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Diffstat (limited to 'src/core/CL/kernels/CLConvolutionKernel.cpp')
| -rw-r--r-- | src/core/CL/kernels/CLConvolutionKernel.cpp | 330 |
1 files changed, 330 insertions, 0 deletions
diff --git a/src/core/CL/kernels/CLConvolutionKernel.cpp b/src/core/CL/kernels/CLConvolutionKernel.cpp new file mode 100644 index 0000000000..bdfe398a1d --- /dev/null +++ b/src/core/CL/kernels/CLConvolutionKernel.cpp @@ -0,0 +1,330 @@ +/* + * Copyright (c) 2016, 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 "arm_compute/core/CL/kernels/CLConvolutionKernel.h" + +#include "arm_compute/core/CL/CLHelpers.h" +#include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/CL/ICLKernel.h" +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/CL/OpenCL.h" +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/core/Validate.h" + +#include <set> +#include <sstream> +#include <string> + +using namespace arm_compute; + +#define MAX_MATRIX_SIZE 81 + +/****************************************************************************************\ + * Square Convolution * +\****************************************************************************************/ + +template <unsigned int matrix_size> +BorderSize CLConvolutionKernel<matrix_size>::border_size() const +{ + return BorderSize(matrix_size / 2); +} + +template <unsigned int matrix_size> +void CLConvolutionKernel<matrix_size>::configure(const ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, bool border_undefined) +{ + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8); + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::S16); + ARM_COMPUTE_ERROR_ON(conv == nullptr); + + _input = input; + _output = output; + + std::stringstream kernel_name; + std::set<std::string> options; + kernel_name << "convolution" << matrix_size << "x" << matrix_size << "_static"; + + if(scale == 0) + { + scale = calculate_matrix_scale(conv, matrix_size); + } + + for(unsigned int i = 0; i < matrix_size * matrix_size; i++) + { + std::stringstream mat_str; + mat_str << "-DMAT" << i << "=" << conv[i]; + options.insert(mat_str.str()); + } + + options.insert("-DSCALE=" + val_to_string(scale)); + + DataType data_type = data_type_for_convolution_matrix(conv, matrix_size * matrix_size); + options.insert("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type)); + + std::stringstream out_type; + out_type << "-DDATA_TYPE_OUT=" << get_cl_type_from_data_type(output->info()->data_type()); + options.insert(out_type.str()); + + _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name.str(), options)); + + // Configure kernel window + constexpr unsigned int num_elems_processed_per_iteration = 8; + constexpr unsigned int num_elems_written_per_iteration = 8; + constexpr unsigned int num_elems_read_per_iteration = 16; + constexpr unsigned int num_rows_read_per_iteration = matrix_size; + + Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration), border_undefined, border_size()); + + AccessWindowRectangle input_access(input->info(), -border_size().left, -border_size().top, num_elems_read_per_iteration, num_rows_read_per_iteration); + AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration); + + update_window_and_padding(win, input_access, output_access); + + output_access.set_valid_region(win, input->info()->valid_region(), border_undefined, border_size()); + + ICLKernel::configure(win); +} + +/****************************************************************************************\ + * Separable Convolution * +\****************************************************************************************/ +template <unsigned int matrix_size> +CLSeparableConvolutionHorKernel<matrix_size>::CLSeparableConvolutionHorKernel() + : _border_size(0) +{ +} + +template <unsigned int matrix_size> +BorderSize CLSeparableConvolutionHorKernel<matrix_size>::border_size() const +{ + return _border_size; +} + +template <unsigned int matrix_size> +void CLSeparableConvolutionHorKernel<matrix_size>::configure(const ICLTensor *input, ICLTensor *output, const int16_t *conv, bool border_undefined) +{ + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8); + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U16, DataType::S16, DataType::S32); + + ARM_COMPUTE_ERROR_ON((matrix_size != 5) && (matrix_size != 7) && (matrix_size != 9)); + + _input = input; + _output = output; + _border_size = BorderSize(border_undefined ? 0 : matrix_size / 2, matrix_size / 2); + + // Set build options + std::set<std::string> build_opts; + + int16_t mat[matrix_size * matrix_size] = { 0 }; + memcpy(mat, conv, matrix_size * sizeof(int16_t)); + + for(unsigned int j = 0; j < matrix_size * matrix_size; j++) + { + build_opts.insert("-DMAT" + val_to_string(j) + "=" + val_to_string(mat[j])); + } + + build_opts.insert("-DSCALE=0"); + + build_opts.insert("-DDATA_TYPE=" + get_cl_type_from_data_type(output->info()->data_type())); + + // Create kernel + _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("convolution_separable1x" + val_to_string(matrix_size) + "_static", build_opts)); + + // Configure kernel window + constexpr unsigned int num_elems_processed_per_iteration = 8; + constexpr unsigned int num_elems_read_per_iteration = 16; + constexpr unsigned int num_elems_written_per_iteration = 8; + + Window win = calculate_max_window_horizontal(*input->info(), Steps(num_elems_processed_per_iteration), border_undefined, border_size()); + + AccessWindowHorizontal input_access(input->info(), -border_size().left, num_elems_read_per_iteration); + AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration); + + update_window_and_padding(win, input_access, output_access); + + output_access.set_valid_region(win, input->info()->valid_region(), border_undefined, border_size()); + + ICLKernel::configure(win); +} + +template <unsigned int matrix_size> +BorderSize CLSeparableConvolutionVertKernel<matrix_size>::border_size() const +{ + return BorderSize(matrix_size / 2, 0); +} + +template <unsigned int matrix_size> +void CLSeparableConvolutionVertKernel<matrix_size>::configure(const ICLTensor *input, ICLTensor *output, + const int16_t *conv, uint32_t scale, bool border_undefined, DataType data_type) +{ + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U16, DataType::S16, DataType::S32); + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::S16); + ARM_COMPUTE_ERROR_ON((matrix_size != 5) && (matrix_size != 7) && (matrix_size != 9)); + ARM_COMPUTE_ERROR_ON(scale == 0); + + _input = input; + _output = output; + + std::set<std::string> build_opts; + + int16_t mat[matrix_size * matrix_size] = { 0 }; + memcpy(mat + matrix_size, conv, matrix_size * sizeof(int16_t)); + + for(unsigned int j = 0; j < matrix_size * matrix_size; j++) + { + build_opts.insert("-DMAT" + val_to_string(j) + "=" + val_to_string(mat[j])); + } + + build_opts.insert("-DSCALE=" + val_to_string(scale)); + + build_opts.insert("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); + + build_opts.insert("-DCOMPUTE_TYPE=" + get_cl_type_from_data_type(data_type)); + + std::stringstream out_type; + out_type << "-DDATA_TYPE_OUT=" << get_cl_type_from_data_type(output->info()->data_type()); + build_opts.insert(out_type.str()); + + // Create kernel + _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("convolution_separable" + val_to_string(matrix_size) + "x1_static", build_opts)); + + // Configure kernel window + constexpr unsigned int num_elems_processed_per_iteration = 8; + constexpr unsigned int num_elems_written_per_iteration = 8; + constexpr unsigned int num_elems_read_per_iteration = 8; + constexpr unsigned int num_rows_read_per_iteration = matrix_size; + + Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration), border_undefined, border_size()); + + AccessWindowRectangle input_access(input->info(), 0, -border_size().top, num_elems_read_per_iteration, num_rows_read_per_iteration); + AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration); + + update_window_and_padding(win, input_access, output_access); + + output_access.set_valid_region(win, input->info()->valid_region(), border_undefined, border_size()); + + ICLKernel::configure(win); +} + +/****************************************************************************************\ + * Rectangle Convolution * +\****************************************************************************************/ + +CLConvolutionRectangleKernel::CLConvolutionRectangleKernel() + : _border_size(0), _input(nullptr), _output(nullptr) +{ +} + +BorderSize CLConvolutionRectangleKernel::border_size() const +{ + return _border_size; +} + +void CLConvolutionRectangleKernel::configure(const ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t width, uint32_t height, uint32_t scale, bool border_undefined) +{ + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8); + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::S16); + ARM_COMPUTE_ERROR_ON(nullptr == conv); + ARM_COMPUTE_ERROR_ON(3 != width && 5 != width && 7 != width && 9 != width); + ARM_COMPUTE_ERROR_ON(3 != height && 5 != height && 7 != height && 9 != height); + ARM_COMPUTE_ERROR_ON(0 == scale); + + _input = input; + _output = output; + _border_size = BorderSize(height / 2, width / 2); + + std::set<std::string> options; + + std::stringstream output_type; + output_type << "-DDATA_TYPE_OUT=" << get_cl_type_from_data_type(output->info()->data_type()); + options.insert(output_type.str()); + + uint32_t matrix_size = width * height; + + int16_t mat[MAX_MATRIX_SIZE] = { 0 }; + + memcpy(mat, conv, matrix_size * sizeof(int16_t)); + + for(unsigned int j = 0; j < MAX_MATRIX_SIZE; j++) + { + options.insert("-DMAT" + val_to_string(j) + "=" + val_to_string(mat[j])); + } + + options.insert("-DSCALE=" + val_to_string(scale)); + + DataType data_type = data_type_for_convolution_matrix(conv, matrix_size); + options.insert("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type)); + + options.insert("-DMATRIX_WIDTH=" + val_to_string(width)); + options.insert("-DMATRIX_HEIGHT=" + val_to_string(height)); + + _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("convolution_rectangle", options)); + + // Configure kernel window + constexpr unsigned int num_elems_processed_per_iteration = 8; + constexpr unsigned int num_elems_read_per_iteration = 16; + constexpr unsigned int num_elems_written_per_iteration = 8; + const unsigned int num_rows_read_per_iteration = height; + + Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration), border_undefined, border_size()); + + AccessWindowRectangle input_access(input->info(), -border_size().left, -border_size().top, num_elems_read_per_iteration, num_rows_read_per_iteration); + AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration); + + update_window_and_padding(win, input_access, output_access); + + output_access.set_valid_region(win, input->info()->valid_region(), border_undefined, border_size()); + + ICLKernel::configure(win); +} + +void CLConvolutionRectangleKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); + + Window slice = window.first_slice_window_2D(); + + do + { + unsigned int idx = 0; + add_2D_tensor_argument(idx, _input, slice); + add_2D_tensor_argument(idx, _output, slice); + enqueue(queue, *this, slice); + } + while(window.slide_window_slice_2D(slice)); +} + +template class arm_compute::CLConvolutionKernel<3>; +template class arm_compute::CLConvolutionKernel<5>; +template class arm_compute::CLConvolutionKernel<7>; +template class arm_compute::CLConvolutionKernel<9>; +template class arm_compute::CLSeparableConvolutionVertKernel<5>; +template class arm_compute::CLSeparableConvolutionVertKernel<7>; +template class arm_compute::CLSeparableConvolutionVertKernel<9>; +template class arm_compute::CLSeparableConvolutionHorKernel<5>; +template class arm_compute::CLSeparableConvolutionHorKernel<7>; +template class arm_compute::CLSeparableConvolutionHorKernel<9>; |