| /* |
| * 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/CLKernelLibrary.h" |
| |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Utils.h" |
| |
| #include <fstream> |
| #include <iostream> |
| #include <utility> |
| #include <vector> |
| |
| using namespace arm_compute; |
| |
| Program::Program() |
| : _context(), _device(), _is_binary(false), _name(), _source(), _binary() |
| { |
| } |
| |
| Program::Program(cl::Context context, std::string name, std::string source) |
| : _context(std::move(context)), _device(), _is_binary(false), _name(std::move(name)), _source(std::move(source)), _binary() |
| { |
| } |
| |
| Program::Program(cl::Context context, cl::Device device, std::string name, std::vector<unsigned char> binary) |
| : _context(std::move(context)), _device(std::move(device)), _is_binary(true), _name(std::move(name)), _source(), _binary(std::move(binary)) |
| { |
| } |
| |
| Program::operator cl::Program() const |
| { |
| if(_is_binary) |
| { |
| return cl::Program(_context, { _device }, { _binary }); |
| } |
| else |
| { |
| return cl::Program(_context, _source, false); |
| } |
| } |
| |
| bool Program::build(const cl::Program &program, const std::string &build_options) |
| { |
| try |
| { |
| return program.build(build_options.c_str()) == CL_SUCCESS; |
| } |
| catch(const cl::Error &e) |
| { |
| cl_int err = CL_SUCCESS; |
| const auto build_info = program.getBuildInfo<CL_PROGRAM_BUILD_LOG>(&err); |
| |
| for(auto &pair : build_info) |
| { |
| std::cerr << pair.second << std::endl; |
| } |
| |
| return false; |
| } |
| } |
| |
| cl::Program Program::build(const std::string &build_options) const |
| { |
| cl::Program cl_program = static_cast<cl::Program>(*this); |
| build(cl_program, build_options); |
| return cl_program; |
| } |
| |
| Kernel::Kernel() |
| : _name(), _kernel() |
| { |
| } |
| |
| Kernel::Kernel(std::string name, const cl::Program &program) |
| : _name(std::move(name)), |
| _kernel(cl::Kernel(program, _name.c_str())) |
| { |
| } |
| |
| const std::map<std::string, std::string> CLKernelLibrary::_kernel_program_map = |
| { |
| { "absdiff", "absdiff.cl" }, |
| { "accumulate", "accumulate.cl" }, |
| { "accumulate_squared", "accumulate.cl" }, |
| { "accumulate_weighted", "accumulate.cl" }, |
| { "activation_layer", "activation_layer.cl" }, |
| { "arithmetic_add", "arithmetic_op.cl" }, |
| { "arithmetic_sub", "arithmetic_op.cl" }, |
| { "bitwise_or", "bitwise_op.cl" }, |
| { "bitwise_and", "bitwise_op.cl" }, |
| { "bitwise_xor", "bitwise_op.cl" }, |
| { "bitwise_not", "bitwise_op.cl" }, |
| { "channel_combine_NV", "channel_combine.cl" }, |
| { "channel_combine_RGB888", "channel_combine.cl" }, |
| { "channel_combine_RGBA8888", "channel_combine.cl" }, |
| { "channel_combine_UYVY422", "channel_combine.cl" }, |
| { "channel_combine_YUYV422", "channel_combine.cl" }, |
| { "channel_extract_NV12", "channel_extract.cl" }, |
| { "channel_extract_NV21", "channel_extract.cl" }, |
| { "channel_extract_RGB888", "channel_extract.cl" }, |
| { "channel_extract_RGBA8888", "channel_extract.cl" }, |
| { "channel_extract_UYVY422", "channel_extract.cl" }, |
| { "channel_extract_YUYV422", "channel_extract.cl" }, |
| { "combine_gradients_L1", "canny.cl" }, |
| { "combine_gradients_L2", "canny.cl" }, |
| { "concatenate_depth", "concatenate.cl" }, |
| { "convolution_rectangle", "convolution_rectangle.cl" }, |
| { "col2im", "convolution_layer.cl" }, |
| { "convolution3x3_static", "convolution3x3.cl" }, |
| { "convolution5x5_static", "convolution5x5.cl" }, |
| { "convolution7x7_static", "convolution7x7.cl" }, |
| { "convolution9x9_static", "convolution9x9.cl" }, |
| { "convolution_separable1x5_static", "convolution5x5.cl" }, |
| { "convolution_separable5x1_static", "convolution5x5.cl" }, |
| { "convolution_separable1x7_static", "convolution7x7.cl" }, |
| { "convolution_separable7x1_static", "convolution7x7.cl" }, |
| { "convolution_separable1x9_static", "convolution9x9.cl" }, |
| { "convolution_separable9x1_static", "convolution9x9.cl" }, |
| { "convert_depth_down", "depth_convert.cl" }, |
| { "convert_depth_up", "depth_convert.cl" }, |
| { "copy_plane", "channel_extract.cl" }, |
| { "copy_planes_3p", "channel_combine.cl" }, |
| { "copy_to_keypoint", "fast_corners.cl" }, |
| { "derivative", "derivative.cl" }, |
| { "dilate", "dilate.cl" }, |
| { "erode", "erode.cl" }, |
| { "fast_corners", "fast_corners.cl" }, |
| { "fill_image_borders_constant", "fill_border.cl" }, |
| { "fill_image_borders_replicate", "fill_border.cl" }, |
| { "finalize", "optical_flow_pyramid_lk.cl" }, |
| { "gaussian1x5_sub_x", "gaussian_pyramid.cl" }, |
| { "gaussian5x1_sub_y", "gaussian_pyramid.cl" }, |
| { "gemm_accumulate_biases_f16", "gemm.cl" }, |
| { "gemm_accumulate_biases_f32", "gemm.cl" }, |
| { "gemm_interleave4x4_8bit", "gemm.cl" }, |
| { "gemm_interleave4x4_16bit", "gemm.cl" }, |
| { "gemm_interleave4x4_32bit", "gemm.cl" }, |
| { "gemm_ma_f16", "gemm.cl" }, |
| { "gemm_ma_f32", "gemm.cl" }, |
| { "gemm_mm_u8", "gemm.cl" }, |
| { "gemm_mm_f16", "gemm.cl" }, |
| { "gemm_mm_f32_midgard", "gemm.cl" }, |
| { "gemm_mm_f32_bifrost", "gemm.cl" }, |
| { "gemm_vm_f16", "gemm.cl" }, |
| { "gemm_vm_f32", "gemm.cl" }, |
| { "gemm_lc_vm_f32", "gemm.cl" }, |
| { "gemm_transpose1x16_u8", "gemm.cl" }, |
| { "gemm_transpose1x8_f16", "gemm.cl" }, |
| { "gemm_transpose1x4_f32", "gemm.cl" }, |
| { "harris_score_3x3", "harris_corners.cl" }, |
| { "harris_score_5x5", "harris_corners.cl" }, |
| { "harris_score_7x7", "harris_corners.cl" }, |
| { "hist_border_kernel", "histogram.cl" }, |
| { "hist_border_kernel_fixed", "histogram.cl" }, |
| { "hist_local_kernel", "histogram.cl" }, |
| { "hist_local_kernel_fixed", "histogram.cl" }, |
| { "hog_block_normalization", "hog.cl" }, |
| { "hog_detector", "hog.cl" }, |
| { "hog_orientation_binning", "hog.cl" }, |
| { "hysteresis", "canny.cl" }, |
| { "im2col_generic", "convolution_layer.cl" }, |
| { "im2col_reduced", "convolution_layer.cl" }, |
| { "init_level", "optical_flow_pyramid_lk.cl" }, |
| { "init_level_max", "optical_flow_pyramid_lk.cl" }, |
| { "init_level_max_initial_estimate", "optical_flow_pyramid_lk.cl" }, |
| { "integral_horizontal", "integral_image.cl" }, |
| { "integral_vertical", "integral_image.cl" }, |
| { "IYUV_to_NV12_bt709", "color_convert.cl" }, |
| { "IYUV_to_RGB888_bt709", "color_convert.cl" }, |
| { "IYUV_to_RGBA8888_bt709", "color_convert.cl" }, |
| { "IYUV_to_YUV444_bt709", "color_convert.cl" }, |
| { "lktracker_stage0", "optical_flow_pyramid_lk.cl" }, |
| { "lktracker_stage1", "optical_flow_pyramid_lk.cl" }, |
| { "magnitude_phase", "magnitude_phase.cl" }, |
| { "mean_stddev_accumulate", "mean_stddev.cl" }, |
| { "minmax", "minmaxloc.cl" }, |
| { "minmax_border", "minmaxloc.cl" }, |
| { "minmaxloc", "minmaxloc.cl" }, |
| { "non_linear_filter_box3x3", "non_linear_filter3x3.cl" }, |
| { "non_linear_filter_cross3x3", "non_linear_filter3x3.cl" }, |
| { "non_linear_filter_disk3x3", "non_linear_filter3x3.cl" }, |
| { "non_linear_filter_box5x5", "non_linear_filter5x5.cl" }, |
| { "non_linear_filter_cross5x5", "non_linear_filter5x5.cl" }, |
| { "non_linear_filter_disk5x5", "non_linear_filter5x5.cl" }, |
| { "non_max_suppression", "nonmax.cl" }, |
| { "normalization_layer_cross_map", "normalization_layer.cl" }, |
| { "normalization_layer_in_map_1D", "normalization_layer.cl" }, |
| { "batchnormalization_layer", "batchnormalization_layer.cl" }, |
| { "NV12_to_IYUV_bt709", "color_convert.cl" }, |
| { "NV12_to_RGB888_bt709", "color_convert.cl" }, |
| { "NV12_to_RGBA8888_bt709", "color_convert.cl" }, |
| { "NV12_to_YUV444_bt709", "color_convert.cl" }, |
| { "NV21_to_IYUV_bt709", "color_convert.cl" }, |
| { "NV21_to_RGB888_bt709", "color_convert.cl" }, |
| { "NV21_to_RGBA8888_bt709", "color_convert.cl" }, |
| { "NV21_to_YUV444_bt709", "color_convert.cl" }, |
| { "pixelwise_mul_float", "pixelwise_mul_float.cl" }, |
| { "pixelwise_mul_int", "pixelwise_mul_int.cl" }, |
| { "pooling_layer_2", "pooling_layer.cl" }, |
| { "pooling_layer_3", "pooling_layer.cl" }, |
| { "remap_nearest_neighbour", "remap.cl" }, |
| { "remap_bilinear", "remap.cl" }, |
| { "reshape_to_columns", "convolution_layer.cl" }, |
| { "RGB888_to_IYUV_bt709", "color_convert.cl" }, |
| { "RGB888_to_NV12_bt709", "color_convert.cl" }, |
| { "RGB888_to_RGBA8888_bt709", "color_convert.cl" }, |
| { "RGB888_to_YUV444_bt709", "color_convert.cl" }, |
| { "RGBA8888_to_IYUV_bt709", "color_convert.cl" }, |
| { "RGBA8888_to_NV12_bt709", "color_convert.cl" }, |
| { "RGBA8888_to_RGB888_bt709", "color_convert.cl" }, |
| { "RGBA8888_to_YUV444_bt709", "color_convert.cl" }, |
| { "scale_nearest_neighbour", "scale.cl" }, |
| { "scale_bilinear", "scale.cl" }, |
| { "scharr3x3", "scharr_filter.cl" }, |
| { "sobel3x3", "sobel_filter.cl" }, |
| { "sobel_separable5x1", "sobel_filter.cl" }, |
| { "sobel_separable1x5", "sobel_filter.cl" }, |
| { "sobel_separable7x1", "sobel_filter.cl" }, |
| { "sobel_separable1x7", "sobel_filter.cl" }, |
| { "softmax_layer_max", "softmax_layer.cl" }, |
| { "softmax_layer_shift_exp_sum", "softmax_layer.cl" }, |
| { "softmax_layer_norm", "softmax_layer.cl" }, |
| { "suppress_non_maximum", "canny.cl" }, |
| { "tablelookup_U8", "tablelookup.cl" }, |
| { "tablelookup_S16", "tablelookup.cl" }, |
| { "threshold_binary", "threshold.cl" }, |
| { "threshold_range", "threshold.cl" }, |
| { "transpose", "transpose.cl" }, |
| { "UYVY422_to_IYUV_bt709", "color_convert.cl" }, |
| { "UYVY422_to_NV12_bt709", "color_convert.cl" }, |
| { "UYVY422_to_RGB888_bt709", "color_convert.cl" }, |
| { "UYVY422_to_RGBA8888_bt709", "color_convert.cl" }, |
| { "warp_affine_nearest_neighbour", "warp_affine.cl" }, |
| { "warp_affine_bilinear", "warp_affine.cl" }, |
| { "warp_perspective_nearest_neighbour", "warp_perspective.cl" }, |
| { "warp_perspective_bilinear", "warp_perspective.cl" }, |
| { "YUYV422_to_IYUV_bt709", "color_convert.cl" }, |
| { "YUYV422_to_NV12_bt709", "color_convert.cl" }, |
| { "YUYV422_to_RGB888_bt709", "color_convert.cl" }, |
| { "YUYV422_to_RGBA8888_bt709", "color_convert.cl" }, |
| }; |
| |
| const std::map<std::string, std::string> CLKernelLibrary::_program_source_map = |
| { |
| #ifdef EMBEDDED_KERNELS |
| { |
| "absdiff.cl", |
| #include "./cl_kernels/absdiff.clembed" |
| }, |
| { |
| "accumulate.cl", |
| #include "./cl_kernels/accumulate.clembed" |
| }, |
| { |
| "activation_layer.cl", |
| #include "./cl_kernels/activation_layer.clembed" |
| }, |
| { |
| "arithmetic_op.cl", |
| #include "./cl_kernels/arithmetic_op.clembed" |
| }, |
| { |
| "bitwise_op.cl", |
| #include "./cl_kernels/bitwise_op.clembed" |
| }, |
| { |
| "canny.cl", |
| #include "./cl_kernels/canny.clembed" |
| }, |
| { |
| "channel_combine.cl", |
| #include "./cl_kernels/channel_combine.clembed" |
| }, |
| { |
| "channel_extract.cl", |
| #include "./cl_kernels/channel_extract.clembed" |
| }, |
| { |
| "concatenate.cl", |
| #include "./cl_kernels/concatenate.clembed" |
| }, |
| { |
| "color_convert.cl", |
| #include "./cl_kernels/color_convert.clembed" |
| }, |
| { |
| "convolution3x3.cl", |
| #include "./cl_kernels/convolution3x3.clembed" |
| }, |
| { |
| "convolution5x5.cl", |
| #include "./cl_kernels/convolution5x5.clembed" |
| }, |
| { |
| "convolution7x7.cl", |
| #include "./cl_kernels/convolution7x7.clembed" |
| }, |
| { |
| "convolution9x9.cl", |
| #include "./cl_kernels/convolution9x9.clembed" |
| }, |
| { |
| "convolution_layer.cl", |
| #include "./cl_kernels/convolution_layer.clembed" |
| }, |
| { |
| "convolution_rectangle.cl", |
| #include "./cl_kernels/convolution_rectangle.clembed" |
| }, |
| { |
| "depth_convert.cl", |
| #include "./cl_kernels/depth_convert.clembed" |
| }, |
| { |
| "derivative.cl", |
| #include "./cl_kernels/derivative.clembed" |
| }, |
| { |
| "dilate.cl", |
| #include "./cl_kernels/dilate.clembed" |
| }, |
| { |
| "erode.cl", |
| #include "./cl_kernels/erode.clembed" |
| }, |
| { |
| "fast_corners.cl", |
| #include "./cl_kernels/fast_corners.clembed" |
| }, |
| { |
| "fill_border.cl", |
| #include "./cl_kernels/fill_border.clembed" |
| }, |
| { |
| "gaussian_pyramid.cl", |
| #include "./cl_kernels/gaussian_pyramid.clembed" |
| }, |
| { |
| "gemm.cl", |
| #include "./cl_kernels/gemm.clembed" |
| }, |
| { |
| "harris_corners.cl", |
| #include "./cl_kernels/harris_corners.clembed" |
| }, |
| { |
| "helpers.h", |
| #include "./cl_kernels/helpers.hembed" |
| }, |
| { |
| "histogram.cl", |
| #include "./cl_kernels/histogram.clembed" |
| }, |
| { |
| "hog.cl", |
| #include "./cl_kernels/hog.clembed" |
| }, |
| { |
| "integral_image.cl", |
| #include "./cl_kernels/integral_image.clembed" |
| }, |
| { |
| "magnitude_phase.cl", |
| #include "./cl_kernels/magnitude_phase.clembed" |
| }, |
| { |
| "mean_stddev.cl", |
| #include "./cl_kernels/mean_stddev.clembed" |
| }, |
| { |
| "minmaxloc.cl", |
| #include "./cl_kernels/minmaxloc.clembed" |
| }, |
| { |
| "non_linear_filter3x3.cl", |
| #include "./cl_kernels/non_linear_filter3x3.clembed" |
| }, |
| { |
| "non_linear_filter5x5.cl", |
| #include "./cl_kernels/non_linear_filter5x5.clembed" |
| }, |
| { |
| "non_linear_filter_helpers.h", |
| #include "./cl_kernels/non_linear_filter_helpers.hembed" |
| }, |
| { |
| "nonmax.cl", |
| #include "./cl_kernels/nonmax.clembed" |
| }, |
| { |
| "normalization_layer.cl", |
| #include "./cl_kernels/normalization_layer.clembed" |
| }, |
| { |
| "batchnormalization_layer.cl", |
| #include "./cl_kernels/batchnormalization_layer.clembed" |
| }, |
| { |
| "optical_flow_pyramid_lk.cl", |
| #include "./cl_kernels/optical_flow_pyramid_lk.clembed" |
| }, |
| { |
| "pixelwise_mul_float.cl", |
| #include "./cl_kernels/pixelwise_mul_float.clembed" |
| }, |
| { |
| "pixelwise_mul_int.cl", |
| #include "./cl_kernels/pixelwise_mul_int.clembed" |
| }, |
| { |
| "pooling_layer.cl", |
| #include "./cl_kernels/pooling_layer.clembed" |
| }, |
| { |
| "remap.cl", |
| #include "./cl_kernels/remap.clembed" |
| }, |
| { |
| "scale.cl", |
| #include "./cl_kernels/scale.clembed" |
| }, |
| { |
| "scharr_filter.cl", |
| #include "./cl_kernels/scharr_filter.clembed" |
| }, |
| { |
| "sobel_filter.cl", |
| #include "./cl_kernels/sobel_filter.clembed" |
| }, |
| { |
| "softmax_layer.cl", |
| #include "./cl_kernels/softmax_layer.clembed" |
| }, |
| { |
| "tablelookup.cl", |
| #include "./cl_kernels/tablelookup.clembed" |
| }, |
| { |
| "threshold.cl", |
| #include "./cl_kernels/threshold.clembed" |
| }, |
| { |
| "transpose.cl", |
| #include "./cl_kernels/transpose.clembed" |
| }, |
| { |
| "types.h", |
| #include "./cl_kernels/types.hembed" |
| }, |
| { |
| "warp_affine.cl", |
| #include "./cl_kernels/warp_affine.clembed" |
| }, |
| { |
| "warp_helpers.h", |
| #include "./cl_kernels/warp_helpers.hembed" |
| }, |
| { |
| "warp_perspective.cl", |
| #include "./cl_kernels/warp_perspective.clembed" |
| } |
| #endif |
| }; |
| |
| CLKernelLibrary::CLKernelLibrary() |
| : _context(), _device(), _kernel_path("."), _programs_map(), _built_programs_map() |
| { |
| } |
| |
| CLKernelLibrary &CLKernelLibrary::get() |
| { |
| static CLKernelLibrary _kernel_library; |
| return _kernel_library; |
| } |
| |
| Kernel CLKernelLibrary::create_kernel(const std::string &kernel_name, const StringSet &build_options_set) const |
| { |
| // Find which program contains the kernel |
| auto kernel_program_it = _kernel_program_map.find(kernel_name); |
| |
| if(_kernel_program_map.end() == kernel_program_it) |
| { |
| ARM_COMPUTE_ERROR("Kernel %s not found in the CLKernelLibrary", kernel_name.c_str()); |
| } |
| |
| // Check if the program has been built before with same build options. |
| const std::string program_name = kernel_program_it->second; |
| const std::string build_options = stringify_set(build_options_set); |
| const std::string built_program_name = program_name + "_" + build_options; |
| auto built_program_it = _built_programs_map.find(built_program_name); |
| |
| cl::Program cl_program; |
| |
| if(_built_programs_map.end() != built_program_it) |
| { |
| // If program has been built, retrieve to create kernel from it |
| cl_program = built_program_it->second; |
| } |
| else |
| { |
| // Get program |
| Program program = load_program(program_name); |
| |
| // Build program |
| cl_program = program.build(build_options); |
| |
| // Add built program to internal map |
| _built_programs_map.emplace(built_program_name, cl_program); |
| } |
| |
| // Create and return kernel |
| return Kernel(kernel_name, cl_program); |
| } |
| |
| const Program &CLKernelLibrary::load_program(const std::string &program_name) const |
| { |
| const auto program_it = _programs_map.find(program_name); |
| |
| if(program_it != _programs_map.end()) |
| { |
| return program_it->second; |
| } |
| |
| Program program; |
| |
| #ifdef EMBEDDED_KERNELS |
| const auto program_source_it = _program_source_map.find(program_name); |
| |
| if(_program_source_map.end() == program_source_it) |
| { |
| ARM_COMPUTE_ERROR("Embedded program for %s does not exist.", program_name.c_str()); |
| } |
| |
| program = Program(_context, program_name, program_source_it->second); |
| #else |
| // Check for binary |
| std::string source_name = _kernel_path + program_name; |
| std::string binary_name = source_name + "bin"; |
| |
| if(std::ifstream(binary_name).is_open()) |
| { |
| const std::string program_binary = read_file(binary_name, true); |
| program = Program(_context, _device, program_name, std::vector<unsigned char>(program_binary.begin(), program_binary.end())); |
| } |
| else if(std::ifstream(source_name).is_open()) |
| { |
| program = Program(_context, program_name, read_file(source_name, false)); |
| } |
| else |
| { |
| ARM_COMPUTE_ERROR("Kernel file %s does not exist.", source_name.c_str()); |
| } |
| #endif |
| |
| // Insert program to program map |
| const auto new_program = _programs_map.emplace(program_name, std::move(program)); |
| |
| return new_program.first->second; |
| } |
| |
| std::string CLKernelLibrary::stringify_set(const StringSet &s) const |
| { |
| std::string concat_set = "-cl-arm-non-uniform-work-group-size "; |
| |
| #ifndef EMBEDDED_KERNELS |
| concat_set += "-I" + _kernel_path + " "; |
| #endif /* EMBEDDED_KERNELS */ |
| |
| // Concatenate set |
| for(const auto &el : s) |
| { |
| concat_set += " " + el; |
| } |
| |
| return concat_set; |
| } |
