| /* |
| * Copyright (c) 2016-2019 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/CL/CLHelpers.h" |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Utils.h" |
| |
| #include <algorithm> |
| #include <fstream> |
| #include <iostream> |
| #include <utility> |
| #include <vector> |
| |
| using namespace arm_compute; |
| |
| CLBuildOptions::CLBuildOptions() |
| : _build_opts() |
| { |
| } |
| |
| void CLBuildOptions::add_option(std::string option) |
| { |
| _build_opts.emplace(std::move(option)); |
| } |
| |
| void CLBuildOptions::add_option_if(bool cond, std::string option) |
| { |
| if(cond) |
| { |
| add_option(std::move(option)); |
| } |
| } |
| |
| void CLBuildOptions::add_option_if_else(bool cond, std::string option_true, std::string option_false) |
| { |
| (cond) ? add_option(std::move(option_true)) : add_option(std::move(option_false)); |
| } |
| |
| void CLBuildOptions::add_options(const StringSet &options) |
| { |
| _build_opts.insert(options.begin(), options.end()); |
| } |
| |
| void CLBuildOptions::add_options_if(bool cond, const StringSet &options) |
| { |
| if(cond) |
| { |
| add_options(options); |
| } |
| } |
| |
| const CLBuildOptions::StringSet &CLBuildOptions::options() const |
| { |
| return _build_opts; |
| } |
| |
| 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" }, |
| { "activation_layer_qa8", "activation_layer_qa8.cl" }, |
| { "activation_layer_logistic_qa8", "activation_layer_qa8.cl" }, |
| { "batch_to_space_nchw", "batch_to_space.cl" }, |
| { "batch_to_space_static_nchw", "batch_to_space.cl" }, |
| { "batch_to_space_nhwc", "batch_to_space.cl" }, |
| { "batch_to_space_static_nhwc", "batch_to_space.cl" }, |
| { "batchnormalization_layer_nchw", "batchnormalization_layer.cl" }, |
| { "batchnormalization_layer_nhwc", "batchnormalization_layer.cl" }, |
| { "bitwise_or", "bitwise_op.cl" }, |
| { "bitwise_and", "bitwise_op.cl" }, |
| { "bitwise_xor", "bitwise_op.cl" }, |
| { "bitwise_not", "bitwise_op.cl" }, |
| { "bounding_box_transform", "bounding_box_transform.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_shuffle_nchw", "channel_shuffle.cl" }, |
| { "channel_shuffle_nhwc", "channel_shuffle.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" }, |
| { "compare_equal", "comparisons.cl" }, |
| { "compare_equal_quantized", "comparisons.cl" }, |
| { "compare_notequal", "comparisons.cl" }, |
| { "compare_notequal_quantized", "comparisons.cl" }, |
| { "compare_greater", "comparisons.cl" }, |
| { "compare_greater_quantized", "comparisons.cl" }, |
| { "compare_greaterequal", "comparisons.cl" }, |
| { "compare_greaterequal_quantized", "comparisons.cl" }, |
| { "compare_less", "comparisons.cl" }, |
| { "compare_less_quantized", "comparisons.cl" }, |
| { "compare_lessequal", "comparisons.cl" }, |
| { "compare_lessequal_quantized", "comparisons.cl" }, |
| { "concatenate_depth", "concatenate.cl" }, |
| { "concatenate_width", "concatenate.cl" }, |
| { "concatenate_height", "concatenate.cl" }, |
| { "concatenate_width_x2", "concatenate.cl" }, |
| { "concatenate_width_x4", "concatenate.cl" }, |
| { "convolution_rectangle", "convolution_rectangle.cl" }, |
| { "col2im", "col2im.cl" }, |
| { "convert_depth_down", "depth_convert.cl" }, |
| { "convert_depth_up", "depth_convert.cl" }, |
| { "convert_fc_weights", "convert_fc_weights.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" }, |
| { "copy_tensor", "copy_tensor.cl" }, |
| { "copy_pad_tensor", "copy_tensor.cl" }, |
| { "copy_plane", "channel_extract.cl" }, |
| { "copy_planes_3p", "channel_combine.cl" }, |
| { "copy_to_keypoint", "fast_corners.cl" }, |
| { "crop_tensor", "crop_tensor.cl" }, |
| { "deconvolution_upsample", "deconvolution_layer.cl" }, |
| { "depthwise_convolution_3x3", "depthwise_convolution.cl" }, |
| { "depthwise_convolution_3x3_f16", "depthwise_convolution.cl" }, |
| { "depthwise_convolution_3x3_nhwc", "depthwise_convolution.cl" }, |
| { "depthwise_convolution_3x3_nhwc_stride1", "depthwise_convolution.cl" }, |
| { "digit_reverse", "fft.cl" }, |
| { "dwc_3x3_native_qasymm8_nchw", "depthwise_convolution_quantized.cl" }, |
| { "dwc_3x3_native_qasymm8_dot8_nchw", "depthwise_convolution_quantized.cl" }, |
| { "dwc_3x3_reshaped_qasymm8_nhwc", "depthwise_convolution_quantized.cl" }, |
| { "dwc_3x3_reshaped_qasymm8_stride1_nhwc", "depthwise_convolution_quantized.cl" }, |
| { "dwc_3x3_reshaped_qasymm8_dot8_stride1_nhwc", "depthwise_convolution_quantized.cl" }, |
| { "depthwise_convolution_3x3_stridex1_stridey1_bifrost_f16", "depthwise_convolution.cl" }, |
| { "depthwise_convolution_3x3_stridex2_stridey2_bifrost_f16", "depthwise_convolution.cl" }, |
| { "depthwise_convolution_3x3_stridex1_stridey1_bifrost_f32", "depthwise_convolution.cl" }, |
| { "depthwise_convolution_3x3_stridex2_stridey2_bifrost_f32", "depthwise_convolution.cl" }, |
| { "depthwise_convolution_reshape_weights", "depthwise_convolution.cl" }, |
| { "depthwise_convolution_reshape_weights_generic", "depthwise_convolution.cl" }, |
| { "depthwise_im2col", "depthwise_convolution.cl" }, |
| { "depthwise_vector_to_tensor", "depthwise_convolution.cl" }, |
| { "dequantization_layer", "dequantization_layer.cl" }, |
| { "derivative", "derivative.cl" }, |
| { "dilate", "dilate.cl" }, |
| { "direct_convolution1x1", "direct_convolution1x1.cl" }, |
| { "direct_convolution1x1_nhwc", "direct_convolution1x1.cl" }, |
| { "direct_convolution1x1_f32_bifrost", "direct_convolution1x1.cl" }, |
| { "direct_convolution3x3", "direct_convolution3x3.cl" }, |
| { "direct_convolution3x3_nhwc", "direct_convolution3x3.cl" }, |
| { "direct_convolution3x3_f32_bifrost", "direct_convolution3x3.cl" }, |
| { "direct_convolution5x5", "direct_convolution5x5.cl" }, |
| { "direct_convolution5x5_nhwc", "direct_convolution5x5.cl" }, |
| { "direct_convolution5x5_f32_bifrost", "direct_convolution5x5.cl" }, |
| { "direct_convolution_1x1_3x3_5x5_quantized", "direct_convolution_1x1_3x3_5x5_quantized.cl" }, |
| { "elementwise_operation_ADD", "elementwise_operation.cl" }, |
| { "elementwise_operation_SUB", "elementwise_operation.cl" }, |
| { "elementwise_operation_MAX", "elementwise_operation.cl" }, |
| { "elementwise_operation_MIN", "elementwise_operation.cl" }, |
| { "elementwise_operation_DIV", "elementwise_operation.cl" }, |
| { "elementwise_operation_SQUARED_DIFF", "elementwise_operation.cl" }, |
| { "elementwise_operation_ADD_quantized", "elementwise_operation_quantized.cl" }, |
| { "elementwise_operation_SUB_quantized", "elementwise_operation_quantized.cl" }, |
| { "elementwise_operation_MAX_quantized", "elementwise_operation_quantized.cl" }, |
| { "elementwise_operation_MIN_quantized", "elementwise_operation_quantized.cl" }, |
| { "elementwise_operation_DIV_quantized", "elementwise_operation_quantized.cl" }, |
| { "elementwise_operation_SQUARED_DIFF_quantized", "elementwise_operation_quantized.cl" }, |
| { "elementwise_unary", "elementwise_unary.cl" }, |
| { "erode", "erode.cl" }, |
| { "fast_corners", "fast_corners.cl" }, |
| { "fft_radix_2_first_stage_axis_0", "fft.cl" }, |
| { "fft_radix_2_axis_0", "fft.cl" }, |
| { "fft_radix_3_first_stage_axis_0", "fft.cl" }, |
| { "fft_radix_3_axis_0", "fft.cl" }, |
| { "fft_radix_4_first_stage_axis_0", "fft.cl" }, |
| { "fft_radix_4_axis_0", "fft.cl" }, |
| { "fft_radix_5_first_stage_axis_0", "fft.cl" }, |
| { "fft_radix_5_axis_0", "fft.cl" }, |
| { "fft_radix_7_first_stage_axis_0", "fft.cl" }, |
| { "fft_radix_7_axis_0", "fft.cl" }, |
| { "fft_radix_8_first_stage_axis_0", "fft.cl" }, |
| { "fft_radix_8_axis_0", "fft.cl" }, |
| { "fill_image_borders_constant", "fill_border.cl" }, |
| { "fill_image_borders_replicate", "fill_border.cl" }, |
| { "finalize", "optical_flow_pyramid_lk.cl" }, |
| { "flatten", "flatten.cl" }, |
| { "floor_layer", "floor.cl" }, |
| { "fuse_batchnormalization_layer", "batchnormalization_layer.cl" }, |
| { "gather", "gather.cl" }, |
| { "gaussian1x5_sub_x", "gaussian_pyramid.cl" }, |
| { "gaussian5x1_sub_y", "gaussian_pyramid.cl" }, |
| { "gemm_accumulate_biases", "gemm.cl" }, |
| { "gemm_interleave4x4", "gemm.cl" }, |
| { "gemm_ma_f16", "gemm.cl" }, |
| { "gemm_ma_f32", "gemm.cl" }, |
| { "gemm_mv", "gemv.cl" }, |
| { "gemm_mv_quantized", "gemv.cl" }, |
| { "gemm_mm_interleaved_transposed_f16", "gemm.cl" }, |
| { "gemm_mm_interleaved_transposed_f16_acc32", "gemm.cl" }, |
| { "gemm_mm_interleaved_transposed_f16_bifrost", "gemm.cl" }, |
| { "gemm_mm_interleaved_transposed_f32", "gemm.cl" }, |
| { "gemm_mm_interleaved_transposed_f32_bifrost", "gemm.cl" }, |
| { "gemm_mm_floating_point", "gemm.cl" }, |
| { "gemm_mm_floating_point_f16_bifrost", "gemm.cl" }, |
| { "gemm_mm_floating_point_f16_bifrost_acc32", "gemm.cl" }, |
| { "gemm_mm_floating_point_f32_bifrost", "gemm.cl" }, |
| { "gemm_mm_floating_point_f32_bifrost_1000", "gemm.cl" }, |
| { "gemm_mm_reshaped_lhs_nt_rhs_t", "gemm.cl" }, |
| { "gemm_mm_reshaped_only_rhs_nt", "gemm.cl" }, |
| { "gemm_mm_reshaped_only_rhs_t", "gemm.cl" }, |
| { "gemm_lc_vm_f32", "gemm.cl" }, |
| { "gemm_transpose1xW", "gemm.cl" }, |
| { "gemm_reshape_lhs_matrix_nt", "gemm.cl" }, |
| { "gemm_reshape_lhs_matrix_t", "gemm.cl" }, |
| { "gemm_reshape_rhs_matrix_nt", "gemm.cl" }, |
| { "gemm_reshape_rhs_matrix_t", "gemm.cl" }, |
| { "gemmlowp_matrix_a_reduction", "gemmlowp.cl" }, |
| { "gemmlowp_matrix_a_reduction_dot8", "gemmlowp.cl" }, |
| { "gemmlowp_matrix_b_reduction", "gemmlowp.cl" }, |
| { "gemmlowp_mm_bifrost", "gemmlowp.cl" }, |
| { "gemmlowp_mm_bifrost_dot8", "gemmlowp.cl" }, |
| { "gemmlowp_mm_midgard", "gemmlowp.cl" }, |
| { "gemmlowp_mm_interleaved_transposed_bifrost", "gemmlowp.cl" }, |
| { "gemmlowp_mm_interleaved_transposed_bifrost_dot8", "gemmlowp.cl" }, |
| { "gemmlowp_mm_interleaved_transposed_midgard", "gemmlowp.cl" }, |
| { "gemmlowp_mm_reshaped_lhs_nt_rhs_t", "gemmlowp.cl" }, |
| { "gemmlowp_mm_reshaped_lhs_nt_rhs_t_dot8", "gemmlowp.cl" }, |
| { "gemmlowp_mm_reshaped_only_rhs_t", "gemmlowp.cl" }, |
| { "gemmlowp_offset_contribution", "gemmlowp.cl" }, |
| { "gemmlowp_offset_contribution_quantize_down", "gemmlowp.cl" }, |
| { "gemmlowp_offset_contribution_quantize_down_fixedpoint", "gemmlowp.cl" }, |
| { "gemmlowp_output_stage_quantize_down", "gemmlowp.cl" }, |
| { "gemmlowp_output_stage_quantize_down_fixedpoint", "gemmlowp.cl" }, |
| { "gemmlowp_output_stage_quantize_down_float", "gemmlowp.cl" }, |
| { "generate_proposals_compute_all_anchors", "generate_proposals.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" }, |
| { "im2col1x1_stridex1_nchw", "im2col.cl" }, |
| { "im2col3x3_nchw", "im2col.cl" }, |
| { "im2col5x5_nchw", "im2col.cl" }, |
| { "im2col11x11_padx0_pady0_nchw", "im2col.cl" }, |
| { "im2col_generic_nchw", "im2col.cl" }, |
| { "im2col_generic_padx0_pady0_nchw", "im2col.cl" }, |
| { "im2col3x3_nhwc", "im2col.cl" }, |
| { "im2col9x9_nhwc", "im2col.cl" }, |
| { "im2col_generic_nhwc", "im2col.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" }, |
| { "l2_normalize_x", "l2_normalize.cl" }, |
| { "l2_normalize_y", "l2_normalize.cl" }, |
| { "l2_normalize_z", "l2_normalize.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" }, |
| { "memset", "memset.cl" }, |
| { "minmax", "minmaxloc.cl" }, |
| { "minmax_border", "minmaxloc.cl" }, |
| { "minmax_layer", "minmax_layer.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_nchw", "normalization_layer.cl" }, |
| { "normalization_layer_in_map_nhwc", "normalization_layer.cl" }, |
| { "normalize_planar_yuv_layer_nchw", "normalize_planar_yuv_layer.cl" }, |
| { "normalize_planar_yuv_layer_nhwc", "normalize_planar_yuv_layer.cl" }, |
| { "normalize_planar_yuv_layer_q8_nchw", "normalize_planar_yuv_layer_quantized.cl" }, |
| { "normalize_planar_yuv_layer_q8_nhwc", "normalize_planar_yuv_layer_quantized.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" }, |
| { "output_stage_quantized", "direct_convolution_1x1_3x3_5x5_quantized.cl" }, |
| { "permute", "permute.cl" }, |
| { "pixelwise_mul_float", "pixelwise_mul_float.cl" }, |
| { "pixelwise_mul_int", "pixelwise_mul_int.cl" }, |
| { "pixelwise_mul_quantized", "pixelwise_mul_int.cl" }, |
| { "pooling_layer_2", "pooling_layer.cl" }, |
| { "pooling_layer_3", "pooling_layer.cl" }, |
| { "pooling_layer_optimized_3", "pooling_layer.cl" }, |
| { "pooling_layer_7", "pooling_layer.cl" }, |
| { "pooling_layer_MxN_nchw", "pooling_layer.cl" }, |
| { "pooling_layer_MxN_nhwc", "pooling_layer.cl" }, |
| { "pooling_layer_MxN_quantized_nhwc", "pooling_layer_quantized.cl" }, |
| { "pooling_layer_MxN_quantized_nchw", "pooling_layer_quantized.cl" }, |
| { "prior_box_layer_nchw", "prior_box_layer.cl" }, |
| { "quantization_layer", "quantization_layer.cl" }, |
| { "range", "range.cl" }, |
| { "range_quantized", "range.cl" }, |
| { "reduction_operation_x", "reduction_operation.cl" }, |
| { "reduction_operation_non_parallel_x", "reduction_operation.cl" }, |
| { "reduction_operation_y", "reduction_operation.cl" }, |
| { "reduction_operation_z", "reduction_operation.cl" }, |
| { "reduction_operation_w", "reduction_operation.cl" }, |
| { "remap_nearest_neighbour", "remap.cl" }, |
| { "remap_bilinear", "remap.cl" }, |
| { "reorg_layer_nchw", "reorg_layer.cl" }, |
| { "reorg_layer_nhwc", "reorg_layer.cl" }, |
| { "reshape_layer", "reshape_layer.cl" }, |
| { "reshape_to_columns", "convolution_layer.cl" }, |
| { "reverse", "reverse.cl" }, |
| { "RGB888_to_IYUV_bt709", "color_convert.cl" }, |
| { "RGB888_to_NV12_bt709", "color_convert.cl" }, |
| { "RGB888_to_RGBA8888_bt709", "color_convert.cl" }, |
| { "RGB888_to_U8_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" }, |
| { "roi_align_layer", "roi_align_layer.cl" }, |
| { "roi_pooling_layer", "roi_pooling_layer.cl" }, |
| { "scale_nearest_neighbour_nchw", "scale.cl" }, |
| { "scale_nearest_neighbour_nhwc", "scale.cl" }, |
| { "scale_bilinear_nchw", "scale.cl" }, |
| { "scale_bilinear_nhwc", "scale.cl" }, |
| { "scale_bilinear_quantized_nchw", "scale_quantized.cl" }, |
| { "scale_bilinear_quantized_nhwc", "scale_quantized.cl" }, |
| { "scharr3x3", "scharr_filter.cl" }, |
| { "select_same_rank", "select.cl" }, |
| { "select_different_rank_2", "select.cl" }, |
| { "select_different_rank_n", "select.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_norm", "softmax_layer.cl" }, |
| { "softmax_layer_norm_quantized", "softmax_layer_quantized.cl" }, |
| { "softmax_layer_max_shift_exp_sum_quantized_serial", "softmax_layer_quantized.cl" }, |
| { "softmax_layer_max_shift_exp_sum_quantized_parallel", "softmax_layer_quantized.cl" }, |
| { "softmax_layer_max_shift_exp_sum_serial", "softmax_layer.cl" }, |
| { "space_to_batch_nchw", "space_to_batch.cl" }, |
| { "space_to_batch_static_nchw", "space_to_batch.cl" }, |
| { "space_to_batch_nhwc", "space_to_batch.cl" }, |
| { "space_to_batch_static_nhwc", "space_to_batch.cl" }, |
| { "softmax_layer_max_shift_exp_sum_parallel", "softmax_layer.cl" }, |
| { "stack_layer", "stack_layer.cl" }, |
| { "strided_slice", "slice_ops.cl" }, |
| { "suppress_non_maximum", "canny.cl" }, |
| { "tablelookup_U8", "tablelookup.cl" }, |
| { "tablelookup_S16", "tablelookup.cl" }, |
| { "threshold_binary", "threshold.cl" }, |
| { "threshold_range", "threshold.cl" }, |
| { "tile", "tile.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" }, |
| { "upsample_layer_nchw", "upsample_layer.cl" }, |
| { "upsample_layer_nhwc", "upsample_layer.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" }, |
| { "winograd_filter_transform_2x2_3x3_nchw", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_2x1_3x1_nchw", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_1x2_1x3_nchw", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_4x4_3x3_nchw", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_4x1_3x1_nchw", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_1x4_1x3_nchw", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_4x4_5x5_nchw", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_4x1_5x1_nchw", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_1x4_1x5_nchw", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_4x1_3x1_nhwc", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_1x4_1x3_nhwc", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_4x4_3x3_nhwc", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_4x4_5x5_nhwc", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_4x1_5x1_nhwc", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_1x4_1x5_nhwc", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_2x2_7x7_nhwc", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_2x1_7x1_nhwc", "winograd_filter_transform.cl" }, |
| { "winograd_filter_transform_1x2_1x7_nhwc", "winograd_filter_transform.cl" }, |
| { "winograd_input_transform_2x2_3x3_stepz1_nchw", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_2x2_3x3_stepz2_nchw", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_2x1_3x1_stepz1_nchw", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_2x1_3x1_stepz2_nchw", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_1x2_1x3_stepz1_nchw", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_1x2_1x3_stepz2_nchw", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_4x4_3x3_stepz1_nchw", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_4x1_3x1_stepz1_nchw", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_1x4_1x3_stepz1_nchw", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_4x4_5x5_stepz1_nchw", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_4x1_5x1_stepz1_nchw", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_1x4_1x5_stepz1_nchw", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_4x1_3x1_stepz1_nhwc", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_1x4_1x3_stepz1_nhwc", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_4x4_3x3_stepz1_nhwc", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_4x4_5x5_stepz1_nhwc", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_4x1_5x1_stepz1_nhwc", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_1x4_1x5_stepz1_nhwc", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_2x2_7x7_stepz1_nhwc", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_2x1_7x1_stepz1_nhwc", "winograd_input_transform.cl" }, |
| { "winograd_input_transform_1x2_1x7_stepz1_nhwc", "winograd_input_transform.cl" }, |
| { "winograd_output_transform_2x2_3x3_nchw", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_2x1_3x1_nchw", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_1x2_1x3_nchw", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_4x4_3x3_nchw", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_4x1_3x1_nchw", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_1x4_1x3_nchw", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_4x4_5x5_nchw", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_4x1_5x1_nchw", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_1x4_1x5_nchw", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_4x1_3x1_nhwc", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_1x4_1x3_nhwc", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_4x4_3x3_nhwc", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_4x4_5x5_nhwc", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_4x1_5x1_nhwc", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_1x4_1x5_nhwc", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_2x2_7x7_nhwc", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_2x1_7x1_nhwc", "winograd_output_transform.cl" }, |
| { "winograd_output_transform_1x2_1x7_nhwc", "winograd_output_transform.cl" }, |
| { "yolo_layer_nchw", "yolo_layer.cl" }, |
| { "yolo_layer_nhwc", "yolo_layer.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" |
| }, |
| { |
| "activation_layer_qa8.cl", |
| #include "./cl_kernels/activation_layer_qa8.clembed" |
| }, |
| { |
| "batch_to_space.cl", |
| #include "./cl_kernels/batch_to_space.clembed" |
| }, |
| { |
| "bitwise_op.cl", |
| #include "./cl_kernels/bitwise_op.clembed" |
| }, |
| { |
| "bounding_box_transform.cl", |
| #include "./cl_kernels/bounding_box_transform.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" |
| }, |
| { |
| "channel_shuffle.cl", |
| #include "./cl_kernels/channel_shuffle.clembed" |
| }, |
| { |
| "col2im.cl", |
| #include "./cl_kernels/col2im.clembed" |
| }, |
| { |
| "comparisons.cl", |
| #include "./cl_kernels/comparisons.clembed" |
| }, |
| { |
| "concatenate.cl", |
| #include "./cl_kernels/concatenate.clembed" |
| }, |
| { |
| "color_convert.cl", |
| #include "./cl_kernels/color_convert.clembed" |
| }, |
| { |
| "convert_fc_weights.cl", |
| #include "./cl_kernels/convert_fc_weights.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" |
| }, |
| { |
| "copy_tensor.cl", |
| #include "./cl_kernels/copy_tensor.clembed" |
| }, |
| { |
| "crop_tensor.cl", |
| #include "./cl_kernels/crop_tensor.clembed" |
| }, |
| { |
| "upsample_layer.cl", |
| #include "./cl_kernels/upsample_layer.clembed" |
| }, |
| { |
| "deconvolution_layer.cl", |
| #include "./cl_kernels/deconvolution_layer.clembed" |
| }, |
| { |
| "depth_convert.cl", |
| #include "./cl_kernels/depth_convert.clembed" |
| }, |
| { |
| "depthwise_convolution.cl", |
| #include "./cl_kernels/depthwise_convolution.clembed" |
| }, |
| { |
| "depthwise_convolution_quantized.cl", |
| #include "./cl_kernels/depthwise_convolution_quantized.clembed" |
| }, |
| { |
| "dequantization_layer.cl", |
| #include "./cl_kernels/dequantization_layer.clembed" |
| }, |
| { |
| "derivative.cl", |
| #include "./cl_kernels/derivative.clembed" |
| }, |
| { |
| "dilate.cl", |
| #include "./cl_kernels/dilate.clembed" |
| }, |
| { |
| "direct_convolution1x1.cl", |
| #include "./cl_kernels/direct_convolution1x1.clembed" |
| }, |
| { |
| "direct_convolution3x3.cl", |
| #include "./cl_kernels/direct_convolution3x3.clembed" |
| }, |
| { |
| "direct_convolution5x5.cl", |
| #include "./cl_kernels/direct_convolution5x5.clembed" |
| }, |
| { |
| "direct_convolution_1x1_3x3_5x5_quantized.cl", |
| #include "./cl_kernels/direct_convolution_1x1_3x3_5x5_quantized.clembed" |
| }, |
| { |
| "elementwise_operation.cl", |
| #include "./cl_kernels/elementwise_operation.clembed" |
| }, |
| { |
| "elementwise_operation_quantized.cl", |
| #include "./cl_kernels/elementwise_operation_quantized.clembed" |
| }, |
| { |
| "elementwise_unary.cl", |
| #include "./cl_kernels/elementwise_unary.clembed" |
| }, |
| { |
| "erode.cl", |
| #include "./cl_kernels/erode.clembed" |
| }, |
| { |
| "fast_corners.cl", |
| #include "./cl_kernels/fast_corners.clembed" |
| }, |
| { |
| "fft.cl", |
| #include "./cl_kernels/fft.clembed" |
| }, |
| { |
| "fill_border.cl", |
| #include "./cl_kernels/fill_border.clembed" |
| }, |
| { |
| "flatten.cl", |
| #include "./cl_kernels/flatten.clembed" |
| }, |
| { |
| "floor.cl", |
| #include "./cl_kernels/floor.clembed" |
| }, |
| { |
| "gather.cl", |
| #include "./cl_kernels/gather.clembed" |
| }, |
| { |
| "gaussian_pyramid.cl", |
| #include "./cl_kernels/gaussian_pyramid.clembed" |
| }, |
| { |
| "gemm.cl", |
| #include "./cl_kernels/gemm.clembed" |
| }, |
| { |
| "gemmlowp.cl", |
| #include "./cl_kernels/gemmlowp.clembed" |
| }, |
| { |
| "gemv.cl", |
| #include "./cl_kernels/gemv.clembed" |
| }, |
| { |
| "generate_proposals.cl", |
| #include "./cl_kernels/generate_proposals.clembed" |
| }, |
| { |
| "harris_corners.cl", |
| #include "./cl_kernels/harris_corners.clembed" |
| }, |
| { |
| "helpers.h", |
| #include "./cl_kernels/helpers.hembed" |
| }, |
| { |
| "helpers_asymm.h", |
| #include "./cl_kernels/helpers_asymm.hembed" |
| }, |
| { |
| "histogram.cl", |
| #include "./cl_kernels/histogram.clembed" |
| }, |
| { |
| "hog.cl", |
| #include "./cl_kernels/hog.clembed" |
| }, |
| { |
| "im2col.cl", |
| #include "./cl_kernels/im2col.clembed" |
| }, |
| { |
| "integral_image.cl", |
| #include "./cl_kernels/integral_image.clembed" |
| }, |
| { |
| "l2_normalize.cl", |
| #include "./cl_kernels/l2_normalize.clembed" |
| }, |
| { |
| "magnitude_phase.cl", |
| #include "./cl_kernels/magnitude_phase.clembed" |
| }, |
| { |
| "mean_stddev.cl", |
| #include "./cl_kernels/mean_stddev.clembed" |
| }, |
| { |
| "memset.cl", |
| #include "./cl_kernels/memset.clembed" |
| }, |
| { |
| "minmaxloc.cl", |
| #include "./cl_kernels/minmaxloc.clembed" |
| }, |
| { |
| "minmax_layer.cl", |
| #include "./cl_kernels/minmax_layer.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" |
| }, |
| { |
| "normalize_planar_yuv_layer.cl", |
| #include "./cl_kernels/normalize_planar_yuv_layer.clembed" |
| }, |
| { |
| "normalize_planar_yuv_layer_quantized.cl", |
| #include "./cl_kernels/normalize_planar_yuv_layer_quantized.clembed" |
| }, |
| { |
| "batchnormalization_layer.cl", |
| #include "./cl_kernels/batchnormalization_layer.clembed" |
| }, |
| { |
| "optical_flow_pyramid_lk.cl", |
| #include "./cl_kernels/optical_flow_pyramid_lk.clembed" |
| }, |
| { |
| "permute.cl", |
| #include "./cl_kernels/permute.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" |
| }, |
| { |
| "pooling_layer_quantized.cl", |
| #include "./cl_kernels/pooling_layer_quantized.clembed" |
| }, |
| { |
| "prior_box_layer.cl", |
| #include "./cl_kernels/prior_box_layer.clembed" |
| }, |
| { |
| "quantization_layer.cl", |
| #include "./cl_kernels/quantization_layer.clembed" |
| }, |
| { |
| "range.cl", |
| #include "./cl_kernels/range.clembed" |
| }, |
| { |
| "reduction_operation.cl", |
| #include "./cl_kernels/reduction_operation.clembed" |
| }, |
| { |
| "remap.cl", |
| #include "./cl_kernels/remap.clembed" |
| }, |
| { |
| "reorg_layer.cl", |
| #include "./cl_kernels/reorg_layer.clembed" |
| }, |
| { |
| "reshape_layer.cl", |
| #include "./cl_kernels/reshape_layer.clembed" |
| }, |
| { |
| "reverse.cl", |
| #include "./cl_kernels/reverse.clembed" |
| }, |
| { |
| "roi_align_layer.cl", |
| #include "./cl_kernels/roi_align_layer.clembed" |
| }, |
| { |
| "roi_pooling_layer.cl", |
| #include "./cl_kernels/roi_pooling_layer.clembed" |
| }, |
| { |
| "scale.cl", |
| #include "./cl_kernels/scale.clembed" |
| }, |
| { |
| "scale_quantized.cl", |
| #include "./cl_kernels/scale_quantized.clembed" |
| }, |
| { |
| "scharr_filter.cl", |
| #include "./cl_kernels/scharr_filter.clembed" |
| }, |
| { |
| "select.cl", |
| #include "./cl_kernels/select.clembed" |
| }, |
| { |
| "sobel_filter.cl", |
| #include "./cl_kernels/sobel_filter.clembed" |
| }, |
| { |
| "softmax_layer.cl", |
| #include "./cl_kernels/softmax_layer.clembed" |
| }, |
| { |
| "softmax_layer_quantized.cl", |
| #include "./cl_kernels/softmax_layer_quantized.clembed" |
| }, |
| { |
| "slice_ops.cl", |
| #include "./cl_kernels/slice_ops.clembed" |
| }, |
| { |
| "space_to_batch.cl", |
| #include "./cl_kernels/space_to_batch.clembed" |
| }, |
| { |
| "stack_layer.cl", |
| #include "./cl_kernels/stack_layer.clembed" |
| }, |
| { |
| "tablelookup.cl", |
| #include "./cl_kernels/tablelookup.clembed" |
| }, |
| { |
| "threshold.cl", |
| #include "./cl_kernels/threshold.clembed" |
| }, |
| { |
| "tile.cl", |
| #include "./cl_kernels/tile.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" |
| }, |
| { |
| "winograd_filter_transform.cl", |
| #include "./cl_kernels/winograd_filter_transform.clembed" |
| }, |
| { |
| "winograd_input_transform.cl", |
| #include "./cl_kernels/winograd_input_transform.clembed" |
| }, |
| { |
| "winograd_output_transform.cl", |
| #include "./cl_kernels/winograd_output_transform.clembed" |
| }, |
| { |
| "yolo_layer.cl", |
| #include "./cl_kernels/yolo_layer.clembed" |
| }, |
| #endif /* EMBEDDED_KERNELS */ |
| }; |
| |
| CLKernelLibrary::CLKernelLibrary() |
| : _context(), _device(), _kernel_path("."), _programs_map(), _built_programs_map() |
| { |
| opencl_is_available(); // Make sure the OpenCL symbols are initialised *before* the CLKernelLibrary is built |
| } |
| |
| 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()); |
| } |
| std::string concat_str; |
| |
| #if defined(ARM_COMPUTE_DEBUG_ENABLED) |
| // Enable debug properties in CL kernels |
| concat_str += " -DARM_COMPUTE_DEBUG_ENABLED"; |
| #endif // defined(ARM_COMPUTE_DEBUG_ENABLED) |
| |
| if(fp16_supported()) |
| { |
| concat_str += " -DARM_COMPUTE_OPENCL_FP16_ENABLED=1 "; |
| } |
| |
| if(dot8_supported(_device)) |
| { |
| concat_str += " -DARM_COMPUTE_OPENCL_DOT8_ENABLED=1 "; |
| } |
| |
| if(dot8_acc_supported(_device)) |
| { |
| concat_str += " -DARM_COMPUTE_OPENCL_DOT8_ACC_ENABLED=1 "; |
| } |
| |
| if(get_cl_version(_device) == CLVersion::CL20) |
| { |
| concat_str += " -cl-std=CL2.0 "; |
| } |
| else if(arm_non_uniform_workgroup_supported(_device)) |
| { |
| concat_str += " -cl-arm-non-uniform-work-group-size "; |
| } |
| else |
| { |
| ARM_COMPUTE_ERROR("Non uniform workgroup size is not supported!!"); |
| } |
| |
| // 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) + concat_str; |
| |
| 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); |
| } |
| |
| void CLKernelLibrary::add_built_program(const std::string &built_program_name, cl::Program program) |
| { |
| _built_programs_map.emplace(built_program_name, program); |
| } |
| |
| bool CLKernelLibrary::fp16_supported() const |
| { |
| return ::fp16_supported(_device); |
| } |
| |
| bool CLKernelLibrary::int64_base_atomics_supported() const |
| { |
| return device_supports_extension(_device, "cl_khr_int64_base_atomics"); |
| } |
| |
| 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 /* EMBEDDED_KERNELS */ |
| // 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 /* EMBEDDED_KERNELS */ |
| |
| // 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; |
| |
| #ifndef EMBEDDED_KERNELS |
| concat_set += "-I" + _kernel_path + " "; |
| #endif /* EMBEDDED_KERNELS */ |
| |
| // Concatenate set |
| for(const auto &el : s) |
| { |
| concat_set += " " + el; |
| } |
| |
| return concat_set; |
| } |
| |
| std::string CLKernelLibrary::get_program_source(const std::string &program_name) |
| { |
| const auto program_source_it = _program_source_map.find(program_name); |
| |
| if(program_source_it == _program_source_map.end()) |
| { |
| ARM_COMPUTE_ERROR("Embedded program for %s does not exist.", program_name.c_str()); |
| } |
| |
| return program_source_it->second; |
| } |
| |
| size_t CLKernelLibrary::max_local_workgroup_size(const cl::Kernel &kernel) const |
| { |
| size_t result; |
| |
| size_t err = kernel.getWorkGroupInfo(_device, CL_KERNEL_WORK_GROUP_SIZE, &result); |
| ARM_COMPUTE_ERROR_ON_MSG(err != 0, "clGetKernelWorkGroupInfo failed to return the maximum workgroup size for the kernel"); |
| ARM_COMPUTE_UNUSED(err); |
| |
| return result; |
| } |
| |
| cl::NDRange CLKernelLibrary::default_ndrange() const |
| { |
| GPUTarget _target = get_target_from_device(_device); |
| cl::NDRange default_range; |
| |
| switch(_target) |
| { |
| case GPUTarget::MIDGARD: |
| case GPUTarget::T600: |
| case GPUTarget::T700: |
| case GPUTarget::T800: |
| default_range = cl::NDRange(128u, 1); |
| break; |
| default: |
| default_range = cl::NullRange; |
| } |
| |
| return default_range; |
| } |
| |
| std::string CLKernelLibrary::get_device_version() |
| { |
| return _device.getInfo<CL_DEVICE_VERSION>(); |
| } |