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Diffstat (limited to 'src/armnn/test/TensorHelpers.hpp')
| -rw-r--r-- | src/armnn/test/TensorHelpers.hpp | 236 |
1 files changed, 5 insertions, 231 deletions
diff --git a/src/armnn/test/TensorHelpers.hpp b/src/armnn/test/TensorHelpers.hpp index 95cea58b30..626cda3d1c 100644 --- a/src/armnn/test/TensorHelpers.hpp +++ b/src/armnn/test/TensorHelpers.hpp @@ -1,235 +1,9 @@ // -// Copyright © 2017 Arm Ltd. All rights reserved. +// Copyright © 2017 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // -#pragma once -#include "PredicateResult.hpp" - -#include <armnn/Tensor.hpp> -#include <armnn/utility/Assert.hpp> -#include <armnnUtils/FloatingPointComparison.hpp> - -#include <QuantizeHelper.hpp> - -#include <doctest/doctest.h> - -#include <array> -#include <cmath> -#include <random> -#include <vector> - -constexpr float g_FloatCloseToZeroTolerance = 1.0e-6f; - -template<typename T, bool isQuantized = true> -struct SelectiveComparer -{ - static bool Compare(T a, T b) - { - return (std::max(a, b) - std::min(a, b)) <= 1; - } - -}; - -template<typename T> -struct SelectiveComparer<T, false> -{ - static bool Compare(T a, T b) - { - // If a or b is zero, percent_tolerance does an exact match, so compare to a small, constant tolerance instead. - if (a == 0.0f || b == 0.0f) - { - return std::abs(a - b) <= g_FloatCloseToZeroTolerance; - } - - if (std::isinf(a) && a == b) - { - return true; - } - - if (std::isnan(a) && std::isnan(b)) - { - return true; - } - - // For unquantized floats we use a tolerance of 1%. - return armnnUtils::within_percentage_tolerance(a, b); - } -}; - -template<typename T> -bool SelectiveCompare(T a, T b) -{ - return SelectiveComparer<T, armnn::IsQuantizedType<T>()>::Compare(a, b); -}; - -template<typename T> -bool SelectiveCompareBoolean(T a, T b) -{ - return (((a == 0) && (b == 0)) || ((a != 0) && (b != 0))); -}; - -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 < numberOfDimensions; ++i) - { - if (actualShape[i] != expectedShape[i]) - { - armnn::PredicateResult res(false); - res.Message() << "Different shapes [" - << actualShape[i] - << "!=" - << expectedShape[i] - << "]"; - return res; - } - } - } - - // Fun iteration over n dimensions. - std::vector<unsigned int> indices; - for (unsigned int i = 0; i < numberOfDimensions; i++) - { - 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(actualData[index], expectedData[index]); - } - else - { - comparison = SelectiveCompare(actualData[index], expectedData[index]); - } - - if (!comparison) - { - ++numFailedElements; - - if (numFailedElements <= maxReportedDifferences) - { - if (numFailedElements >= 2) - { - errorString << ", "; - } - errorString << "["; - for (unsigned int i = 0; i < numberOfDimensions; ++i) - { - errorString << indices[i]; - if (i != numberOfDimensions - 1) - { - errorString << ","; - } - } - errorString << "]"; - - errorString << " (" << +actualData[index] << " != " << +expectedData[index] << ")"; - } - } - - ++indices[numberOfDimensions - 1]; - for (unsigned int i=numberOfDimensions-1; i>0; i--) - { - if (indices[i] == actualShape[i]) - { - indices[i] = 0; - ++indices[i - 1]; - } - } - if (indices[0] == actualShape[0]) - { - break; - } - - index++; - } - - armnn::PredicateResult comparisonResult(true); - if (numFailedElements > 0) - { - comparisonResult.SetResult(false); - comparisonResult.Message() << numFailedElements << " different values at: "; - if (numFailedElements > maxReportedDifferences) - { - errorString << ", ... (and " << (numFailedElements - maxReportedDifferences) << " other differences)"; - } - comparisonResult.Message() << errorString.str(); - } - - return comparisonResult; -} - -template <typename T> -std::vector<T> MakeRandomTensor(const armnn::TensorInfo& tensorInfo, - unsigned int seed, - float min = -10.0f, - float max = 10.0f) -{ - 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++) - { - init[i] = dist(gen); - } - - const float qScale = tensorInfo.GetQuantizationScale(); - const int32_t qOffset = tensorInfo.GetQuantizationOffset(); - - return armnnUtils::QuantizedVector<T>(init, qScale, qOffset); -} +// This file is deprecated and will be removed soon. +// Please use the new header in armnnTestUtils instead. +// This will use the new armnnTestUtils header. +#include "../../armnnTestUtils/TensorHelpers.hpp"
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