Gian Marco Iodice | 4b90865 | 2018-10-18 10:21:02 +0100 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2018 ARM Limited. |
| 3 | * |
| 4 | * SPDX-License-Identifier: MIT |
| 5 | * |
| 6 | * Permission is hereby granted, free of charge, to any person obtaining a copy |
| 7 | * of this software and associated documentation files (the "Software"), to |
| 8 | * deal in the Software without restriction, including without limitation the |
| 9 | * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| 10 | * sell copies of the Software, and to permit persons to whom the Software is |
| 11 | * furnished to do so, subject to the following conditions: |
| 12 | * |
| 13 | * The above copyright notice and this permission notice shall be included in all |
| 14 | * copies or substantial portions of the Software. |
| 15 | * |
| 16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| 17 | * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| 18 | * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| 19 | * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| 20 | * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| 21 | * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| 22 | * SOFTWARE. |
| 23 | */ |
| 24 | #include "arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionOutputStageKernel.h" |
| 25 | |
| 26 | #include "arm_compute/core/AccessWindowStatic.h" |
| 27 | #include "arm_compute/core/CL/ICLTensor.h" |
| 28 | #include "arm_compute/core/Error.h" |
| 29 | #include "arm_compute/core/Helpers.h" |
| 30 | #include "arm_compute/core/TensorInfo.h" |
| 31 | #include "arm_compute/core/Types.h" |
| 32 | #include "arm_compute/core/Utils.h" |
| 33 | #include "arm_compute/core/Validate.h" |
| 34 | #include "arm_compute/core/Window.h" |
| 35 | #include "support/ToolchainSupport.h" |
| 36 | |
| 37 | #include <cstddef> |
| 38 | #include <cstdint> |
| 39 | |
| 40 | using namespace arm_compute; |
| 41 | |
| 42 | namespace arm_compute |
| 43 | { |
| 44 | class Coordinates; |
| 45 | } // namespace arm_compute |
| 46 | |
| 47 | namespace |
| 48 | { |
| 49 | Status validate_arguments(const ITensorInfo *mm_result, const ITensorInfo *vector_sum_col, const ITensorInfo *vector_sum_row, const ITensorInfo *bias, const ITensorInfo *output, |
| 50 | int32_t a_offset, int32_t b_offset, const GEMMLowpOutputStageInfo &output_stage) |
| 51 | { |
| 52 | ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(mm_result, 1, DataType::S32); |
| 53 | ARM_COMPUTE_RETURN_ERROR_ON(output_stage.type == GEMMLowpOutputStageType::NONE); |
| 54 | ARM_COMPUTE_RETURN_ERROR_ON(bias == nullptr && a_offset == 0 && b_offset == 0); |
| 55 | ARM_COMPUTE_RETURN_ERROR_ON(output_stage.gemmlowp_max_bound > 255); |
| 56 | ARM_COMPUTE_RETURN_ERROR_ON(output_stage.gemmlowp_min_bound < 0 || output_stage.gemmlowp_min_bound > output_stage.gemmlowp_max_bound); |
| 57 | |
| 58 | if(bias != nullptr) |
| 59 | { |
| 60 | ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(bias, 1, DataType::S32); |
| 61 | ARM_COMPUTE_RETURN_ERROR_ON(bias->num_dimensions() > 1); |
| 62 | ARM_COMPUTE_RETURN_ERROR_ON(mm_result->dimension(0) != bias->dimension(0)); |
| 63 | } |
| 64 | |
| 65 | // If a_offset == 0, vector_sum_col can be a nullptr |
| 66 | if(a_offset != 0) |
| 67 | { |
| 68 | ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_col, 1, DataType::S32); |
| 69 | ARM_COMPUTE_RETURN_ERROR_ON(vector_sum_col->dimension(0) != mm_result->dimension(0)); |
| 70 | } |
| 71 | |
| 72 | // If b_offset == 0, vector_sum_row can be a nullptr |
| 73 | if(b_offset != 0) |
| 74 | { |
| 75 | ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_row, 1, DataType::S32); |
| 76 | |
| 77 | // Check if input is a 3D reinterpretation |
| 78 | const bool reinterpret_as_3d = mm_result->num_dimensions() > 1 && mm_result->tensor_shape().y() != vector_sum_row->tensor_shape().x(); |
| 79 | |
| 80 | // Validate input |
| 81 | ARM_COMPUTE_RETURN_ERROR_ON(reinterpret_as_3d && vector_sum_row->dimension(0) != (mm_result->dimension(1) * mm_result->dimension(2))); |
| 82 | ARM_COMPUTE_RETURN_ERROR_ON(!reinterpret_as_3d && vector_sum_row->dimension(0) != mm_result->dimension(1)); |
| 83 | |
| 84 | TensorShape output_shape = mm_result->tensor_shape(); |
| 85 | if(output_shape.num_dimensions() > 1) |
| 86 | { |
| 87 | const unsigned int output_batch_idx = reinterpret_as_3d ? 3 : 2; |
| 88 | |
| 89 | TensorShape vector_sum_row_shape = vector_sum_row->tensor_shape(); |
| 90 | vector_sum_row_shape.collapse_from(1); |
| 91 | output_shape.collapse_from(output_batch_idx); |
| 92 | |
| 93 | ARM_COMPUTE_RETURN_ERROR_ON_MSG(vector_sum_row_shape[1] != output_shape[output_batch_idx], |
| 94 | "mm_result tensor must have the same number of batches of output tensor"); |
| 95 | |
| 96 | if(a_offset != 0) |
| 97 | { |
| 98 | TensorShape vector_sum_col_shape = vector_sum_col->tensor_shape(); |
| 99 | vector_sum_col_shape.collapse_from(1); |
| 100 | |
| 101 | ARM_COMPUTE_RETURN_ERROR_ON_MSG(vector_sum_col_shape[1] != 1 && vector_sum_col_shape[1] != vector_sum_row_shape[1], |
| 102 | "vector_sum_col tensor must have the same number of batches of vector_sum_row_shape or the number of batches must be set to 1"); |
| 103 | } |
| 104 | } |
| 105 | } |
| 106 | |
| 107 | if(output->total_size() != 0) |
| 108 | { |
| 109 | ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8); |
| 110 | ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mm_result, output); |
| 111 | } |
| 112 | |
| 113 | return Status{}; |
| 114 | } |
| 115 | |
| 116 | std::pair<Status, Window> validate_and_configure_window(ITensorInfo *mm_result, ITensorInfo *vector_sum_col, ITensorInfo *vector_sum_row, ITensorInfo *bias, ITensorInfo *output, |
| 117 | int32_t a_offset, int32_t b_offset) |
| 118 | { |
| 119 | constexpr unsigned int num_elems_processed_per_iteration = 4; |
| 120 | bool window_changed = false; |
| 121 | |
| 122 | // Auto initialize the output |
| 123 | auto_init_if_empty(*output, mm_result->clone()->set_data_type(DataType::QASYMM8)); |
| 124 | |
| 125 | // Configure kernel window |
| 126 | Window win = calculate_max_window(*mm_result, Steps(num_elems_processed_per_iteration)); |
| 127 | |
| 128 | AccessWindowHorizontal mm_result_access(mm_result, 0, num_elems_processed_per_iteration); |
| 129 | window_changed = window_changed || update_window_and_padding(win, mm_result_access); |
| 130 | |
| 131 | AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); |
| 132 | window_changed = window_changed || update_window_and_padding(win, output_access); |
| 133 | |
| 134 | if(a_offset != 0) |
| 135 | { |
| 136 | AccessWindowHorizontal vector_sum_col_access(vector_sum_col, 0, num_elems_processed_per_iteration); |
| 137 | window_changed = window_changed || update_window_and_padding(win, vector_sum_col_access); |
| 138 | } |
| 139 | if(b_offset != 0) |
| 140 | { |
| 141 | AccessWindowStatic vector_sum_row_access(vector_sum_row, 0, 0, vector_sum_row->dimension(0), 0); // NOLINT |
| 142 | window_changed = window_changed || update_window_and_padding(win, vector_sum_row_access); |
| 143 | } |
| 144 | |
| 145 | if(bias != nullptr) |
| 146 | { |
| 147 | AccessWindowStatic bias_access(bias, 0, 0, ceil_to_multiple(bias->dimension(0), num_elems_processed_per_iteration), bias->tensor_shape()[1]); |
| 148 | window_changed = window_changed || update_window_and_padding(win, bias_access); |
| 149 | } |
| 150 | |
| 151 | Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; |
| 152 | return std::make_pair(err, win); |
| 153 | } |
| 154 | } // namespace |
| 155 | |
| 156 | CLGEMMLowpOffsetContributionOutputStageKernel::CLGEMMLowpOffsetContributionOutputStageKernel() |
| 157 | : _mm_result(nullptr), _vector_sum_col(nullptr), _vector_sum_row(nullptr), _bias(nullptr), _output(nullptr) |
| 158 | { |
| 159 | } |
| 160 | |
| 161 | void CLGEMMLowpOffsetContributionOutputStageKernel::configure(const ICLTensor *mm_result, const ICLTensor *vector_sum_col, const ICLTensor *vector_sum_row, const ICLTensor *bias, ICLTensor *output, |
| 162 | int32_t k, int32_t a_offset, int32_t b_offset, const GEMMLowpOutputStageInfo &output_stage) |
| 163 | { |
| 164 | // Perform validate step |
| 165 | ARM_COMPUTE_ERROR_ON_NULLPTR(mm_result, output); |
| 166 | ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(mm_result->info(), |
| 167 | vector_sum_col != nullptr ? vector_sum_col->info() : nullptr, |
| 168 | vector_sum_row != nullptr ? vector_sum_row->info() : nullptr, |
| 169 | bias != nullptr ? bias->info() : nullptr, |
| 170 | output->info(), |
| 171 | a_offset, b_offset, output_stage)); // NOLINT |
| 172 | |
| 173 | const int min = output_stage.gemmlowp_min_bound; |
| 174 | const int max = output_stage.gemmlowp_max_bound; |
| 175 | |
| 176 | _vector_sum_col = vector_sum_col; |
| 177 | _vector_sum_row = vector_sum_row; |
| 178 | _mm_result = mm_result; |
| 179 | _bias = bias; |
| 180 | _output = output; |
| 181 | |
| 182 | // Check if input is a 3D reinterpretation |
| 183 | const bool reinterpret_as_3d = vector_sum_row != nullptr |
| 184 | && mm_result->info()->num_dimensions() > 1 |
| 185 | && mm_result->info()->tensor_shape().y() != vector_sum_row->info()->tensor_shape().x(); |
| 186 | |
| 187 | // Set the arguments to pass at compile time |
| 188 | CLBuildOptions build_opts; |
| 189 | |
| 190 | // If a_offset == 0, vector_sum_col can be a nullptr |
| 191 | if(a_offset != 0) |
| 192 | { |
| 193 | build_opts.add_option("-DA_OFFSET=" + support::cpp11::to_string(a_offset)); |
| 194 | build_opts.add_option_if(vector_sum_col->info()->tensor_shape().num_dimensions() > 1, "-DSUM_COL_HAS_BATCHES"); |
| 195 | } |
| 196 | // If b_offset == 0, vector_sum_row can be a nullptr |
| 197 | build_opts.add_option_if(b_offset != 0, "-DB_OFFSET=" + support::cpp11::to_string(b_offset)); |
| 198 | build_opts.add_option("-DK_OFFSET=" + support::cpp11::to_string(a_offset * b_offset * k)); |
| 199 | build_opts.add_option_if(reinterpret_as_3d, "-DHEIGHT_INPUT3D=" + support::cpp11::to_string(mm_result->info()->dimension(1))); |
| 200 | build_opts.add_option_if(reinterpret_as_3d, "-DDEPTH_INPUT3D=" + support::cpp11::to_string(mm_result->info()->dimension(2))); |
| 201 | build_opts.add_option_if(bias != nullptr, "-DADD_BIAS"); |
| 202 | build_opts.add_option("-DRESULT_OFFSET=" + support::cpp11::to_string(output_stage.gemmlowp_offset)); |
| 203 | build_opts.add_option("-DRESULT_MULTIPLIER=" + support::cpp11::to_string(output_stage.gemmlowp_multiplier)); |
| 204 | build_opts.add_option("-DRESULT_SHIFT=" + support::cpp11::to_string(output_stage.gemmlowp_shift)); |
| 205 | build_opts.add_option_if((min != 0) && (min != max), "-DMIN_BOUND=" + support::cpp11::to_string(min)); |
| 206 | build_opts.add_option_if((max != 255) && (min != max), "-DMAX_BOUND=" + support::cpp11::to_string(max)); |
| 207 | |
| 208 | std::string kernel_name("gemmlowp_offset_contribution"); |
| 209 | |
| 210 | // Fuse output stage |
| 211 | if(output_stage.type != GEMMLowpOutputStageType::NONE) |
| 212 | { |
| 213 | kernel_name += "_" + string_from_gemmlowp_output_stage(output_stage.type); |
| 214 | } |
| 215 | else |
| 216 | { |
| 217 | ARM_COMPUTE_ERROR("GEMMLowpOutputStage can not be NONE!"); |
| 218 | } |
| 219 | |
| 220 | // Create kernel |
| 221 | _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options())); |
| 222 | |
| 223 | // Configure kernel window |
| 224 | auto win_config = validate_and_configure_window(mm_result->info(), |
| 225 | vector_sum_col != nullptr ? vector_sum_col->info() : nullptr, |
| 226 | vector_sum_row != nullptr ? vector_sum_row->info() : nullptr, |
| 227 | bias != nullptr ? bias->info() : nullptr, |
| 228 | output->info(), |
| 229 | a_offset, b_offset); // NOLINT |
| 230 | ARM_COMPUTE_ERROR_THROW_ON(win_config.first); |
| 231 | ICLKernel::configure_internal(win_config.second); |
| 232 | |
| 233 | // Set config_id for enabling LWS tuning |
| 234 | _config_id = kernel_name + "_"; |
| 235 | _config_id += support::cpp11::to_string(mm_result->info()->dimension(0)); |
| 236 | _config_id += "_"; |
| 237 | _config_id += support::cpp11::to_string(mm_result->info()->dimension(1)); |
| 238 | _config_id += "_"; |
| 239 | _config_id += support::cpp11::to_string(mm_result->info()->dimension(2)); |
| 240 | } |
| 241 | |
| 242 | Status CLGEMMLowpOffsetContributionOutputStageKernel::validate(const ITensorInfo *mm_result, const ITensorInfo *vector_sum_col, const ITensorInfo *vector_sum_row, const ITensorInfo *bias, |
| 243 | const ITensorInfo *output, |
| 244 | int32_t a_offset, int32_t b_offset, const GEMMLowpOutputStageInfo &output_stage) |
| 245 | { |
| 246 | ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(mm_result, vector_sum_col, vector_sum_row, bias, output, a_offset, b_offset, output_stage)); |
| 247 | ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(mm_result->clone().get(), |
| 248 | vector_sum_col != nullptr ? vector_sum_col->clone().get() : nullptr, |
| 249 | vector_sum_row != nullptr ? vector_sum_row->clone().get() : nullptr, |
| 250 | bias != nullptr ? bias->clone().get() : nullptr, |
| 251 | output->clone().get(), |
| 252 | a_offset, b_offset) |
| 253 | .first); // NOLINT |
| 254 | |
| 255 | return Status{}; |
| 256 | } |
| 257 | |
| 258 | void CLGEMMLowpOffsetContributionOutputStageKernel::run(const Window &window, cl::CommandQueue &queue) |
| 259 | { |
| 260 | ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| 261 | ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); |
| 262 | |
| 263 | Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); |
| 264 | Window slice = collapsed.first_slice_window_3D(); |
| 265 | |
| 266 | // Set window for vector_sum_col |
| 267 | Window win_vector_sum_col = slice; |
| 268 | win_vector_sum_col.set(Window::DimY, Window::Dimension(0, 0, 0)); |
| 269 | win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0)); |
| 270 | |
| 271 | // Set window for vector_sum_row |
| 272 | Window win_vector_sum_row = slice; |
| 273 | win_vector_sum_row.set(Window::DimX, Window::Dimension(0, 0, 0)); |
| 274 | win_vector_sum_row.set(Window::DimY, Window::Dimension(0, 0, 0)); |
| 275 | win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0)); |
| 276 | |
| 277 | Window biases_slice = slice; |
| 278 | biases_slice.set(Window::DimY, Window::Dimension(0, 1, 1)); |
| 279 | biases_slice.set(Window::DimZ, Window::Dimension(0, 1, 1)); |
| 280 | |
| 281 | do |
| 282 | { |
| 283 | unsigned int idx = 0; |
| 284 | add_3D_tensor_argument(idx, _mm_result, slice); |
| 285 | if(_vector_sum_col != nullptr) |
| 286 | { |
| 287 | add_2D_tensor_argument(idx, _vector_sum_col, win_vector_sum_col); |
| 288 | } |
| 289 | if(_vector_sum_row != nullptr) |
| 290 | { |
| 291 | add_2D_tensor_argument(idx, _vector_sum_row, win_vector_sum_row); |
| 292 | } |
| 293 | if(_bias != nullptr) |
| 294 | { |
| 295 | add_1D_tensor_argument(idx, _bias, biases_slice); |
| 296 | } |
| 297 | add_3D_tensor_argument(idx, _output, slice); |
| 298 | enqueue(queue, *this, slice, lws_hint()); |
| 299 | } |
| 300 | while(collapsed.slide_window_slice_3D(slice)); |
| 301 | } |