Michele Di Giorgio | d556d7b | 2020-10-27 10:56:31 +0000 | [diff] [blame] | 1 | /* |
ramelg01 | c827e99 | 2022-04-08 03:52:28 +0100 | [diff] [blame] | 2 | * Copyright (c) 2021-2022 Arm Limited. |
Michele Di Giorgio | d556d7b | 2020-10-27 10:56:31 +0000 | [diff] [blame] | 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 | |
| 25 | #pragma once |
| 26 | |
ramelg01 | c827e99 | 2022-04-08 03:52:28 +0100 | [diff] [blame] | 27 | #include "depthfirst_driver.hpp" |
| 28 | #include "src/core/NEON/kernels/arm_conv/addressing.hpp" |
Michele Di Giorgio | d556d7b | 2020-10-27 10:56:31 +0000 | [diff] [blame] | 29 | #include "utils.hpp" |
Pablo Marquez Tello | 84a0941 | 2022-06-30 17:00:09 +0100 | [diff] [blame] | 30 | #if !defined(_WIN64) && !defined(__OpenBSD__) |
ramelg01 | c827e99 | 2022-04-08 03:52:28 +0100 | [diff] [blame] | 31 | #include <alloca.h> |
Pablo Marquez Tello | 84a0941 | 2022-06-30 17:00:09 +0100 | [diff] [blame] | 32 | #endif /* !defined(_WIN64) && !defined(__OpenBSD__) */ |
Michele Di Giorgio | d556d7b | 2020-10-27 10:56:31 +0000 | [diff] [blame] | 33 | #include <limits> |
| 34 | |
| 35 | namespace arm_conv { |
| 36 | namespace pooling { |
| 37 | |
ramelg01 | c827e99 | 2022-04-08 03:52:28 +0100 | [diff] [blame] | 38 | template <typename TInput, typename TOutput> |
| 39 | class DepthfirstStrategy : public IDepthfirstStrategy |
Michele Di Giorgio | d556d7b | 2020-10-27 10:56:31 +0000 | [diff] [blame] | 40 | { |
ramelg01 | c827e99 | 2022-04-08 03:52:28 +0100 | [diff] [blame] | 41 | unsigned int input_rows, input_cols, output_rows, output_cols; |
Michele Di Giorgio | d556d7b | 2020-10-27 10:56:31 +0000 | [diff] [blame] | 42 | |
ramelg01 | c827e99 | 2022-04-08 03:52:28 +0100 | [diff] [blame] | 43 | public: |
| 44 | DepthfirstStrategy(unsigned int window_rows, unsigned int window_cols, |
| 45 | unsigned int stride_rows, unsigned int stride_cols, |
| 46 | unsigned int output_rows, unsigned int output_cols) |
| 47 | : input_rows(output_rows + (window_rows - 1) * stride_rows), |
| 48 | input_cols(output_cols + (window_cols - 1) * stride_cols), |
| 49 | output_rows(output_rows), output_cols(output_cols) |
Michele Di Giorgio | d556d7b | 2020-10-27 10:56:31 +0000 | [diff] [blame] | 50 | { |
Michele Di Giorgio | d556d7b | 2020-10-27 10:56:31 +0000 | [diff] [blame] | 51 | } |
| 52 | |
ramelg01 | c827e99 | 2022-04-08 03:52:28 +0100 | [diff] [blame] | 53 | unsigned int get_input_rows() const override { return input_rows; } |
| 54 | unsigned int get_input_cols() const override { return input_cols; } |
| 55 | unsigned int get_output_rows() const override { return output_rows; } |
| 56 | unsigned int get_output_cols() const override { return output_cols; } |
Michele Di Giorgio | d556d7b | 2020-10-27 10:56:31 +0000 | [diff] [blame] | 57 | |
ramelg01 | c827e99 | 2022-04-08 03:52:28 +0100 | [diff] [blame] | 58 | typedef void (*KernelType)( |
| 59 | unsigned int n_channels, |
| 60 | const TInput *const *, |
| 61 | TOutput *const *, |
| 62 | bool exclude_padding, |
| 63 | unsigned int pad_left, |
| 64 | unsigned int pad_top, |
| 65 | unsigned int pad_right, |
| 66 | unsigned int pad_bottom |
| 67 | ); |
| 68 | virtual KernelType get_kernel(void) const = 0; |
| 69 | }; |
| 70 | |
| 71 | |
| 72 | struct WorkingSpace |
| 73 | { |
| 74 | void *input_buffer; |
| 75 | void *output_buffer; |
| 76 | }; |
| 77 | |
| 78 | |
| 79 | template <typename TInput, typename TOutput=TInput, class OutputStage=Nothing> |
| 80 | class PoolingDepthfirst : public DepthfirstDriver<TInput, TOutput> |
| 81 | { |
Michele Di Giorgio | d556d7b | 2020-10-27 10:56:31 +0000 | [diff] [blame] | 82 | size_t sizeof_input_buffer(void) const |
| 83 | { |
ramelg01 | c827e99 | 2022-04-08 03:52:28 +0100 | [diff] [blame] | 84 | return sizeof(TInput) * this->m_args.n_channels; |
Michele Di Giorgio | d556d7b | 2020-10-27 10:56:31 +0000 | [diff] [blame] | 85 | } |
| 86 | |
| 87 | size_t sizeof_output_buffer(void) const |
| 88 | { |
ramelg01 | c827e99 | 2022-04-08 03:52:28 +0100 | [diff] [blame] | 89 | return sizeof(TOutput) * this->m_args.n_channels; |
| 90 | } |
| 91 | |
| 92 | protected: |
| 93 | /* Compute the amount of working space required for a single thread. */ |
| 94 | size_t get_working_size_per_thread(unsigned int n_channels) const override |
| 95 | { |
| 96 | return sizeof(WorkingSpace) + n_channels * (sizeof(TInput) + sizeof(TOutput)); |
| 97 | } |
| 98 | |
| 99 | /* Initialise the working space for a thread. */ |
| 100 | void initialise_working_space(void *raw_ws, unsigned int n_channels) const override |
| 101 | { |
| 102 | auto ws = reinterpret_cast<WorkingSpace *>(raw_ws); |
| 103 | ws->input_buffer = ws + 1; |
| 104 | ws->output_buffer = reinterpret_cast<TInput *>(ws + 1) + n_channels; |
| 105 | |
| 106 | // Fill the input buffer with an appropriate value |
| 107 | TInput fill_val = 0; |
| 108 | if (this->m_args.pool_type == PoolingType::MAX) |
| 109 | { |
| 110 | using limits = std::numeric_limits<TInput>; |
| 111 | if (limits::has_infinity) |
| 112 | { |
| 113 | fill_val = -limits::infinity(); |
| 114 | } |
| 115 | else |
| 116 | { |
| 117 | fill_val = limits::min(); |
| 118 | } |
| 119 | } |
| 120 | |
| 121 | auto ptr = reinterpret_cast<TInput *>(ws->input_buffer); |
| 122 | for (; n_channels; n_channels--) |
| 123 | { |
| 124 | *(ptr++) = fill_val; |
| 125 | } |
| 126 | } |
| 127 | |
| 128 | /* Compute a portion of the output tensor with padding. */ |
| 129 | void compute_tile_padded( |
| 130 | unsigned int output_i, unsigned int output_j, |
| 131 | unsigned int channel_start, unsigned int channel_end, |
| 132 | const TensorSpec<const TInput *> &input, |
| 133 | const TensorSpec<TOutput *> &output, |
| 134 | void *working_space |
| 135 | ) const override |
| 136 | { |
| 137 | const auto kern = reinterpret_cast<const DepthfirstStrategy<TInput, TOutput> *>( |
| 138 | this->m_strat.get())->get_kernel(); |
| 139 | |
| 140 | // Get the working space, and some space on the stack for pointer arrays |
| 141 | auto ws = reinterpret_cast<WorkingSpace *>(working_space); |
| 142 | auto inptr_array = reinterpret_cast<const TInput **>(alloca( |
| 143 | sizeof(TInput *) * this->m_strat->get_input_rows() * this->m_strat->get_input_cols())); |
| 144 | auto outptr_array = reinterpret_cast<TOutput **>(alloca( |
| 145 | sizeof(TOutput *) * this->m_strat->get_output_rows() * this->m_strat->get_output_cols())); |
| 146 | |
| 147 | // Prepare the input pointers |
| 148 | const int ii = static_cast<int>(output_i * this->m_args.pool_stride.rows) - this->m_args.padding.top; |
| 149 | const auto input_pad_top = static_cast<unsigned int>(ii < 0 ? -ii : 0); |
| 150 | const auto input_i = static_cast<unsigned int>(ii < 0 ? 0 : ii); |
| 151 | |
| 152 | const unsigned int end_ii = ii + this->m_strat->get_input_rows(); |
| 153 | const auto input_pad_bottom = end_ii < this->m_args.input_rows ? 0 : end_ii - this->m_args.input_rows; |
| 154 | |
| 155 | const int ij = static_cast<int>(output_j * this->m_args.pool_stride.cols) - this->m_args.padding.left; |
| 156 | const auto input_pad_left = static_cast<unsigned int>(ij < 0 ? -ij : 0); |
| 157 | const auto input_j = static_cast<unsigned int>(ij < 0 ? 0 : ij); |
| 158 | |
| 159 | const unsigned int end_ij = ij + this->m_strat->get_input_cols(); |
| 160 | const auto input_pad_right = end_ij < this->m_args.input_cols ? 0 : end_ij - this->m_args.input_cols; |
| 161 | |
| 162 | fill_pointer_array<const TInput>( |
| 163 | inptr_array, this->m_strat->get_input_rows(), this->m_strat->get_input_cols(), |
| 164 | input.base + input_i*input.ld_row + input_j*input.ld_col + channel_start, |
| 165 | input.ld_row, input.ld_col, |
| 166 | reinterpret_cast<const TInput *>(ws->input_buffer), |
| 167 | input_pad_top, this->m_args.input_rows - input_i, |
| 168 | input_pad_left, this->m_args.input_cols - input_j |
| 169 | ); |
| 170 | |
| 171 | // Prepare the output pointers |
| 172 | fill_pointer_array( |
| 173 | outptr_array, this->m_strat->get_output_rows(), this->m_strat->get_output_cols(), |
| 174 | output.base + output_i*output.ld_row + output_j*output.ld_col + channel_start, |
| 175 | output.ld_row, output.ld_col, |
| 176 | reinterpret_cast<TOutput *>(ws->output_buffer), |
| 177 | 0, this->m_args.output_rows - output_i, // Top padding, # valid rows |
| 178 | 0, this->m_args.output_cols - output_j // Left padding, # valid columns |
| 179 | ); |
| 180 | |
| 181 | // Call the kernel |
| 182 | kern( |
| 183 | channel_end - channel_start, inptr_array, outptr_array, |
| 184 | this->m_args.exclude_padding, |
| 185 | input_pad_left, input_pad_top, |
| 186 | input_pad_right, input_pad_bottom |
| 187 | ); |
| 188 | } |
| 189 | |
| 190 | // Compute a portion of the work with only top/bottom padding. |
| 191 | void compute_row_padded_tile_row( |
| 192 | const unsigned int output_i, unsigned int output_j, unsigned int n_tile_cols, |
| 193 | const unsigned int channel_start, const unsigned int channel_end, |
| 194 | const TensorSpec<const TInput *> &input, |
| 195 | const TensorSpec<TOutput *> &output, |
| 196 | void *working_space |
| 197 | ) const override |
| 198 | { |
| 199 | const auto kern = reinterpret_cast<const DepthfirstStrategy<TInput, TOutput> *>( |
| 200 | this->m_strat.get())->get_kernel(); |
| 201 | |
| 202 | // Get the working space, and some space on the stack for pointer arrays |
| 203 | auto ws = reinterpret_cast<WorkingSpace *>(working_space); |
| 204 | auto inptr_array = reinterpret_cast<const TInput **>(alloca( |
| 205 | sizeof(TInput *) * this->m_strat->get_input_rows() * this->m_strat->get_input_cols())); |
| 206 | auto outptr_array = reinterpret_cast<TOutput **>(alloca( |
| 207 | sizeof(TOutput *) * this->m_strat->get_output_rows() * this->m_strat->get_output_cols())); |
| 208 | |
| 209 | // Prepare the initial input pointers |
| 210 | const int ii = static_cast<int>(output_i * this->m_args.pool_stride.rows) - this->m_args.padding.top; |
| 211 | const auto input_pad_top = static_cast<unsigned int>(ii < 0 ? -ii : 0); |
| 212 | const auto input_i = static_cast<unsigned int>(ii < 0 ? 0 : ii); |
| 213 | |
| 214 | const unsigned int end_ii = ii + this->m_strat->get_input_rows(); |
| 215 | const auto input_pad_bottom = end_ii < this->m_args.input_rows ? 0 : end_ii - this->m_args.input_rows; |
| 216 | |
| 217 | const int ij = static_cast<int>(output_j * this->m_args.pool_stride.cols) - this->m_args.padding.left; |
| 218 | const auto input_j = static_cast<unsigned int>(ij < 0 ? 0 : ij); |
| 219 | |
| 220 | const auto end_oi = output_i + this->m_strat->get_output_cols(); |
| 221 | const auto output_pad_bottom = end_oi < this->m_args.output_rows ? 0 : end_oi - this->m_args.output_rows; |
| 222 | |
| 223 | fill_pointer_array<const TInput>( |
| 224 | inptr_array, this->m_strat->get_input_rows(), this->m_strat->get_input_cols(), |
| 225 | input.base + input_i*input.ld_row + input_j*input.ld_col + channel_start, |
| 226 | input.ld_row, input.ld_col, |
| 227 | reinterpret_cast<const TInput *>(ws->input_buffer), |
| 228 | input_pad_top, this->m_args.input_rows - input_i, |
| 229 | 0, this->m_args.input_cols - input_j |
| 230 | ); |
| 231 | |
| 232 | // Prepare the initial output pointers |
| 233 | fill_pointer_array( |
| 234 | outptr_array, this->m_strat->get_output_rows(), this->m_strat->get_output_cols(), |
| 235 | output.base + output_i*output.ld_row + output_j*output.ld_col + channel_start, |
| 236 | output.ld_row, output.ld_col, |
| 237 | reinterpret_cast<TOutput *>(ws->output_buffer), |
| 238 | 0, this->m_args.output_rows - output_i, // Top padding, # valid rows |
| 239 | 0, this->m_args.output_cols - output_j // Left padding, # valid columns |
| 240 | ); |
| 241 | |
| 242 | // Call the kernel |
| 243 | for (; n_tile_cols; n_tile_cols--) |
| 244 | { |
| 245 | kern( |
| 246 | channel_end - channel_start, inptr_array, outptr_array, |
| 247 | this->m_args.exclude_padding, |
| 248 | 0, input_pad_top, |
| 249 | 0, input_pad_bottom |
| 250 | ); |
| 251 | |
| 252 | // Progress the input and output pointer arrays |
| 253 | const auto input_col_stride = input.ld_col * this->m_strat->get_output_cols() * this->m_args.pool_stride.cols; |
| 254 | for ( |
| 255 | auto n = input_pad_top * this->m_strat->get_input_cols(); |
| 256 | n < (this->m_strat->get_input_rows() - input_pad_bottom) * this->m_strat->get_input_cols(); |
| 257 | n++ |
| 258 | ) |
| 259 | { |
| 260 | inptr_array[n] += input_col_stride; |
| 261 | } |
| 262 | |
| 263 | const auto output_col_stride = output.ld_col * this->m_strat->get_output_cols(); |
| 264 | for ( |
| 265 | auto n = 0u; |
| 266 | n < (this->m_strat->get_output_rows() - output_pad_bottom) * this->m_strat->get_output_cols(); |
| 267 | n++ |
| 268 | ) |
| 269 | { |
| 270 | outptr_array[n] += output_col_stride; |
| 271 | } |
| 272 | } |
Michele Di Giorgio | d556d7b | 2020-10-27 10:56:31 +0000 | [diff] [blame] | 273 | } |
| 274 | |
| 275 | public: |
ramelg01 | c827e99 | 2022-04-08 03:52:28 +0100 | [diff] [blame] | 276 | PoolingDepthfirst(const DepthfirstStrategy<TInput, TOutput> *strat, |
| 277 | const PoolingArgs &args, const OutputStage &os = {}) |
| 278 | : DepthfirstDriver<TInput, TOutput>(strat, args) |
Michele Di Giorgio | d556d7b | 2020-10-27 10:56:31 +0000 | [diff] [blame] | 279 | { |
ramelg01 | c827e99 | 2022-04-08 03:52:28 +0100 | [diff] [blame] | 280 | ARM_COMPUTE_UNUSED(os); |
Michele Di Giorgio | d556d7b | 2020-10-27 10:56:31 +0000 | [diff] [blame] | 281 | } |
| 282 | }; |
| 283 | |
| 284 | } // namespace pooling |
| 285 | } // namespace arm_conv |