| /* |
| * 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 "support/ToolchainSupport.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 ®ion, 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), bool wrap_range = false) |
| : _target{ target }, _reference{ reference }, _tolerance{ tolerance }, _wrap_range{ wrap_range } |
| { |
| } |
| |
| typename T::value_type _target{}; |
| typename T::value_type _reference{}; |
| T _tolerance{}; |
| bool _wrap_range{}; |
| }; |
| |
| 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(!support::cpp11::isfinite(this->_target) || !support::cpp11::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; |
| |
| if(this->_wrap_range) |
| { |
| const comparison_type abs_difference(std::abs(static_cast<comparison_type>(this->_target)) - std::abs(static_cast<comparison_type>(this->_reference))); |
| return abs_difference <= static_cast<comparison_type>(this->_tolerance); |
| } |
| |
| 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(!support::cpp11::isfinite(this->_target) || !support::cpp11::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_wrap(const IAccessor &tensor, const SimpleTensor<T> &reference, U tolerance_value, float tolerance_number) |
| { |
| // Validate with valid region covering the entire shape |
| validate_wrap(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); |
| } |
| } |
| |
| template <typename T, typename U> |
| void validate_wrap(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]; |
| |
| bool equal = compare<U>(target_value, reference_value, tolerance_value); |
| |
| if(!equal) |
| { |
| equal = compare<U>(target_value, reference_value, tolerance_value, true); |
| } |
| |
| if(!equal) |
| { |
| 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__ */ |