tests/validation/ReferenceCPP.cpp - ml/ComputeLibrary - Gitiles

 /*
  * 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 "ReferenceCPP.h"

 #include "TensorFactory.h"
 #include "TensorOperations.h"
 #include "TensorVisitors.h"
 #include "TypePrinter.h"

 #include "arm_compute/core/Coordinates.h"
 #include "arm_compute/core/Error.h"
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/TensorShape.h"
 #include "arm_compute/runtime/Tensor.h"

 #include "boost_wrapper.h"

 #include <algorithm>
 #include <functional>
 #include <memory>
 #include <numeric>
 #include <vector>

 using namespace arm_compute::test::validation::tensor_visitors;

 namespace arm_compute
 {
 namespace test
 {
 namespace validation
 {
 // Sobel 3x3
 void ReferenceCPP::sobel_3x3(RawTensor &src, RawTensor &dst_x, RawTensor &dst_y, BorderMode border_mode, uint8_t constant_border_value)
 {
     ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst_x.data_type() != DataType::S16 || dst_y.data_type() != DataType::S16);
     Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
     Tensor<int16_t> dx(dst_x.shape(), dst_x.data_type(), dst_x.fixed_point_position(), reinterpret_cast<int16_t *>(dst_x.data()));
     Tensor<int16_t> dy(dst_y.shape(), dst_y.data_type(), dst_y.fixed_point_position(), reinterpret_cast<int16_t *>(dst_y.data()));
     tensor_operations::sobel_3x3(s, dx, dy, border_mode, constant_border_value);
 }

 // Sobel 5x5
 void ReferenceCPP::sobel_5x5(RawTensor &src, RawTensor &dst_x, RawTensor &dst_y, BorderMode border_mode, uint8_t constant_border_value)
 {
     ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst_x.data_type() != DataType::S16 || dst_y.data_type() != DataType::S16);
     Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
     Tensor<int16_t> dx(dst_x.shape(), dst_x.data_type(), dst_x.fixed_point_position(), reinterpret_cast<int16_t *>(dst_x.data()));
     Tensor<int16_t> dy(dst_y.shape(), dst_y.data_type(), dst_y.fixed_point_position(), reinterpret_cast<int16_t *>(dst_y.data()));
     tensor_operations::sobel_5x5(s, dx, dy, border_mode, constant_border_value);
 }

 // Absolute difference
 void ReferenceCPP::absolute_difference(const RawTensor &src1, const RawTensor &src2, RawTensor &dst)
 {
     const TensorVariant s1 = TensorFactory::get_tensor(src1);
     const TensorVariant s2 = TensorFactory::get_tensor(src2);
     TensorVariant       d  = TensorFactory::get_tensor(dst);
     boost::apply_visitor(absolute_difference_visitor(), s1, s2, d);
 }

 // Mean and standard deviation
 void ReferenceCPP::mean_and_standard_deviation(const RawTensor &src, float &mean, float &std_dev)
 {
     ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8);
     const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
     tensor_operations::mean_and_standard_deviation(s, mean, std_dev);
 }

 // Integral image
 void ReferenceCPP::integral_image(const RawTensor &src, RawTensor &dst)
 {
     ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U32);
     const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
     Tensor<uint32_t>      d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint32_t *>(dst.data()));
     tensor_operations::integral_image(s, d);
 }

 // Accumulate
 void ReferenceCPP::accumulate(const RawTensor &src, RawTensor &dst)
 {
     ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::S16);
     const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
     Tensor<int16_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<int16_t *>(dst.data()));
     tensor_operations::accumulate(s, d);
 }

 // Accumulate squared
 void ReferenceCPP::accumulate_squared(const RawTensor &src, RawTensor &dst, uint32_t shift)
 {
     ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::S16);
     const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
     Tensor<int16_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<int16_t *>(dst.data()));
     tensor_operations::accumulate_squared(s, d, shift);
 }

 // Accumulate weighted
 void ReferenceCPP::accumulate_weighted(const RawTensor &src, RawTensor &dst, float alpha)
 {
     ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8);
     const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
     Tensor<uint8_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
     tensor_operations::accumulate_weighted(s, d, alpha);
 }

 // Arithmetic addition
 void ReferenceCPP::arithmetic_addition(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, ConvertPolicy convert_policy)
 {
     const TensorVariant s1 = TensorFactory::get_tensor(src1);
     const TensorVariant s2 = TensorFactory::get_tensor(src2);
     TensorVariant       d  = TensorFactory::get_tensor(dst);
     boost::apply_visitor(arithmetic_addition_visitor(convert_policy), s1, s2, d);
 }

 // Arithmetic subtraction
 void ReferenceCPP::arithmetic_subtraction(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, ConvertPolicy convert_policy)
 {
     const TensorVariant s1 = TensorFactory::get_tensor(src1);
     const TensorVariant s2 = TensorFactory::get_tensor(src2);
     TensorVariant       d  = TensorFactory::get_tensor(dst);
     boost::apply_visitor(arithmetic_subtraction_visitor(convert_policy), s1, s2, d);
 }

 // Bitwise and
 void ReferenceCPP::bitwise_and(const RawTensor &src1, const RawTensor &src2, RawTensor &dst)
 {
     ARM_COMPUTE_ERROR_ON(src1.data_type() != DataType::U8 || src2.data_type() != DataType::U8 || dst.data_type() != DataType::U8);
     const Tensor<uint8_t> s1(src1.shape(), src1.data_type(), src1.fixed_point_position(), reinterpret_cast<const uint8_t *>(src1.data()));
     const Tensor<uint8_t> s2(src2.shape(), src2.data_type(), src2.fixed_point_position(), reinterpret_cast<const uint8_t *>(src2.data()));
     Tensor<uint8_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
     tensor_operations::bitwise_and(s1, s2, d);
 }

 // Bitwise or
 void ReferenceCPP::bitwise_or(const RawTensor &src1, const RawTensor &src2, RawTensor &dst)
 {
     ARM_COMPUTE_ERROR_ON(src1.data_type() != DataType::U8 || src2.data_type() != DataType::U8 || dst.data_type() != DataType::U8);
     const Tensor<uint8_t> s1(src1.shape(), src1.data_type(), src1.fixed_point_position(), reinterpret_cast<const uint8_t *>(src1.data()));
     const Tensor<uint8_t> s2(src2.shape(), src2.data_type(), src2.fixed_point_position(), reinterpret_cast<const uint8_t *>(src2.data()));
     Tensor<uint8_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
     tensor_operations::bitwise_or(s1, s2, d);
 }

 // Bitwise xor
 void ReferenceCPP::bitwise_xor(const RawTensor &src1, const RawTensor &src2, RawTensor &dst)
 {
     ARM_COMPUTE_ERROR_ON(src1.data_type() != DataType::U8 || src2.data_type() != DataType::U8 || dst.data_type() != DataType::U8);
     const Tensor<uint8_t> s1(src1.shape(), src1.data_type(), src1.fixed_point_position(), reinterpret_cast<const uint8_t *>(src1.data()));
     const Tensor<uint8_t> s2(src2.shape(), src2.data_type(), src2.fixed_point_position(), reinterpret_cast<const uint8_t *>(src2.data()));
     Tensor<uint8_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
     tensor_operations::bitwise_xor(s1, s2, d);
 }

 // Bitwise not
 void ReferenceCPP::bitwise_not(const RawTensor &src, RawTensor &dst)
 {
     ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8);
     const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
     Tensor<uint8_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
     tensor_operations::bitwise_not(s, d);
 }

 // Box3x3 filter
 void ReferenceCPP::box3x3(const RawTensor &src, RawTensor &dst, BorderMode border_mode, uint8_t constant_border_value)
 {
     ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8);
     const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
     Tensor<uint8_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
     tensor_operations::box3x3(s, d, border_mode, constant_border_value);
 }

 // Depth conversion
 void ReferenceCPP::depth_convert(const RawTensor &src, RawTensor &dst, ConvertPolicy policy, uint32_t shift)
 {
     const TensorVariant s = TensorFactory::get_tensor(src);
     TensorVariant       d = TensorFactory::get_tensor(dst);
     boost::apply_visitor(tensor_visitors::depth_convert_visitor(policy, shift), s, d);
 }

 // Gaussian3x3 filter
 void ReferenceCPP::gaussian3x3(const RawTensor &src, RawTensor &dst, BorderMode border_mode, uint8_t constant_border_value)
 {
     ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8);
     const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
     Tensor<uint8_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
     tensor_operations::gaussian3x3(s, d, border_mode, constant_border_value);
 }

 // Gaussian5x5 filter
 void ReferenceCPP::gaussian5x5(const RawTensor &src, RawTensor &dst, BorderMode border_mode, uint8_t constant_border_value)
 {
     ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8);
     const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
     Tensor<uint8_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
     tensor_operations::gaussian5x5(s, d, border_mode, constant_border_value);
 }

 // GEMM
 void ReferenceCPP::gemm(const RawTensor &src1, const RawTensor &src2, const RawTensor &src3,
                         RawTensor &dst, float alpha, float beta)
 {
     const TensorVariant s1 = TensorFactory::get_tensor(src1);
     const TensorVariant s2 = TensorFactory::get_tensor(src2);
     const TensorVariant s3 = TensorFactory::get_tensor(src3);
     TensorVariant       d  = TensorFactory::get_tensor(dst);

     boost::apply_visitor(tensor_visitors::gemm_visitor(s1, s2, s3, alpha, beta), d);
 }
 // Non linear filter
 void ReferenceCPP::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)
 {
     ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8);
     const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
     Tensor<uint8_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
     tensor_operations::non_linear_filter(s, d, function, mask_size, pattern, mask, border_mode, constant_border_value);
 }

 // Pixel-wise multiplication
 void ReferenceCPP::pixel_wise_multiplication(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, float scale, ConvertPolicy convert_policy, RoundingPolicy rounding_policy)
 {
     const TensorVariant s1 = TensorFactory::get_tensor(src1);
     const TensorVariant s2 = TensorFactory::get_tensor(src2);
     TensorVariant       d  = TensorFactory::get_tensor(dst);
     boost::apply_visitor(pixel_wise_multiplication_visitor(scale, convert_policy, rounding_policy), s1, s2, d);
 }

 // Fixed-point Pixel-wise multiplication
 void ReferenceCPP::fixed_point_pixel_wise_multiplication(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, float scale, ConvertPolicy convert_policy, RoundingPolicy rounding_policy)
 {
     const TensorVariant s1 = TensorFactory::get_tensor(src1);
     const TensorVariant s2 = TensorFactory::get_tensor(src2);
     TensorVariant       d  = TensorFactory::get_tensor(dst);
     boost::apply_visitor(tensor_visitors::fixed_point_pixel_wise_multiplication_visitor(s1, s2, scale, convert_policy, rounding_policy), d);
 }

 // Table lookup
 template <typename T>
 void ReferenceCPP::table_lookup(const RawTensor &src, RawTensor &dst, std::map<T, T> &lut)
 {
     const TensorVariant s = TensorFactory::get_tensor(src);
     TensorVariant       d = TensorFactory::get_tensor(dst);
     boost::apply_visitor(tensor_visitors::table_lookup<T>(s, lut), d);
 }
 #ifndef DOXYGEN_SKIP_THIS
 template void arm_compute::test::validation::ReferenceCPP::table_lookup<uint8_t>(const RawTensor &src, RawTensor &dst, std::map<uint8_t, uint8_t> &lut);
 template void arm_compute::test::validation::ReferenceCPP::table_lookup<int16_t>(const RawTensor &src, RawTensor &dst, std::map<int16_t, int16_t> &lut);
 #endif /* DOXYGEN_SKIP_THIS */

 // Threshold
 void ReferenceCPP::threshold(const RawTensor &src, RawTensor &dst, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper)
 {
     ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8);
     const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
     Tensor<uint8_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
     tensor_operations::threshold(s, d, threshold, false_value, true_value, type, upper);
 }

 // Activation layer
 void ReferenceCPP::activation_layer(const RawTensor &input, RawTensor &output, ActivationLayerInfo act_info)
 {
     const TensorVariant s = TensorFactory::get_tensor(input);
     TensorVariant       d = TensorFactory::get_tensor(output);
     boost::apply_visitor(tensor_visitors::activation_layer_visitor(s, act_info), d);
 }

 // Batch Normalization Layer
 void ReferenceCPP::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)
 {
     const TensorVariant s = TensorFactory::get_tensor(src);
     TensorVariant       d = TensorFactory::get_tensor(dst);
     const TensorVariant m = TensorFactory::get_tensor(mean);
     const TensorVariant v = TensorFactory::get_tensor(var);
     const TensorVariant b = TensorFactory::get_tensor(beta);
     const TensorVariant g = TensorFactory::get_tensor(gamma);
     boost::apply_visitor(tensor_visitors::batch_normalization_layer_visitor(s, m, v, b, g, epsilon, fixed_point_position), d);
 }

 // Convolution Layer
 void ReferenceCPP::convolution_layer(const RawTensor &src, const RawTensor &weights, const RawTensor &bias, RawTensor &dst, const PadStrideInfo &conv_info)
 {
     const TensorVariant s = TensorFactory::get_tensor(src);
     const TensorVariant w = TensorFactory::get_tensor(weights);
     const TensorVariant b = TensorFactory::get_tensor(bias);
     TensorVariant       d = TensorFactory::get_tensor(dst);
     boost::apply_visitor(tensor_visitors::convolution_layer_visitor(s, w, b, conv_info), d);
 }

 // Depth concatenate layer
 void ReferenceCPP::depth_concatenate_layer(const std::vector<std::unique_ptr<RawTensor>> &srcs, RawTensor &dst)
 {
     std::vector<TensorVariant> ss;
     ss.resize(srcs.size());
     std::transform(srcs.begin(), srcs.end(), ss.begin(), [](std::unique_ptr<RawTensor> const & t)
     {
         return TensorFactory::get_tensor(*t);
     });
     TensorVariant d = TensorFactory::get_tensor(dst);
     boost::apply_visitor(tensor_visitors::depth_concatenate_layer_visitor(ss), d);
 }

 // Fully connected layer
 void ReferenceCPP::fully_connected_layer(const RawTensor &src, const RawTensor &weights, const RawTensor &bias, RawTensor &dst)
 {
     const TensorVariant s = TensorFactory::get_tensor(src);
     const TensorVariant w = TensorFactory::get_tensor(weights);
     const TensorVariant b = TensorFactory::get_tensor(bias);
     TensorVariant       d = TensorFactory::get_tensor(dst);
     boost::apply_visitor(tensor_visitors::fully_connected_layer_visitor(s, w, b), d);
 }

 // Normalization Layer
 void ReferenceCPP::normalization_layer(const RawTensor &src, RawTensor &dst, NormalizationLayerInfo norm_info)
 {
     const TensorVariant s = TensorFactory::get_tensor(src);
     TensorVariant       d = TensorFactory::get_tensor(dst);
     boost::apply_visitor(tensor_visitors::normalization_layer_visitor(s, norm_info), d);
 }

 // Pooling Layer
 void ReferenceCPP::pooling_layer(const RawTensor &src, RawTensor &dst, PoolingLayerInfo pool_info, int fixed_point_position)
 {
     const TensorVariant s = TensorFactory::get_tensor(src);
     TensorVariant       d = TensorFactory::get_tensor(dst);
     boost::apply_visitor(tensor_visitors::pooling_layer_visitor(s, pool_info, fixed_point_position), d);
 }

 // ROI Pooling Layer
 void ReferenceCPP::roi_pooling_layer(const RawTensor &src, RawTensor &dst, const std::vector<ROI> &rois, const ROIPoolingLayerInfo &pool_info)
 {
     const TensorVariant s = TensorFactory::get_tensor(src);
     TensorVariant       d = TensorFactory::get_tensor(dst);
     boost::apply_visitor(tensor_visitors::roi_pooling_layer_visitor(s, rois, pool_info), d);
 }

 // Softmax Layer
 void ReferenceCPP::softmax_layer(const RawTensor &src, RawTensor &dst)
 {
     const TensorVariant s = TensorFactory::get_tensor(src);
     TensorVariant       d = TensorFactory::get_tensor(dst);
     boost::apply_visitor(tensor_visitors::softmax_layer_visitor(s), d);
 }

 // Fixed point operation
 void ReferenceCPP::fixed_point_operation(const RawTensor &src, RawTensor &dst, FixedPointOp op)
 {
     const TensorVariant s = TensorFactory::get_tensor(src);
     TensorVariant       d = TensorFactory::get_tensor(dst);
     boost::apply_visitor(tensor_visitors::fixed_point_operation_visitor(s, op), d);
 }

 } // namespace validation
 } // namespace test
 } // namespace arm_compute
	/*
	* 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 "ReferenceCPP.h"

	#include "TensorFactory.h"
	#include "TensorOperations.h"
	#include "TensorVisitors.h"
	#include "TypePrinter.h"

	#include "arm_compute/core/Coordinates.h"
	#include "arm_compute/core/Error.h"
	#include "arm_compute/core/TensorInfo.h"
	#include "arm_compute/core/TensorShape.h"
	#include "arm_compute/runtime/Tensor.h"

	#include "boost_wrapper.h"

	#include <algorithm>
	#include <functional>
	#include <memory>
	#include <numeric>
	#include <vector>

	using namespace arm_compute::test::validation::tensor_visitors;

	namespace arm_compute
	{
	namespace test
	{
	namespace validation
	{
	// Sobel 3x3
	void ReferenceCPP::sobel_3x3(RawTensor &src, RawTensor &dst_x, RawTensor &dst_y, BorderMode border_mode, uint8_t constant_border_value)
	{
	ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 \|\| dst_x.data_type() != DataType::S16 \|\| dst_y.data_type() != DataType::S16);
	Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
	Tensor<int16_t> dx(dst_x.shape(), dst_x.data_type(), dst_x.fixed_point_position(), reinterpret_cast<int16_t *>(dst_x.data()));
	Tensor<int16_t> dy(dst_y.shape(), dst_y.data_type(), dst_y.fixed_point_position(), reinterpret_cast<int16_t *>(dst_y.data()));
	tensor_operations::sobel_3x3(s, dx, dy, border_mode, constant_border_value);
	}

	// Sobel 5x5
	void ReferenceCPP::sobel_5x5(RawTensor &src, RawTensor &dst_x, RawTensor &dst_y, BorderMode border_mode, uint8_t constant_border_value)
	{
	ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 \|\| dst_x.data_type() != DataType::S16 \|\| dst_y.data_type() != DataType::S16);
	Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
	Tensor<int16_t> dx(dst_x.shape(), dst_x.data_type(), dst_x.fixed_point_position(), reinterpret_cast<int16_t *>(dst_x.data()));
	Tensor<int16_t> dy(dst_y.shape(), dst_y.data_type(), dst_y.fixed_point_position(), reinterpret_cast<int16_t *>(dst_y.data()));
	tensor_operations::sobel_5x5(s, dx, dy, border_mode, constant_border_value);
	}

	// Absolute difference
	void ReferenceCPP::absolute_difference(const RawTensor &src1, const RawTensor &src2, RawTensor &dst)
	{
	const TensorVariant s1 = TensorFactory::get_tensor(src1);
	const TensorVariant s2 = TensorFactory::get_tensor(src2);
	TensorVariant d = TensorFactory::get_tensor(dst);
	boost::apply_visitor(absolute_difference_visitor(), s1, s2, d);
	}

	// Mean and standard deviation
	void ReferenceCPP::mean_and_standard_deviation(const RawTensor &src, float &mean, float &std_dev)
	{
	ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8);
	const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
	tensor_operations::mean_and_standard_deviation(s, mean, std_dev);
	}

	// Integral image
	void ReferenceCPP::integral_image(const RawTensor &src, RawTensor &dst)
	{
	ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 \|\| dst.data_type() != DataType::U32);
	const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
	Tensor<uint32_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint32_t *>(dst.data()));
	tensor_operations::integral_image(s, d);
	}

	// Accumulate
	void ReferenceCPP::accumulate(const RawTensor &src, RawTensor &dst)
	{
	ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 \|\| dst.data_type() != DataType::S16);
	const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
	Tensor<int16_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<int16_t *>(dst.data()));
	tensor_operations::accumulate(s, d);
	}

	// Accumulate squared
	void ReferenceCPP::accumulate_squared(const RawTensor &src, RawTensor &dst, uint32_t shift)
	{
	ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 \|\| dst.data_type() != DataType::S16);
	const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
	Tensor<int16_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<int16_t *>(dst.data()));
	tensor_operations::accumulate_squared(s, d, shift);
	}

	// Accumulate weighted
	void ReferenceCPP::accumulate_weighted(const RawTensor &src, RawTensor &dst, float alpha)
	{
	ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 \|\| dst.data_type() != DataType::U8);
	const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
	Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
	tensor_operations::accumulate_weighted(s, d, alpha);
	}

	// Arithmetic addition
	void ReferenceCPP::arithmetic_addition(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, ConvertPolicy convert_policy)
	{
	const TensorVariant s1 = TensorFactory::get_tensor(src1);
	const TensorVariant s2 = TensorFactory::get_tensor(src2);
	TensorVariant d = TensorFactory::get_tensor(dst);
	boost::apply_visitor(arithmetic_addition_visitor(convert_policy), s1, s2, d);
	}

	// Arithmetic subtraction
	void ReferenceCPP::arithmetic_subtraction(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, ConvertPolicy convert_policy)
	{
	const TensorVariant s1 = TensorFactory::get_tensor(src1);
	const TensorVariant s2 = TensorFactory::get_tensor(src2);
	TensorVariant d = TensorFactory::get_tensor(dst);
	boost::apply_visitor(arithmetic_subtraction_visitor(convert_policy), s1, s2, d);
	}

	// Bitwise and
	void ReferenceCPP::bitwise_and(const RawTensor &src1, const RawTensor &src2, RawTensor &dst)
	{
	ARM_COMPUTE_ERROR_ON(src1.data_type() != DataType::U8 \|\| src2.data_type() != DataType::U8 \|\| dst.data_type() != DataType::U8);
	const Tensor<uint8_t> s1(src1.shape(), src1.data_type(), src1.fixed_point_position(), reinterpret_cast<const uint8_t *>(src1.data()));
	const Tensor<uint8_t> s2(src2.shape(), src2.data_type(), src2.fixed_point_position(), reinterpret_cast<const uint8_t *>(src2.data()));
	Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
	tensor_operations::bitwise_and(s1, s2, d);
	}

	// Bitwise or
	void ReferenceCPP::bitwise_or(const RawTensor &src1, const RawTensor &src2, RawTensor &dst)
	{
	ARM_COMPUTE_ERROR_ON(src1.data_type() != DataType::U8 \|\| src2.data_type() != DataType::U8 \|\| dst.data_type() != DataType::U8);
	const Tensor<uint8_t> s1(src1.shape(), src1.data_type(), src1.fixed_point_position(), reinterpret_cast<const uint8_t *>(src1.data()));
	const Tensor<uint8_t> s2(src2.shape(), src2.data_type(), src2.fixed_point_position(), reinterpret_cast<const uint8_t *>(src2.data()));
	Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
	tensor_operations::bitwise_or(s1, s2, d);
	}

	// Bitwise xor
	void ReferenceCPP::bitwise_xor(const RawTensor &src1, const RawTensor &src2, RawTensor &dst)
	{
	ARM_COMPUTE_ERROR_ON(src1.data_type() != DataType::U8 \|\| src2.data_type() != DataType::U8 \|\| dst.data_type() != DataType::U8);
	const Tensor<uint8_t> s1(src1.shape(), src1.data_type(), src1.fixed_point_position(), reinterpret_cast<const uint8_t *>(src1.data()));
	const Tensor<uint8_t> s2(src2.shape(), src2.data_type(), src2.fixed_point_position(), reinterpret_cast<const uint8_t *>(src2.data()));
	Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
	tensor_operations::bitwise_xor(s1, s2, d);
	}

	// Bitwise not
	void ReferenceCPP::bitwise_not(const RawTensor &src, RawTensor &dst)
	{
	ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 \|\| dst.data_type() != DataType::U8);
	const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
	Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
	tensor_operations::bitwise_not(s, d);
	}

	// Box3x3 filter
	void ReferenceCPP::box3x3(const RawTensor &src, RawTensor &dst, BorderMode border_mode, uint8_t constant_border_value)
	{
	ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 \|\| dst.data_type() != DataType::U8);
	const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
	Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
	tensor_operations::box3x3(s, d, border_mode, constant_border_value);
	}

	// Depth conversion
	void ReferenceCPP::depth_convert(const RawTensor &src, RawTensor &dst, ConvertPolicy policy, uint32_t shift)
	{
	const TensorVariant s = TensorFactory::get_tensor(src);
	TensorVariant d = TensorFactory::get_tensor(dst);
	boost::apply_visitor(tensor_visitors::depth_convert_visitor(policy, shift), s, d);
	}

	// Gaussian3x3 filter
	void ReferenceCPP::gaussian3x3(const RawTensor &src, RawTensor &dst, BorderMode border_mode, uint8_t constant_border_value)
	{
	ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 \|\| dst.data_type() != DataType::U8);
	const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
	Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
	tensor_operations::gaussian3x3(s, d, border_mode, constant_border_value);
	}

	// Gaussian5x5 filter
	void ReferenceCPP::gaussian5x5(const RawTensor &src, RawTensor &dst, BorderMode border_mode, uint8_t constant_border_value)
	{
	ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 \|\| dst.data_type() != DataType::U8);
	const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
	Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
	tensor_operations::gaussian5x5(s, d, border_mode, constant_border_value);
	}

	// GEMM
	void ReferenceCPP::gemm(const RawTensor &src1, const RawTensor &src2, const RawTensor &src3,
	RawTensor &dst, float alpha, float beta)
	{
	const TensorVariant s1 = TensorFactory::get_tensor(src1);
	const TensorVariant s2 = TensorFactory::get_tensor(src2);
	const TensorVariant s3 = TensorFactory::get_tensor(src3);
	TensorVariant d = TensorFactory::get_tensor(dst);

	boost::apply_visitor(tensor_visitors::gemm_visitor(s1, s2, s3, alpha, beta), d);
	}
	// Non linear filter
	void ReferenceCPP::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)
	{
	ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 \|\| dst.data_type() != DataType::U8);
	const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
	Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
	tensor_operations::non_linear_filter(s, d, function, mask_size, pattern, mask, border_mode, constant_border_value);
	}

	// Pixel-wise multiplication
	void ReferenceCPP::pixel_wise_multiplication(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, float scale, ConvertPolicy convert_policy, RoundingPolicy rounding_policy)
	{
	const TensorVariant s1 = TensorFactory::get_tensor(src1);
	const TensorVariant s2 = TensorFactory::get_tensor(src2);
	TensorVariant d = TensorFactory::get_tensor(dst);
	boost::apply_visitor(pixel_wise_multiplication_visitor(scale, convert_policy, rounding_policy), s1, s2, d);
	}

	// Fixed-point Pixel-wise multiplication
	void ReferenceCPP::fixed_point_pixel_wise_multiplication(const RawTensor &src1, const RawTensor &src2, RawTensor &dst, float scale, ConvertPolicy convert_policy, RoundingPolicy rounding_policy)
	{
	const TensorVariant s1 = TensorFactory::get_tensor(src1);
	const TensorVariant s2 = TensorFactory::get_tensor(src2);
	TensorVariant d = TensorFactory::get_tensor(dst);
	boost::apply_visitor(tensor_visitors::fixed_point_pixel_wise_multiplication_visitor(s1, s2, scale, convert_policy, rounding_policy), d);
	}

	// Table lookup
	template <typename T>
	void ReferenceCPP::table_lookup(const RawTensor &src, RawTensor &dst, std::map<T, T> &lut)
	{
	const TensorVariant s = TensorFactory::get_tensor(src);
	TensorVariant d = TensorFactory::get_tensor(dst);
	boost::apply_visitor(tensor_visitors::table_lookup<T>(s, lut), d);
	}
	#ifndef DOXYGEN_SKIP_THIS
	template void arm_compute::test::validation::ReferenceCPP::table_lookup<uint8_t>(const RawTensor &src, RawTensor &dst, std::map<uint8_t, uint8_t> &lut);
	template void arm_compute::test::validation::ReferenceCPP::table_lookup<int16_t>(const RawTensor &src, RawTensor &dst, std::map<int16_t, int16_t> &lut);
	#endif /* DOXYGEN_SKIP_THIS */

	// Threshold
	void ReferenceCPP::threshold(const RawTensor &src, RawTensor &dst, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper)
	{
	ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 \|\| dst.data_type() != DataType::U8);
	const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
	Tensor<uint8_t> d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
	tensor_operations::threshold(s, d, threshold, false_value, true_value, type, upper);
	}

	// Activation layer
	void ReferenceCPP::activation_layer(const RawTensor &input, RawTensor &output, ActivationLayerInfo act_info)
	{
	const TensorVariant s = TensorFactory::get_tensor(input);
	TensorVariant d = TensorFactory::get_tensor(output);
	boost::apply_visitor(tensor_visitors::activation_layer_visitor(s, act_info), d);
	}

	// Batch Normalization Layer
	void ReferenceCPP::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)
	{
	const TensorVariant s = TensorFactory::get_tensor(src);
	TensorVariant d = TensorFactory::get_tensor(dst);
	const TensorVariant m = TensorFactory::get_tensor(mean);
	const TensorVariant v = TensorFactory::get_tensor(var);
	const TensorVariant b = TensorFactory::get_tensor(beta);
	const TensorVariant g = TensorFactory::get_tensor(gamma);
	boost::apply_visitor(tensor_visitors::batch_normalization_layer_visitor(s, m, v, b, g, epsilon, fixed_point_position), d);
	}

	// Convolution Layer
	void ReferenceCPP::convolution_layer(const RawTensor &src, const RawTensor &weights, const RawTensor &bias, RawTensor &dst, const PadStrideInfo &conv_info)
	{
	const TensorVariant s = TensorFactory::get_tensor(src);
	const TensorVariant w = TensorFactory::get_tensor(weights);
	const TensorVariant b = TensorFactory::get_tensor(bias);
	TensorVariant d = TensorFactory::get_tensor(dst);
	boost::apply_visitor(tensor_visitors::convolution_layer_visitor(s, w, b, conv_info), d);
	}

	// Depth concatenate layer
	void ReferenceCPP::depth_concatenate_layer(const std::vector<std::unique_ptr<RawTensor>> &srcs, RawTensor &dst)
	{
	std::vector<TensorVariant> ss;
	ss.resize(srcs.size());
	std::transform(srcs.begin(), srcs.end(), ss.begin(), [](std::unique_ptr<RawTensor> const & t)
	{
	return TensorFactory::get_tensor(*t);
	});
	TensorVariant d = TensorFactory::get_tensor(dst);
	boost::apply_visitor(tensor_visitors::depth_concatenate_layer_visitor(ss), d);
	}

	// Fully connected layer
	void ReferenceCPP::fully_connected_layer(const RawTensor &src, const RawTensor &weights, const RawTensor &bias, RawTensor &dst)
	{
	const TensorVariant s = TensorFactory::get_tensor(src);
	const TensorVariant w = TensorFactory::get_tensor(weights);
	const TensorVariant b = TensorFactory::get_tensor(bias);
	TensorVariant d = TensorFactory::get_tensor(dst);
	boost::apply_visitor(tensor_visitors::fully_connected_layer_visitor(s, w, b), d);
	}

	// Normalization Layer
	void ReferenceCPP::normalization_layer(const RawTensor &src, RawTensor &dst, NormalizationLayerInfo norm_info)
	{
	const TensorVariant s = TensorFactory::get_tensor(src);
	TensorVariant d = TensorFactory::get_tensor(dst);
	boost::apply_visitor(tensor_visitors::normalization_layer_visitor(s, norm_info), d);
	}

	// Pooling Layer
	void ReferenceCPP::pooling_layer(const RawTensor &src, RawTensor &dst, PoolingLayerInfo pool_info, int fixed_point_position)
	{
	const TensorVariant s = TensorFactory::get_tensor(src);
	TensorVariant d = TensorFactory::get_tensor(dst);
	boost::apply_visitor(tensor_visitors::pooling_layer_visitor(s, pool_info, fixed_point_position), d);
	}

	// ROI Pooling Layer
	void ReferenceCPP::roi_pooling_layer(const RawTensor &src, RawTensor &dst, const std::vector<ROI> &rois, const ROIPoolingLayerInfo &pool_info)
	{
	const TensorVariant s = TensorFactory::get_tensor(src);
	TensorVariant d = TensorFactory::get_tensor(dst);
	boost::apply_visitor(tensor_visitors::roi_pooling_layer_visitor(s, rois, pool_info), d);
	}

	// Softmax Layer
	void ReferenceCPP::softmax_layer(const RawTensor &src, RawTensor &dst)
	{
	const TensorVariant s = TensorFactory::get_tensor(src);
	TensorVariant d = TensorFactory::get_tensor(dst);
	boost::apply_visitor(tensor_visitors::softmax_layer_visitor(s), d);
	}

	// Fixed point operation
	void ReferenceCPP::fixed_point_operation(const RawTensor &src, RawTensor &dst, FixedPointOp op)
	{
	const TensorVariant s = TensorFactory::get_tensor(src);
	TensorVariant d = TensorFactory::get_tensor(dst);
	boost::apply_visitor(tensor_visitors::fixed_point_operation_visitor(s, op), d);
	}

	} // namespace validation
	} // namespace test
	} // namespace arm_compute