1/* 2 * Copyright (c) 2016-2021 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 "helpers.h" 25#include "helpers_asymm.h" 26 27#if defined(FLOAT_DATA_TYPE) 28#define ISGREATER(x, y) (SELECT_VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE))(isgreater(x, y)) 29#define ISLESS(x, y) (SELECT_VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE))(isless(x, y)) 30#define ISGREATER_SCALAR(x, y) (SELECT_DATA_TYPE(DATA_TYPE_PROMOTED))(isgreater(x, y)) 31#define ISLESS_SCALAR(x, y) (SELECT_DATA_TYPE(DATA_TYPE_PROMOTED))(isless(x, y)) 32#else // !FLOAT_DATA_TYPE 33#if defined(WIDTH) 34#define ISGREATER(x, y) (x > y) ? 1 : 0 35#define ISLESS(x, y) (x < y) ? 1 : 0 36#define ISGREATER_SCALAR ISGREATER 37#define ISLESS_SCALAR ISLESS 38#else // !defined(WIDTH) 39#define ISGREATER(x, y) select((VEC_DATA_TYPE(int, VEC_SIZE))0, (VEC_DATA_TYPE(int, VEC_SIZE)) - 1, x > y) 40#define ISLESS(x, y) select((VEC_DATA_TYPE(int, VEC_SIZE))0, (VEC_DATA_TYPE(int, VEC_SIZE)) - 1, x < y) 41#endif // defined(WIDTH) 42#endif // defined(FLOAT_DATA_TYPE) 43 44#if defined(WIDTH) 45#if defined(OPERATION) 46 47#define sum(in0, in1, size) (in0 + SUM_REDUCE(in1, size)) 48#define square_sum(in0, in1, size) (in0 + SUM_REDUCE((in1 * in1), size)) 49#define product(in0, in1, size) (in0 * PROD_REDUCE(in1, size)) 50 51/** This kernel performs parallel reduction given an operation on x-axis. 52 * 53 * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float 54 * @note The operation we want to perform must be passed at compile time using -DOPERATION e.g. -DOPERATION=square_sum 55 * @note The mean flag must be passed at compile time using -DMEAN if we want to compute the mean value 56 * @note The product flag must be passed at compile time using -DPROD if we want to compute the product, otherwise sum will be used 57 * @note The width size must be passed at compile time using -DWIDTH e.g. -DWIDTH=128 if we want to compute the mean value 58 * 59 * @param[in] input_ptr Pointer to the source tensor. Supported data types: F16/F32 60 * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes) 61 * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) 62 * @param[in] input_stride_y Stride of the source tensor in Y dimension (in bytes) 63 * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) 64 * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source tensor 65 * @param[in] output_ptr Pointer to the destination tensor. Supported data types: same as @p input 66 * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes) 67 * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) 68 * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes) 69 * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) 70 * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor 71 */ 72__kernel void reduction_operation_x( 73 TENSOR3D_DECLARATION(input), 74 TENSOR3D_DECLARATION(output)) 75{ 76 int y = get_global_id(1); 77 int z = get_global_id(2); 78 79 __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + y * input_stride_y + z * input_stride_z; 80 __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + y * output_stride_y + z * output_stride_z; 81 82#if defined(PROD) 83 DATA_TYPE res = (DATA_TYPE)1; 84#else // defined(PROD) 85 DATA_TYPE res = (DATA_TYPE)0; 86#endif // defined(PROD) 87 88 int x = 0; 89 90 for(; x <= (WIDTH - VEC_SIZE); x += VEC_SIZE) 91 { 92 VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) 93 vals = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + x * sizeof(DATA_TYPE))); 94 res = OPERATION(res, vals, VEC_SIZE); 95 } 96 97#if(WIDTH % VEC_SIZE) 98 _Pragma("unroll") for(; x < WIDTH; ++x) 99 { 100 DATA_TYPE val = *((__global DATA_TYPE *)(input_addr + x * sizeof(DATA_TYPE))); 101 res = OPERATION(res, val, 1); 102 } 103#endif // (WIDTH % VEC_SIZE) 104 105#if defined(MEAN) 106 res /= WIDTH; 107#endif // defined(MEAN) 108 *((__global DATA_TYPE *)output_addr) = res; 109} 110#endif // defined(OPERATION) 111/** This kernel performs reduction on x-axis. (Non parallel) 112 * 113 * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float 114 * @note The width size must be passed at compile time using -DWIDTH e.g. -DWIDTH=128 115 * @note The product flag must be passed at compile time using -DPROD if we want to compute the product, otherwise sum will be used 116 * 117 * @param[in] input_ptr Pointer to the source tensor. Supported data types: S32/F16/F32 and QASYMM8/QASYMM8_SIGNED for operation MEAN 118 * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes) 119 * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) 120 * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source tensor 121 * @param[in] output_ptr The local buffer to hold sumed values. Supported data types: same as @p input_ptr 122 * @param[in] output_stride_x Stride of the output tensor in X dimension (in bytes) 123 * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) 124 * @param[in] output_offset_first_element_in_bytes The offset of the first element in the source tensor 125 */ 126__kernel void reduction_operation_non_parallel_x( 127 VECTOR_DECLARATION(input), 128 VECTOR_DECLARATION(output)) 129{ 130 Vector input = CONVERT_TO_VECTOR_STRUCT(input); 131 Vector output = CONVERT_TO_VECTOR_STRUCT(output); 132 133 DATA_TYPE_PROMOTED res = CONVERT(*((__global DATA_TYPE *)vector_offset(&input, 0)), DATA_TYPE_PROMOTED); 134 135 // Convert input into F32 in order to perform quantized multiplication 136#if defined(PROD) && defined(OFFSET) && defined(SCALE) 137 float res_f = DEQUANTIZE(res, OFFSET, SCALE, DATA_TYPE_PROMOTED, 1); 138#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) 139 140 for(unsigned int x = 1; x < WIDTH; ++x) 141 { 142 DATA_TYPE_PROMOTED in = CONVERT(*((__global DATA_TYPE *)vector_offset(&input, x)), DATA_TYPE_PROMOTED); 143#if defined(MIN) 144 res = select(res, in, ISLESS_SCALAR(in, res)); 145#elif defined(MAX) 146 res = select(res, in, ISGREATER_SCALAR(in, res)); 147#elif defined(PROD) 148#if defined(OFFSET) && defined(SCALE) 149 res_f *= DEQUANTIZE(in, OFFSET, SCALE, DATA_TYPE_PROMOTED, 1); 150#else // !(defined(OFFSET) && defined(SCALE)) 151 res *= in; 152#endif // defined(OFFSET) && defined(SCALE) 153#else // defined(SUM)) 154 res += in; 155#endif // defined(MAX) || defined(MIN) || defined(PROD) 156 } 157 158 // Store result 159#if defined(MEAN) 160 res /= WIDTH; 161#endif // defined(MEAN) 162 163 // Subtract the offsets in case of quantized SUM 164#if defined(SUM) && defined(OFFSET) && defined(SCALE) 165 res -= (WIDTH - 1) * OFFSET; 166#endif // defined(OFFSET) && defined(OFFSET) && defined(SCALE) 167 168 // Re-quantize 169#if defined(PROD) && defined(OFFSET) && defined(SCALE) 170 res = QUANTIZE(res_f, OFFSET, SCALE, DATA_TYPE_PROMOTED, 1); 171#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) 172 173 *((__global DATA_TYPE *)output.ptr) = CONVERT_SAT(res, DATA_TYPE); 174} 175#endif // defined(WIDTH) 176 177#if defined(HEIGHT) 178/** This kernel performs reduction on y-axis. 179 * 180 * @note The input data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float 181 * @note The height size must be passed at compile time using -DHEIGHT e.g. -DHEIGHT=128 182 * 183 * @param[in] input_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED/S32/F16/F32 184 * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes) 185 * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) 186 * @param[in] input_stride_y Stride of the source tensor in Y dimension (in bytes) 187 * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) 188 * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source tensor 189 * @param[in] output_ptr The local buffer to hold sumed values. Supported data types: same as @p input_ptr 190 * @param[in] output_stride_x Stride of the output tensor in X dimension (in bytes) 191 * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) 192 * @param[in] output_stride_y Stride of the output tensor in Y dimension (in bytes) 193 * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) 194 * @param[in] output_offset_first_element_in_bytes The offset of the first element in the source tensor 195 */ 196__kernel void reduction_operation_y( 197 IMAGE_DECLARATION(input), 198 IMAGE_DECLARATION(output)) 199{ 200 int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); 201 int y = get_global_id(1); 202 203 __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * input_stride_y; 204 __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * output_stride_y; 205 206 VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) 207 res = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input_addr), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); 208 209 // Convert input into F32 in order to perform quantized multiplication 210#if defined(PROD) && defined(OFFSET) && defined(SCALE) 211 VEC_DATA_TYPE(float, VEC_SIZE) 212 res_f = DEQUANTIZE(res, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); 213#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) 214 215#if defined(SUM_SQUARE) 216 res *= res; 217#endif // defined(SUM_SQUARE) 218 219 for(unsigned int y = 1; y < HEIGHT; ++y) 220 { 221 VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) 222 in = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + y * input_stride_y)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); 223#if defined(MIN) 224 res = select(res, in, ISLESS(in, res)); 225#elif defined(MAX) 226 res = select(res, in, ISGREATER(in, res)); 227#else // !(defined(MAX) || defined(MIN)) 228#if defined(SUM_SQUARE) 229 in *= in; 230#endif // defined(SUM_SQUARE) 231#if defined(PROD) 232 233#if defined(OFFSET) && defined(SCALE) 234 res_f *= DEQUANTIZE(in, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); 235#else // !(defined(OFFSET) && defined(SCALE)) 236 res *= in; 237#endif // defined(OFFSET) && defined(SCALE) 238 239#else // !defined(PROD) 240 res += in; 241#endif // defined(PROD) 242#endif // defined(MAX) || defined(MIN) 243 } 244 245#if defined(MEAN) 246 res /= HEIGHT; 247#endif // defined(MEAN) 248 249 // Subtract the offsets in case of quantized SUM 250#if defined(SUM) && defined(OFFSET) && defined(SCALE) 251 res -= (HEIGHT - 1) * OFFSET; 252#endif // defined(OFFSET) && defined(OFFSET) && defined(SCALE) 253 254 // Re-quantize 255#if defined(PROD) && defined(OFFSET) && defined(SCALE) 256 res = QUANTIZE(res_f, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); 257#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) 258 259 // Store result 260 VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) 261 res0 = CONVERT_SAT(res, VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)); 262 STORE_VECTOR_SELECT(res, DATA_TYPE, output_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0); 263} 264#endif // defined(HEIGHT) 265 266#if defined(DEPTH) 267/** This kernel performs reduction on z-axis. 268 * 269 * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float 270 * @note The depth size must be passed at compile time using -DDEPTH e.g. -DDEPTH=128 271 * 272 * @param[in] input_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED/S32/F16/F32 273 * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes) 274 * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) 275 * @param[in] input_stride_y Stride of the source tensor in Y dimension (in bytes) 276 * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) 277 * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes) 278 * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) 279 * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source tensor 280 * @param[in] output_ptr The local buffer to hold sumed values. Supported data types: same as @p input_ptr 281 * @param[in] output_stride_x Stride of the output tensor in X dimension (in bytes) 282 * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) 283 * @param[in] output_stride_y Stride of the output tensor in Y dimension (in bytes) 284 * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) 285 * @param[in] output_stride_z Stride of the output tensor in Z dimension (in bytes) 286 * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes) 287 * @param[in] output_offset_first_element_in_bytes The offset of the first element in the source tensor 288 */ 289__kernel void reduction_operation_z( 290 TENSOR3D_DECLARATION(input), 291 TENSOR3D_DECLARATION(output)) 292{ 293 int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); 294 int y = get_global_id(1); 295 int z = get_global_id(2); 296 297 __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * input_stride_y + z * input_stride_z; 298 __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * output_stride_y + z * output_stride_z; 299 300 VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) 301 res = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input_addr), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); 302 303 // Convert input into F32 in order to perform quantized multiplication 304#if defined(PROD) && defined(OFFSET) && defined(SCALE) 305 VEC_DATA_TYPE(float, VEC_SIZE) 306 res_f = DEQUANTIZE(res, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); 307#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) 308 309#if defined(SUM_SQUARE) 310 res *= res; 311#endif // defined(SUM_SQUARE) 312 313 for(unsigned int z = 1; z < DEPTH; ++z) 314 { 315 VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) 316 in = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + z * input_stride_z)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); 317 318#if defined(MIN) 319 res = select(res, in, ISLESS(in, res)); 320#elif defined(MAX) 321 res = select(res, in, ISGREATER(in, res)); 322#else // !(defined(MAX) || defined(MIN)) 323#if defined(SUM_SQUARE) 324 in *= in; 325#endif // defined(SUM_SQUARE) 326#if defined(PROD) 327 328#if defined(OFFSET) && defined(SCALE) 329 res_f *= DEQUANTIZE(in, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); 330#else // !(defined(OFFSET) && defined(SCALE)) 331 res *= in; 332#endif // defined(OFFSET) && defined(SCALE) 333 334#else // !defined(PROD) 335 res += in; 336#endif // defined(PROD) 337#endif // defined(MAX) || defined(MIN) 338 } 339 340#if defined(MEAN) 341 res /= DEPTH; 342#endif // defined(MEAN) 343 344 // Subtract the offsets in case of quantized SUM 345#if defined(SUM) && defined(OFFSET) && defined(SCALE) 346 res -= (DEPTH - 1) * OFFSET; 347#endif // defined(OFFSET) && defined(OFFSET) && defined(SCALE) 348 349 // Re-quantize 350#if defined(PROD) && defined(OFFSET) && defined(SCALE) 351 res = QUANTIZE(res_f, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); 352#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) 353 354 // Store result 355 VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) 356 res0 = CONVERT_SAT(res, VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)); 357 358 STORE_VECTOR_SELECT(res, DATA_TYPE, output_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0); 359} 360#endif /* defined(DEPTH) */ 361 362#if defined(BATCH) && defined(DEPTH) 363/** This kernel performs reduction on w-axis. 364 * 365 * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float 366 * @note The batch size must be passed at compile time using -DBATCH e.g. -DBATCH=128 367 * @note The depth size must be passed at compile time using -DBATCH e.g. -DDEPTH=128 368 * 369 * @param[in] input_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED/S32/F16/F32 370 * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes) 371 * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) 372 * @param[in] input_stride_y Stride of the source tensor in Y dimension (in bytes) 373 * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) 374 * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes) 375 * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) 376 * @param[in] input_stride_w Stride of the source tensor in W dimension (in bytes) 377 * @param[in] input_step_w input_stride_w * number of elements along W processed per workitem(in bytes) 378 * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source tensor 379 * @param[in] output_ptr The local buffer to hold sumed values. Supported data types: same as @p input_ptr 380 * @param[in] output_stride_x Stride of the output tensor in X dimension (in bytes) 381 * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) 382 * @param[in] output_stride_y Stride of the output tensor in Y dimension (in bytes) 383 * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) 384 * @param[in] output_stride_z Stride of the output tensor in Z dimension (in bytes) 385 * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes) 386 * @param[in] output_stride_w Stride of the output tensor in W dimension (in bytes) 387 * @param[in] output_step_w output_stride_w * number of elements along W processed per workitem(in bytes) 388 * @param[in] output_offset_first_element_in_bytes The offset of the first element in the source tensor 389 */ 390__kernel void reduction_operation_w( 391 TENSOR4D_DECLARATION(input), 392 TENSOR4D_DECLARATION(output)) 393{ 394 int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); 395 int y = get_global_id(1); 396 int z = get_global_id(2); 397 398 __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * input_stride_y + (z % DEPTH) * input_stride_z + (z / DEPTH) * input_stride_w; 399 __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * output_stride_y + (z % DEPTH) * output_stride_z + (z / DEPTH) * output_stride_z; 400 401 VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) 402 res = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input_addr), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); 403 404 // Convert input into F32 in order to perform quantized multiplication 405#if defined(PROD) && defined(OFFSET) && defined(SCALE) 406 VEC_DATA_TYPE(float, VEC_SIZE) 407 res_f = DEQUANTIZE(res, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); 408#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) 409 410#if defined(SUM_SQUARE) 411 res *= res; 412#endif // defined(SUM_SQUARE) 413 414 for(unsigned int w = 1; w < BATCH; ++w) 415 { 416 VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) 417 in = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + w * input_stride_w)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); 418 419#if defined(MIN) 420 res = select(res, in, ISLESS(in, res)); 421#elif defined(MAX) 422 res = select(res, in, ISGREATER(in, res)); 423#else // !(defined(MAX) || defined(MIN)) 424#if defined(SUM_SQUARE) 425 in *= in; 426#endif // defined(SUM_SQUARE) 427#if defined(PROD) 428 429#if defined(OFFSET) && defined(SCALE) 430 res_f *= DEQUANTIZE(in, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); 431#else // !(defined(OFFSET) && defined(SCALE)) 432 res *= in; 433#endif // defined(OFFSET) && defined(SCALE) 434 435#else // !defined(PROD) 436 res += in; 437#endif //defined(PROD) 438#endif // defined(MAX) || defined(MIN) 439 } 440 441#if defined(MEAN) 442 res /= BATCH; 443#endif // defined(MEAN) 444 445 // Subtract the offsets in case of quantized SUM 446#if defined(SUM) && defined(OFFSET) && defined(SCALE) 447 res -= (BATCH - 1) * OFFSET; 448#endif // defined(OFFSET) && defined(OFFSET) && defined(SCALE) 449 450 // Re-quantize 451#if defined(PROD) && defined(OFFSET) && defined(SCALE) 452 res = QUANTIZE(res_f, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); 453#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) 454 455 // Store result 456 VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) 457 res0 = CONVERT_SAT(res, VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)); 458 STORE_VECTOR_SELECT(res, DATA_TYPE, output_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0); 459} 460#endif /* defined(BATCH) && defined(DEPTH) */ 461