| /* |
| * 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. |
| */ |
| #include "Validation.h" |
| |
| #include "IAccessor.h" |
| #include "RawTensor.h" |
| #include "TypePrinter.h" |
| #include "Utils.h" |
| |
| #include "arm_compute/core/Coordinates.h" |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/FixedPoint.h" |
| #include "arm_compute/core/TensorShape.h" |
| #include "arm_compute/runtime/Tensor.h" |
| |
| #include <array> |
| #include <cmath> |
| #include <cstddef> |
| #include <cstdint> |
| #include <iomanip> |
| |
| #ifdef ARM_COMPUTE_ENABLE_FP16 |
| #include <arm_fp16.h> // needed for float16_t |
| #endif /* ARM_COMPUTE_ENABLE_FP16 */ |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace |
| { |
| /** Get the data from *ptr after casting according to @p data_type and then convert the data to double. |
| * |
| * @param[in] ptr Pointer to value. |
| * @param[in] data_type Data type of both values. |
| * |
| * @return The data from the ptr after converted to double. |
| */ |
| double get_double_data(const void *ptr, DataType data_type) |
| { |
| if(ptr == nullptr) |
| { |
| ARM_COMPUTE_ERROR("Can't dereference a null pointer!"); |
| } |
| |
| switch(data_type) |
| { |
| case DataType::U8: |
| return *reinterpret_cast<const uint8_t *>(ptr); |
| case DataType::S8: |
| return *reinterpret_cast<const int8_t *>(ptr); |
| case DataType::QS8: |
| return *reinterpret_cast<const qint8_t *>(ptr); |
| case DataType::U16: |
| return *reinterpret_cast<const uint16_t *>(ptr); |
| case DataType::S16: |
| return *reinterpret_cast<const int16_t *>(ptr); |
| case DataType::QS16: |
| return *reinterpret_cast<const qint16_t *>(ptr); |
| case DataType::U32: |
| return *reinterpret_cast<const uint32_t *>(ptr); |
| case DataType::S32: |
| return *reinterpret_cast<const int32_t *>(ptr); |
| case DataType::U64: |
| return *reinterpret_cast<const uint64_t *>(ptr); |
| case DataType::S64: |
| return *reinterpret_cast<const int64_t *>(ptr); |
| #ifdef ARM_COMPUTE_ENABLE_FP16 |
| case DataType::F16: |
| return *reinterpret_cast<const float16_t *>(ptr); |
| #endif /* ARM_COMPUTE_ENABLE_FP16 */ |
| case DataType::F32: |
| return *reinterpret_cast<const float *>(ptr); |
| case DataType::F64: |
| return *reinterpret_cast<const double *>(ptr); |
| case DataType::SIZET: |
| return *reinterpret_cast<const size_t *>(ptr); |
| default: |
| ARM_COMPUTE_ERROR("NOT SUPPORTED!"); |
| } |
| } |
| |
| bool is_equal(double target, double ref, double max_absolute_error = std::numeric_limits<double>::epsilon(), double max_relative_error = 0.0001f) |
| { |
| if(!std::isfinite(target) || !std::isfinite(ref)) |
| { |
| return false; |
| } |
| |
| // No need further check if they are equal |
| if(ref == target) |
| { |
| return true; |
| } |
| |
| // Need this check for the situation when the two values close to zero but have different sign |
| if(std::abs(std::abs(ref) - std::abs(target)) <= max_absolute_error) |
| { |
| return true; |
| } |
| |
| double relative_error = 0; |
| |
| if(std::abs(target) > std::abs(ref)) |
| { |
| relative_error = std::abs((target - ref) / target); |
| } |
| else |
| { |
| relative_error = std::abs((ref - target) / ref); |
| } |
| |
| return relative_error <= max_relative_error; |
| } |
| |
| void check_border_element(const IAccessor &tensor, const Coordinates &id, |
| const BorderMode &border_mode, const void *border_value, |
| int64_t &num_elements, int64_t &num_mismatches) |
| { |
| const size_t channel_size = element_size_from_data_type(tensor.data_type()); |
| const auto ptr = static_cast<const uint8_t *>(tensor(id)); |
| |
| if(border_mode == BorderMode::REPLICATE) |
| { |
| Coordinates border_id{ id }; |
| border_id.set(1, 0); |
| border_value = tensor(border_id); |
| } |
| |
| // Iterate over all channels within one element |
| for(int channel = 0; channel < tensor.num_channels(); ++channel) |
| { |
| const size_t channel_offset = channel * channel_size; |
| const double target = get_double_data(ptr + channel_offset, tensor.data_type()); |
| const double ref = get_double_data(static_cast<const uint8_t *>(border_value) + channel_offset, tensor.data_type()); |
| const bool equal = is_equal(target, ref); |
| |
| BOOST_TEST_INFO("id = " << id); |
| BOOST_TEST_INFO("channel = " << channel); |
| BOOST_TEST_INFO("reference = " << std::setprecision(5) << ref); |
| BOOST_TEST_INFO("target = " << std::setprecision(5) << target); |
| BOOST_TEST_WARN(equal); |
| |
| if(!equal) |
| { |
| ++num_mismatches; |
| } |
| |
| ++num_elements; |
| } |
| } |
| |
| void check_single_element(const Coordinates &id, const IAccessor &tensor, const RawTensor &reference, float tolerance_value, |
| uint64_t wrap_range, int min_channels, size_t channel_size, int64_t &num_mismatches, int64_t &num_elements) |
| { |
| const auto ptr = static_cast<const uint8_t *>(tensor(id)); |
| const auto ref_ptr = static_cast<const uint8_t *>(reference(id)); |
| |
| // Iterate over all channels within one element |
| for(int channel = 0; channel < min_channels; ++channel) |
| { |
| const size_t channel_offset = channel * channel_size; |
| const double target = get_double_data(ptr + channel_offset, reference.data_type()); |
| const double ref = get_double_data(ref_ptr + channel_offset, reference.data_type()); |
| bool equal = is_equal(target, ref, tolerance_value); |
| |
| if(wrap_range != 0 && !equal) |
| { |
| equal = is_equal(target, ref, wrap_range - tolerance_value); |
| } |
| |
| if(!equal) |
| { |
| BOOST_TEST_INFO("id = " << id); |
| BOOST_TEST_INFO("channel = " << channel); |
| BOOST_TEST_INFO("reference = " << std::setprecision(5) << ref); |
| BOOST_TEST_INFO("target = " << std::setprecision(5) << target); |
| BOOST_TEST_WARN(equal); |
| |
| ++num_mismatches; |
| } |
| ++num_elements; |
| } |
| } |
| } // namespace |
| |
| void validate(const arm_compute::ValidRegion ®ion, const arm_compute::ValidRegion &reference) |
| { |
| BOOST_TEST(region.anchor.num_dimensions() == reference.anchor.num_dimensions()); |
| BOOST_TEST(region.shape.num_dimensions() == reference.shape.num_dimensions()); |
| |
| for(unsigned int d = 0; d < region.anchor.num_dimensions(); ++d) |
| { |
| BOOST_TEST(region.anchor[d] == reference.anchor[d]); |
| } |
| |
| for(unsigned int d = 0; d < region.shape.num_dimensions(); ++d) |
| { |
| BOOST_TEST(region.shape[d] == reference.shape[d]); |
| } |
| } |
| |
| void validate(const arm_compute::PaddingSize &padding, const arm_compute::PaddingSize &reference) |
| { |
| BOOST_TEST(padding.top == reference.top); |
| BOOST_TEST(padding.right == reference.right); |
| BOOST_TEST(padding.bottom == reference.bottom); |
| BOOST_TEST(padding.left == reference.left); |
| } |
| |
| void validate(const IAccessor &tensor, const RawTensor &reference, float tolerance_value, float tolerance_number, uint64_t wrap_range) |
| { |
| // Validate with valid region covering the entire shape |
| validate(tensor, reference, shape_to_valid_region(tensor.shape()), tolerance_value, tolerance_number, wrap_range); |
| } |
| |
| void validate(const IAccessor &tensor, const RawTensor &reference, const ValidRegion &valid_region, float tolerance_value, float tolerance_number, uint64_t wrap_range) |
| { |
| int64_t num_mismatches = 0; |
| int64_t num_elements = 0; |
| |
| BOOST_TEST(tensor.element_size() == reference.element_size()); |
| BOOST_TEST(tensor.format() == reference.format()); |
| BOOST_TEST(tensor.data_type() == reference.data_type()); |
| BOOST_TEST(tensor.num_channels() == reference.num_channels()); |
| BOOST_TEST(compare_dimensions(tensor.shape(), reference.shape())); |
| |
| const int min_elements = std::min(tensor.num_elements(), reference.num_elements()); |
| const int min_channels = std::min(tensor.num_channels(), reference.num_channels()); |
| const size_t channel_size = element_size_from_data_type(reference.data_type()); |
| |
| // 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)) |
| { |
| check_single_element(id, tensor, reference, tolerance_value, wrap_range, min_channels, channel_size, num_mismatches, num_elements); |
| } |
| } |
| |
| const int64_t absolute_tolerance_number = tolerance_number * num_elements; |
| const float percent_mismatches = static_cast<float>(num_mismatches) / num_elements * 100.f; |
| |
| BOOST_TEST(num_mismatches <= absolute_tolerance_number, |
| num_mismatches << " values (" << std::setprecision(2) << percent_mismatches |
| << "%) mismatched (maximum tolerated " << std::setprecision(2) << tolerance_number << "%)"); |
| } |
| |
| void validate(const IAccessor &tensor, const void *reference_value) |
| { |
| BOOST_TEST_REQUIRE((reference_value != nullptr)); |
| |
| int64_t num_mismatches = 0; |
| int64_t num_elements = 0; |
| const size_t channel_size = element_size_from_data_type(tensor.data_type()); |
| |
| // Iterate over all elements, e.g. U8, S16, RGB888, ... |
| for(int element_idx = 0; element_idx < tensor.num_elements(); ++element_idx) |
| { |
| const Coordinates id = index2coord(tensor.shape(), element_idx); |
| |
| const auto ptr = static_cast<const uint8_t *>(tensor(id)); |
| |
| // Iterate over all channels within one element |
| for(int channel = 0; channel < tensor.num_channels(); ++channel) |
| { |
| const size_t channel_offset = channel * channel_size; |
| const double target = get_double_data(ptr + channel_offset, tensor.data_type()); |
| const double ref = get_double_data(reference_value, tensor.data_type()); |
| const bool equal = is_equal(target, ref); |
| |
| BOOST_TEST_INFO("id = " << id); |
| BOOST_TEST_INFO("channel = " << channel); |
| BOOST_TEST_INFO("reference = " << std::setprecision(5) << ref); |
| BOOST_TEST_INFO("target = " << std::setprecision(5) << target); |
| BOOST_TEST_WARN(equal); |
| |
| if(!equal) |
| { |
| ++num_mismatches; |
| } |
| |
| ++num_elements; |
| } |
| } |
| |
| const float percent_mismatches = static_cast<float>(num_mismatches) / num_elements * 100.f; |
| |
| BOOST_TEST(num_mismatches == 0, |
| num_mismatches << " values (" << std::setprecision(2) << percent_mismatches << "%) mismatched"); |
| } |
| |
| void validate(const IAccessor &tensor, BorderSize border_size, const BorderMode &border_mode, const void *border_value) |
| { |
| if(border_mode == BorderMode::UNDEFINED) |
| { |
| return; |
| } |
| else if(border_mode == BorderMode::CONSTANT) |
| { |
| BOOST_TEST((border_value != nullptr)); |
| } |
| |
| int64_t num_mismatches = 0; |
| int64_t num_elements = 0; |
| const int slice_size = tensor.shape()[0] * tensor.shape()[1]; |
| |
| for(int element_idx = 0; element_idx < tensor.num_elements(); element_idx += slice_size) |
| { |
| Coordinates id = index2coord(tensor.shape(), element_idx); |
| |
| // Top border |
| for(int y = -border_size.top; y < 0; ++y) |
| { |
| id.set(1, y); |
| |
| for(int x = -border_size.left; x < static_cast<int>(tensor.shape()[0]) + static_cast<int>(border_size.right); ++x) |
| { |
| id.set(0, x); |
| |
| check_border_element(tensor, id, border_mode, border_value, num_elements, num_mismatches); |
| } |
| } |
| |
| // Bottom border |
| for(int y = tensor.shape()[1]; y < static_cast<int>(tensor.shape()[1]) + static_cast<int>(border_size.bottom); ++y) |
| { |
| id.set(1, y); |
| |
| for(int x = -border_size.left; x < static_cast<int>(tensor.shape()[0]) + static_cast<int>(border_size.right); ++x) |
| { |
| id.set(0, x); |
| |
| check_border_element(tensor, id, border_mode, border_value, num_elements, num_mismatches); |
| } |
| } |
| |
| // Left/right border |
| for(int y = 0; y < static_cast<int>(tensor.shape()[1]); ++y) |
| { |
| id.set(1, y); |
| |
| // Left border |
| for(int x = -border_size.left; x < 0; ++x) |
| { |
| id.set(0, x); |
| |
| check_border_element(tensor, id, border_mode, border_value, num_elements, num_mismatches); |
| } |
| |
| // Right border |
| for(int x = tensor.shape()[0]; x < static_cast<int>(tensor.shape()[0]) + static_cast<int>(border_size.right); ++x) |
| { |
| id.set(0, x); |
| |
| check_border_element(tensor, id, border_mode, border_value, num_elements, num_mismatches); |
| } |
| } |
| } |
| |
| const float percent_mismatches = static_cast<float>(num_mismatches) / num_elements * 100.f; |
| |
| BOOST_TEST(num_mismatches == 0, |
| num_mismatches << " values (" << std::setprecision(2) << percent_mismatches << "%) mismatched"); |
| } |
| |
| void validate(std::vector<unsigned int> classified_labels, std::vector<unsigned int> expected_labels) |
| { |
| ARM_COMPUTE_UNUSED(classified_labels); |
| ARM_COMPUTE_UNUSED(expected_labels); |
| BOOST_TEST(expected_labels.size() != 0); |
| BOOST_TEST(classified_labels.size() == expected_labels.size()); |
| |
| for(unsigned int i = 0; i < expected_labels.size(); ++i) |
| { |
| BOOST_TEST(classified_labels[i] == expected_labels[i]); |
| } |
| } |
| |
| void validate(float target, float ref, float tolerance_abs_error, float tolerance_relative_error) |
| { |
| const bool equal = is_equal(target, ref, tolerance_abs_error, tolerance_relative_error); |
| |
| BOOST_TEST_INFO("reference = " << std::setprecision(5) << ref); |
| BOOST_TEST_INFO("target = " << std::setprecision(5) << target); |
| BOOST_TEST(equal); |
| } |
| |
| void validate_min_max_loc(int32_t min, int32_t ref_min, int32_t max, int32_t ref_max, |
| Coordinates2DArray &min_loc, Coordinates2DArray &ref_min_loc, Coordinates2DArray &max_loc, Coordinates2DArray &ref_max_loc, |
| uint32_t min_count, uint32_t ref_min_count, uint32_t max_count, uint32_t ref_max_count) |
| { |
| BOOST_TEST(min == ref_min); |
| BOOST_TEST(max == ref_max); |
| |
| BOOST_TEST(min_count == min_loc.num_values()); |
| BOOST_TEST(max_count == max_loc.num_values()); |
| BOOST_TEST(ref_min_count == ref_min_loc.num_values()); |
| BOOST_TEST(ref_max_count == ref_max_loc.num_values()); |
| |
| BOOST_TEST(min_count == ref_min_count); |
| BOOST_TEST(max_count == ref_max_count); |
| |
| for(uint32_t i = 0; i < min_count; i++) |
| { |
| BOOST_TEST(min_loc.at(i).x == ref_min_loc.at(i).x); |
| BOOST_TEST(min_loc.at(i).y == ref_min_loc.at(i).y); |
| } |
| |
| for(uint32_t i = 0; i < max_count; i++) |
| { |
| BOOST_TEST(max_loc.at(i).x == ref_max_loc.at(i).x); |
| BOOST_TEST(max_loc.at(i).y == ref_max_loc.at(i).y); |
| } |
| } |
| |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |