| Ferran Balaguer | 0dcffec | 2019-06-18 16:25:06 +0100 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2017 Arm Ltd. All rights reserved. |
| 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #include <boost/test/unit_test.hpp> |
| 7 | #include "ParserFlatbuffersSerializeFixture.hpp" |
| 8 | #include "../Deserializer.hpp" |
| 9 | |
| 10 | #include <string> |
| 11 | #include <iostream> |
| 12 | |
| 13 | BOOST_AUTO_TEST_SUITE(Deserializer) |
| 14 | |
| 15 | struct L2NormalizationFixture : public ParserFlatbuffersSerializeFixture |
| 16 | { |
| 17 | explicit L2NormalizationFixture(const std::string &inputShape, |
| 18 | const std::string &outputShape, |
| 19 | const std::string &dataType, |
| 20 | const std::string &dataLayout, |
| 21 | const std::string epsilon) |
| 22 | { |
| 23 | m_JsonString = R"( |
| 24 | { |
| 25 | inputIds: [0], |
| 26 | outputIds: [2], |
| 27 | layers: [ |
| 28 | { |
| 29 | layer_type: "InputLayer", |
| 30 | layer: { |
| 31 | base: { |
| 32 | layerBindingId: 0, |
| 33 | base: { |
| 34 | index: 0, |
| 35 | layerName: "InputLayer", |
| 36 | layerType: "Input", |
| 37 | inputSlots: [{ |
| 38 | index: 0, |
| 39 | connection: {sourceLayerIndex:0, outputSlotIndex:0 }, |
| 40 | }], |
| 41 | outputSlots: [{ |
| 42 | index: 0, |
| 43 | tensorInfo: { |
| 44 | dimensions: )" + inputShape + R"(, |
| 45 | dataType: ")" + dataType + R"(", |
| 46 | quantizationScale: 0.5, |
| 47 | quantizationOffset: 0 |
| 48 | }, |
| 49 | }] |
| 50 | }, |
| 51 | } |
| 52 | }, |
| 53 | }, |
| 54 | { |
| 55 | layer_type: "L2NormalizationLayer", |
| 56 | layer : { |
| 57 | base: { |
| 58 | index:1, |
| 59 | layerName: "L2NormalizationLayer", |
| 60 | layerType: "L2Normalization", |
| 61 | inputSlots: [{ |
| 62 | index: 0, |
| 63 | connection: {sourceLayerIndex:0, outputSlotIndex:0 }, |
| 64 | }], |
| 65 | outputSlots: [{ |
| 66 | index: 0, |
| 67 | tensorInfo: { |
| 68 | dimensions: )" + outputShape + R"(, |
| 69 | dataType: ")" + dataType + R"(" |
| 70 | }, |
| 71 | }], |
| 72 | }, |
| 73 | descriptor: { |
| 74 | dataLayout: ")" + dataLayout + R"(", |
| 75 | eps: )" + epsilon + R"( |
| 76 | }, |
| 77 | }, |
| 78 | }, |
| 79 | { |
| 80 | layer_type: "OutputLayer", |
| 81 | layer: { |
| 82 | base:{ |
| 83 | layerBindingId: 0, |
| 84 | base: { |
| 85 | index: 2, |
| 86 | layerName: "OutputLayer", |
| 87 | layerType: "Output", |
| 88 | inputSlots: [{ |
| 89 | index: 0, |
| 90 | connection: {sourceLayerIndex:1, outputSlotIndex:0 }, |
| 91 | }], |
| 92 | outputSlots: [ { |
| 93 | index: 0, |
| 94 | tensorInfo: { |
| 95 | dimensions: )" + outputShape + R"(, |
| 96 | dataType: ")" + dataType + R"(" |
| 97 | }, |
| 98 | }], |
| 99 | } |
| 100 | }}, |
| 101 | }] |
| 102 | } |
| 103 | )"; |
| 104 | Setup(); |
| 105 | } |
| 106 | }; |
| 107 | |
| 108 | struct L2NormFixture : L2NormalizationFixture |
| 109 | { |
| 110 | // Using a non standard epsilon value of 1e-8 |
| 111 | L2NormFixture():L2NormalizationFixture("[ 1, 3, 1, 1 ]", |
| 112 | "[ 1, 3, 1, 1 ]", |
| 113 | "Float32", |
| 114 | "NCHW", |
| 115 | "0.00000001"){} |
| 116 | }; |
| 117 | |
| 118 | BOOST_FIXTURE_TEST_CASE(L2NormalizationFloat32, L2NormFixture) |
| 119 | { |
| 120 | // 1 / sqrt(1^2 + 2^2 + 3^2) |
| 121 | const float approxInvL2Norm = 0.267261f; |
| 122 | |
| 123 | RunTest<4, armnn::DataType::Float32>(0, |
| 124 | {{"InputLayer", { 1.0f, 2.0f, 3.0f }}}, |
| 125 | {{"OutputLayer",{ 1.0f * approxInvL2Norm, |
| 126 | 2.0f * approxInvL2Norm, |
| 127 | 3.0f * approxInvL2Norm }}}); |
| 128 | } |
| 129 | |
| 130 | BOOST_FIXTURE_TEST_CASE(L2NormalizationEpsilonLimitFloat32, L2NormFixture) |
| 131 | { |
| 132 | // 1 / sqrt(1e-8) |
| 133 | const float approxInvL2Norm = 10000; |
| 134 | |
| 135 | RunTest<4, armnn::DataType::Float32>(0, |
| 136 | {{"InputLayer", { 0.00000001f, 0.00000002f, 0.00000003f }}}, |
| 137 | {{"OutputLayer",{ 0.00000001f * approxInvL2Norm, |
| 138 | 0.00000002f * approxInvL2Norm, |
| 139 | 0.00000003f * approxInvL2Norm }}}); |
| 140 | } |
| 141 | |
| 142 | BOOST_AUTO_TEST_SUITE_END() |