diff options
Diffstat (limited to 'src/armnnDeserializer/test')
-rw-r--r-- | src/armnnDeserializer/test/DeserializeL2Normalization.cpp | 142 |
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 index 0000000000..d8604a5cd5 --- /dev/null +++ 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() |