| /* |
| * 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_H__ |
| #define __ARM_COMPUTE_TEST_REFERENCE_REFERENCE_H__ |
| |
| #include "RawTensor.h" |
| #include "Types.h" |
| #include "arm_compute/runtime/Array.h" |
| |
| #include <map> |
| #include <vector> |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| /** Interface for reference implementations. */ |
| class Reference |
| { |
| public: |
| /** Compute reference sobel 3x3. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @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 |
| * |
| * @return Computed raw tensors along x and y axis. |
| */ |
| static std::pair<RawTensor, RawTensor> compute_reference_sobel_3x3(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value); |
| /** Compute reference sobel 5x5. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @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 |
| * |
| * @return Computed raw tensors along x and y axis. |
| */ |
| static std::pair<RawTensor, RawTensor> compute_reference_sobel_5x5(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value); |
| /** Compute reference Harris corners. |
| * |
| * @param[in] shape Shape of input tensor |
| * @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[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. |
| * |
| * @return Computed corners' keypoints. |
| */ |
| static KeyPointArray compute_reference_harris_corners(const TensorShape &shape, float threshold, float min_dist, float sensitivity, |
| int32_t gradient_size, int32_t block_size, BorderMode border_mode, uint8_t constant_border_value); |
| /** Compute min max location. |
| * |
| * @param[in] shape Shape of the input tensors. |
| * @param[in] dt_in Data type of input tensor. |
| * @param[out] min Minimum value of tensor |
| * @param[out] max Maximum value of 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 |
| * |
| * @return Computed minimum, maximum values and their locations. |
| */ |
| static void compute_reference_min_max_location(const TensorShape &shape, DataType dt_in, void *min, void *max, IArray<Coordinates2D> &min_loc, IArray<Coordinates2D> &max_loc, |
| uint32_t &min_count, |
| uint32_t &max_count); |
| /** Compute reference mean and standard deviation. |
| * |
| * @param[in] shape Shape of the input tensors. |
| * |
| * @return Computed mean and standard deviation. |
| */ |
| static std::pair<float, float> compute_reference_mean_and_standard_deviation(const TensorShape &shape); |
| /** Compute reference integral image. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_integral_image(const TensorShape &shape); |
| /** Compute reference absolute difference. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @param[in] dt_in0 Data type of first input tensor. |
| * @param[in] dt_in1 Data type of second input tensor. |
| * @param[in] dt_out Data type of the output tensor. |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_absolute_difference(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out); |
| /** Compute reference accumulate. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_accumulate(const TensorShape &shape); |
| /** Compute reference accumulate. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @param[in] shift A uint32_t value within the range of [0, 15] |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_accumulate_squared(const TensorShape &shape, uint32_t shift); |
| /** Compute reference accumulate. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @param[in] alpha A float value within the range of [0, 1] |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_accumulate_weighted(const TensorShape &shape, float alpha); |
| /** Compute reference arithmetic addition. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @param[in] dt_in0 Data type of first input tensor. |
| * @param[in] dt_in1 Data type of second input tensor. |
| * @param[in] dt_out Data type of the output tensor. |
| * @param[in] convert_policy Overflow policy of the operation. |
| * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of the fixed point numbers |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_arithmetic_addition(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, ConvertPolicy convert_policy, int fixed_point_position = 0); |
| /** Compute reference arithmetic subtraction. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @param[in] dt_in0 Data type of first input tensor. |
| * @param[in] dt_in1 Data type of second input tensor. |
| * @param[in] dt_out Data type of the output tensor. |
| * @param[in] convert_policy Overflow policy of the operation. |
| * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of the fixed point numbers |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_arithmetic_subtraction(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, ConvertPolicy convert_policy, int fixed_point_position = 0); |
| /** Compute reference bitwise xor. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_bitwise_xor(const TensorShape &shape); |
| /** Compute reference bitwise not. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_bitwise_not(const TensorShape &shape); |
| /** Compute reference box3x3 filter. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @param[in] border_mode BorderMode used by the input tensor. |
| * @param[in] constant_border_value Constant to use if @p border_mode == CONSTANT. |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_box3x3(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value); |
| /** Compute reference depth convert. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @param[in] dt_in Data type of input tensor. |
| * @param[in] dt_out Data type of the output tensor. |
| * @param[in] policy Overflow policy of the operation. |
| * @param[in] shift Value for down/up conversions. Must be 0 <= shift < 8. |
| * @param[in] fixed_point_position_in (Optional) Fixed point position for the input tensor. |
| * @param[in] fixed_point_position_out (Optional) Fixed point position for the output tensor. |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_depth_convert(const TensorShape &shape, DataType dt_in, DataType dt_out, ConvertPolicy policy, |
| uint32_t shift, uint32_t fixed_point_position_in = 0, uint32_t fixed_point_position_out = 0); |
| /** Compute reference gaussian3x3 filter. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @param[in] border_mode BorderMode used by the input tensor |
| * @param[in] constant_border_value Constant to use if @p border_mode == CONSTANT |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_gaussian3x3(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value); |
| /** Compute reference gaussian5x5 filter. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @param[in] border_mode BorderMode used by the input tensor. |
| * @param[in] constant_border_value Constant to use if @p border_mode == CONSTANT. |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_gaussian5x5(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value); |
| /** Compute reference non linear filter function |
| * |
| * @param[in] shape Shape of the input and output tensors.Data type supported: U8 |
| * @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. Will be used only if pattern is specified to PATTERN_OTHER |
| * @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. |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_non_linear_filter(const TensorShape &shape, NonLinearFilterFunction function, unsigned int mask_size, |
| MatrixPattern pattern, const uint8_t *mask, BorderMode border_mode, uint8_t constant_border_value = 0); |
| /** Compute reference pixel-wise multiplication |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @param[in] dt_in0 Data type of first input tensor. |
| * @param[in] dt_in1 Data type of second input tensor. |
| * @param[in] dt_out Data type of the output tensor. |
| * @param[in] scale Non-negative scale. |
| * @param[in] convert_policy Overflow policy of the operation. |
| * @param[in] rounding_policy Rounding policy of the operation. |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_pixel_wise_multiplication(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, float scale, ConvertPolicy convert_policy, |
| RoundingPolicy rounding_policy); |
| /** Compute reference pixel-wise multiplication. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @param[in] dt_in0 Data type of first input tensor. |
| * @param[in] dt_in1 Data type of second input tensor. |
| * @param[in] dt_out Data type of the output tensor. |
| * @param[in] scale Scale to apply after multiplication. Must be positive. |
| * @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number. |
| * @param[in] convert_policy Overflow policy of the operation. |
| * @param[in] rounding_policy Rounding policy of the operation. |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_fixed_point_pixel_wise_multiplication(const TensorShape &shape, DataType dt_in0, DataType dt_in1, DataType dt_out, float scale, int fixed_point_position, |
| ConvertPolicy convert_policy, RoundingPolicy rounding_policy); |
| /** Compute reference Table Lookup. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @param[in] dt_inout Data type of input/output tensor. |
| * @param[in] lut Input lookup table. |
| * |
| * @return Computed raw tensor. |
| */ |
| template <typename T> |
| static RawTensor compute_reference_table_lookup(const TensorShape &shape, DataType dt_inout, std::map<T, T> &lut); |
| /** Compute reference threshold. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @param[in] threshold Threshold. When the threshold 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. |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_threshold(const TensorShape &shape, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper); |
| |
| /** Compute reference Warp Perspective. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @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. |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_warp_perspective(const TensorShape &shape, RawTensor &valid_mask, const float *matrix, InterpolationPolicy policy, BorderMode border_mode, |
| uint8_t constant_border_value); |
| |
| /** Compute reference batch normalization layer. |
| * |
| * @param[in] shape0 Shape of the input and output tensors. |
| * @param[in] shape1 Shape of the vector tensors. |
| * @param[in] dt Data type of all input and output tensors. |
| * @param[in] epsilon Small value to avoid division with zero. |
| * @param[in] fixed_point_position Fixed point position. |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_batch_normalization_layer(const TensorShape &shape0, const TensorShape &shape1, DataType dt, float epsilon, int fixed_point_position = 0); |
| /** Compute reference for fully connected layer function |
| * |
| * @param[in] input_shape Shape for the input tensor |
| * @param[in] weights_shape Shape for the weights tensor |
| * @param[in] bias_shape Shape for the bias tensor |
| * @param[in] output_shape Shape for the output tensor |
| * @param[in] dt Data type to use |
| * @param[in] transpose_weights Transpose the weights if true |
| * @param[in] fixed_point_position Number of bits for the fractional part of the fixed point numbers |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_fully_connected_layer(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, DataType dt, |
| bool transpose_weights, int fixed_point_position); |
| /** Compute reference pooling layer. |
| * |
| * @param[in] shape_in Shape of the input tensor. |
| * @param[in] shape_out Shape of the output tensor. |
| * @param[in] dt Data type of input and output tensors. |
| * @param[in] pool_info Pooling Layer information. |
| * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of the fixed point numbers. |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_pooling_layer(const TensorShape &shape_in, const TensorShape &shape_out, DataType dt, PoolingLayerInfo pool_info, int fixed_point_position = 0); |
| /** Compute reference roi pooling layer. |
| * |
| * @param[in] shape Shape of the input tensor. |
| * @param[in] dt Data type of input and output tensors. |
| * @param[in] rois Region of interest vector. |
| * @param[in] pool_info ROI Pooling Layer information. |
| */ |
| static RawTensor compute_reference_roi_pooling_layer(const TensorShape &shape, DataType dt, const std::vector<ROI> &rois, const ROIPoolingLayerInfo &pool_info); |
| /** Compute reference fixed point operation. |
| * |
| * @param[in] shape Shape of the input and output tensors. |
| * @param[in] dt_in Data type of the input tensor. |
| * @param[in] dt_out Data type of the output tensor. |
| * @param[in] op Fixed point operation to perform. |
| * @param[in] fixed_point_position Number of bits for the fractional part of the fixed point numbers |
| * |
| * @return Computed raw tensor. |
| */ |
| static RawTensor compute_reference_fixed_point_operation(const TensorShape &shape, DataType dt_in, DataType dt_out, FixedPointOp op, int fixed_point_position); |
| |
| protected: |
| Reference() = default; |
| ~Reference() = default; |
| }; |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |
| #endif /* __ARM_COMPUTE_TEST_REFERENCE_REFERENCE_H__ */ |