1/* 2 * Copyright (c) 2021-2023 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 25#include "activation_float_helpers.h" 26#include "helpers.h" 27#include "helpers_asymm.h" 28#include "tile_helpers.h" 29 30//! @cond Doxygen_Suppress 31/** OpenCL kernel to compute the direct convolution. 32 * 33 * @note Data layout supported: NHWC 34 * @note Data type supported: F32/F16/QASYMM8/QASYMM8_SIGNED 35 * @note The accumulation data type must be passed at compile time using -DACC_DATA_TYPE (e.g. -DDATA_TYPE_PROMOTED=half) 36 * @note The convolution padding (left and top) must be passed at compile time using -DPAD_LEFT and -DPAD_TOP (e.g. -DPAD_LEFT=2, -DPAD_TOP=2) 37 * @note The convolution strides must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y (e.g. -DSTRIDE_X=2, -DSTRIDE_Y=2) 38 * @note The spatial dimensions of the weights must be passed at compile time using -DWEI_WIDTH and -DWEI_HEIGHT (e.g. -DWEI_WIDTH=9, -DWEI_HEIGHT=9) 39 * @note The spatial dimensions of the source tensor must be passed at compile time using -DSRC_WIDTH and -DSRC_HEIGHT (e.g. -DSRC_WIDTH=96, -DSRC_HEIGHT=64) 40 * @note The spatial dimensions of the destination tensor must be passed at compile time using -DDST_WIDTH and -DDST_HEIGHT (e.g. -DDST_WIDTH=96, -DDST_HEIGHT=64) 41 * @note The channels of the source tensor must be passed at compile time using -DSRC_CHANNELS (e.g. -DSRC_CHANNELS=64) 42 * @note The channels of the destination tensor must be passed at compile time using -DDST_CHANNELS (e.g. -DDDST_CHANNELS=64) 43 * @note The tensor type ("BUFFER" or "IMAGE") of the source tensor must be passed at compile time using -DSRC_TENSOR_TYPE (e.g. -DSRC_TENSOR_TYPE=BUFFER) 44 * @note The tensor type ("BUFFER" or "IMAGE") of the weights tensor must be passed at compile time using -DWEI_TENSOR_TYPE (e.g. -DWEI_TENSOR_TYPE=BUFFER) 45 * @note The tensor type ("BUFFER" or "IMAGE") of the destination tensor must be passed at compile time using -DDST_TENSOR_TYPE (e.g. -DDST_TENSOR_TYPE=BUFFER) 46 * @note The data type of the source tensor must be passed at compile time using -DSRC_DATA_TYPE (e.g. -DSRC_DATA_TYPE=float) 47 * @note The data type of the weights tensor must be passed at compile time using -DWEI_DATA_TYPE (e.g. -DWEI_DATA_TYPE=float) 48 * @note The data type of the destination tensor must be passed at compile time using -DDST_DATA_TYPE (e.g. -DDST_DATA_TYPE=float) 49 * @note The data type of the accumulators must be passed at compile time using -DACC_DATA_TYPE (e.g. -DACC_DATA_TYPE=float) 50 * @note The number of M0 rows (width*height) to process must be passed at compile time using -DM0 (e.g. -DM0=2) 51 * @note The number of N0 output channels to process must be passed at compile time using -DN0 (e.g. -DN0=2) 52 * @note The number of K0 inner accumulations must be passed at compile time using -DK0 (e.g. -DK0=2) 53 * @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_N0 (e.g. -DPARTIAL_N0=1) 54 * @note The zero value must be passed at compile time using -DZERO_VALUE (e.g. -DZERO_VALUE=0) 55 * @note Only the following configurations of M0, N0 and K0 are currently supported: 56 * - M0 = 1, 2, 3, 4, 5, 6, 7, and 8 57 * - N0 = 2, 3, 4, 8, 16 58 * - K0 = 2, 3, 4, 8, 16 (only 4, 8 and 16 if WEI_TENSOR_TYPE=IMAGE) 59 * 60 *@note In case of QASYMM8/QASYMM8_SIGNED, the following extra information must be passed at compile time: 61 * - -DIS_QUANTIZED 62 * - The destination quantization multiplier e.g. -DDST_MULTIPLIER=1234 63 * - The destination quantization shift e.g. -DDST_SHIFT=4 64 * - The destination offset e.g. -DDST_OFFSET=4 65 * - The source offset e.g. -DSRC_OFFSET=4 66 * - The weights offset e.g. -DWEI_OFFSET=4 67 * - The quantized zero value e.g. -DZERO_VALUE=4 68 * 69 * @param[in] src_img (Not supported) Read only cl_image object for the source tensor. Included when SRC_TENSOR_TYPE=IMAGE 70 * @param[in] src_ptr Pointer to the source tensor. Supported data type: F16/F32/QASYMM8 71 * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) 72 * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) 73 * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes) 74 * @param[in] src_c The size of the channels dimension of the source tensor 75 * @param[in] src_w The size of the width dimension of the source tensor 76 * @param[in] src_h The size of the height dimension of the source tensor 77 * @param[in] src_n The size of the batches dimension of the source tensor 78 * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor 79 * @param[out] dst_img (Not supported) Write only cl_image object for the destination tensor. Included when DST_TENSOR_TYPE=IMAGE 80 * @param[out] dst_ptr Pointer to the destination tensor. Supported data type: same as @p src_ptr 81 * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) 82 * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) 83 * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes) 84 * @param[in] dst_c The size of the channels dimension of the destination tensor 85 * @param[in] dst_w The size of the width dimension of the destination tensor 86 * @param[in] dst_h The size of the height dimension of the destination tensor 87 * @param[in] dst_n The size of the batches dimension of the destination tensor 88 * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor 89 * @param[in] wei_img (Optional) Read only cl_image object for the weights tensor. Included when WEI_TENSOR_TYPE=IMAGE 90 * @param[in] wei_ptr Pointer to the weights tensor. Supported data type: same as @p src_ptr 91 * @param[in] wei_stride_y Stride of the weights tensor in Y dimension (in bytes) 92 * @param[in] wei_stride_z Stride of the weights tensor in Z dimension (in bytes) 93 * @param[in] wei_stride_w Stride of the weights tensor in W dimension (in bytes) 94 * @param[in] wei_c The size of the channels dimension of the weights tensor 95 * @param[in] wei_w The size of the width dimension of the weights tensor 96 * @param[in] wei_h The size of the height dimension of the weights tensor 97 * @param[in] wei_n The size of the batches dimension of the weights tensor 98 * @param[in] wei_offset_first_element_in_bytes The offset of the first element in the weights matrix 99 * @param[in] bia_ptr (Optional) Pointer to the bias tensor Supported data type: same as @p src_ptr (if F32/F16) or S32 (if QASYMM8/QASYMM8_SIGNED) 100 * @param[in] bia_stride_x (Optional) Stride of the bias tensor in X dimension (in bytes) 101 * @param[in] bia_step_x (Optional) bia_stride_x * number of elements along X processed per workitem(in bytes) 102 * @param[in] bia_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix 103 */ 104//! @endcond 105__kernel void direct_convolution_nhwc( 106 TENSOR4D_RO_T(src, SRC_TENSOR_TYPE), 107 TENSOR4D_WO_T(dst, DST_TENSOR_TYPE), 108 TENSOR4D_RO_T(wei, WEI_TENSOR_TYPE) 109#if defined(HAS_BIAS) 110 , 111 VECTOR_DECLARATION(bia) 112#endif // defined(HAS_BIAS) 113) 114{ 115 // All the tensor dimensions are passed at compile time. 116 // In case of dynamic tensor support, the following dimensions should be passed as function argument. 117#define _IWEI_WIDTH WEI_WIDTH 118#define _IWEI_HEIGHT WEI_HEIGHT 119#define _ISRC_WIDTH SRC_WIDTH 120#define _ISRC_HEIGHT SRC_HEIGHT 121#define _ISRC_CHANNELS SRC_CHANNELS 122#define _IDST_WIDTH DST_WIDTH 123#define _IDST_HEIGHT DST_HEIGHT 124#define _IDST_CHANNELS DST_CHANNELS 125#define _IY_MULTIPLIER (_IWEI_WIDTH * _IWEI_HEIGHT) 126 127 // If quantized, the output tile has to be quantized first before being stored to global memory 128#if defined(IS_QUANTIZED) 129#define _IOUTPUT_TILE cq 130#else // defined(IS_QUANTIZED) 131#define _IOUTPUT_TILE c 132#endif // defined(IS_QUANTIZED) 133 134 const int cout = GET_SPATIAL_IDX(0, N0, PARTIAL_N0); // OFM 135 const int mout = GET_SPATIAL_IDX(1, M0, 0); // WIDTH x HEIGHT 136 const int bout = GET_SPATIAL_IDX(2, 1, 0); // BATCH SIZE IDX 137 138 // .v = access the whole vector (OpenCL vector) 139 // .s[x] = access the vector element at position x (scalar access) 140 TILE(int, 1, M0, xi); 141 TILE(int, 1, M0, yi); 142 143 // Convert the linear index to coordinate 144 LOOP_UNROLLING(int, i, 0, 1, M0, 145 { 146 xi[0].s[i] = ((mout + i) % _IDST_WIDTH) * STRIDE_X; 147 yi[0].s[i] = ((mout + i) / _IDST_WIDTH) * STRIDE_Y; 148 xi[0].s[i] -= PAD_LEFT; 149 yi[0].s[i] -= PAD_TOP; 150 }) 151 152 // Initialize the accumulators 153 TILE(ACC_DATA_TYPE, M0, N0, c); 154 155 LOOP_UNROLLING(int, i, 0, 1, M0, 156 { 157 c[i].v = 0; 158 }) 159 160 for(int i = 0; i < (_IWEI_WIDTH * _IWEI_HEIGHT); ++i) 161 { 162 int xk = i % _IWEI_WIDTH; 163 int yk = i / _IWEI_WIDTH; 164 165 TILE(int, 1, M0, my); 166 167 LOOP_UNROLLING(int, i, 0, 1, M0, 168 { 169 int x_s = xi[0].s[i] + xk; 170 int y_s = yi[0].s[i] + yk; 171 my[0].s[i] = x_s + y_s *_ISRC_WIDTH; 172 my[0].s[i] = my[0].s[i] + bout * (int)(_ISRC_WIDTH * _ISRC_HEIGHT); 173 my[0].s[i] = select(-1, my[0].s[i], x_s >= 0); 174 my[0].s[i] = select(-1, my[0].s[i], x_s < _ISRC_WIDTH); 175 my[0].s[i] = select(-1, my[0].s[i], y_s >= 0); 176 my[0].s[i] = select(-1, my[0].s[i], y_s < _ISRC_HEIGHT); 177 }) 178 179 int ck = 0; 180 for(; ck <= (_ISRC_CHANNELS - K0); ck += K0) 181 { 182 TILE(SRC_DATA_TYPE, M0, K0, a); 183 TILE(WEI_DATA_TYPE, N0, K0, b); 184 185 // Initialize tiles 186 LOOP_UNROLLING(int, i, 0, 1, M0, 187 { 188 a[i].v = ZERO_VALUE; 189 }) 190 191 LOOP_UNROLLING(int, i, 0, 1, N0, 192 { 193 b[i].v = ZERO_VALUE; 194 }) 195 196 // Load tile from the src tensor 197 T_LOAD2D_INDIRECT(SRC_DATA_TYPE, M0, K0, SRC_TENSOR_TYPE, src, ck, src_stride_y, my, a); 198 199 // Load tile from the weights tensor 200 T_LOAD(WEI_DATA_TYPE, N0, K0, WEI_TENSOR_TYPE, wei, ck, cout * _IY_MULTIPLIER + i, _IY_MULTIPLIER, wei_stride_y, b); 201 202 // Compute the matrix multiplication between two tiles 203 T_MMUL(SRC_DATA_TYPE, WEI_DATA_TYPE, ACC_DATA_TYPE, M0, N0, K0, NT, T, a, b, c); 204 205 // Apply the offset correction (correction usually needed for asymmetric quantized computation) 206 // The computation is not performed if both SRC_OFFSET and WEI_OFFSET are zero 207 T_OFFSET_CORRECTION(ACC_DATA_TYPE, M0, N0, K0, SRC_OFFSET, WEI_OFFSET, a, b, c); 208 } 209 210 // This #if directive should be removed in case of dynamic tensor support 211#if defined(LEFTOVER_LOOP) 212 // Left-over accumulations 213 for(; ck < _ISRC_CHANNELS; ++ck) 214 { 215 TILE(SRC_DATA_TYPE, M0, 1, a); 216 TILE(WEI_DATA_TYPE, N0, 1, b); 217 218 // Initialize tiles 219 LOOP_UNROLLING(int, i, 0, 1, M0, 220 { 221 a[i].v = ZERO_VALUE; 222 }) 223 224 LOOP_UNROLLING(int, i, 0, 1, N0, 225 { 226 b[i].v = ZERO_VALUE; 227 }) 228 229 // Load tile from the src tensor 230 T_LOAD2D_INDIRECT(SRC_DATA_TYPE, M0, 1, SRC_TENSOR_TYPE, src, ck, src_stride_y, my, a); 231 232 // Load tile from the weights tensor 233 // The T_LOAD for the left-over elements can only use BUFFER because we load one element per iteration 234 T_LOAD(WEI_DATA_TYPE, N0, 1, BUFFER, wei, ck, cout * _IY_MULTIPLIER + i, _IY_MULTIPLIER, wei_stride_y, b); 235 236 // Compute the matrix multiplication between two tiles 237 T_MMUL(SRC_DATA_TYPE, WEI_DATA_TYPE, ACC_DATA_TYPE, M0, N0, 1, NT, T, a, b, c); 238 239 // Apply the offset correction (operation usually needed for asymmetric quantized computation) 240 // The computation is not performed if both SRC_OFFSET and WEI_OFFSET are zero 241 T_OFFSET_CORRECTION(ACC_DATA_TYPE, M0, N0, 1, SRC_OFFSET, WEI_OFFSET, a, b, c); 242 } 243#endif // defined(LEFTOVER_LOOP) 244 } 245 246 // Offset correction required for the quantized asymmetric computation 247 // The computation is not performed if both SRC_OFFSET and WEI_OFFSET are zero 248 T_ADD_CONSTANT(ACC_DATA_TYPE, M0, N0, c, (_IWEI_WIDTH * _IWEI_HEIGHT * _ISRC_CHANNELS * SRC_OFFSET * WEI_OFFSET), c); 249 250#if defined(HAS_BIAS) 251 TILE(BIA_DATA_TYPE, 1, N0, bias0); 252 253 T_LOAD(BIA_DATA_TYPE, 1, N0, BUFFER, bia, cout, 0, 1, 0, bias0); 254 255 // c = c + bias[broadcasted] 256 T_ELTWISE_BROADCAST_ADD_X(ACC_DATA_TYPE, M0, N0, c, bias0, c); 257 258#endif // HAS_BIAS 259 260#if defined(IS_QUANTIZED) 261 262 TILE(DST_DATA_TYPE, M0, N0, cq); 263 264 // Quantize the tile 265 T_QUANTIZE8_ASYMMETRIC(ACC_DATA_TYPE, DST_DATA_TYPE, M0, N0, DST_OFFSET, DST_SHIFT, DST_MULTIPLIER, c, cq); 266#endif // defined(IS_QUANTIZED) 267 268 // Apply activation 269 T_ACTIVATION(DST_DATA_TYPE, M0, N0, ACTIVATION_TYPE, A_VAL, B_VAL, _IOUTPUT_TILE, _IOUTPUT_TILE); 270 271 TILE(uint, M0, 1, dst_indirect_y); 272 273 // Calculate the destination indirect Y 274 LOOP_UNROLLING(int, i, 0, 1, M0, 275 { 276 dst_indirect_y[i].v = (uint)min(mout + i, (int)(_IDST_WIDTH * _IDST_HEIGHT) - 1); 277 dst_indirect_y[i].v += bout * (int)(_IDST_WIDTH * _IDST_HEIGHT); 278 }) 279 280 bool x_cond = PARTIAL_N0 != 0 && get_global_id(0) == 0; 281 282 // _IOUTPUT_TILE: c = fp32/fp16, cq=qasymm8 283 // Store the tile in reverse order so the invalid values are overwritten with the valid ones 284 T_STORE_INDIRECT_WIDTH_SELECT(DST_DATA_TYPE, M0, N0, PARTIAL_N0, DST_TENSOR_TYPE, dst, cout, dst_stride_y, x_cond, _IOUTPUT_TILE, dst_indirect_y); 285 286#undef _IWEI_WIDTH 287#undef _IWEI_HEIGHT 288#undef _ISRC_WIDTH 289#undef _ISRC_HEIGHT 290#undef _ISRC_CHANNELS 291#undef _IDST_WIDTH 292#undef _IDST_HEIGHT 293#undef _IDST_CHANNELS 294#undef _IY_MULTIPLIER 295} 296