| /* |
| * 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); |
| /** 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); |
| /** 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__ */ |