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/*
* 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 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, int32_t &min, int32_t &max, IArray<Coordinates2D> &min_loc, IArray<Coordinates2D> &max_loc, uint32_t &min_count, uint32_t &max_count);
/** Function to compute the mean and standard deviation of a tensor.
*
* @param[in] src Input tensor.
* @param[out] mean Mean of the tensor.
* @param[out] std_dev Standard deviation of the tensor
*/
static void mean_and_standard_deviation(const RawTensor &src, float &mean, float &std_dev);
/** 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 the bitwise and between two tensors.
*
* @param[in] src1 First tensor.
* @param[in] src2 Second tensor.
* @param[out] dst Result tensor.
*/
static void bitwise_and(const RawTensor &src1, const RawTensor &src2, RawTensor &dst);
/** Function to compute the bitwise or between two tensors.
*
* @param[in] src1 First tensor.
* @param[in] src2 Second tensor.
* @param[out] dst Result tensor.
*/
static void bitwise_or(const RawTensor &src1, const RawTensor &src2, RawTensor &dst);
/** Function to compute the bitwise xor between two tensors.
*
* @param[in] src1 First tensor.
* @param[in] src2 Second tensor.
* @param[out] dst Result tensor.
*/
static void bitwise_xor(const RawTensor &src1, const RawTensor &src2, RawTensor &dst);
/** Function to compute the bitwise not of a tensor.
*
* @param[in] src Input tensor.
* @param[out] dst Result tensor.
*/
static void bitwise_not(const RawTensor &src, RawTensor &dst);
/** 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 GEMM function.
*
* @param[in] src1 First input tensor
* @param[in] src2 Second input tensor
* @param[in] src3 Third input tensor
* @param[out] dst Output tensr
* @param[in] alpha Weight of the matrix product
* @param[in] beta Weight of the third matrix
*/
static void gemm(const RawTensor &src1, const RawTensor &src2, const RawTensor &src3,
RawTensor &dst, float alpha, float beta);
/** 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);
/** Activation layer of @p src base on information from @p act_info.
*
* @param[in] input Input tensor.
* @param[in] output Second tensor.
* @param[out] act_info Activation layer information.
*/
static void activation_layer(const RawTensor &input, RawTensor &output, ActivationLayerInfo act_info);
/** 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);
/** Convolution layer function
*
* @param[in] src Input tensor.
* @param[in] weights Weights tensor.
* @param[in] bias Bias tensor.
* @param[out] dst Result tensor.
* @param[in] conv_info Pads and strides information for the convolution layer.
*/
static void convolution_layer(const RawTensor &src, const RawTensor &weights, const RawTensor &bias, RawTensor &dst, const PadStrideInfo &conv_info);
/** Depth concatenate layer from @p srcs to @p dst
*
* @param[in] srcs Input tensors.
* @param[out] dst Result tensor.
*/
static void depth_concatenate_layer(const std::vector<std::unique_ptr<RawTensor>> &srcs, RawTensor &dst);
/** Fully connected layer function
*
* @param[in] src Input tensor
* @param[in] weights Weights tensor.
* @param[in] bias Bias tensor.
* @param[out] dst Result tensor.
*/
static void fully_connected_layer(const RawTensor &src, const RawTensor &weights, const RawTensor &bias, RawTensor &dst);
/** Pooling layer of @p src based on the information from @p pool_info.
*
* @param[in] src Input tensor.
* @param[out] dst Result tensor.
* @param[in] pool_info Pooling Layer information.
* @param[in] fixed_point_position Fixed point position. (Optional)
*/
static void pooling_layer(const RawTensor &src, RawTensor &dst, PoolingLayerInfo pool_info, 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__ */
|
