XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 1 | // Copyright (c) Facebook, Inc. and its affiliates. |
| 2 | // All rights reserved. |
| 3 | // |
| 4 | // Copyright 2019 Google LLC |
| 5 | // |
| 6 | // This source code is licensed under the BSD-style license found in the |
| 7 | // LICENSE file in the root directory of this source tree. |
| 8 | |
| 9 | #include <assert.h> |
| 10 | #include <math.h> |
| 11 | #include <stddef.h> |
| 12 | #include <stdint.h> |
| 13 | #include <stdlib.h> |
| 14 | |
| 15 | #include <xnnpack.h> |
| 16 | #include <xnnpack/allocator.h> |
| 17 | #include <xnnpack/operator.h> |
| 18 | #include <xnnpack/log.h> |
| 19 | |
| 20 | |
| 21 | enum xnn_status xnn_create_sigmoid_nc_q8( |
| 22 | size_t channels, |
| 23 | size_t input_stride, |
| 24 | size_t output_stride, |
| 25 | uint8_t input_zero_point, |
| 26 | float input_scale, |
| 27 | uint8_t output_zero_point, |
| 28 | float output_scale, |
| 29 | uint8_t output_min, |
| 30 | uint8_t output_max, |
| 31 | uint32_t flags, |
| 32 | xnn_operator_t* sigmoid_op_out) |
| 33 | { |
| 34 | xnn_operator_t sigmoid_op = NULL; |
| 35 | enum xnn_status status = xnn_status_uninitialized; |
| 36 | |
| 37 | if (!xnn_params.initialized) { |
| 38 | xnn_log_error("failed to create Sigmoid operator: XNNPACK is not initialized"); |
| 39 | goto error; |
| 40 | } |
| 41 | |
| 42 | status = xnn_status_invalid_parameter; |
| 43 | |
| 44 | if (channels == 0) { |
| 45 | xnn_log_error( |
| 46 | "failed to create Sigmoid operator with %zu channels: number of channels must be non-zero", channels); |
| 47 | goto error; |
| 48 | } |
| 49 | |
| 50 | if (input_stride < channels) { |
| 51 | xnn_log_error( |
| 52 | "failed to create Sigmoid operator with input element stride of %zu: " |
| 53 | "stride must be at least as large as the number of channels (%zu)", |
| 54 | input_stride, channels); |
| 55 | goto error; |
| 56 | } |
| 57 | |
| 58 | if (output_stride < channels) { |
| 59 | xnn_log_error( |
| 60 | "failed to create Sigmoid operator with output element stride of %zu: " |
| 61 | "stride must be at least as large as the number of channels (%zu)", |
| 62 | output_stride, channels); |
| 63 | goto error; |
| 64 | } |
| 65 | |
| 66 | if (input_scale <= 0.0f || !isnormal(input_scale)) { |
| 67 | xnn_log_error( |
| 68 | "failed to create Sigmoid operator with %.7g input scale: scale must be finite, normalized, and positive", |
| 69 | input_scale); |
| 70 | goto error; |
| 71 | } |
| 72 | |
| 73 | if (output_scale <= 0.0f || !isnormal(output_scale)) { |
| 74 | xnn_log_error( |
| 75 | "failed to create Sigmoid operator with %.7g output scale: scale must be finite, normalized, and positive", |
| 76 | output_scale); |
| 77 | goto error; |
| 78 | } |
| 79 | |
| 80 | if (output_min >= output_max) { |
| 81 | xnn_log_error( |
| 82 | "failed to create Sigmoid operator with [%" PRIu8 ", %" PRIu8 "] output range: range min must be below range max", |
| 83 | output_min, output_max); |
| 84 | goto error; |
| 85 | } |
| 86 | |
| 87 | status = xnn_status_unsupported_parameter; |
| 88 | |
| 89 | if (output_scale != 0x1.0p-8f) { |
| 90 | xnn_log_error( |
| 91 | "failed to create Sigmoid operator with %.7g output scale: only output scale of 1/256 is supported", |
| 92 | output_scale); |
| 93 | goto error; |
| 94 | } |
| 95 | |
| 96 | if (output_zero_point != 0) { |
| 97 | xnn_log_error( |
| 98 | "failed to create Sigmoid operator with %" PRIu8 " output zero point: only output zero point of 0 is supported", |
| 99 | output_zero_point); |
| 100 | goto error; |
| 101 | } |
| 102 | |
| 103 | status = xnn_status_out_of_memory; |
| 104 | |
Marat Dukhan | 04f03be | 2019-11-19 12:36:47 -0800 | [diff] [blame] | 105 | sigmoid_op = xnn_allocate_zero_simd_memory(sizeof(struct xnn_operator)); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 106 | if (sigmoid_op == NULL) { |
| 107 | xnn_log_error("failed to allocate %zu bytes for Sigmoid operator descriptor", sizeof(struct xnn_operator)); |
| 108 | goto error; |
| 109 | } |
| 110 | |
Marat Dukhan | 04f03be | 2019-11-19 12:36:47 -0800 | [diff] [blame] | 111 | sigmoid_op->lookup_table = xnn_allocate_simd_memory(256 * sizeof(uint8_t)); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 112 | if (sigmoid_op->lookup_table == NULL) { |
| 113 | xnn_log_error("failed to allocate 256 bytes for Sigmoid lookup table"); |
| 114 | goto error; |
| 115 | } |
| 116 | |
| 117 | uint8_t* lookup_table = sigmoid_op->lookup_table; |
| 118 | const float scaled_min = (float) (int32_t) output_min; |
| 119 | const float scaled_max = (float) (int32_t) output_max; |
| 120 | for (int32_t i = 0; i < 256; i++) { |
| 121 | const float x = input_scale * (float) (i - (int32_t) (uint32_t) input_zero_point); |
| 122 | // Scale sigmoid(x) by 1 / output scale = 256.0 |
| 123 | float scaled_sigmoid_x = 256.0f / (1.0f + expf(-x)); |
| 124 | if (scaled_sigmoid_x < scaled_min) { |
| 125 | scaled_sigmoid_x = scaled_min; |
| 126 | } |
| 127 | if (scaled_sigmoid_x > scaled_max) { |
| 128 | scaled_sigmoid_x = scaled_max; |
| 129 | } |
| 130 | lookup_table[(uint32_t) i] = (uint8_t) lrintf(scaled_sigmoid_x); |
| 131 | } |
| 132 | |
| 133 | sigmoid_op->channels = channels; |
| 134 | sigmoid_op->input_pixel_stride = input_stride; |
| 135 | sigmoid_op->output_pixel_stride = output_stride; |
| 136 | |
Marat Dukhan | efc47b8 | 2019-11-18 09:25:38 -0800 | [diff] [blame] | 137 | sigmoid_op->type = xnn_operator_type_sigmoid_nc_q8; |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 138 | sigmoid_op->ukernel.type = xnn_ukernel_type_lut; |
| 139 | |
| 140 | sigmoid_op->state = xnn_run_state_invalid; |
| 141 | |
| 142 | *sigmoid_op_out = sigmoid_op; |
| 143 | return xnn_status_success; |
| 144 | |
| 145 | error: |
| 146 | xnn_delete_operator(sigmoid_op); |
| 147 | return status; |
| 148 | } |
| 149 | |
Marat Dukhan | 346a9e5 | 2019-11-15 09:06:30 -0800 | [diff] [blame] | 150 | enum xnn_status xnn_create_sigmoid_nc_f32( |
| 151 | size_t channels, |
| 152 | size_t input_stride, |
| 153 | size_t output_stride, |
| 154 | uint32_t flags, |
| 155 | xnn_operator_t* sigmoid_op_out) |
| 156 | { |
| 157 | xnn_operator_t sigmoid_op = NULL; |
| 158 | enum xnn_status status = xnn_status_uninitialized; |
| 159 | |
| 160 | if (!xnn_params.initialized) { |
| 161 | xnn_log_error("failed to create Sigmoid operator: XNNPACK is not initialized"); |
| 162 | goto error; |
| 163 | } |
| 164 | |
| 165 | status = xnn_status_invalid_parameter; |
| 166 | |
| 167 | if (channels == 0) { |
| 168 | xnn_log_error( |
| 169 | "failed to create Sigmoid operator with %zu channels: number of channels must be non-zero", channels); |
| 170 | goto error; |
| 171 | } |
| 172 | |
| 173 | if (input_stride < channels) { |
| 174 | xnn_log_error( |
| 175 | "failed to create Sigmoid operator with input element stride of %zu: " |
| 176 | "stride must be at least as large as the number of channels (%zu)", |
| 177 | input_stride, channels); |
| 178 | goto error; |
| 179 | } |
| 180 | |
| 181 | if (output_stride < channels) { |
| 182 | xnn_log_error( |
| 183 | "failed to create Sigmoid operator with output element stride of %zu: " |
| 184 | "stride must be at least as large as the number of channels (%zu)", |
| 185 | output_stride, channels); |
| 186 | goto error; |
| 187 | } |
| 188 | |
| 189 | status = xnn_status_unsupported_hardware; |
| 190 | |
| 191 | if (xnn_params.f32.sigmoid == NULL) { |
| 192 | xnn_log_error( |
| 193 | "failed to create Sigmoid operator: " |
| 194 | "only selected hardware configurations are supported"); |
| 195 | goto error; |
| 196 | } |
| 197 | |
| 198 | status = xnn_status_out_of_memory; |
| 199 | |
Marat Dukhan | 04f03be | 2019-11-19 12:36:47 -0800 | [diff] [blame] | 200 | sigmoid_op = xnn_allocate_zero_simd_memory(sizeof(struct xnn_operator)); |
Marat Dukhan | 346a9e5 | 2019-11-15 09:06:30 -0800 | [diff] [blame] | 201 | if (sigmoid_op == NULL) { |
| 202 | xnn_log_error("failed to allocate %zu bytes for xnn_operator structure", sizeof(struct xnn_operator)); |
| 203 | goto error; |
| 204 | } |
| 205 | |
| 206 | sigmoid_op->channels = channels; |
| 207 | sigmoid_op->input_pixel_stride = input_stride; |
| 208 | sigmoid_op->output_pixel_stride = output_stride; |
| 209 | |
Marat Dukhan | efc47b8 | 2019-11-18 09:25:38 -0800 | [diff] [blame] | 210 | sigmoid_op->type = xnn_operator_type_sigmoid_nc_f32; |
Marat Dukhan | 346a9e5 | 2019-11-15 09:06:30 -0800 | [diff] [blame] | 211 | sigmoid_op->ukernel.type = xnn_ukernel_type_sigmoid; |
| 212 | |
| 213 | sigmoid_op->state = xnn_run_state_invalid; |
| 214 | |
| 215 | *sigmoid_op_out = sigmoid_op; |
| 216 | return xnn_status_success; |
| 217 | |
| 218 | error: |
| 219 | xnn_delete_operator(sigmoid_op); |
| 220 | return status; |
| 221 | } |
| 222 | |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 223 | enum xnn_status xnn_setup_sigmoid_nc_q8( |
| 224 | xnn_operator_t sigmoid_op, |
| 225 | size_t batch_size, |
| 226 | const uint8_t* input, |
| 227 | uint8_t* output, |
| 228 | pthreadpool_t threadpool) |
| 229 | { |
Marat Dukhan | efc47b8 | 2019-11-18 09:25:38 -0800 | [diff] [blame] | 230 | if (sigmoid_op->type != xnn_operator_type_sigmoid_nc_q8) { |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 231 | xnn_log_error("failed to setup Sigmoid (Q8) operator: operator type mismatch"); |
| 232 | return xnn_status_invalid_parameter; |
| 233 | } |
| 234 | sigmoid_op->state = xnn_run_state_invalid; |
| 235 | |
| 236 | if (!xnn_params.initialized) { |
| 237 | xnn_log_error("failed to setup Sigmoid operator: XNNPACK is not initialized"); |
| 238 | return xnn_status_uninitialized; |
| 239 | } |
| 240 | |
| 241 | if (batch_size == 0) { |
| 242 | sigmoid_op->state = xnn_run_state_skip; |
| 243 | return xnn_status_success; |
| 244 | } |
| 245 | |
| 246 | sigmoid_op->batch_size = batch_size; |
| 247 | sigmoid_op->input = input; |
| 248 | sigmoid_op->output = output; |
| 249 | |
| 250 | const size_t channels = sigmoid_op->channels; |
| 251 | const size_t input_stride = sigmoid_op->input_pixel_stride; |
| 252 | const size_t output_stride = sigmoid_op->output_pixel_stride; |
| 253 | if ((((input_stride ^ channels) | (output_stride ^ channels)) == 0) || batch_size == 1) { |
| 254 | const size_t block_size = 1024; |
| 255 | sigmoid_op->context.lut_contiguous = (struct lut_contiguous_context) { |
| 256 | .x = input, |
| 257 | .x_stride = input_stride * sizeof(uint8_t), |
| 258 | .t = sigmoid_op->lookup_table, |
| 259 | .y = output, |
| 260 | .y_stride = output_stride * sizeof(uint8_t), |
| 261 | .ukernel = xnn_params.x8.lut, |
| 262 | }; |
| 263 | sigmoid_op->compute.type = xnn_parallelization_type_1d_tile_1d; |
| 264 | sigmoid_op->compute.task_1d_tile_1d = (pthreadpool_task_1d_tile_1d_t) xnn_compute_lut_contiguous; |
| 265 | sigmoid_op->compute.range[0] = batch_size * channels * sizeof(uint8_t); |
| 266 | sigmoid_op->compute.tile[0] = block_size; |
| 267 | } else { |
| 268 | sigmoid_op->context.lut_strided = (struct lut_strided_context) { |
| 269 | .n = channels, |
| 270 | .x = input, |
| 271 | .x_stride = input_stride * sizeof(uint8_t), |
| 272 | .t = sigmoid_op->lookup_table, |
| 273 | .y = output, |
| 274 | .y_stride = output_stride * sizeof(uint8_t), |
| 275 | .ukernel = xnn_params.x8.lut, |
| 276 | }; |
| 277 | sigmoid_op->compute.type = xnn_parallelization_type_1d; |
| 278 | sigmoid_op->compute.task_1d = (pthreadpool_task_1d_t) xnn_compute_lut_strided; |
| 279 | sigmoid_op->compute.range[0] = batch_size; |
| 280 | sigmoid_op->compute.tile[0] = 0; |
| 281 | } |
| 282 | sigmoid_op->state = xnn_run_state_ready; |
| 283 | |
| 284 | return xnn_status_success; |
| 285 | } |
Marat Dukhan | 346a9e5 | 2019-11-15 09:06:30 -0800 | [diff] [blame] | 286 | |
| 287 | enum xnn_status xnn_setup_sigmoid_nc_f32( |
| 288 | xnn_operator_t sigmoid_op, |
| 289 | size_t batch_size, |
| 290 | const float* input, |
| 291 | float* output, |
| 292 | pthreadpool_t threadpool) |
| 293 | { |
Marat Dukhan | efc47b8 | 2019-11-18 09:25:38 -0800 | [diff] [blame] | 294 | if (sigmoid_op->type != xnn_operator_type_sigmoid_nc_f32) { |
Marat Dukhan | 346a9e5 | 2019-11-15 09:06:30 -0800 | [diff] [blame] | 295 | xnn_log_error("failed to setup Sigmoid (F32) operator: operator type mismatch"); |
| 296 | return xnn_status_invalid_parameter; |
| 297 | } |
| 298 | sigmoid_op->state = xnn_run_state_invalid; |
| 299 | |
| 300 | if (!xnn_params.initialized) { |
| 301 | xnn_log_error("failed to setup Sigmoid operator: XNNPACK is not initialized"); |
| 302 | return xnn_status_uninitialized; |
| 303 | } |
| 304 | |
| 305 | if (batch_size == 0) { |
| 306 | sigmoid_op->state = xnn_run_state_skip; |
| 307 | return xnn_status_success; |
| 308 | } |
| 309 | |
| 310 | const size_t channels = sigmoid_op->channels; |
| 311 | const size_t input_stride = sigmoid_op->input_pixel_stride; |
| 312 | const size_t output_stride = sigmoid_op->output_pixel_stride; |
| 313 | if ((((input_stride ^ channels) | (output_stride ^ channels)) == 0) || batch_size == 1) { |
| 314 | const size_t block_size = 4096; |
| 315 | sigmoid_op->context.univector_contiguous = (struct univector_contiguous_context) { |
| 316 | .x = input, |
| 317 | .x_stride = input_stride * sizeof(float), |
| 318 | .y = output, |
| 319 | .y_stride = output_stride * sizeof(float), |
| 320 | .ukernel = xnn_params.f32.sigmoid, |
| 321 | }; |
| 322 | sigmoid_op->compute.type = xnn_parallelization_type_1d_tile_1d; |
| 323 | sigmoid_op->compute.task_1d_tile_1d = (pthreadpool_task_1d_tile_1d_t) xnn_compute_univector_contiguous; |
| 324 | sigmoid_op->compute.range[0] = batch_size * channels * sizeof(float); |
| 325 | sigmoid_op->compute.tile[0] = block_size; |
| 326 | } else { |
| 327 | sigmoid_op->context.univector_strided = (struct univector_strided_context) { |
| 328 | .n = channels * sizeof(float), |
| 329 | .x = input, |
| 330 | .x_stride = input_stride * sizeof(float), |
| 331 | .y = output, |
| 332 | .y_stride = output_stride * sizeof(float), |
| 333 | .ukernel = xnn_params.f32.sigmoid, |
| 334 | }; |
| 335 | sigmoid_op->compute.type = xnn_parallelization_type_1d_tile_1d; |
| 336 | sigmoid_op->compute.task_1d_tile_1d = (pthreadpool_task_1d_tile_1d_t) xnn_compute_univector_strided; |
| 337 | sigmoid_op->compute.range[0] = batch_size; |
| 338 | sigmoid_op->compute.tile[0] = 1; |
| 339 | } |
| 340 | sigmoid_op->state = xnn_run_state_ready; |
| 341 | |
| 342 | return xnn_status_success; |
| 343 | } |