diff options
Diffstat (limited to 'src/armnn/test/TensorHelpers.hpp')
| -rw-r--r-- | src/armnn/test/TensorHelpers.hpp | 159 |
1 files changed, 72 insertions, 87 deletions
diff --git a/src/armnn/test/TensorHelpers.hpp b/src/armnn/test/TensorHelpers.hpp index ceb6d0f9d7..b8788e7826 100644 --- a/src/armnn/test/TensorHelpers.hpp +++ b/src/armnn/test/TensorHelpers.hpp @@ -5,19 +5,18 @@ #pragma once #include "PredicateResult.hpp" + #include <armnn/Tensor.hpp> #include <armnn/utility/Assert.hpp> #include <armnnUtils/FloatingPointComparison.hpp> #include <QuantizeHelper.hpp> -#include <boost/multi_array.hpp> -#include <boost/random/uniform_real_distribution.hpp> -#include <boost/random/mersenne_twister.hpp> #include <boost/test/unit_test.hpp> #include <array> #include <cmath> +#include <random> #include <vector> constexpr float g_FloatCloseToZeroTolerance = 1.0e-6f; @@ -70,56 +69,91 @@ bool SelectiveCompareBoolean(T a, T b) return (((a == 0) && (b == 0)) || ((a != 0) && (b != 0))); }; -template <typename T, std::size_t n> -armnn::PredicateResult CompareTensors(const boost::multi_array<T, n>& a, - const boost::multi_array<T, n>& b, - bool compareBoolean = false, - bool isDynamic = false) +template <typename T> +armnn::PredicateResult CompareTensors(const std::vector<T>& actualData, + const std::vector<T>& expectedData, + const armnn::TensorShape& actualShape, + const armnn::TensorShape& expectedShape, + bool compareBoolean = false, + bool isDynamic = false) { + if (actualData.size() != expectedData.size()) + { + armnn::PredicateResult res(false); + res.Message() << "Different data size [" + << actualData.size() + << "!=" + << expectedData.size() + << "]"; + return res; + } + + if (actualShape.GetNumDimensions() != expectedShape.GetNumDimensions()) + { + armnn::PredicateResult res(false); + res.Message() << "Different number of dimensions [" + << actualShape.GetNumDimensions() + << "!=" + << expectedShape.GetNumDimensions() + << "]"; + return res; + } + + if (actualShape.GetNumElements() != expectedShape.GetNumElements()) + { + armnn::PredicateResult res(false); + res.Message() << "Different number of elements [" + << actualShape.GetNumElements() + << "!=" + << expectedShape.GetNumElements() + << "]"; + return res; + } + + unsigned int numberOfDimensions = actualShape.GetNumDimensions(); + if (!isDynamic) { // Checks they are same shape. - for (unsigned int i = 0; - i < n; - i++) + for (unsigned int i = 0; i < numberOfDimensions; ++i) { - if (a.shape()[i] != b.shape()[i]) + if (actualShape[i] != expectedShape[i]) { armnn::PredicateResult res(false); res.Message() << "Different shapes [" - << a.shape()[i] + << actualShape[i] << "!=" - << b.shape()[i] + << expectedShape[i] << "]"; return res; } } } - // Now compares element-wise. - // Fun iteration over n dimensions. - std::array<unsigned int, n> indices; - for (unsigned int i = 0; i < n; i++) + std::vector<unsigned int> indices; + for (unsigned int i = 0; i < numberOfDimensions; i++) { - indices[i] = 0; + indices.emplace_back(0); } std::stringstream errorString; int numFailedElements = 0; constexpr int maxReportedDifferences = 3; + unsigned int index = 0; + // Compare data element by element. while (true) { bool comparison; // As true for uint8_t is non-zero (1-255) we must have a dedicated compare for Booleans. if(compareBoolean) { - comparison = SelectiveCompareBoolean(a(indices), b(indices)); + comparison = SelectiveCompareBoolean(actualData[index], expectedData[index]); } else { - comparison = SelectiveCompare(a(indices), b(indices)); + comparison = SelectiveCompare(actualData[index], expectedData[index]); } if (!comparison) @@ -133,34 +167,35 @@ armnn::PredicateResult CompareTensors(const boost::multi_array<T, n>& a, errorString << ", "; } errorString << "["; - for (unsigned int i = 0; i < n; ++i) + for (unsigned int i = 0; i < numberOfDimensions; ++i) { errorString << indices[i]; - if (i != n - 1) + if (i != numberOfDimensions - 1) { errorString << ","; } } errorString << "]"; - errorString << " (" << +a(indices) << " != " << +b(indices) << ")"; + errorString << " (" << +actualData[index] << " != " << +expectedData[index] << ")"; } } - ++indices[n - 1]; - for (unsigned int i=n-1; i>0; i--) + ++indices[numberOfDimensions - 1]; + for (unsigned int i=numberOfDimensions-1; i>0; i--) { - if (indices[i] == a.shape()[i]) + if (indices[i] == actualShape[i]) { indices[i] = 0; ++indices[i - 1]; } } - - if (indices[0] == a.shape()[0]) + if (indices[0] == actualShape[0]) { break; } + + index++; } armnn::PredicateResult comparisonResult(true); @@ -178,64 +213,14 @@ armnn::PredicateResult CompareTensors(const boost::multi_array<T, n>& a, return comparisonResult; } - -// Creates a boost::multi_array with the shape defined by the given TensorInfo. -template <typename T, std::size_t n> -boost::multi_array<T, n> MakeTensor(const armnn::TensorInfo& tensorInfo) -{ - std::array<unsigned int, n> shape; - - for (unsigned int i = 0; i < n; i++) - { - shape[i] = tensorInfo.GetShape()[i]; - } - - return boost::multi_array<T, n>(shape); -} - -// Creates a boost::multi_array with the shape defined by the given TensorInfo and contents defined by the given vector. -template <typename T, std::size_t n> -boost::multi_array<T, n> MakeTensor( - const armnn::TensorInfo& tensorInfo, const std::vector<T>& flat, bool isDynamic = false) -{ - if (!isDynamic) - { - ARMNN_ASSERT_MSG(flat.size() == tensorInfo.GetNumElements(), "Wrong number of components supplied to tensor"); - } - - std::array<unsigned int, n> shape; - - // NOTE: tensorInfo.GetNumDimensions() might be different from n - const unsigned int returnDimensions = static_cast<unsigned int>(n); - const unsigned int actualDimensions = tensorInfo.GetNumDimensions(); - - const unsigned int paddedDimensions = - returnDimensions > actualDimensions ? returnDimensions - actualDimensions : 0u; - - for (unsigned int i = 0u; i < returnDimensions; i++) - { - if (i < paddedDimensions) - { - shape[i] = 1u; - } - else - { - shape[i] = tensorInfo.GetShape()[i - paddedDimensions]; - } - } - - boost::const_multi_array_ref<T, n> arrayRef(&flat[0], shape); - return boost::multi_array<T, n>(arrayRef); -} - -template <typename T, std::size_t n> -boost::multi_array<T, n> MakeRandomTensor(const armnn::TensorInfo& tensorInfo, - unsigned int seed, - float min = -10.0f, - float max = 10.0f) +template <typename T> +std::vector<T> MakeRandomTensor(const armnn::TensorInfo& tensorInfo, + unsigned int seed, + float min = -10.0f, + float max = 10.0f) { - boost::random::mt19937 gen(seed); - boost::random::uniform_real_distribution<float> dist(min, max); + std::mt19937 gen(seed); + std::uniform_real_distribution<float> dist(min, max); std::vector<float> init(tensorInfo.GetNumElements()); for (unsigned int i = 0; i < init.size(); i++) @@ -246,5 +231,5 @@ boost::multi_array<T, n> MakeRandomTensor(const armnn::TensorInfo& tensorInfo, const float qScale = tensorInfo.GetQuantizationScale(); const int32_t qOffset = tensorInfo.GetQuantizationOffset(); - return MakeTensor<T, n>(tensorInfo, armnnUtils::QuantizedVector<T>(init, qScale, qOffset)); + return armnnUtils::QuantizedVector<T>(init, qScale, qOffset); } |