerType: "Output",
+ inputSlots: [{
+ index: 0,
+ connection: {sourceLayerIndex:1, outputSlotIndex:0 },
+ }],
+ outputSlots: [ {
+ index: 0,
+ tensorInfo: {
+ dimensions: )" + outputShape + R"(,
+ dataType: ")" + dataType + R"("
+ },
+ }],
+ }
+ }},
+ }]
+ }
+)";
+ Setup();
+ }
+};
+
+struct L2NormFixture : L2NormalizationFixture
+{
+ // Using a non standard epsilon value of 1e-8
+ L2NormFixture():L2NormalizationFixture("[ 1, 3, 1, 1 ]",
+ "[ 1, 3, 1, 1 ]",
+ "Float32",
+ "NCHW",
+ "0.00000001"){}
+};
+
+BOOST_FIXTURE_TEST_CASE(L2NormalizationFloat32, L2NormFixture)
+{
+ // 1 / sqrt(1^2 + 2^2 + 3^2)
+ const float approxInvL2Norm = 0.267261f;
+
+ RunTest<4, armnn::DataType::Float32>(0,
+ {{"InputLayer", { 1.0f, 2.0f, 3.0f }}},
+ {{"OutputLayer",{ 1.0f * approxInvL2Norm,
+ 2.0f * approxInvL2Norm,
+ 3.0f * approxInvL2Norm }}});
+}
+
+BOOST_FIXTURE_TEST_CASE(L2NormalizationEpsilonLimitFloat32, L2NormFixture)
+{
+ // 1 / sqrt(1e-8)
+ const float approxInvL2Norm = 10000;
+
+ RunTest<4, armnn::DataType::Float32>(0,
+ {{"InputLayer", { 0.00000001f, 0.00000002f, 0.00000003f }}},
+ {{"OutputLayer",{ 0.00000001f * approxInvL2Norm,
+ 0.00000002f * approxInvL2Norm,
+ 0.00000003f * approxInvL2Norm }}});
+}
+
+BOOST_AUTO_TEST_SUITE_END()