tests/validation/Validation.h - platform/external/ComputeLibrary - Git at Google

 /*
  * Copyright (c) 2017 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
  * Permission is hereby granted, free of charge, to any person obtaining a copy
  * of this software and associated documentation files (the "Software"), to
  * deal in the Software without restriction, including without limitation the
  * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
  * sell copies of the Software, and to permit persons to whom the Software is
  * furnished to do so, subject to the following conditions:
  *
  * The above copyright notice and this permission notice shall be included in all
  * copies or substantial portions of the Software.
  *
  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
 #ifndef __ARM_COMPUTE_TEST_VALIDATION_H__
 #define __ARM_COMPUTE_TEST_VALIDATION_H__

 #include "arm_compute/core/FixedPoint.h"
 #include "arm_compute/core/IArray.h"
 #include "arm_compute/core/Types.h"
 #include "tests/IAccessor.h"
 #include "tests/SimpleTensor.h"
 #include "tests/Types.h"
 #include "tests/Utils.h"
 #include "tests/framework/Asserts.h"
 #include "tests/framework/Exceptions.h"
 #include "utils/TypePrinter.h"

 #include <iomanip>
 #include <ios>
 #include <vector>

 namespace arm_compute
 {
 namespace test
 {
 namespace validation
 {
 /** Class reprensenting an absolute tolerance value. */
 template <typename T>
 class AbsoluteTolerance
 {
 public:
     /** Underlying type. */
     using value_type = T;

     /* Default constructor.
      *
      * Initialises the tolerance to 0.
      */
     AbsoluteTolerance() = default;

     /** Constructor.
      *
      * @param[in] value Absolute tolerance value.
      */
     explicit constexpr AbsoluteTolerance(T value)
         : _value{ value }
     {
     }

     /** Implicit conversion to the underlying type. */
     constexpr operator T() const
     {
         return _value;
     }

 private:
     T _value{ std::numeric_limits<T>::epsilon() };
 };

 /** Class reprensenting a relative tolerance value. */
 template <typename T>
 class RelativeTolerance
 {
 public:
     /** Underlying type. */
     using value_type = T;

     /* Default constructor.
      *
      * Initialises the tolerance to 0.
      */
     RelativeTolerance() = default;

     /** Constructor.
      *
      * @param[in] value Relative tolerance value.
      */
     explicit constexpr RelativeTolerance(value_type value)
         : _value{ value }
     {
     }

     /** Implicit conversion to the underlying type. */
     constexpr operator value_type() const
     {
         return _value;
     }

 private:
     value_type _value{ std::numeric_limits<T>::epsilon() };
 };

 /** Print AbsoluteTolerance type. */
 template <typename T>
 inline ::std::ostream &operator<<(::std::ostream &os, const AbsoluteTolerance<T> &tolerance)
 {
     os << static_cast<typename AbsoluteTolerance<T>::value_type>(tolerance);

     return os;
 }

 /** Print RelativeTolerance type. */
 template <typename T>
 inline ::std::ostream &operator<<(::std::ostream &os, const RelativeTolerance<T> &tolerance)
 {
     os << static_cast<typename RelativeTolerance<T>::value_type>(tolerance);

     return os;
 }

 template <typename T>
 bool compare_dimensions(const Dimensions<T> &dimensions1, const Dimensions<T> &dimensions2)
 {
     if(dimensions1.num_dimensions() != dimensions2.num_dimensions())
     {
         return false;
     }

     for(unsigned int i = 0; i < dimensions1.num_dimensions(); ++i)
     {
         if(dimensions1[i] != dimensions2[i])
         {
             return false;
         }
     }

     return true;
 }

 /** Validate valid regions.
  *
  * - Dimensionality has to be the same.
  * - Anchors have to match.
  * - Shapes have to match.
  */
 void validate(const arm_compute::ValidRegion &region, const arm_compute::ValidRegion &reference);

 /** Validate padding.
  *
  * Padding on all sides has to be the same.
  */
 void validate(const arm_compute::PaddingSize &padding, const arm_compute::PaddingSize &reference);

 /** Validate tensors.
  *
  * - Dimensionality has to be the same.
  * - All values have to match.
  *
  * @note: wrap_range allows cases where reference tensor rounds up to the wrapping point, causing it to wrap around to
  * zero while the test tensor stays at wrapping point to pass. This may permit true erroneous cases (difference between
  * reference tensor and test tensor is multiple of wrap_range), but such errors would be detected by
  * other test cases.
  */
 template <typename T, typename U = AbsoluteTolerance<T>>
 void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, U tolerance_value = U(), float tolerance_number = 0.f);

 /** Validate tensors with valid region.
  *
  * - Dimensionality has to be the same.
  * - All values have to match.
  *
  * @note: wrap_range allows cases where reference tensor rounds up to the wrapping point, causing it to wrap around to
  * zero while the test tensor stays at wrapping point to pass. This may permit true erroneous cases (difference between
  * reference tensor and test tensor is multiple of wrap_range), but such errors would be detected by
  * other test cases.
  */
 template <typename T, typename U = AbsoluteTolerance<T>>
 void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, const ValidRegion &valid_region, U tolerance_value = U(), float tolerance_number = 0.f);

 /** Validate tensors with valid mask.
  *
  * - Dimensionality has to be the same.
  * - All values have to match.
  *
  * @note: wrap_range allows cases where reference tensor rounds up to the wrapping point, causing it to wrap around to
  * zero while the test tensor stays at wrapping point to pass. This may permit true erroneous cases (difference between
  * reference tensor and test tensor is multiple of wrap_range), but such errors would be detected by
  * other test cases.
  */
 template <typename T, typename U = AbsoluteTolerance<T>>
 void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, const SimpleTensor<T> &valid_mask, U tolerance_value = U(), float tolerance_number = 0.f);

 /** Validate tensors against constant value.
  *
  * - All values have to match.
  */
 void validate(const IAccessor &tensor, const void *reference_value);

 /** Validate border against a constant value.
  *
  * - All border values have to match the specified value if mode is CONSTANT.
  * - All border values have to be replicated if mode is REPLICATE.
  * - Nothing is validated for mode UNDEFINED.
  */
 void validate(const IAccessor &tensor, BorderSize border_size, const BorderMode &border_mode, const void *border_value);

 /** Validate classified labels against expected ones.
  *
  * - All values should match
  */
 void validate(std::vector<unsigned int> classified_labels, std::vector<unsigned int> expected_labels);

 /** Validate float value.
  *
  * - All values should match
  */
 template <typename T, typename U = AbsoluteTolerance<T>>
 bool validate(T target, T reference, U tolerance = AbsoluteTolerance<T>());

 /** Validate key points. */
 template <typename T, typename U, typename V = AbsoluteTolerance<float>>
 void validate_keypoints(T target_first, T target_last, U reference_first, U reference_last, V tolerance = AbsoluteTolerance<float>());

 template <typename T>
 struct compare_base
 {
     compare_base(typename T::value_type target, typename T::value_type reference, T tolerance = T(0))
         : _target{ target }, _reference{ reference }, _tolerance{ tolerance }
     {
     }

     typename T::value_type _target{};
     typename T::value_type _reference{};
     T                      _tolerance{};
 };

 template <typename T>
 struct compare;

 template <typename U>
 struct compare<AbsoluteTolerance<U>> : public compare_base<AbsoluteTolerance<U>>
 {
     using compare_base<AbsoluteTolerance<U>>::compare_base;

     operator bool() const
     {
         if(!std::isfinite(this->_target) || !std::isfinite(this->_reference))
         {
             return false;
         }
         else if(this->_target == this->_reference)
         {
             return true;
         }

         using comparison_type = typename std::conditional<std::is_integral<U>::value, int64_t, U>::type;

         const comparison_type abs_difference(std::abs(static_cast<comparison_type>(this->_target) - static_cast<comparison_type>(this->_reference)));

         return abs_difference <= static_cast<comparison_type>(this->_tolerance);
     }
 };

 template <typename U>
 struct compare<RelativeTolerance<U>> : public compare_base<RelativeTolerance<U>>
 {
     using compare_base<RelativeTolerance<U>>::compare_base;

     operator bool() const
     {
         if(!std::isfinite(this->_target) || !std::isfinite(this->_reference))
         {
             return false;
         }
         else if(this->_target == this->_reference)
         {
             return true;
         }

         const U epsilon = (std::is_same<half, typename std::remove_cv<U>::type>::value || (this->_reference == 0)) ? static_cast<U>(0.01) : static_cast<U>(1e-05);

         if(std::abs(static_cast<double>(this->_reference) - static_cast<double>(this->_target)) <= epsilon)
         {
             return true;
         }
         else
         {
             if(static_cast<double>(this->_reference) == 0.0f) // We have checked whether _reference and _target is closing. If _reference is 0 but not closed to _target, it should return false
             {
                 return false;
             }

             const double relative_change = std::abs(static_cast<double>(this->_target) - static_cast<double>(this->_reference)) / this->_reference;

             return relative_change <= static_cast<U>(this->_tolerance);
         }
     }
 };

 template <typename T, typename U>
 void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, U tolerance_value, float tolerance_number)
 {
     // Validate with valid region covering the entire shape
     validate(tensor, reference, shape_to_valid_region(tensor.shape()), tolerance_value, tolerance_number);
 }

 template <typename T, typename U>
 void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, const ValidRegion &valid_region, U tolerance_value, float tolerance_number)
 {
     int64_t num_mismatches = 0;
     int64_t num_elements   = 0;

     ARM_COMPUTE_EXPECT_EQUAL(tensor.element_size(), reference.element_size(), framework::LogLevel::ERRORS);
     ARM_COMPUTE_EXPECT_EQUAL(tensor.data_type(), reference.data_type(), framework::LogLevel::ERRORS);

     if(reference.format() != Format::UNKNOWN)
     {
         ARM_COMPUTE_EXPECT_EQUAL(tensor.format(), reference.format(), framework::LogLevel::ERRORS);
     }

     ARM_COMPUTE_EXPECT_EQUAL(tensor.num_channels(), reference.num_channels(), framework::LogLevel::ERRORS);
     ARM_COMPUTE_EXPECT(compare_dimensions(tensor.shape(), reference.shape()), framework::LogLevel::ERRORS);

     const int min_elements = std::min(tensor.num_elements(), reference.num_elements());
     const int min_channels = std::min(tensor.num_channels(), reference.num_channels());

     // Iterate over all elements within valid region, e.g. U8, S16, RGB888, ...
     for(int element_idx = 0; element_idx < min_elements; ++element_idx)
     {
         const Coordinates id = index2coord(reference.shape(), element_idx);

         if(is_in_valid_region(valid_region, id))
         {
             // Iterate over all channels within one element
             for(int c = 0; c < min_channels; ++c)
             {
                 const T &target_value    = reinterpret_cast<const T *>(tensor(id))[c];
                 const T &reference_value = reinterpret_cast<const T *>(reference(id))[c];

                 if(!compare<U>(target_value, reference_value, tolerance_value))
                 {
                     ARM_COMPUTE_TEST_INFO("id = " << id);
                     ARM_COMPUTE_TEST_INFO("channel = " << c);
                     ARM_COMPUTE_TEST_INFO("target = " << std::setprecision(5) << framework::make_printable(target_value));
                     ARM_COMPUTE_TEST_INFO("reference = " << std::setprecision(5) << framework::make_printable(reference_value));
                     ARM_COMPUTE_TEST_INFO("tolerance = " << std::setprecision(5) << framework::make_printable(static_cast<typename U::value_type>(tolerance_value)));
                     framework::ARM_COMPUTE_PRINT_INFO();

                     ++num_mismatches;
                 }

                 ++num_elements;
             }
         }
     }

     if(num_elements > 0)
     {
         const int64_t absolute_tolerance_number = tolerance_number * num_elements;
         const float   percent_mismatches        = static_cast<float>(num_mismatches) / num_elements * 100.f;

         ARM_COMPUTE_TEST_INFO(num_mismatches << " values (" << std::fixed << std::setprecision(2) << percent_mismatches
                               << "%) mismatched (maximum tolerated " << std::setprecision(2) << tolerance_number << "%)");
         ARM_COMPUTE_EXPECT(num_mismatches <= absolute_tolerance_number, framework::LogLevel::ERRORS);
     }
 }

 /** Check which keypoints from [first1, last1) are missing in [first2, last2) */
 template <typename T, typename U, typename V>
 std::pair<int64_t, int64_t> compare_keypoints(T first1, T last1, U first2, U last2, V tolerance)
 {
     int64_t num_missing    = 0;
     int64_t num_mismatches = 0;

     while(first1 != last1)
     {
         const auto point = std::find_if(first2, last2, [&](KeyPoint point)
         {
             return point.x == first1->x && point.y == first1->y;
         });

         if(point == last2)
         {
             ++num_missing;
             ARM_COMPUTE_TEST_INFO("keypoint1 = " << *first1)
             ARM_COMPUTE_EXPECT_FAIL("Key point not found", framework::LogLevel::DEBUG);
         }
         else if(!validate(point->tracking_status, first1->tracking_status) || !validate(point->strength, first1->strength, tolerance) || !validate(point->scale, first1->scale)
                 || !validate(point->orientation, first1->orientation) || !validate(point->error, first1->error))
         {
             ++num_mismatches;
             ARM_COMPUTE_TEST_INFO("keypoint1 = " << *first1)
             ARM_COMPUTE_TEST_INFO("keypoint2 = " << *point)
             ARM_COMPUTE_EXPECT_FAIL("Mismatching keypoint", framework::LogLevel::DEBUG);
         }

         ++first1;
     }

     return std::make_pair(num_missing, num_mismatches);
 }

 template <typename T, typename U, typename V>
 void validate_keypoints(T target_first, T target_last, U reference_first, U reference_last, V tolerance)
 {
     const int64_t num_elements_target    = std::distance(target_first, target_last);
     const int64_t num_elements_reference = std::distance(reference_first, reference_last);

     ARM_COMPUTE_EXPECT_EQUAL(num_elements_target, num_elements_reference, framework::LogLevel::ERRORS);

     int64_t num_missing    = 0;
     int64_t num_mismatches = 0;

     if(num_elements_reference > 0)
     {
         std::tie(num_missing, num_mismatches) = compare_keypoints(reference_first, reference_last, target_first, target_last, tolerance);

         const float percent_missing    = static_cast<float>(num_missing) / num_elements_reference * 100.f;
         const float percent_mismatches = static_cast<float>(num_mismatches) / num_elements_reference * 100.f;

         ARM_COMPUTE_TEST_INFO(num_missing << " keypoints (" << std::fixed << std::setprecision(2) << percent_missing << "%) are missing in target");
         ARM_COMPUTE_EXPECT_EQUAL(num_missing, 0, framework::LogLevel::ERRORS);

         ARM_COMPUTE_TEST_INFO(num_mismatches << " keypoints (" << std::fixed << std::setprecision(2) << percent_mismatches << "%) mismatched");
         ARM_COMPUTE_EXPECT_EQUAL(num_mismatches, 0, framework::LogLevel::ERRORS);
     }

     if(num_elements_target > 0)
     {
         std::tie(num_missing, num_mismatches) = compare_keypoints(target_first, target_last, reference_first, reference_last, tolerance);

         const float percent_missing = static_cast<float>(num_missing) / num_elements_target * 100.f;

         ARM_COMPUTE_TEST_INFO(num_missing << " keypoints (" << std::fixed << std::setprecision(2) << percent_missing << "%) are not part of target");
         ARM_COMPUTE_EXPECT_EQUAL(num_missing, 0, framework::LogLevel::ERRORS);
     }
 }

 template <typename T, typename U>
 void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, const SimpleTensor<T> &valid_mask, U tolerance_value, float tolerance_number)
 {
     int64_t num_mismatches = 0;
     int64_t num_elements   = 0;

     ARM_COMPUTE_EXPECT_EQUAL(tensor.element_size(), reference.element_size(), framework::LogLevel::ERRORS);
     ARM_COMPUTE_EXPECT_EQUAL(tensor.data_type(), reference.data_type(), framework::LogLevel::ERRORS);

     if(reference.format() != Format::UNKNOWN)
     {
         ARM_COMPUTE_EXPECT_EQUAL(tensor.format(), reference.format(), framework::LogLevel::ERRORS);
     }

     ARM_COMPUTE_EXPECT_EQUAL(tensor.num_channels(), reference.num_channels(), framework::LogLevel::ERRORS);
     ARM_COMPUTE_EXPECT(compare_dimensions(tensor.shape(), reference.shape()), framework::LogLevel::ERRORS);

     const int min_elements = std::min(tensor.num_elements(), reference.num_elements());
     const int min_channels = std::min(tensor.num_channels(), reference.num_channels());

     // Iterate over all elements within valid region, e.g. U8, S16, RGB888, ...
     for(int element_idx = 0; element_idx < min_elements; ++element_idx)
     {
         const Coordinates id = index2coord(reference.shape(), element_idx);

         if(valid_mask[element_idx] == 1)
         {
             // Iterate over all channels within one element
             for(int c = 0; c < min_channels; ++c)
             {
                 const T &target_value    = reinterpret_cast<const T *>(tensor(id))[c];
                 const T &reference_value = reinterpret_cast<const T *>(reference(id))[c];

                 if(!compare<U>(target_value, reference_value, tolerance_value))
                 {
                     ARM_COMPUTE_TEST_INFO("id = " << id);
                     ARM_COMPUTE_TEST_INFO("channel = " << c);
                     ARM_COMPUTE_TEST_INFO("target = " << std::setprecision(5) << framework::make_printable(target_value));
                     ARM_COMPUTE_TEST_INFO("reference = " << std::setprecision(5) << framework::make_printable(reference_value));
                     ARM_COMPUTE_TEST_INFO("tolerance = " << std::setprecision(5) << framework::make_printable(static_cast<typename U::value_type>(tolerance_value)));
                     framework::ARM_COMPUTE_PRINT_INFO();

                     ++num_mismatches;
                 }

                 ++num_elements;
             }
         }
         else
         {
             ++num_elements;
         }
     }

     if(num_elements > 0)
     {
         const int64_t absolute_tolerance_number = tolerance_number * num_elements;
         const float   percent_mismatches        = static_cast<float>(num_mismatches) / num_elements * 100.f;

         ARM_COMPUTE_TEST_INFO(num_mismatches << " values (" << std::fixed << std::setprecision(2) << percent_mismatches
                               << "%) mismatched (maximum tolerated " << std::setprecision(2) << tolerance_number << "%)");
         ARM_COMPUTE_EXPECT(num_mismatches <= absolute_tolerance_number, framework::LogLevel::ERRORS);
     }
 }

 template <typename T, typename U>
 bool validate(T target, T reference, U tolerance)
 {
     ARM_COMPUTE_TEST_INFO("reference = " << std::setprecision(5) << framework::make_printable(reference));
     ARM_COMPUTE_TEST_INFO("target = " << std::setprecision(5) << framework::make_printable(target));
     ARM_COMPUTE_TEST_INFO("tolerance = " << std::setprecision(5) << framework::make_printable(static_cast<typename U::value_type>(tolerance)));

     const bool equal = compare<U>(target, reference, tolerance);

     ARM_COMPUTE_EXPECT(equal, framework::LogLevel::ERRORS);

     return equal;
 }

 template <typename T, typename U>
 void validate_min_max_loc(const MinMaxLocationValues<T> &target, const MinMaxLocationValues<U> &reference)
 {
     ARM_COMPUTE_EXPECT_EQUAL(target.min, reference.min, framework::LogLevel::ERRORS);
     ARM_COMPUTE_EXPECT_EQUAL(target.max, reference.max, framework::LogLevel::ERRORS);

     ARM_COMPUTE_EXPECT_EQUAL(target.min_loc.size(), reference.min_loc.size(), framework::LogLevel::ERRORS);
     ARM_COMPUTE_EXPECT_EQUAL(target.max_loc.size(), reference.max_loc.size(), framework::LogLevel::ERRORS);

     for(uint32_t i = 0; i < target.min_loc.size(); ++i)
     {
         const auto same_coords = std::find_if(reference.min_loc.begin(), reference.min_loc.end(), [&target, i](Coordinates2D coord)
         {
             return coord.x == target.min_loc.at(i).x && coord.y == target.min_loc.at(i).y;
         });

         ARM_COMPUTE_EXPECT(same_coords != reference.min_loc.end(), framework::LogLevel::ERRORS);
     }

     for(uint32_t i = 0; i < target.max_loc.size(); ++i)
     {
         const auto same_coords = std::find_if(reference.max_loc.begin(), reference.max_loc.end(), [&target, i](Coordinates2D coord)
         {
             return coord.x == target.max_loc.at(i).x && coord.y == target.max_loc.at(i).y;
         });

         ARM_COMPUTE_EXPECT(same_coords != reference.max_loc.end(), framework::LogLevel::ERRORS);
     }
 }

 } // namespace validation
 } // namespace test
 } // namespace arm_compute
 #endif /* __ARM_COMPUTE_TEST_REFERENCE_VALIDATION_H__ */
	/*
	* Copyright (c) 2017 ARM Limited.
	*
	* SPDX-License-Identifier: MIT
	*
	* Permission is hereby granted, free of charge, to any person obtaining a copy
	* of this software and associated documentation files (the "Software"), to
	* deal in the Software without restriction, including without limitation the
	* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
	* sell copies of the Software, and to permit persons to whom the Software is
	* furnished to do so, subject to the following conditions:
	*
	* The above copyright notice and this permission notice shall be included in all
	* copies or substantial portions of the Software.
	*
	* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
	* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
	* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
	* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
	* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
	* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
	* SOFTWARE.
	*/
	#ifndef __ARM_COMPUTE_TEST_VALIDATION_H__
	#define __ARM_COMPUTE_TEST_VALIDATION_H__

	#include "arm_compute/core/FixedPoint.h"
	#include "arm_compute/core/IArray.h"
	#include "arm_compute/core/Types.h"
	#include "tests/IAccessor.h"
	#include "tests/SimpleTensor.h"
	#include "tests/Types.h"
	#include "tests/Utils.h"
	#include "tests/framework/Asserts.h"
	#include "tests/framework/Exceptions.h"
	#include "utils/TypePrinter.h"

	#include <iomanip>
	#include <ios>
	#include <vector>

	namespace arm_compute
	{
	namespace test
	{
	namespace validation
	{
	/** Class reprensenting an absolute tolerance value. */
	template <typename T>
	class AbsoluteTolerance
	{
	public:
	/** Underlying type. */
	using value_type = T;

	/* Default constructor.
	*
	* Initialises the tolerance to 0.
	*/
	AbsoluteTolerance() = default;

	/** Constructor.
	*
	* @param[in] value Absolute tolerance value.
	*/
	explicit constexpr AbsoluteTolerance(T value)
	: _value{ value }
	{
	}

	/** Implicit conversion to the underlying type. */
	constexpr operator T() const
	{
	return _value;
	}

	private:
	T _value{ std::numeric_limits<T>::epsilon() };
	};

	/** Class reprensenting a relative tolerance value. */
	template <typename T>
	class RelativeTolerance
	{
	public:
	/** Underlying type. */
	using value_type = T;

	/* Default constructor.
	*
	* Initialises the tolerance to 0.
	*/
	RelativeTolerance() = default;

	/** Constructor.
	*
	* @param[in] value Relative tolerance value.
	*/
	explicit constexpr RelativeTolerance(value_type value)
	: _value{ value }
	{
	}

	/** Implicit conversion to the underlying type. */
	constexpr operator value_type() const
	{
	return _value;
	}

	private:
	value_type _value{ std::numeric_limits<T>::epsilon() };
	};

	/** Print AbsoluteTolerance type. */
	template <typename T>
	inline ::std::ostream &operator<<(::std::ostream &os, const AbsoluteTolerance<T> &tolerance)
	{
	os << static_cast<typename AbsoluteTolerance<T>::value_type>(tolerance);

	return os;
	}

	/** Print RelativeTolerance type. */
	template <typename T>
	inline ::std::ostream &operator<<(::std::ostream &os, const RelativeTolerance<T> &tolerance)
	{
	os << static_cast<typename RelativeTolerance<T>::value_type>(tolerance);

	return os;
	}

	template <typename T>
	bool compare_dimensions(const Dimensions<T> &dimensions1, const Dimensions<T> &dimensions2)
	{
	if(dimensions1.num_dimensions() != dimensions2.num_dimensions())
	{
	return false;
	}

	for(unsigned int i = 0; i < dimensions1.num_dimensions(); ++i)
	{
	if(dimensions1[i] != dimensions2[i])
	{
	return false;
	}
	}

	return true;
	}

	/** Validate valid regions.
	*
	* - Dimensionality has to be the same.
	* - Anchors have to match.
	* - Shapes have to match.
	*/
	void validate(const arm_compute::ValidRegion &region, const arm_compute::ValidRegion &reference);

	/** Validate padding.
	*
	* Padding on all sides has to be the same.
	*/
	void validate(const arm_compute::PaddingSize &padding, const arm_compute::PaddingSize &reference);

	/** Validate tensors.
	*
	* - Dimensionality has to be the same.
	* - All values have to match.
	*
	* @note: wrap_range allows cases where reference tensor rounds up to the wrapping point, causing it to wrap around to
	* zero while the test tensor stays at wrapping point to pass. This may permit true erroneous cases (difference between
	* reference tensor and test tensor is multiple of wrap_range), but such errors would be detected by
	* other test cases.
	*/
	template <typename T, typename U = AbsoluteTolerance<T>>
	void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, U tolerance_value = U(), float tolerance_number = 0.f);

	/** Validate tensors with valid region.
	*
	* - Dimensionality has to be the same.
	* - All values have to match.
	*
	* @note: wrap_range allows cases where reference tensor rounds up to the wrapping point, causing it to wrap around to
	* zero while the test tensor stays at wrapping point to pass. This may permit true erroneous cases (difference between
	* reference tensor and test tensor is multiple of wrap_range), but such errors would be detected by
	* other test cases.
	*/
	template <typename T, typename U = AbsoluteTolerance<T>>
	void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, const ValidRegion &valid_region, U tolerance_value = U(), float tolerance_number = 0.f);

	/** Validate tensors with valid mask.
	*
	* - Dimensionality has to be the same.
	* - All values have to match.
	*
	* @note: wrap_range allows cases where reference tensor rounds up to the wrapping point, causing it to wrap around to
	* zero while the test tensor stays at wrapping point to pass. This may permit true erroneous cases (difference between
	* reference tensor and test tensor is multiple of wrap_range), but such errors would be detected by
	* other test cases.
	*/
	template <typename T, typename U = AbsoluteTolerance<T>>
	void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, const SimpleTensor<T> &valid_mask, U tolerance_value = U(), float tolerance_number = 0.f);

	/** Validate tensors against constant value.
	*
	* - All values have to match.
	*/
	void validate(const IAccessor &tensor, const void *reference_value);

	/** Validate border against a constant value.
	*
	* - All border values have to match the specified value if mode is CONSTANT.
	* - All border values have to be replicated if mode is REPLICATE.
	* - Nothing is validated for mode UNDEFINED.
	*/
	void validate(const IAccessor &tensor, BorderSize border_size, const BorderMode &border_mode, const void *border_value);

	/** Validate classified labels against expected ones.
	*
	* - All values should match
	*/
	void validate(std::vector<unsigned int> classified_labels, std::vector<unsigned int> expected_labels);

	/** Validate float value.
	*
	* - All values should match
	*/
	template <typename T, typename U = AbsoluteTolerance<T>>
	bool validate(T target, T reference, U tolerance = AbsoluteTolerance<T>());

	/** Validate key points. */
	template <typename T, typename U, typename V = AbsoluteTolerance<float>>
	void validate_keypoints(T target_first, T target_last, U reference_first, U reference_last, V tolerance = AbsoluteTolerance<float>());

	template <typename T>
	struct compare_base
	{
	compare_base(typename T::value_type target, typename T::value_type reference, T tolerance = T(0))
	: _target{ target }, _reference{ reference }, _tolerance{ tolerance }
	{
	}

	typename T::value_type _target{};
	typename T::value_type _reference{};
	T _tolerance{};
	};

	template <typename T>
	struct compare;

	template <typename U>
	struct compare<AbsoluteTolerance<U>> : public compare_base<AbsoluteTolerance<U>>
	{
	using compare_base<AbsoluteTolerance<U>>::compare_base;

	operator bool() const
	{
	if(!std::isfinite(this->_target) \|\| !std::isfinite(this->_reference))
	{
	return false;
	}
	else if(this->_target == this->_reference)
	{
	return true;
	}

	using comparison_type = typename std::conditional<std::is_integral<U>::value, int64_t, U>::type;

	const comparison_type abs_difference(std::abs(static_cast<comparison_type>(this->_target) - static_cast<comparison_type>(this->_reference)));

	return abs_difference <= static_cast<comparison_type>(this->_tolerance);
	}
	};

	template <typename U>
	struct compare<RelativeTolerance<U>> : public compare_base<RelativeTolerance<U>>
	{
	using compare_base<RelativeTolerance<U>>::compare_base;

	operator bool() const
	{
	if(!std::isfinite(this->_target) \|\| !std::isfinite(this->_reference))
	{
	return false;
	}
	else if(this->_target == this->_reference)
	{
	return true;
	}

	const U epsilon = (std::is_same<half, typename std::remove_cv<U>::type>::value \|\| (this->_reference == 0)) ? static_cast<U>(0.01) : static_cast<U>(1e-05);

	if(std::abs(static_cast<double>(this->_reference) - static_cast<double>(this->_target)) <= epsilon)
	{
	return true;
	}
	else
	{
	if(static_cast<double>(this->_reference) == 0.0f) // We have checked whether _reference and _target is closing. If _reference is 0 but not closed to _target, it should return false
	{
	return false;
	}

	const double relative_change = std::abs(static_cast<double>(this->_target) - static_cast<double>(this->_reference)) / this->_reference;

	return relative_change <= static_cast<U>(this->_tolerance);
	}
	}
	};

	template <typename T, typename U>
	void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, U tolerance_value, float tolerance_number)
	{
	// Validate with valid region covering the entire shape
	validate(tensor, reference, shape_to_valid_region(tensor.shape()), tolerance_value, tolerance_number);
	}

	template <typename T, typename U>
	void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, const ValidRegion &valid_region, U tolerance_value, float tolerance_number)
	{
	int64_t num_mismatches = 0;
	int64_t num_elements = 0;

	ARM_COMPUTE_EXPECT_EQUAL(tensor.element_size(), reference.element_size(), framework::LogLevel::ERRORS);
	ARM_COMPUTE_EXPECT_EQUAL(tensor.data_type(), reference.data_type(), framework::LogLevel::ERRORS);

	if(reference.format() != Format::UNKNOWN)
	{
	ARM_COMPUTE_EXPECT_EQUAL(tensor.format(), reference.format(), framework::LogLevel::ERRORS);
	}

	ARM_COMPUTE_EXPECT_EQUAL(tensor.num_channels(), reference.num_channels(), framework::LogLevel::ERRORS);
	ARM_COMPUTE_EXPECT(compare_dimensions(tensor.shape(), reference.shape()), framework::LogLevel::ERRORS);

	const int min_elements = std::min(tensor.num_elements(), reference.num_elements());
	const int min_channels = std::min(tensor.num_channels(), reference.num_channels());

	// Iterate over all elements within valid region, e.g. U8, S16, RGB888, ...
	for(int element_idx = 0; element_idx < min_elements; ++element_idx)
	{
	const Coordinates id = index2coord(reference.shape(), element_idx);

	if(is_in_valid_region(valid_region, id))
	{
	// Iterate over all channels within one element
	for(int c = 0; c < min_channels; ++c)
	{
	const T &target_value = reinterpret_cast<const T *>(tensor(id))[c];
	const T &reference_value = reinterpret_cast<const T *>(reference(id))[c];

	if(!compare<U>(target_value, reference_value, tolerance_value))
	{
	ARM_COMPUTE_TEST_INFO("id = " << id);
	ARM_COMPUTE_TEST_INFO("channel = " << c);
	ARM_COMPUTE_TEST_INFO("target = " << std::setprecision(5) << framework::make_printable(target_value));
	ARM_COMPUTE_TEST_INFO("reference = " << std::setprecision(5) << framework::make_printable(reference_value));
	ARM_COMPUTE_TEST_INFO("tolerance = " << std::setprecision(5) << framework::make_printable(static_cast<typename U::value_type>(tolerance_value)));
	framework::ARM_COMPUTE_PRINT_INFO();

	++num_mismatches;
	}

	++num_elements;
	}
	}
	}

	if(num_elements > 0)
	{
	const int64_t absolute_tolerance_number = tolerance_number * num_elements;
	const float percent_mismatches = static_cast<float>(num_mismatches) / num_elements * 100.f;

	ARM_COMPUTE_TEST_INFO(num_mismatches << " values (" << std::fixed << std::setprecision(2) << percent_mismatches
	<< "%) mismatched (maximum tolerated " << std::setprecision(2) << tolerance_number << "%)");
	ARM_COMPUTE_EXPECT(num_mismatches <= absolute_tolerance_number, framework::LogLevel::ERRORS);
	}
	}

	/** Check which keypoints from [first1, last1) are missing in [first2, last2) */
	template <typename T, typename U, typename V>
	std::pair<int64_t, int64_t> compare_keypoints(T first1, T last1, U first2, U last2, V tolerance)
	{
	int64_t num_missing = 0;
	int64_t num_mismatches = 0;

	while(first1 != last1)
	{
	const auto point = std::find_if(first2, last2, [&](KeyPoint point)
	{
	return point.x == first1->x && point.y == first1->y;
	});

	if(point == last2)
	{
	++num_missing;
	ARM_COMPUTE_TEST_INFO("keypoint1 = " << *first1)
	ARM_COMPUTE_EXPECT_FAIL("Key point not found", framework::LogLevel::DEBUG);
	}
	else if(!validate(point->tracking_status, first1->tracking_status) \|\| !validate(point->strength, first1->strength, tolerance) \|\| !validate(point->scale, first1->scale)
	\|\| !validate(point->orientation, first1->orientation) \|\| !validate(point->error, first1->error))
	{
	++num_mismatches;
	ARM_COMPUTE_TEST_INFO("keypoint1 = " << *first1)
	ARM_COMPUTE_TEST_INFO("keypoint2 = " << *point)
	ARM_COMPUTE_EXPECT_FAIL("Mismatching keypoint", framework::LogLevel::DEBUG);
	}

	++first1;
	}

	return std::make_pair(num_missing, num_mismatches);
	}

	template <typename T, typename U, typename V>
	void validate_keypoints(T target_first, T target_last, U reference_first, U reference_last, V tolerance)
	{
	const int64_t num_elements_target = std::distance(target_first, target_last);
	const int64_t num_elements_reference = std::distance(reference_first, reference_last);

	ARM_COMPUTE_EXPECT_EQUAL(num_elements_target, num_elements_reference, framework::LogLevel::ERRORS);

	int64_t num_missing = 0;
	int64_t num_mismatches = 0;

	if(num_elements_reference > 0)
	{
	std::tie(num_missing, num_mismatches) = compare_keypoints(reference_first, reference_last, target_first, target_last, tolerance);

	const float percent_missing = static_cast<float>(num_missing) / num_elements_reference * 100.f;
	const float percent_mismatches = static_cast<float>(num_mismatches) / num_elements_reference * 100.f;

	ARM_COMPUTE_TEST_INFO(num_missing << " keypoints (" << std::fixed << std::setprecision(2) << percent_missing << "%) are missing in target");
	ARM_COMPUTE_EXPECT_EQUAL(num_missing, 0, framework::LogLevel::ERRORS);

	ARM_COMPUTE_TEST_INFO(num_mismatches << " keypoints (" << std::fixed << std::setprecision(2) << percent_mismatches << "%) mismatched");
	ARM_COMPUTE_EXPECT_EQUAL(num_mismatches, 0, framework::LogLevel::ERRORS);
	}

	if(num_elements_target > 0)
	{
	std::tie(num_missing, num_mismatches) = compare_keypoints(target_first, target_last, reference_first, reference_last, tolerance);

	const float percent_missing = static_cast<float>(num_missing) / num_elements_target * 100.f;

	ARM_COMPUTE_TEST_INFO(num_missing << " keypoints (" << std::fixed << std::setprecision(2) << percent_missing << "%) are not part of target");
	ARM_COMPUTE_EXPECT_EQUAL(num_missing, 0, framework::LogLevel::ERRORS);
	}
	}

	template <typename T, typename U>
	void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, const SimpleTensor<T> &valid_mask, U tolerance_value, float tolerance_number)
	{
	int64_t num_mismatches = 0;
	int64_t num_elements = 0;

	ARM_COMPUTE_EXPECT_EQUAL(tensor.element_size(), reference.element_size(), framework::LogLevel::ERRORS);
	ARM_COMPUTE_EXPECT_EQUAL(tensor.data_type(), reference.data_type(), framework::LogLevel::ERRORS);

	if(reference.format() != Format::UNKNOWN)
	{
	ARM_COMPUTE_EXPECT_EQUAL(tensor.format(), reference.format(), framework::LogLevel::ERRORS);
	}

	ARM_COMPUTE_EXPECT_EQUAL(tensor.num_channels(), reference.num_channels(), framework::LogLevel::ERRORS);
	ARM_COMPUTE_EXPECT(compare_dimensions(tensor.shape(), reference.shape()), framework::LogLevel::ERRORS);

	const int min_elements = std::min(tensor.num_elements(), reference.num_elements());
	const int min_channels = std::min(tensor.num_channels(), reference.num_channels());

	// Iterate over all elements within valid region, e.g. U8, S16, RGB888, ...
	for(int element_idx = 0; element_idx < min_elements; ++element_idx)
	{
	const Coordinates id = index2coord(reference.shape(), element_idx);

	if(valid_mask[element_idx] == 1)
	{
	// Iterate over all channels within one element
	for(int c = 0; c < min_channels; ++c)
	{
	const T &target_value = reinterpret_cast<const T *>(tensor(id))[c];
	const T &reference_value = reinterpret_cast<const T *>(reference(id))[c];

	if(!compare<U>(target_value, reference_value, tolerance_value))
	{
	ARM_COMPUTE_TEST_INFO("id = " << id);
	ARM_COMPUTE_TEST_INFO("channel = " << c);
	ARM_COMPUTE_TEST_INFO("target = " << std::setprecision(5) << framework::make_printable(target_value));
	ARM_COMPUTE_TEST_INFO("reference = " << std::setprecision(5) << framework::make_printable(reference_value));
	ARM_COMPUTE_TEST_INFO("tolerance = " << std::setprecision(5) << framework::make_printable(static_cast<typename U::value_type>(tolerance_value)));
	framework::ARM_COMPUTE_PRINT_INFO();

	++num_mismatches;
	}

	++num_elements;
	}
	}
	else
	{
	++num_elements;
	}
	}

	if(num_elements > 0)
	{
	const int64_t absolute_tolerance_number = tolerance_number * num_elements;
	const float percent_mismatches = static_cast<float>(num_mismatches) / num_elements * 100.f;

	ARM_COMPUTE_TEST_INFO(num_mismatches << " values (" << std::fixed << std::setprecision(2) << percent_mismatches
	<< "%) mismatched (maximum tolerated " << std::setprecision(2) << tolerance_number << "%)");
	ARM_COMPUTE_EXPECT(num_mismatches <= absolute_tolerance_number, framework::LogLevel::ERRORS);
	}
	}

	template <typename T, typename U>
	bool validate(T target, T reference, U tolerance)
	{
	ARM_COMPUTE_TEST_INFO("reference = " << std::setprecision(5) << framework::make_printable(reference));
	ARM_COMPUTE_TEST_INFO("target = " << std::setprecision(5) << framework::make_printable(target));
	ARM_COMPUTE_TEST_INFO("tolerance = " << std::setprecision(5) << framework::make_printable(static_cast<typename U::value_type>(tolerance)));

	const bool equal = compare<U>(target, reference, tolerance);

	ARM_COMPUTE_EXPECT(equal, framework::LogLevel::ERRORS);

	return equal;
	}

	template <typename T, typename U>
	void validate_min_max_loc(const MinMaxLocationValues<T> &target, const MinMaxLocationValues<U> &reference)
	{
	ARM_COMPUTE_EXPECT_EQUAL(target.min, reference.min, framework::LogLevel::ERRORS);
	ARM_COMPUTE_EXPECT_EQUAL(target.max, reference.max, framework::LogLevel::ERRORS);

	ARM_COMPUTE_EXPECT_EQUAL(target.min_loc.size(), reference.min_loc.size(), framework::LogLevel::ERRORS);
	ARM_COMPUTE_EXPECT_EQUAL(target.max_loc.size(), reference.max_loc.size(), framework::LogLevel::ERRORS);

	for(uint32_t i = 0; i < target.min_loc.size(); ++i)
	{
	const auto same_coords = std::find_if(reference.min_loc.begin(), reference.min_loc.end(), [&target, i](Coordinates2D coord)
	{
	return coord.x == target.min_loc.at(i).x && coord.y == target.min_loc.at(i).y;
	});

	ARM_COMPUTE_EXPECT(same_coords != reference.min_loc.end(), framework::LogLevel::ERRORS);
	}

	for(uint32_t i = 0; i < target.max_loc.size(); ++i)
	{
	const auto same_coords = std::find_if(reference.max_loc.begin(), reference.max_loc.end(), [&target, i](Coordinates2D coord)
	{
	return coord.x == target.max_loc.at(i).x && coord.y == target.max_loc.at(i).y;
	});

	ARM_COMPUTE_EXPECT(same_coords != reference.max_loc.end(), framework::LogLevel::ERRORS);
	}
	}

	} // namespace validation
	} // namespace test
	} // namespace arm_compute
	#endif /* __ARM_COMPUTE_TEST_REFERENCE_VALIDATION_H__ */