Marat Dukhan | 1d75a54 | 2020-02-03 12:23:01 -0800 | [diff] [blame] | 1 | // Copyright 2020 Google LLC |
| 2 | // |
| 3 | // This source code is licensed under the BSD-style license found in the |
| 4 | // LICENSE file in the root directory of this source tree. |
| 5 | |
| 6 | #include <math.h> |
| 7 | #include <stddef.h> |
| 8 | #include <stdint.h> |
| 9 | #include <stdlib.h> |
| 10 | |
| 11 | #include <xnnpack.h> |
| 12 | #include <xnnpack/allocator.h> |
| 13 | #include <xnnpack/log.h> |
| 14 | #include <xnnpack/math.h> |
| 15 | #include <xnnpack/params.h> |
| 16 | #include <xnnpack/subgraph.h> |
| 17 | |
| 18 | |
| 19 | enum xnn_status xnn_create_subgraph( |
| 20 | uint32_t external_value_ids, |
| 21 | uint32_t flags, |
| 22 | xnn_subgraph_t* subgraph_out) |
| 23 | { |
| 24 | struct xnn_subgraph* subgraph = NULL; |
| 25 | enum xnn_status status = xnn_status_uninitialized; |
| 26 | |
Marat Dukhan | 854fb6b | 2020-06-19 12:33:44 -0700 | [diff] [blame] | 27 | if ((xnn_params.init_flags & XNN_INIT_FLAG_XNNPACK) == 0) { |
Marat Dukhan | 1d75a54 | 2020-02-03 12:23:01 -0800 | [diff] [blame] | 28 | xnn_log_error("failed to create subgraph: XNNPACK is not initialized"); |
| 29 | goto error; |
| 30 | } |
| 31 | |
| 32 | status = xnn_status_out_of_memory; |
| 33 | |
| 34 | subgraph = xnn_allocate_zero_memory(sizeof(struct xnn_subgraph)); |
| 35 | if (subgraph == NULL) { |
| 36 | xnn_log_error("failed to allocate %zu bytes for subgraph descriptor", sizeof(struct xnn_subgraph)); |
| 37 | goto error; |
| 38 | } |
| 39 | |
| 40 | subgraph->external_value_ids = external_value_ids; |
| 41 | |
| 42 | subgraph->values = xnn_allocate_zero_memory(external_value_ids * sizeof(struct xnn_value)); |
| 43 | if (subgraph->values == NULL) { |
| 44 | xnn_log_error("failed to allocate %zu bytes for subgraph values", external_value_ids * sizeof(struct xnn_value)); |
| 45 | goto error; |
| 46 | } |
| 47 | for (size_t i = 0; i < external_value_ids; i++) { |
| 48 | subgraph->values[i].id = i; |
| 49 | } |
| 50 | subgraph->num_values = external_value_ids; |
| 51 | subgraph->num_reserved_values = external_value_ids; |
| 52 | |
| 53 | *subgraph_out = subgraph; |
| 54 | return xnn_status_success; |
| 55 | |
| 56 | error: |
| 57 | xnn_delete_subgraph(subgraph); |
| 58 | return status; |
| 59 | } |
| 60 | |
| 61 | |
| 62 | struct xnn_value* xnn_subgraph_new_internal_value(xnn_subgraph_t subgraph) |
| 63 | { |
| 64 | struct xnn_value* values = subgraph->values; |
| 65 | const size_t size = subgraph->num_values; |
| 66 | const size_t capacity = subgraph->num_reserved_values; |
| 67 | if (capacity < size + 1) { |
| 68 | const size_t new_capacity = max(min(capacity * 2, capacity + 512), capacity + 64); |
| 69 | assert(new_capacity >= size + 1); |
| 70 | values = xnn_reallocate_memory(values, new_capacity * sizeof(struct xnn_value)); |
| 71 | if (values == NULL) { |
| 72 | xnn_log_error("failed to allocate %zu bytes for subgraph values", |
| 73 | capacity * sizeof(struct xnn_value)); |
| 74 | return values; |
| 75 | } |
| 76 | |
| 77 | memset(values + size, 0, (new_capacity - size) * sizeof(struct xnn_value)); |
| 78 | subgraph->num_reserved_values = new_capacity; |
| 79 | subgraph->values = values; |
| 80 | } |
| 81 | subgraph->num_values = size + 1; |
| 82 | struct xnn_value* new_value = values + size; |
| 83 | new_value->id = size; |
| 84 | return new_value; |
| 85 | } |
| 86 | |
Marat Dukhan | 1f19872 | 2020-05-24 14:07:03 -0700 | [diff] [blame] | 87 | void xnn_node_clear(struct xnn_node* node) { |
| 88 | assert(node != NULL); |
| 89 | assert(node->type != xnn_node_type_invalid); |
| 90 | memset(node, 0, sizeof(struct xnn_node)); |
| 91 | } |
| 92 | |
| 93 | void xnn_value_clear(struct xnn_value* value) { |
| 94 | assert(value != NULL); |
| 95 | assert(value->type != xnn_value_type_invalid); |
| 96 | memset(value, 0, sizeof(struct xnn_value)); |
| 97 | } |
| 98 | |
Marat Dukhan | 1d75a54 | 2020-02-03 12:23:01 -0800 | [diff] [blame] | 99 | struct xnn_node* xnn_subgraph_new_node(xnn_subgraph_t subgraph) |
| 100 | { |
| 101 | struct xnn_node* nodes = subgraph->nodes; |
| 102 | const size_t size = subgraph->num_nodes; |
| 103 | const size_t capacity = subgraph->num_reserved_nodes; |
| 104 | |
| 105 | if (capacity < size + 1) { |
| 106 | const size_t new_capacity = max(min(capacity * 2, capacity + 512), capacity + 64); |
| 107 | assert(new_capacity >= size + 1); |
| 108 | nodes = xnn_reallocate_memory(nodes, new_capacity * sizeof(struct xnn_node)); |
| 109 | if (nodes == NULL) { |
| 110 | xnn_log_error("failed to allocate %zu bytes for subgraph nodes", |
| 111 | capacity * sizeof(struct xnn_node)); |
| 112 | return nodes; |
| 113 | } |
| 114 | |
| 115 | memset(nodes + size, 0, (new_capacity - size) * sizeof(struct xnn_node)); |
| 116 | subgraph->num_reserved_nodes = new_capacity; |
| 117 | subgraph->nodes = nodes; |
| 118 | } |
| 119 | subgraph->num_nodes = size + 1; |
| 120 | struct xnn_node* new_node = nodes + size; |
| 121 | new_node->id = size; |
| 122 | return new_node; |
| 123 | } |
| 124 | |
Marat Dukhan | 9de90e0 | 2020-06-18 16:04:12 -0700 | [diff] [blame] | 125 | #define XNN_LAYOUT_FLAG_COMPATIBLE_NCHW 1 |
| 126 | #define XNN_LAYOUT_FLAG_COMPATIBLE_NHWC2NCHW 2 |
| 127 | #define XNN_LAYOUT_FLAG_COMPATIBLE_NCHW2NHWC 4 |
| 128 | #define XNN_LAYOUT_FLAG_INCOMPATIBLE_CLUSTER 8 |
| 129 | |
Marat Dukhan | 9de90e0 | 2020-06-18 16:04:12 -0700 | [diff] [blame] | 130 | uint32_t xnn_check_nchw_compatibility(xnn_subgraph_t subgraph, struct xnn_node* node) { |
| 131 | switch (node->type) { |
| 132 | case xnn_node_type_convolution_2d: |
| 133 | // Supported cases: |
| 134 | // - 1x1 convolution (no stride, no dilation, no padding, no groups) |
| 135 | // - 3x3 stride-2 convolution (no dilation, padding 1 on each side, no groups, 3 input channels) |
| 136 | if (node->params.convolution_2d.groups != 1) { |
| 137 | return 0; |
| 138 | } |
| 139 | if ((node->params.convolution_2d.dilation_height | node->params.convolution_2d.dilation_width) != 1) { |
| 140 | return 0; |
| 141 | } |
| 142 | if ((node->params.convolution_2d.kernel_height | node->params.convolution_2d.kernel_width) == 1) { |
| 143 | if ((node->params.convolution_2d.input_padding_top | node->params.convolution_2d.input_padding_right | |
| 144 | node->params.convolution_2d.input_padding_bottom | node->params.convolution_2d.input_padding_left) != 0) |
| 145 | { |
| 146 | return 0; |
| 147 | } |
| 148 | if ((node->params.convolution_2d.subsampling_height | node->params.convolution_2d.subsampling_width) != 1) { |
| 149 | return 0; |
| 150 | } |
| 151 | return XNN_LAYOUT_FLAG_COMPATIBLE_NCHW; |
| 152 | } else if (node->params.convolution_2d.kernel_height == 3 && node->params.convolution_2d.kernel_width == 3) { |
| 153 | if (node->params.convolution_2d.input_padding_top != 1 || node->params.convolution_2d.input_padding_right != 1 || |
| 154 | node->params.convolution_2d.input_padding_bottom != 1 || node->params.convolution_2d.input_padding_left != 1) |
| 155 | { |
| 156 | return 0; |
| 157 | } |
| 158 | if ((node->params.convolution_2d.subsampling_height | node->params.convolution_2d.subsampling_width) != 2) { |
| 159 | return 0; |
| 160 | } |
| 161 | if (node->params.convolution_2d.group_input_channels != 3) { |
| 162 | return 0; |
| 163 | } |
| 164 | return XNN_LAYOUT_FLAG_COMPATIBLE_NHWC2NCHW; |
| 165 | } |
| 166 | return 0; |
| 167 | case xnn_node_type_depthwise_convolution_2d: |
| 168 | // Supported cases: |
| 169 | // - 3x3 stride-1 convolution (no dilation, padding 1 on each side) |
| 170 | // - 3x3 stride-2 convolution (no dilation, padding 1 on each side) |
| 171 | // - 5x5 stride-1 convolution (no dilation, padding 2 on each side) |
| 172 | // - 5x5 stride-2 convolution (no dilation, padding 2 on each side) |
| 173 | if ((node->params.depthwise_convolution_2d.dilation_height | node->params.depthwise_convolution_2d.dilation_width) != 1) { |
| 174 | return 0; |
| 175 | } |
| 176 | if (node->flags & XNN_FLAG_TENSORFLOW_SAME_PADDING) { |
| 177 | return 0; |
| 178 | } |
| 179 | if (node->params.depthwise_convolution_2d.depth_multiplier != 1) { |
| 180 | return 0; |
| 181 | } |
| 182 | if (node->params.depthwise_convolution_2d.subsampling_height != node->params.depthwise_convolution_2d.subsampling_width) { |
| 183 | return 0; |
| 184 | } |
| 185 | switch (node->params.depthwise_convolution_2d.subsampling_height) { |
| 186 | case 1: |
| 187 | case 2: |
| 188 | break; |
| 189 | default: |
| 190 | return 0; |
| 191 | } |
| 192 | if (node->params.depthwise_convolution_2d.kernel_height != node->params.depthwise_convolution_2d.kernel_width) { |
| 193 | return 0; |
| 194 | } |
| 195 | switch (node->params.depthwise_convolution_2d.kernel_height) { |
| 196 | case 3: |
| 197 | return node->params.depthwise_convolution_2d.input_padding_top == 1 && |
| 198 | node->params.depthwise_convolution_2d.input_padding_right == 1 && |
| 199 | node->params.depthwise_convolution_2d.input_padding_bottom == 1 && |
| 200 | node->params.depthwise_convolution_2d.input_padding_left == 1 ? XNN_LAYOUT_FLAG_COMPATIBLE_NCHW : 0; |
| 201 | case 5: |
| 202 | return node->params.depthwise_convolution_2d.input_padding_top == 2 && |
| 203 | node->params.depthwise_convolution_2d.input_padding_right == 2 && |
| 204 | node->params.depthwise_convolution_2d.input_padding_bottom == 2 && |
| 205 | node->params.depthwise_convolution_2d.input_padding_left == 2 ? XNN_LAYOUT_FLAG_COMPATIBLE_NCHW : 0; |
| 206 | default: |
| 207 | return 0; |
| 208 | } |
Artsiom Ablavatski | bbe8506 | 2020-11-05 14:07:37 -0800 | [diff] [blame] | 209 | case xnn_node_type_depth_to_space: |
Marat Dukhan | f56b4bb | 2020-12-06 19:06:04 -0800 | [diff] [blame] | 210 | return XNN_LAYOUT_FLAG_COMPATIBLE_NCHW2NHWC; |
| 211 | case xnn_node_type_global_average_pooling_2d: |
Marat Dukhan | 9de90e0 | 2020-06-18 16:04:12 -0700 | [diff] [blame] | 212 | return XNN_LAYOUT_FLAG_COMPATIBLE_NCHW | XNN_LAYOUT_FLAG_COMPATIBLE_NCHW2NHWC; |
| 213 | case xnn_node_type_add2: |
| 214 | case xnn_node_type_multiply2: |
| 215 | assert(node->num_inputs == 2); |
| 216 | assert(node->num_outputs == 1); |
| 217 | if (subgraph->values[node->inputs[0]].shape.num_dims != 4 || |
| 218 | subgraph->values[node->inputs[1]].shape.num_dims != 4) |
| 219 | { |
| 220 | return 0; |
| 221 | } |
| 222 | |
| 223 | if (subgraph->values[node->inputs[0]].data != NULL) { |
| 224 | // Check that the first input is representable as either a scalar, or a vector |
| 225 | size_t num_nonunit_dims = 0; |
| 226 | for (uint32_t i = 0; i < subgraph->values[node->inputs[0]].shape.num_dims; i++) { |
| 227 | if (subgraph->values[node->inputs[0]].shape.dim[i] != 1) { |
| 228 | num_nonunit_dims += 1; |
| 229 | } |
| 230 | } |
| 231 | if (num_nonunit_dims > 1) { |
| 232 | return 0; |
| 233 | } |
| 234 | } |
| 235 | |
| 236 | if (subgraph->values[node->inputs[1]].data != NULL) { |
| 237 | // Check that the second input is representable as either a scalar, or a vector |
| 238 | size_t num_nonunit_dims = 0; |
| 239 | for (uint32_t i = 0; i < subgraph->values[node->inputs[0]].shape.num_dims; i++) { |
| 240 | if (subgraph->values[node->inputs[0]].shape.dim[i] != 1) { |
| 241 | num_nonunit_dims += 1; |
| 242 | } |
| 243 | } |
| 244 | if (num_nonunit_dims > 1) { |
| 245 | return 0; |
| 246 | } |
| 247 | } |
| 248 | |
| 249 | return XNN_LAYOUT_FLAG_COMPATIBLE_NCHW; |
Artsiom Ablavatski | e6beeba | 2020-10-28 09:12:19 -0700 | [diff] [blame] | 250 | case xnn_node_type_static_resize_bilinear_2d: |
| 251 | return subgraph->values[node->inputs[0]].shape.dim[1] > 1 && |
| 252 | subgraph->values[node->inputs[0]].shape.dim[2] > 1 ? XNN_LAYOUT_FLAG_COMPATIBLE_NCHW : 0; |
Marat Dukhan | 9de90e0 | 2020-06-18 16:04:12 -0700 | [diff] [blame] | 253 | case xnn_node_type_abs: |
| 254 | case xnn_node_type_bankers_rounding: |
| 255 | case xnn_node_type_ceiling: |
| 256 | case xnn_node_type_clamp: |
Marat Dukhan | 094e692 | 2020-12-08 12:54:38 -0800 | [diff] [blame] | 257 | case xnn_node_type_elu: |
Marat Dukhan | 9de90e0 | 2020-06-18 16:04:12 -0700 | [diff] [blame] | 258 | case xnn_node_type_floor: |
| 259 | case xnn_node_type_hardswish: |
| 260 | case xnn_node_type_leaky_relu: |
| 261 | case xnn_node_type_negate: |
| 262 | case xnn_node_type_sigmoid: |
| 263 | case xnn_node_type_square: |
| 264 | assert(node->num_inputs == 1); |
| 265 | assert(node->num_outputs == 1); |
| 266 | return subgraph->values[node->inputs[0]].shape.num_dims == 4 ? XNN_LAYOUT_FLAG_COMPATIBLE_NCHW : 0; |
| 267 | default: |
| 268 | return false; |
| 269 | } |
| 270 | } |
| 271 | |
XNNPACK Team | ab8c4c8 | 2020-10-09 08:05:51 -0700 | [diff] [blame] | 272 | void xnn_subgraph_rewrite_for_nchw(xnn_subgraph_t subgraph) |
Marat Dukhan | 9de90e0 | 2020-06-18 16:04:12 -0700 | [diff] [blame] | 273 | { |
| 274 | // Convert parts of the subgraph to NCHW for sparse inference |
| 275 | // Step 1: detect NCHW-compatible Nodes |
| 276 | // Step 2: detect NCHW-compatible clusters (run connected components graph algorithm) |
| 277 | // Step 3: check that all NCHW-compatible Values are consumed only by NCHW-compatible Nodes |
| 278 | // Step 4: switch Values' layout to NCHW |
| 279 | for (uint32_t n = 0; n < subgraph->num_nodes; n++) { |
| 280 | struct xnn_node* node = &subgraph->nodes[n]; |
| 281 | node->layout_flags = xnn_check_nchw_compatibility(subgraph, node); |
| 282 | xnn_log_debug("Node #%" PRIu32 ": %s (NCHW: %s, NHWC->NCHW: %s, NCHW->NHWC: %s)", |
| 283 | n, xnn_node_type_to_string(node->type), |
| 284 | node->layout_flags & XNN_LAYOUT_FLAG_COMPATIBLE_NCHW ? "yes" : "no", |
| 285 | node->layout_flags & XNN_LAYOUT_FLAG_COMPATIBLE_NHWC2NCHW ? "yes" : "no", |
| 286 | node->layout_flags & XNN_LAYOUT_FLAG_COMPATIBLE_NCHW2NHWC ? "yes" : "no"); |
| 287 | } |
| 288 | |
XNNPACK Team | a117ce7 | 2020-10-05 17:26:02 -0700 | [diff] [blame] | 289 | // Run Shiloach-Vishkin connected components algorithm i.e. find all |
| 290 | // XNN_LAYOUT_FLAG_COMPATIBLE_NCHW2NHWC nodes and set them as cluster leaders |
| 291 | // to all the producer nodes |
Marat Dukhan | 9de90e0 | 2020-06-18 16:04:12 -0700 | [diff] [blame] | 292 | bool update = false; |
| 293 | for (uint32_t n = 0; n < subgraph->num_nodes; n++) { |
| 294 | struct xnn_node* node = &subgraph->nodes[n]; |
| 295 | node->cluster_leader = n; |
| 296 | if (node->layout_flags & XNN_LAYOUT_FLAG_COMPATIBLE_NCHW2NHWC) { |
| 297 | for (uint32_t i = 0; i < node->num_inputs; i++) { |
| 298 | const struct xnn_value* value = &subgraph->values[node->inputs[i]]; |
| 299 | if (value->data != NULL) { |
| 300 | // Static data, skip this input value. Compatibility of this static input with NCHW layout was validated |
| 301 | // during the initial NCHW compatibility check for the Node. |
| 302 | continue; |
| 303 | } |
| 304 | if ((value->flags & (XNN_VALUE_FLAG_EXTERNAL_INPUT | XNN_VALUE_FLAG_EXTERNAL_OUTPUT)) != 0) { |
| 305 | // External value, invalid cluster |
| 306 | node->layout_flags |= XNN_LAYOUT_FLAG_INCOMPATIBLE_CLUSTER; |
| 307 | continue; |
| 308 | } |
| 309 | const uint32_t producer_id = value->producer; |
| 310 | assert(producer_id != XNN_INVALID_NODE_ID); |
| 311 | assert(producer_id < n); |
| 312 | struct xnn_node* producer_node = &subgraph->nodes[producer_id]; |
| 313 | if ((producer_node->layout_flags & (XNN_LAYOUT_FLAG_COMPATIBLE_NHWC2NCHW | XNN_LAYOUT_FLAG_COMPATIBLE_NCHW)) != 0 && |
| 314 | (producer_node->layout_flags & XNN_LAYOUT_FLAG_INCOMPATIBLE_CLUSTER) == 0) |
| 315 | { |
| 316 | producer_node->layout_flags &= ~XNN_LAYOUT_FLAG_COMPATIBLE_NCHW2NHWC; |
| 317 | if (producer_node->cluster_leader != node->cluster_leader) { |
| 318 | producer_node->cluster_leader = node->cluster_leader = math_max_u32(producer_node->cluster_leader, node->cluster_leader); |
| 319 | update = true; |
| 320 | } |
| 321 | } else { |
| 322 | node->layout_flags |= XNN_LAYOUT_FLAG_INCOMPATIBLE_CLUSTER; |
| 323 | } |
| 324 | } |
| 325 | } |
| 326 | } |
XNNPACK Team | a117ce7 | 2020-10-05 17:26:02 -0700 | [diff] [blame] | 327 | // No NCHW2NHWC compatible nodes have been found thus the graph rewriting |
| 328 | // pratically cannot happen. |
| 329 | if (!update) { |
| 330 | return; |
| 331 | } |
| 332 | // Propagate the cluster leader to other nodes in the graph untill all the |
| 333 | // nodes in the cluster is not updated |
Marat Dukhan | 9de90e0 | 2020-06-18 16:04:12 -0700 | [diff] [blame] | 334 | while (update) { |
| 335 | update = false; |
| 336 | for (uint32_t n = 0; n < subgraph->num_nodes; n++) { |
| 337 | struct xnn_node* node = &subgraph->nodes[n]; |
| 338 | if (node->layout_flags & XNN_LAYOUT_FLAG_INCOMPATIBLE_CLUSTER) { |
| 339 | continue; |
| 340 | } |
| 341 | |
| 342 | if ((node->layout_flags & (XNN_LAYOUT_FLAG_COMPATIBLE_NCHW | XNN_LAYOUT_FLAG_COMPATIBLE_NCHW2NHWC)) == 0) { |
| 343 | continue; |
| 344 | } |
| 345 | |
| 346 | for (uint32_t i = 0; i < node->num_inputs; i++) { |
| 347 | const struct xnn_value* value = &subgraph->values[node->inputs[i]]; |
| 348 | if (value->data != NULL) { |
| 349 | // Static data, skip this input value. Compatibility of this static input with NCHW layout was validated |
| 350 | // during the initial NCHW compatibility check for the Node. |
| 351 | continue; |
| 352 | } |
| 353 | if ((value->flags & (XNN_VALUE_FLAG_EXTERNAL_INPUT | XNN_VALUE_FLAG_EXTERNAL_OUTPUT)) != 0) { |
| 354 | // External value, invalid cluster |
| 355 | node->layout_flags |= XNN_LAYOUT_FLAG_INCOMPATIBLE_CLUSTER; |
| 356 | continue; |
| 357 | } |
| 358 | const uint32_t producer_id = value->producer; |
| 359 | assert(producer_id != XNN_INVALID_NODE_ID); |
| 360 | assert(producer_id < n); |
| 361 | struct xnn_node* producer_node = &subgraph->nodes[producer_id]; |
| 362 | if ((producer_node->layout_flags & (XNN_LAYOUT_FLAG_COMPATIBLE_NHWC2NCHW | XNN_LAYOUT_FLAG_COMPATIBLE_NCHW)) != 0 && |
| 363 | (producer_node->layout_flags & XNN_LAYOUT_FLAG_INCOMPATIBLE_CLUSTER) == 0) |
| 364 | { |
| 365 | producer_node->layout_flags &= ~XNN_LAYOUT_FLAG_COMPATIBLE_NCHW2NHWC; |
| 366 | if (producer_node->cluster_leader != node->cluster_leader) { |
| 367 | producer_node->cluster_leader = node->cluster_leader = math_max_u32(producer_node->cluster_leader, node->cluster_leader); |
| 368 | update = true; |
| 369 | } |
| 370 | } else { |
| 371 | node->layout_flags |= XNN_LAYOUT_FLAG_INCOMPATIBLE_CLUSTER; |
| 372 | } |
| 373 | } |
| 374 | } |
| 375 | } |
| 376 | // Propagate XNN_LAYOUT_FLAG_INCOMPATIBLE_CLUSTER flags up to the cluster leaders |
| 377 | for (uint32_t n = 0; n < subgraph->num_nodes; n++) { |
| 378 | struct xnn_node* node = &subgraph->nodes[n]; |
| 379 | subgraph->nodes[node->cluster_leader].layout_flags |= node->layout_flags & XNN_LAYOUT_FLAG_INCOMPATIBLE_CLUSTER; |
| 380 | } |
| 381 | // Check that all Values consumed by NCHW-compatible cluster don't have NCHW-incompatible consumers |
| 382 | for (uint32_t n = 0; n < subgraph->num_nodes; n++) { |
| 383 | struct xnn_node* node = &subgraph->nodes[n]; |
| 384 | if ((subgraph->nodes[node->cluster_leader].layout_flags & XNN_LAYOUT_FLAG_INCOMPATIBLE_CLUSTER) != 0) { |
| 385 | continue; |
| 386 | } |
| 387 | |
| 388 | if ((node->layout_flags & (XNN_LAYOUT_FLAG_COMPATIBLE_NCHW2NHWC | XNN_LAYOUT_FLAG_COMPATIBLE_NCHW)) == 0) { |
| 389 | continue; |
| 390 | } |
| 391 | |
| 392 | for (uint32_t i = 0; i < node->num_inputs; i++) { |
| 393 | struct xnn_value* value = &subgraph->values[node->inputs[i]]; |
| 394 | if (value->data != NULL) { |
| 395 | // Static data, skip this input value because it doesn't have a producer Node. |
| 396 | continue; |
| 397 | } |
| 398 | assert((value->flags & (XNN_VALUE_FLAG_EXTERNAL_INPUT | XNN_VALUE_FLAG_EXTERNAL_OUTPUT)) == 0); |
| 399 | value->num_nchw_compatible_consumers += 1; |
| 400 | } |
| 401 | } |
| 402 | for (uint32_t n = 0; n < subgraph->num_nodes; n++) { |
| 403 | struct xnn_node* node = &subgraph->nodes[n]; |
| 404 | if ((subgraph->nodes[node->cluster_leader].layout_flags & XNN_LAYOUT_FLAG_INCOMPATIBLE_CLUSTER) != 0) { |
| 405 | continue; |
| 406 | } |
| 407 | |
| 408 | if ((node->layout_flags & (XNN_LAYOUT_FLAG_COMPATIBLE_NCHW2NHWC | XNN_LAYOUT_FLAG_COMPATIBLE_NCHW)) == 0) { |
| 409 | continue; |
| 410 | } |
| 411 | |
| 412 | for (uint32_t i = 0; i < node->num_inputs; i++) { |
| 413 | const struct xnn_value* value = &subgraph->values[node->inputs[i]]; |
| 414 | if (value->data != NULL) { |
| 415 | // Static data, skip this input value because it doesn't have a producer Node. |
| 416 | continue; |
| 417 | } |
| 418 | assert((value->flags & (XNN_VALUE_FLAG_EXTERNAL_INPUT | XNN_VALUE_FLAG_EXTERNAL_OUTPUT)) == 0); |
| 419 | assert(value->num_nchw_compatible_consumers > 0); |
| 420 | if (value->num_nchw_compatible_consumers != value->num_consumers) { |
| 421 | subgraph->nodes[node->cluster_leader].layout_flags |= XNN_LAYOUT_FLAG_INCOMPATIBLE_CLUSTER; |
| 422 | } |
| 423 | } |
| 424 | } |
Marat Dukhan | 54b2d54 | 2020-12-08 00:19:52 -0800 | [diff] [blame] | 425 | // Evaluate if it is profitable to run the model as sparse: |
| 426 | // - Compute the number of parameters and zeroes in 1x1 Convolution weights |
| 427 | // - Disable sparse rewriting for clusters without 1x1 Convolutions (num_params == 0) |
| 428 | // or with less than 2/3rd of zeroes in 1x1 Convolution filters |
| 429 | for (uint32_t n = 0; n < subgraph->num_nodes; n++) { |
| 430 | struct xnn_node* node = &subgraph->nodes[n]; |
| 431 | if ((subgraph->nodes[node->cluster_leader].layout_flags & XNN_LAYOUT_FLAG_INCOMPATIBLE_CLUSTER) != 0) { |
| 432 | continue; |
| 433 | } |
| 434 | |
| 435 | if (node->type == xnn_node_type_convolution_2d && |
| 436 | max(node->params.convolution_2d.kernel_height, node->params.convolution_2d.kernel_width) == 1) |
| 437 | { |
| 438 | assert(node->num_inputs >= 2); |
| 439 | |
| 440 | const struct xnn_value* filter = &subgraph->values[node->inputs[1]]; |
| 441 | assert(filter->data != NULL); |
| 442 | assert(filter->shape.num_dims == 4); |
| 443 | |
| 444 | const size_t num_params = filter->shape.dim[0] * filter->shape.dim[3]; |
| 445 | subgraph->nodes[node->cluster_leader].num_params += num_params; |
| 446 | |
| 447 | const float* data = (const float*) filter->data; |
| 448 | size_t num_zeroes = 0; |
| 449 | for (size_t i = 0; i < num_params; i++) { |
| 450 | num_zeroes += (size_t) (data[i] == 0.0f); |
| 451 | } |
| 452 | xnn_log_debug("1x1 Convolution 2D Node #%" PRIu32 ": %zu / %zu sparsity", n, num_zeroes, num_params); |
| 453 | subgraph->nodes[node->cluster_leader].num_zeroes += num_zeroes; |
| 454 | } |
| 455 | } |
Artsiom Ablavatski | cd3e068 | 2021-06-02 19:25:22 -0700 | [diff] [blame] | 456 | bool use_nchw_layout = false; |
Marat Dukhan | 9de90e0 | 2020-06-18 16:04:12 -0700 | [diff] [blame] | 457 | for (uint32_t n = 0; n < subgraph->num_nodes; n++) { |
| 458 | struct xnn_node* node = &subgraph->nodes[n]; |
| 459 | if ((subgraph->nodes[node->cluster_leader].layout_flags & XNN_LAYOUT_FLAG_INCOMPATIBLE_CLUSTER) != 0) { |
| 460 | continue; |
| 461 | } |
| 462 | |
| 463 | if ((node->layout_flags & (XNN_LAYOUT_FLAG_COMPATIBLE_NCHW2NHWC | XNN_LAYOUT_FLAG_COMPATIBLE_NCHW)) == 0) { |
| 464 | continue; |
| 465 | } |
| 466 | |
Marat Dukhan | 54b2d54 | 2020-12-08 00:19:52 -0800 | [diff] [blame] | 467 | if (subgraph->nodes[node->cluster_leader].num_zeroes * 3 <= subgraph->nodes[node->cluster_leader].num_params * 2) { |
| 468 | xnn_log_info("Node #%" PRIu32 ": sparse inference disabled: 1x1 Convolutions contain %zu / %zu zero weights", |
| 469 | n, subgraph->nodes[node->cluster_leader].num_zeroes, subgraph->nodes[node->cluster_leader].num_params); |
| 470 | continue; |
| 471 | } |
| 472 | |
Marat Dukhan | 9de90e0 | 2020-06-18 16:04:12 -0700 | [diff] [blame] | 473 | for (uint32_t i = 0; i < node->num_inputs; i++) { |
| 474 | struct xnn_value* value = &subgraph->values[node->inputs[i]]; |
| 475 | if (value->data != NULL) { |
| 476 | // Static data, skip this input value because it doesn't have a producer Node. |
| 477 | continue; |
| 478 | } |
| 479 | assert((value->flags & (XNN_VALUE_FLAG_EXTERNAL_INPUT | XNN_VALUE_FLAG_EXTERNAL_OUTPUT)) == 0); |
| 480 | assert(value->num_nchw_compatible_consumers > 0); |
| 481 | assert(value->num_nchw_compatible_consumers == value->num_consumers); |
| 482 | if (value->layout != xnn_layout_type_nchw) { |
| 483 | value->layout = xnn_layout_type_nchw; |
| 484 | xnn_log_info("set Value #%"PRIu32" layout to NCHW", node->inputs[i]); |
Artsiom Ablavatski | cd3e068 | 2021-06-02 19:25:22 -0700 | [diff] [blame] | 485 | use_nchw_layout = true; |
Marat Dukhan | 9de90e0 | 2020-06-18 16:04:12 -0700 | [diff] [blame] | 486 | } |
| 487 | } |
| 488 | } |
Artsiom Ablavatski | cd3e068 | 2021-06-02 19:25:22 -0700 | [diff] [blame] | 489 | if (use_nchw_layout) { |
| 490 | xnn_log_info("XNNPACK has switched to sparse inference mode!"); |
| 491 | } |
Marat Dukhan | 9de90e0 | 2020-06-18 16:04:12 -0700 | [diff] [blame] | 492 | } |
Marat Dukhan | 9de90e0 | 2020-06-18 16:04:12 -0700 | [diff] [blame] | 493 | |
Marat Dukhan | 1f19872 | 2020-05-24 14:07:03 -0700 | [diff] [blame] | 494 | enum xnn_status xnn_subgraph_optimize( |
| 495 | xnn_subgraph_t subgraph, |
| 496 | uint32_t flags) |
| 497 | { |
| 498 | // Initialize producer/consumer fields to safe defaults. |
| 499 | for (uint32_t i = 0; i < subgraph->num_values; i++) { |
| 500 | struct xnn_value* value = &subgraph->values[i]; |
| 501 | value->producer = XNN_INVALID_NODE_ID; |
| 502 | value->first_consumer = XNN_INVALID_NODE_ID; |
| 503 | value->num_consumers = 0; |
| 504 | } |
| 505 | |
| 506 | // Analyse Nodes' inputs and output and update Values' producer/consumer fields |
| 507 | for (uint32_t n = 0; n < subgraph->num_nodes; n++) { |
| 508 | struct xnn_node* node = &subgraph->nodes[n]; |
| 509 | |
| 510 | for (uint32_t i = 0; i < node->num_inputs; i++) { |
| 511 | const uint32_t input_id = node->inputs[i]; |
| 512 | assert(input_id < subgraph->num_values); |
| 513 | |
| 514 | if (subgraph->values[input_id].num_consumers++ == 0) { |
| 515 | assert(subgraph->values[input_id].first_consumer == XNN_INVALID_NODE_ID); |
| 516 | subgraph->values[input_id].first_consumer = n; |
| 517 | } |
| 518 | } |
| 519 | |
| 520 | for (uint32_t o = 0; o < node->num_outputs; o++) { |
| 521 | const uint32_t output_id = node->outputs[o]; |
| 522 | assert(output_id < subgraph->num_values); |
| 523 | |
| 524 | assert(subgraph->values[output_id].producer == XNN_INVALID_NODE_ID); |
| 525 | subgraph->values[output_id].producer = n; |
| 526 | } |
| 527 | } |
| 528 | |
| 529 | // Count extra consumer for Values which are external outputs. |
| 530 | // Remove unreferenced values. |
| 531 | for (uint32_t i = 0; i < subgraph->num_values; i++) { |
| 532 | struct xnn_value* value = &subgraph->values[i]; |
| 533 | if (value->type == xnn_value_type_invalid) { |
| 534 | continue; |
| 535 | } |
| 536 | |
| 537 | if (value->flags & XNN_VALUE_FLAG_EXTERNAL_OUTPUT) { |
| 538 | value->num_consumers += 1; |
| 539 | } |
| 540 | if ((value->flags & XNN_VALUE_FLAG_EXTERNAL_INPUT) == 0 && value->num_consumers == 0) { |
| 541 | xnn_value_clear(value); |
| 542 | } |
| 543 | } |
| 544 | |
| 545 | // Fuse Nodes where possible |
| 546 | for (uint32_t i = 0; i < subgraph->num_values; i++) { |
| 547 | struct xnn_value* value = &subgraph->values[i]; |
| 548 | if (value->num_consumers == 1) { |
| 549 | const uint32_t producer_id = value->producer; |
| 550 | if (producer_id == XNN_INVALID_NODE_ID) { |
| 551 | continue; |
| 552 | } |
| 553 | assert(producer_id < subgraph->num_nodes); |
| 554 | |
| 555 | const uint32_t consumer_id = value->first_consumer; |
| 556 | if (consumer_id == XNN_INVALID_NODE_ID) { |
| 557 | continue; |
| 558 | } |
| 559 | assert(consumer_id < subgraph->num_nodes); |
| 560 | |
| 561 | struct xnn_node* producer = &subgraph->nodes[producer_id]; |
| 562 | assert(producer->type != xnn_node_type_invalid); |
| 563 | struct xnn_node* consumer = &subgraph->nodes[consumer_id]; |
| 564 | assert(consumer->type != xnn_node_type_invalid); |
| 565 | |
| 566 | // Try to fuse Clamp Node upstream into producer Node |
| 567 | if (consumer->type == xnn_node_type_clamp) { |
| 568 | switch (producer->type) { |
| 569 | case xnn_node_type_add2: |
| 570 | case xnn_node_type_average_pooling_2d: |
| 571 | case xnn_node_type_clamp: |
| 572 | case xnn_node_type_convolution_2d: |
Marat Dukhan | b293e8d | 2020-07-23 20:10:45 -0700 | [diff] [blame] | 573 | case xnn_node_type_divide: |
| 574 | case xnn_node_type_deconvolution_2d: |
Marat Dukhan | 1f19872 | 2020-05-24 14:07:03 -0700 | [diff] [blame] | 575 | case xnn_node_type_depthwise_convolution_2d: |
| 576 | case xnn_node_type_fully_connected: |
| 577 | case xnn_node_type_multiply2: |
| 578 | case xnn_node_type_max_pooling_2d: |
Marat Dukhan | b293e8d | 2020-07-23 20:10:45 -0700 | [diff] [blame] | 579 | case xnn_node_type_subtract: |
Marat Dukhan | 1f19872 | 2020-05-24 14:07:03 -0700 | [diff] [blame] | 580 | xnn_log_info("fuse Clamp Node #%"PRIu32" into upstream Node #%"PRIu32, consumer_id, producer_id); |
| 581 | assert(producer->num_outputs == 1); |
| 582 | assert(consumer->num_inputs == 1); |
| 583 | assert(consumer->num_outputs == 1); |
| 584 | |
| 585 | const uint32_t fused_output_id = consumer->outputs[0]; |
| 586 | assert(fused_output_id < subgraph->num_values); |
| 587 | subgraph->values[fused_output_id].producer = producer_id; |
| 588 | producer->outputs[0] = fused_output_id; |
| 589 | |
| 590 | producer->activation.output_min = |
| 591 | math_max_f32(producer->activation.output_min, consumer->activation.output_min); |
| 592 | producer->activation.output_max = |
| 593 | math_min_f32(producer->activation.output_max, consumer->activation.output_max); |
| 594 | |
| 595 | xnn_node_clear(consumer); |
| 596 | xnn_value_clear(value); |
| 597 | break; |
| 598 | default: |
| 599 | break; |
| 600 | } |
| 601 | } |
Marat Dukhan | f3d1205 | 2020-05-25 15:41:37 -0700 | [diff] [blame] | 602 | // Try to fuse Constant Pad node downstream into [Depthwise] Convolution 2D Node |
Marat Dukhan | aff24e2 | 2020-07-23 01:43:58 -0700 | [diff] [blame] | 603 | if (producer->type == xnn_node_type_static_constant_pad) { |
Marat Dukhan | f3d1205 | 2020-05-25 15:41:37 -0700 | [diff] [blame] | 604 | assert(producer->num_inputs == 1); |
| 605 | assert(producer->num_outputs == 1); |
Marat Dukhan | 62a6949 | 2020-06-16 23:36:40 -0700 | [diff] [blame] | 606 | const bool is_spatial_2d_zero_padding = value->shape.num_dims == 4 && |
Marat Dukhan | f3d1205 | 2020-05-25 15:41:37 -0700 | [diff] [blame] | 607 | (producer->params.static_pad.pre_paddings[0] | producer->params.static_pad.post_paddings[0] | |
Marat Dukhan | 62a6949 | 2020-06-16 23:36:40 -0700 | [diff] [blame] | 608 | producer->params.static_pad.pre_paddings[3] | producer->params.static_pad.post_paddings[3]) == 0 && |
| 609 | producer->params.static_pad.padding_value == 0; |
Marat Dukhan | f3d1205 | 2020-05-25 15:41:37 -0700 | [diff] [blame] | 610 | switch (consumer->type) { |
| 611 | case xnn_node_type_convolution_2d: |
Marat Dukhan | 62a6949 | 2020-06-16 23:36:40 -0700 | [diff] [blame] | 612 | if (is_spatial_2d_zero_padding && !(consumer->flags & XNN_FLAG_TENSORFLOW_SAME_PADDING)) { |
Marat Dukhan | f3d1205 | 2020-05-25 15:41:37 -0700 | [diff] [blame] | 613 | xnn_log_info("fuse Constant Pad Node #%"PRIu32" into Convolution 2D Node #%"PRIu32, |
| 614 | consumer_id, producer_id); |
| 615 | assert(consumer->num_inputs >= 1); |
| 616 | assert(consumer->inputs[0] == producer->outputs[0]); |
| 617 | |
| 618 | consumer->params.convolution_2d.input_padding_top += producer->params.static_pad.pre_paddings[1]; |
Marat Dukhan | facecc5 | 2020-08-10 08:00:08 -0700 | [diff] [blame] | 619 | consumer->params.convolution_2d.input_padding_right += producer->params.static_pad.post_paddings[2]; |
Marat Dukhan | f3d1205 | 2020-05-25 15:41:37 -0700 | [diff] [blame] | 620 | consumer->params.convolution_2d.input_padding_bottom += producer->params.static_pad.post_paddings[1]; |
Marat Dukhan | facecc5 | 2020-08-10 08:00:08 -0700 | [diff] [blame] | 621 | consumer->params.convolution_2d.input_padding_left += producer->params.static_pad.pre_paddings[2]; |
Marat Dukhan | f3d1205 | 2020-05-25 15:41:37 -0700 | [diff] [blame] | 622 | |
| 623 | consumer->inputs[0] = producer->inputs[0]; |
| 624 | |
| 625 | const uint32_t fused_input_id = producer->inputs[0]; |
| 626 | assert(fused_input_id < subgraph->num_values); |
| 627 | if (subgraph->values[fused_input_id].first_consumer == producer_id) { |
| 628 | subgraph->values[fused_input_id].first_consumer = consumer_id; |
| 629 | } |
| 630 | |
| 631 | xnn_node_clear(producer); |
| 632 | xnn_value_clear(value); |
| 633 | } |
| 634 | break; |
| 635 | case xnn_node_type_depthwise_convolution_2d: |
Marat Dukhan | 62a6949 | 2020-06-16 23:36:40 -0700 | [diff] [blame] | 636 | if (is_spatial_2d_zero_padding && !(consumer->flags & XNN_FLAG_TENSORFLOW_SAME_PADDING)) { |
Marat Dukhan | f3d1205 | 2020-05-25 15:41:37 -0700 | [diff] [blame] | 637 | xnn_log_info("fuse Constant Pad Node #%"PRIu32" into Depthwise Convolution 2D Node #%"PRIu32, |
| 638 | consumer_id, producer_id); |
| 639 | assert(consumer->num_inputs >= 1); |
| 640 | assert(consumer->inputs[0] == producer->outputs[0]); |
| 641 | |
| 642 | consumer->params.depthwise_convolution_2d.input_padding_top += |
| 643 | producer->params.static_pad.pre_paddings[1]; |
| 644 | consumer->params.depthwise_convolution_2d.input_padding_right += |
Marat Dukhan | facecc5 | 2020-08-10 08:00:08 -0700 | [diff] [blame] | 645 | producer->params.static_pad.post_paddings[2]; |
Marat Dukhan | f3d1205 | 2020-05-25 15:41:37 -0700 | [diff] [blame] | 646 | consumer->params.depthwise_convolution_2d.input_padding_bottom += |
| 647 | producer->params.static_pad.post_paddings[1]; |
| 648 | consumer->params.depthwise_convolution_2d.input_padding_left += |
Marat Dukhan | facecc5 | 2020-08-10 08:00:08 -0700 | [diff] [blame] | 649 | producer->params.static_pad.pre_paddings[2]; |
Marat Dukhan | f3d1205 | 2020-05-25 15:41:37 -0700 | [diff] [blame] | 650 | |
| 651 | consumer->inputs[0] = producer->inputs[0]; |
| 652 | |
| 653 | const uint32_t fused_input_id = producer->inputs[0]; |
| 654 | assert(fused_input_id < subgraph->num_values); |
| 655 | if (subgraph->values[fused_input_id].first_consumer == producer_id) { |
| 656 | subgraph->values[fused_input_id].first_consumer = consumer_id; |
| 657 | } |
| 658 | |
| 659 | xnn_node_clear(producer); |
| 660 | xnn_value_clear(value); |
| 661 | } |
| 662 | break; |
| 663 | default: |
| 664 | break; |
| 665 | } |
| 666 | } |
Marat Dukhan | 1f19872 | 2020-05-24 14:07:03 -0700 | [diff] [blame] | 667 | } |
| 668 | } |
Marat Dukhan | 9de90e0 | 2020-06-18 16:04:12 -0700 | [diff] [blame] | 669 | |
| 670 | #if XNN_ENABLE_SPARSE |
Marat Dukhan | cfbed0a | 2020-12-08 10:01:51 -0800 | [diff] [blame] | 671 | if ((flags & XNN_FLAG_SPARSE_INFERENCE) && (xnn_params.init_flags & XNN_INIT_FLAG_CHW_OPT)) { |
Marat Dukhan | 7332e83 | 2020-12-06 23:26:11 -0800 | [diff] [blame] | 672 | xnn_subgraph_rewrite_for_nchw(subgraph); |
| 673 | } |
Marat Dukhan | 9de90e0 | 2020-06-18 16:04:12 -0700 | [diff] [blame] | 674 | #endif |
| 675 | |
Marat Dukhan | 1f19872 | 2020-05-24 14:07:03 -0700 | [diff] [blame] | 676 | return xnn_status_success; |
| 677 | } |
| 678 | |
Marat Dukhan | 1d75a54 | 2020-02-03 12:23:01 -0800 | [diff] [blame] | 679 | enum xnn_status xnn_delete_subgraph( |
| 680 | xnn_subgraph_t subgraph) |
| 681 | { |
| 682 | if (subgraph != NULL) { |
| 683 | memset(subgraph->nodes, 0, sizeof(struct xnn_node) * subgraph->num_nodes); |
| 684 | xnn_release_memory(subgraph->nodes); |
| 685 | |
| 686 | memset(subgraph->values, 0, sizeof(struct xnn_value) * subgraph->num_values); |
| 687 | xnn_release_memory(subgraph->values); |
| 688 | |
| 689 | memset(subgraph, 0, sizeof(struct xnn_subgraph)); |
| 690 | xnn_release_memory(subgraph); |
| 691 | } |
| 692 | return xnn_status_success; |
| 693 | } |