telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame^] | 1 | // |
| 2 | // Copyright © 2017 Arm Ltd. All rights reserved. |
| 3 | // See LICENSE file in the project root for full license information. |
| 4 | // |
| 5 | #pragma once |
| 6 | |
| 7 | #include <armnn/TensorFwd.hpp> |
| 8 | #include <boost/test/unit_test.hpp> |
| 9 | #include <boost/multi_array.hpp> |
| 10 | #include <vector> |
| 11 | #include <array> |
| 12 | |
| 13 | #include <boost/assert.hpp> |
| 14 | #include <boost/test/tools/floating_point_comparison.hpp> |
| 15 | #include <boost/random/uniform_real_distribution.hpp> |
| 16 | #include <boost/random/mersenne_twister.hpp> |
| 17 | #include <boost/numeric/conversion/cast.hpp> |
| 18 | |
| 19 | #include "armnn/Tensor.hpp" |
| 20 | |
| 21 | #include "backends/test/QuantizeHelper.hpp" |
| 22 | |
| 23 | #include <cmath> |
| 24 | |
| 25 | constexpr float g_FloatCloseToZeroTolerance = 1.0e-7f; |
| 26 | |
| 27 | template<typename T, bool isQuantized = true> |
| 28 | struct SelectiveComparer |
| 29 | { |
| 30 | static bool Compare(T a, T b) |
| 31 | { |
| 32 | return (std::max(a, b) - std::min(a, b)) <= 1; |
| 33 | } |
| 34 | |
| 35 | }; |
| 36 | |
| 37 | template<typename T> |
| 38 | struct SelectiveComparer<T, false> |
| 39 | { |
| 40 | static bool Compare(T a, T b) |
| 41 | { |
| 42 | // if a or b is zero, percent_tolerance does an exact match, so compare to a small, constant tolerance instead |
| 43 | if (a == 0.0f || b == 0.0f) |
| 44 | { |
| 45 | return std::abs(a - b) <= g_FloatCloseToZeroTolerance; |
| 46 | } |
| 47 | // For unquantized floats we use a tolerance of 1%. |
| 48 | boost::math::fpc::close_at_tolerance<float> comparer(boost::math::fpc::percent_tolerance(1.0f)); |
| 49 | return comparer(a, b); |
| 50 | } |
| 51 | }; |
| 52 | |
| 53 | template<typename T> |
| 54 | bool SelectiveCompare(T a, T b) |
| 55 | { |
| 56 | return SelectiveComparer<T, armnn::IsQuantizedType<T>()>::Compare(a, b); |
| 57 | }; |
| 58 | |
| 59 | |
| 60 | |
| 61 | template <typename T, std::size_t n> |
| 62 | boost::test_tools::predicate_result CompareTensors(const boost::multi_array<T, n>& a, |
| 63 | const boost::multi_array<T, n>& b) |
| 64 | { |
| 65 | // check they are same shape |
| 66 | for (unsigned int i=0; i<n; i++) |
| 67 | { |
| 68 | if (a.shape()[i] != b.shape()[i]) |
| 69 | { |
| 70 | boost::test_tools::predicate_result res(false); |
| 71 | res.message() << "Different shapes [" |
| 72 | << a.shape()[i] |
| 73 | << "!=" |
| 74 | << b.shape()[i] |
| 75 | << "]"; |
| 76 | return res; |
| 77 | } |
| 78 | } |
| 79 | |
| 80 | // now compare element-wise |
| 81 | |
| 82 | // fun iteration over n dimensions |
| 83 | std::array<unsigned int, n> indices; |
| 84 | for (unsigned int i = 0; i < n; i++) |
| 85 | { |
| 86 | indices[i] = 0; |
| 87 | } |
| 88 | |
| 89 | std::stringstream errorString; |
| 90 | int numFailedElements = 0; |
| 91 | constexpr int maxReportedDifferences = 3; |
| 92 | |
| 93 | while (true) |
| 94 | { |
| 95 | bool comparison = SelectiveCompare(a(indices), b(indices)); |
| 96 | if (!comparison) |
| 97 | { |
| 98 | ++numFailedElements; |
| 99 | |
| 100 | if (numFailedElements <= maxReportedDifferences) |
| 101 | { |
| 102 | if (numFailedElements >= 2) |
| 103 | { |
| 104 | errorString << ", "; |
| 105 | } |
| 106 | errorString << "["; |
| 107 | for (unsigned int i = 0; i < n; ++i) |
| 108 | { |
| 109 | errorString << indices[i]; |
| 110 | if (i != n - 1) |
| 111 | { |
| 112 | errorString << ","; |
| 113 | } |
| 114 | } |
| 115 | errorString << "]"; |
| 116 | |
| 117 | errorString << " (" << +a(indices) << " != " << +b(indices) << ")"; |
| 118 | } |
| 119 | } |
| 120 | |
| 121 | ++indices[n - 1]; |
| 122 | for (unsigned int i=n-1; i>0; i--) |
| 123 | { |
| 124 | if (indices[i] == a.shape()[i]) |
| 125 | { |
| 126 | indices[i] = 0; |
| 127 | ++indices[i - 1]; |
| 128 | } |
| 129 | } |
| 130 | |
| 131 | if (indices[0] == a.shape()[0]) |
| 132 | { |
| 133 | break; |
| 134 | } |
| 135 | } |
| 136 | |
| 137 | boost::test_tools::predicate_result comparisonResult(true); |
| 138 | if (numFailedElements > 0) |
| 139 | { |
| 140 | comparisonResult = false; |
| 141 | comparisonResult.message() << numFailedElements << " different values at: "; |
| 142 | if (numFailedElements > maxReportedDifferences) |
| 143 | { |
| 144 | errorString << ", ... (and " << (numFailedElements - maxReportedDifferences) << " other differences)"; |
| 145 | } |
| 146 | comparisonResult.message() << errorString.str(); |
| 147 | } |
| 148 | |
| 149 | return comparisonResult; |
| 150 | } |
| 151 | |
| 152 | |
| 153 | // Creates a boost::multi_array with shape defined by the given TensorInfo. |
| 154 | template <typename T, std::size_t n> |
| 155 | boost::multi_array<T, n> MakeTensor(const armnn::TensorInfo& tensorInfo) |
| 156 | { |
| 157 | std::array<unsigned int, n> shape; |
| 158 | |
| 159 | for (unsigned int i = 0; i < n; i++) |
| 160 | { |
| 161 | shape[i] = tensorInfo.GetShape()[i]; |
| 162 | } |
| 163 | |
| 164 | return boost::multi_array<T, n>(shape); |
| 165 | } |
| 166 | |
| 167 | // Creates a boost::multi_array with shape defined by the given TensorInfo and contents defined by the given vector. |
| 168 | template <typename T, std::size_t n> |
| 169 | boost::multi_array<T, n> MakeTensor(const armnn::TensorInfo& tensorInfo, const std::vector<T>& flat) |
| 170 | { |
| 171 | BOOST_ASSERT_MSG(flat.size() == tensorInfo.GetNumElements(), "Wrong number of components supplied to tensor"); |
| 172 | |
| 173 | std::array<unsigned int, n> shape; |
| 174 | |
| 175 | for (unsigned int i = 0; i < n; i++) |
| 176 | { |
| 177 | shape[i] = tensorInfo.GetShape()[i]; |
| 178 | } |
| 179 | |
| 180 | boost::const_multi_array_ref<T, n> arrayRef(&flat[0], shape); |
| 181 | return boost::multi_array<T, n>(arrayRef); |
| 182 | } |
| 183 | |
| 184 | template <typename T, std::size_t n> |
| 185 | boost::multi_array<T, n> MakeRandomTensor(const armnn::TensorInfo& tensorInfo, |
| 186 | unsigned int seed, |
| 187 | float min = -10.0f, |
| 188 | float max = 10.0f) |
| 189 | { |
| 190 | boost::random::mt19937 gen(seed); |
| 191 | boost::random::uniform_real_distribution<float> dist(min, max); |
| 192 | |
| 193 | std::vector<float> init(tensorInfo.GetNumElements()); |
| 194 | for (unsigned int i = 0; i < init.size(); i++) |
| 195 | { |
| 196 | init[i] = dist(gen); |
| 197 | } |
| 198 | float qScale = tensorInfo.GetQuantizationScale(); |
| 199 | int32_t qOffset = tensorInfo.GetQuantizationOffset(); |
| 200 | return MakeTensor<T, n>(tensorInfo, QuantizedVector<T>(qScale, qOffset, init)); |
| 201 | } |