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Diffstat (limited to 'tests/validation_old/ReferenceCPP.h')
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diff --git a/tests/validation_old/ReferenceCPP.h b/tests/validation_old/ReferenceCPP.h new file mode 100644 index 0000000000..fcc4da471d --- /dev/null +++ b/tests/validation_old/ReferenceCPP.h @@ -0,0 +1,278 @@ +/* + * 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_REFERENCE_REFERENCE_CPP_H__ +#define __ARM_COMPUTE_TEST_REFERENCE_REFERENCE_CPP_H__ + +#include "RawTensor.h" +#include "Reference.h" + +#include <map> +#include <memory> +#include <ostream> +#include <vector> + +namespace arm_compute +{ +class Tensor; + +namespace test +{ +namespace validation +{ +/** C++ reference implementation. */ +class ReferenceCPP final : public Reference +{ +public: + /** Function to compute reference sobel 3x3. + * + * @param[in] src Input tensor. + * @param[in] dst_x Result tensor along x axis + * @param[in] dst_y Result tensor along y axis + * @param[in] border_mode Border mode to use for input tensor + * @param[in] constant_border_value Constant value to use if @p border_mode is constant + * + */ + static void sobel_3x3(RawTensor &src, RawTensor &dst_x, RawTensor &dst_y, BorderMode border_mode, uint8_t constant_border_value); + /** Function to compute reference sobel 5x5. + * + * @param[in] src Input tensor. + * @param[in] dst_x Result tensor along x axis + * @param[in] dst_y Result tensor along y axis + * @param[in] border_mode Border mode to use for input tensor + * @param[in] constant_border_value Constant value to use if @p border_mode is constant + * + */ + static void sobel_5x5(RawTensor &src, RawTensor &dst_x, RawTensor &dst_y, BorderMode border_mode, uint8_t constant_border_value); + /** Function to compute reference Harris corners. + * + * @param[in] src Input tensor + * @param[in] Gx Tensor used to compute Sobel along the x axis + * @param[in] Gy Tensor used to compute Sobel along the y axis + * @param[in] candidates Tensor used to store candidate corners + * @param[in] non_maxima Tensor used to store non_maxima suppressed candidate corners + * @param[in] threshold Minimum threshold with which to eliminate Harris Corner scores (computed using the normalized Sobel kernel). + * @param[in] min_dist Radial Euclidean distance for the euclidean distance stage + * @param[in] sensitivity Sensitivity threshold k from the Harris-Stephens equation + * @param[in] gradient_size The gradient window size to use on the input. The implementation supports 3, 5, and 7 + * @param[in] block_size The block window size used to compute the Harris Corner score. The implementation supports 3, 5, and 7. + * @param[out] corners Array of keypoints to store the results. + * @param[in] border_mode Border mode to use + * @param[in] constant_border_value Constant value to use for borders if border_mode is set to CONSTANT. + * + */ + static void harris_corners(RawTensor &src, RawTensor &Gx, RawTensor &Gy, const RawTensor &candidates, const RawTensor &non_maxima, float threshold, float min_dist, float sensitivity, + int32_t gradient_size, int32_t block_size, KeyPointArray &corners, BorderMode border_mode, uint8_t constant_border_value); + /** Function to compute the min max values and their location in a tensor. + * + * @param[in] src Input tensor. + * @param[out] min Minimum value of the tensor. + * @param[out] max Maximum value of the tensor + * @param[out] min_loc Array with locations of minimum values + * @param[out] max_loc Array with locations of maximum values + * @param[out] min_count Number of minimum values found + * @param[out] max_count Number of maximum values found + */ + static void min_max_location(const RawTensor &src, void *min, void *max, IArray<Coordinates2D> &min_loc, IArray<Coordinates2D> &max_loc, uint32_t &min_count, uint32_t &max_count); + /** Function to compute the integral image of a tensor. + * + * @param[in] src Input tensor. + * @param[out] dst Result tensor. + */ + static void integral_image(const RawTensor &src, RawTensor &dst); + /** Function to compute the absolute difference between two tensors. + * + * @param[in] src1 First tensor. + * @param[in] src2 Second tensor. + * @param[out] dst Result tensor. + */ + static void absolute_difference(const RawTensor &src1, const RawTensor &src2, RawTensor &dst); + /** Function to accumulate an input tensor into an output tensor. + * + * @param[in] src Input tensor. + * @param[in, out] dst Result tensor. + */ + static void accumulate(const RawTensor &src, RawTensor &dst); + /** Function to accumulate a squared value from an input tensor to an output tensor. + * + * @param[in] src Input tensor. + * @param[in, out] dst Result tensor. + * @param[in] shift A uint32_t value within the range of [0, 15] + */ + static void accumulate_squared(const RawTensor &src, RawTensor &dst, uint32_t shift); + /** Function to accumulate a weighted value from an input tensor to an output tensor. + * + * @param[in] src Input tensor. + * @param[in, out] dst Result tensor. + * @param[in] alpha A float value within the range of [0, 1] + */ + static void accumulate_weighted(const RawTensor &src, RawTensor &dst, float alpha); + /** Arithmetic addition of @p src1 and @p src2 + * + * @param[in] src1 First tensor. + * @param[in] src2 Second tensor. + * @param[out] dst Result tensor. + * @param[in] convert_policy Overflow policy. + */ + static void arithmetic_addition(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, ConvertPolicy convert_policy); + /** Arithmetic subtraction of @p src2 from @p src1 + * + * @param[in] src1 First tensor. + * @param[in] src2 Second tensor. + * @param[out] dst Result tensor. + * @param[in] convert_policy Overflow policy. + */ + static void arithmetic_subtraction(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, ConvertPolicy convert_policy); + /** Function to compute box3x3 filtered result tensor. + * + * @param[in] src Input tensor. + * @param[out] dst Result tensor. + * @param[in] border_mode Border mode. + * @param[in] constant_border_value Constant border value if @p border_mode is BorderMode::CONSTANT. + */ + static void box3x3(const RawTensor &src, RawTensor &dst, BorderMode border_mode, uint8_t constant_border_value); + /** Depth conversion from @p src to @p dst + * + * @param[in] src First tensor. + * @param[out] dst Result tensor. + * @param[in] policy Overflow policy. + * @param[in] shift Value for down/up conversions. + */ + static void depth_convert(const RawTensor &src, RawTensor &dst, ConvertPolicy policy, uint32_t shift); + /** Function to compute gaussian3x3 filtered result tensor. + * + * @param[in] src Input tensor. + * @param[out] dst Result tensor. + * @param[in] border_mode Border mode + * @param[in] constant_border_value Constant border value if @p border_mode is BorderMode::CONSTANT + */ + static void gaussian3x3(const RawTensor &src, RawTensor &dst, BorderMode border_mode, uint8_t constant_border_value); + /** Function to compute gaussian5x5 filtered result tensor. + * + * @param[in] src Input tensor. + * @param[out] dst Result tensor. + * @param[in] border_mode Border mode + * @param[in] constant_border_value Constant border value if @p border_mode is BorderMode::CONSTANT + */ + static void gaussian5x5(const RawTensor &src, RawTensor &dst, BorderMode border_mode, uint8_t constant_border_value); + /** Compute non linear filter function. + * + * @param[in] src First input tensor + * @param[out] dst Output tensor + * @param[in] function Non linear function to perform + * @param[in] mask_size Mask size. Supported sizes: 3, 5 + * @param[in] pattern Matrix pattern + * @param[in] mask The given mask. + * @param[in] border_mode Strategy to use for borders. + * @param[in] constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT. + */ + static void non_linear_filter(const RawTensor &src, RawTensor &dst, NonLinearFilterFunction function, unsigned int mask_size, + MatrixPattern pattern, const uint8_t *mask, BorderMode border_mode, uint8_t constant_border_value = 0); + /** Element-wise multiplication of @p src1, @p src2 and @p scale + * + * @param[in] src1 First tensor. + * @param[in] src2 Second tensor. + * @param[out] dst Result tensor. + * @param[in] scale A non-negative float multiplied to each product. + * @param[in] convert_policy Overflow policy. + * @param[in] rounding_policy Rounding policy. + */ + static void pixel_wise_multiplication(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, float scale, ConvertPolicy convert_policy, RoundingPolicy rounding_policy); + /** Fixed-point Pixel-wise multiplication of @p src1 by @p src2 + * + * @param[in] src1 First tensor. + * @param[in] src2 Second tensor. + * @param[out] dst Result tensor. + * @param[in] scale A non-negative float multiplied to each product. + * @param[in] convert_policy Overflow policy. + * @param[in] rounding_policy Rounding policy. + */ + static void fixed_point_pixel_wise_multiplication(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, float scale, ConvertPolicy convert_policy, RoundingPolicy rounding_policy); + /** Table Lookup f@p src to @p dst + * + * @param[in] src Input tensor. + * @param[out] dst Result tensor. + * @param[in] lut Input lookup table. + */ + template <typename T> + static void table_lookup(const RawTensor &src, RawTensor &dst, std::map<T, T> &lut); + /** Threshold of@p src to @p dst + * + * @param[in] src Input tensor. + * @param[out] dst Result tensor. + * @param[in] threshold Threshold. When the threhold type is RANGE, this is used as the lower threshold. + * @param[in] false_value value to set when the condition is not respected. + * @param[in] true_value value to set when the condition is respected. + * @param[in] type Thresholding type. Either RANGE or BINARY. + * @param[in] upper Upper threshold. Only used when the thresholding type is RANGE. + */ + static void threshold(const RawTensor &src, RawTensor &dst, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper); + /** Warp perspective of@p src to @p dst + * + * @param[in] src First tensor. + * @param[out] dst Result tensor. + * @param[out] valid_mask Valid mask tensor. + * @param[in] matrix The perspective matrix. Must be 3x3 of type float. + * @param[in] policy The interpolation type. + * @param[in] border_mode Strategy to use for borders. + * @param[in] constant_border_value Constant value to use for borders if border_mode is set to CONSTANT. + */ + static void warp_perspective(const RawTensor &src, RawTensor &dst, RawTensor &valid_mask, const float *matrix, InterpolationPolicy policy, BorderMode border_mode, uint8_t constant_border_value); + + /** Batch Normalization of @p src based on the information from @p norm_info. + * + * @param[in] src Input tensor. + * @param[out] dst Result tensor. + * @param[out] mean Mean vector tensor. + * @param[out] var Var vector tensor. + * @param[out] beta Beta vector tensor. + * @param[out] gamma Gamma vector tensor. + * @param[in] epsilon Small value to avoid division with zero. + * @param[in] fixed_point_position Fixed point position. + */ + static void batch_normalization_layer(const RawTensor &src, RawTensor &dst, const RawTensor &mean, const RawTensor &var, const RawTensor &beta, const RawTensor &gamma, float epsilon, + int fixed_point_position = 0); + /** ROI Pooling layer of @p src based on the information from @p pool_info and @p rois. + * + * @param[in] src Input tensor. + * @param[out] dst Result tensor. + * @param[in] rois Region of Interest points. + * @param[in] pool_info ROI Pooling Layer information. + */ + static void roi_pooling_layer(const RawTensor &src, RawTensor &dst, const std::vector<ROI> &rois, const ROIPoolingLayerInfo &pool_info); + /** Fixed point operations of @p src + * + * @param[in] src Input tensor. + * @param[out] dst Result tensor. + * @param[in] op Fixed point operation to perform. + */ + static void fixed_point_operation(const RawTensor &src, RawTensor &dst, FixedPointOp op); + +private: + ReferenceCPP() = delete; + ~ReferenceCPP() = delete; +}; +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif /* __ARM_COMPUTE_TEST_REFERENCE_REFERENCE_CPP_H__ */ |