Bug Summary

File:nnc/ccv_nnc_graph.c
Warning:line 1270, column 22
Assigned value is garbage or undefined

Annotated Source Code

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clang -cc1 -cc1 -triple x86_64-unknown-linux-gnu -analyze -disable-free -clear-ast-before-backend -disable-llvm-verifier -discard-value-names -main-file-name ccv_nnc_graph.c -analyzer-checker=core -analyzer-checker=apiModeling -analyzer-checker=unix -analyzer-checker=deadcode -analyzer-checker=security.insecureAPI.UncheckedReturn -analyzer-checker=security.insecureAPI.getpw -analyzer-checker=security.insecureAPI.gets -analyzer-checker=security.insecureAPI.mktemp -analyzer-checker=security.insecureAPI.mkstemp -analyzer-checker=security.insecureAPI.vfork -analyzer-checker=nullability.NullPassedToNonnull -analyzer-checker=nullability.NullReturnedFromNonnull -analyzer-output plist -w -setup-static-analyzer -mrelocation-model pic -pic-level 2 -pic-is-pie -mframe-pointer=none -fmath-errno -ffp-contract=on -fno-rounding-math -mconstructor-aliases -funwind-tables=2 -target-cpu x86-64 -target-feature +sse2 -tune-cpu generic -debugger-tuning=gdb -fdebug-compilation-dir=/home/liu/actions-runner/_work/ccv/ccv/lib/nnc -fcoverage-compilation-dir=/home/liu/actions-runner/_work/ccv/ccv/lib/nnc -resource-dir /usr/local/lib/clang/18 -I ../ -I /usr/local/cuda/include -D HAVE_CBLAS -D HAVE_LIBPNG -D HAVE_LIBJPEG -D HAVE_FFTW3 -D HAVE_PTHREAD -D HAVE_LIBLINEAR -D HAVE_TESSERACT -D HAVE_AVCODEC -D HAVE_AVFORMAT -D HAVE_AVUTIL -D HAVE_SWSCALE -D HAVE_SSE2 -D HAVE_GSL -D HAVE_CUDA -D HAVE_CUDNN -D HAVE_NCCL -D USE_SYSTEM_CUB -D HAVE_CUDA_SM80 -I /usr/local/include -internal-isystem /usr/local/lib/clang/18/include -internal-isystem /usr/local/include -internal-isystem /usr/lib/gcc/x86_64-linux-gnu/12/../../../../x86_64-linux-gnu/include -internal-externc-isystem /usr/include/x86_64-linux-gnu -internal-externc-isystem /include -internal-externc-isystem /usr/include -O3 -ferror-limit 19 -fgnuc-version=4.2.1 -fskip-odr-check-in-gmf -vectorize-loops -vectorize-slp -analyzer-output=html -faddrsig -D__GCC_HAVE_DWARF2_CFI_ASM=1 -o /home/liu/actions-runner/_work/ccv/ccv/_analyze/2024-06-10-094233-222984-1 -x c ccv_nnc_graph.c
1#include "ccv_nnc.h"
2#include "ccv_nnc_easy.h"
3#include "ccv_nnc_internal.h"
4#include "ccv_internal.h"
5#include "_ccv_nnc_graph.h"
6
7// MARK - Level-2 API
8
9ccv_nnc_graph_t* ccv_nnc_graph_new(void)
10{
11 ccv_nnc_graph_t* graph = (ccv_nnc_graph_t*)cccalloccalloc(1, sizeof(ccv_nnc_graph_t));
12 graph->exec_info = ccv_array_new(sizeof(ccv_nnc_graph_exec_info_t), 5, 0);
13 return graph;
14}
15
16void ccv_nnc_graph_set_sources(ccv_nnc_graph_t* const graph, const ccv_nnc_graph_exec_t* const sources, const int source_size)
17{
18 if (!graph->sources)
19 graph->sources = ccv_array_new(sizeof(ccv_nnc_graph_exec_t), source_size, 0);
20 else
21 ccv_array_clear(graph->sources);
22 int i;
23 for (i = 0; i < source_size; i++)
24 ccv_array_push(graph->sources, sources + i);
25 graph->topsorted = 0;
26}
27
28ccv_nnc_graph_exec_t* ccv_nnc_graph_sources(const ccv_nnc_graph_t* const graph)
29{
30 return graph->sources ? (ccv_nnc_graph_exec_t*)ccv_array_get(graph->sources, 0)((void*)(((char*)((graph->sources)->data)) + (size_t)(graph
->sources)->rsize * (size_t)(0))) : 0;
31}
32
33int ccv_nnc_graph_source_size(const ccv_nnc_graph_t* const graph)
34{
35 return graph->sources ? graph->sources->rnum : 0;
36}
37
38void ccv_nnc_graph_set_destinations(ccv_nnc_graph_t* const graph, const ccv_nnc_graph_exec_t* const destinations, const int destination_size)
39{
40 if (!graph->destinations)
41 graph->destinations = ccv_array_new(sizeof(ccv_nnc_graph_exec_t), destination_size, 0);
42 else
43 ccv_array_clear(graph->sources);
44 int i;
45 for (i = 0; i < destination_size; i++)
46 ccv_array_push(graph->destinations, destinations + i);
47 graph->topsorted = 0;
48}
49
50ccv_nnc_graph_exec_t* ccv_nnc_graph_destinations(const ccv_nnc_graph_t* const graph)
51{
52 return graph->destinations ? (ccv_nnc_graph_exec_t*)ccv_array_get(graph->destinations, 0)((void*)(((char*)((graph->destinations)->data)) + (size_t
)(graph->destinations)->rsize * (size_t)(0))) : 0;
53}
54
55int ccv_nnc_graph_destination_size(const ccv_nnc_graph_t* const graph)
56{
57 return graph->destinations ? graph->destinations->rnum : 0;
58}
59
60void ccv_nnc_graph_exec_set(ccv_nnc_graph_t* const graph, const ccv_nnc_graph_exec_t exec, const ccv_nnc_cmd_t cmd)
61{
62 assert(exec.d < graph->exec_info->rnum)((void) sizeof ((exec.d < graph->exec_info->rnum) ? 1
: 0), __extension__ ({ if (exec.d < graph->exec_info->
rnum) ; else __assert_fail ("exec.d < graph->exec_info->rnum"
, "ccv_nnc_graph.c", 62, __extension__ __PRETTY_FUNCTION__); }
));
63 assert(exec.graph == graph)((void) sizeof ((exec.graph == graph) ? 1 : 0), __extension__
({ if (exec.graph == graph) ; else __assert_fail ("exec.graph == graph"
, "ccv_nnc_graph.c", 63, __extension__ __PRETTY_FUNCTION__); }
));
64 ccv_nnc_graph_exec_info_t* const exec_info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, exec.d)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(exec.d)));
65 exec_info->cmd = cmd;
66}
67
68ccv_nnc_cmd_t ccv_nnc_graph_exec_cmd(const ccv_nnc_graph_t* const graph, const ccv_nnc_graph_exec_t exec)
69{
70 assert(exec.d < graph->exec_info->rnum)((void) sizeof ((exec.d < graph->exec_info->rnum) ? 1
: 0), __extension__ ({ if (exec.d < graph->exec_info->
rnum) ; else __assert_fail ("exec.d < graph->exec_info->rnum"
, "ccv_nnc_graph.c", 70, __extension__ __PRETTY_FUNCTION__); }
));
71 assert(exec.graph == graph)((void) sizeof ((exec.graph == graph) ? 1 : 0), __extension__
({ if (exec.graph == graph) ; else __assert_fail ("exec.graph == graph"
, "ccv_nnc_graph.c", 71, __extension__ __PRETTY_FUNCTION__); }
));
72 ccv_nnc_graph_exec_info_t* const exec_info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, exec.d)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(exec.d)));
73 return exec_info->cmd;
74}
75
76void ccv_nnc_graph_exec_set_hint(ccv_nnc_graph_t* const graph, const ccv_nnc_graph_exec_t exec, const ccv_nnc_hint_t hint)
77{
78 assert(exec.d < graph->exec_info->rnum)((void) sizeof ((exec.d < graph->exec_info->rnum) ? 1
: 0), __extension__ ({ if (exec.d < graph->exec_info->
rnum) ; else __assert_fail ("exec.d < graph->exec_info->rnum"
, "ccv_nnc_graph.c", 78, __extension__ __PRETTY_FUNCTION__); }
));
79 assert(exec.graph == graph)((void) sizeof ((exec.graph == graph) ? 1 : 0), __extension__
({ if (exec.graph == graph) ; else __assert_fail ("exec.graph == graph"
, "ccv_nnc_graph.c", 79, __extension__ __PRETTY_FUNCTION__); }
));
80 ccv_nnc_graph_exec_info_t* const exec_info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, exec.d)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(exec.d)));
81 exec_info->hint = hint;
82}
83
84static int _ccv_nnc_tensor_multiview_level_count(const ccv_nnc_tensor_multiview_t* const mv)
85{
86 if (!CCV_IS_TENSOR_MULTIVIEW(mv)((*(int*)(mv)) & CCV_TENSOR_MULTIVIEW))
87 return 1;
88 const int count = mv->kind + mv->repeat;
89 int i, c = 0;
90 for (i = 0; i < count; i++)
91 {
92 ccv_nnc_tensor_t* tv = CCV_NNC_MULTIVIEW_DATA(mv)((mv)->_heap_data ? (mv)->_heap_data : (mv)->_inline_data
)[i];
93 if (tv == CCV_NNC_TENSOR_PLACEHOLDER((ccv_nnc_tensor_t*)(intptr_t)(0x10)))
94 c = ccv_max(c, 1)({ typeof (c) _a = (c); typeof (1) _b = (1); (_a > _b) ? _a
: _b; });
95 else
96 c = ccv_max(c, _ccv_nnc_tensor_multiview_level_count((ccv_nnc_tensor_multiview_t*)tv))({ typeof (c) _a = (c); typeof (_ccv_nnc_tensor_multiview_level_count
((ccv_nnc_tensor_multiview_t*)tv)) _b = (_ccv_nnc_tensor_multiview_level_count
((ccv_nnc_tensor_multiview_t*)tv)); (_a > _b) ? _a : _b; }
);
97 }
98 return c + 1;
99}
100
101static ccv_nnc_graph_tensor_wrap_t* _ccv_nnc_graph_tensor_wrap_new(const ccv_nnc_tensor_multiview_t* const mv)
102{
103 const int level_count = _ccv_nnc_tensor_multiview_level_count(mv);
104 ccv_nnc_graph_tensor_wrap_t* tensor_wrap = (ccv_nnc_graph_tensor_wrap_t*)ccmallocmalloc(sizeof(ccv_nnc_graph_tensor_wrap_t) + sizeof(ccv_nnc_tensor_t*) * (level_count - 1));
105 tensor_wrap->update_required = 0;
106 tensor_wrap->count = level_count;
107 tensor_wrap->index = 0;
108 tensor_wrap->tensors[0] = (ccv_nnc_tensor_t*)mv;
109 return tensor_wrap;
110}
111
112static void _ccv_nnc_graph_exec_rewind(ccv_nnc_graph_exec_info_t* const info, ccv_nnc_graph_t* const graph)
113{
114 if (!info->tensor_wraps_ref)
115 return;
116 int i;
117 assert(info->tensor_wraps_ref <= graph->tensor_wraps->rnum)((void) sizeof ((info->tensor_wraps_ref <= graph->tensor_wraps
->rnum) ? 1 : 0), __extension__ ({ if (info->tensor_wraps_ref
<= graph->tensor_wraps->rnum) ; else __assert_fail (
"info->tensor_wraps_ref <= graph->tensor_wraps->rnum"
, "ccv_nnc_graph.c", 117, __extension__ __PRETTY_FUNCTION__);
}));
118 ccv_nnc_graph_tensor_wrap_array_t* const tensor_wrap_array = *(ccv_nnc_graph_tensor_wrap_array_t**)ccv_array_get(graph->tensor_wraps, info->tensor_wraps_ref - 1)((void*)(((char*)((graph->tensor_wraps)->data)) + (size_t
)(graph->tensor_wraps)->rsize * (size_t)(info->tensor_wraps_ref
- 1)));;
119 // Rewind from tensor wraps.
120 for (i = 0; i < info->input_size; i++)
121 if (tensor_wrap_array->tensor_wraps[i])
122 info->inputs[i] = tensor_wrap_array->tensor_wraps[i]->tensors[0];
123 const int d = info->input_size;
124 for (i = 0; i < info->output_size; i++)
125 if (tensor_wrap_array->tensor_wraps[d + i])
126 info->outputs[i] = tensor_wrap_array->tensor_wraps[d + i]->tensors[0];
127 const int dd = info->input_size + info->output_size;
128 for (i = 0; i < info->update_size; i++)
129 if (tensor_wrap_array->tensor_wraps[dd + i])
130 info->updates[i] = tensor_wrap_array->tensor_wraps[dd + i]->tensors[0];
131}
132
133static void _ccv_nnc_graph_tensor_wrap_free(ccv_nnc_graph_tensor_wrap_t* const tensor_wrap)
134{
135 ccfreefree(tensor_wrap);
136}
137
138ccv_nnc_graph_tensor_wrap_array_t* ccv_nnc_get_tensor_wrap_array(ccv_nnc_graph_t* const graph, const int tensor_wrap_size, int* const tensor_wraps_ref)
139{
140 ccv_nnc_graph_tensor_wrap_array_t** tensor_wrap_array_ref = *tensor_wraps_ref ? (ccv_nnc_graph_tensor_wrap_array_t**)ccv_array_get(graph->tensor_wraps, *tensor_wraps_ref - 1)((void*)(((char*)((graph->tensor_wraps)->data)) + (size_t
)(graph->tensor_wraps)->rsize * (size_t)(*tensor_wraps_ref
- 1))) : 0;
141 // Otherwise, find an open slot.
142 if (!tensor_wrap_array_ref)
143 {
144 if (!graph->tensor_wraps)
145 graph->tensor_wraps = ccv_array_new(sizeof(ccv_nnc_graph_tensor_wrap_array_t*), 0, 0);
146 ccv_nnc_graph_tensor_wrap_array_t* const tensor_wrap_array = 0;
147 ccv_array_push(graph->tensor_wraps, &tensor_wrap_array);
148 tensor_wrap_array_ref = (ccv_nnc_graph_tensor_wrap_array_t**)ccv_array_get(graph->tensor_wraps, graph->tensor_wraps->rnum - 1)((void*)(((char*)((graph->tensor_wraps)->data)) + (size_t
)(graph->tensor_wraps)->rsize * (size_t)(graph->tensor_wraps
->rnum - 1)));
149 *tensor_wraps_ref = graph->tensor_wraps->rnum;
150 }
151 int i;
152 if (*tensor_wrap_array_ref)
153 {
154 if ((*tensor_wrap_array_ref)->size != tensor_wrap_size)
155 *tensor_wrap_array_ref = (ccv_nnc_graph_tensor_wrap_array_t*)ccreallocrealloc(*tensor_wrap_array_ref, sizeof(ccv_nnc_graph_tensor_wrap_array_t) + sizeof(ccv_nnc_graph_tensor_wrap_t*) * (tensor_wrap_size - 1));
156 for (i = (*tensor_wrap_array_ref)->size; i < tensor_wrap_size; i++)
157 (*tensor_wrap_array_ref)->tensor_wraps[i] = 0;
158 } else
159 *tensor_wrap_array_ref = (ccv_nnc_graph_tensor_wrap_array_t*)cccalloccalloc(sizeof(ccv_nnc_graph_tensor_wrap_array_t) + sizeof(ccv_nnc_graph_tensor_wrap_t*) * (tensor_wrap_size - 1), 1);
160 ccv_nnc_graph_tensor_wrap_array_t* const tensor_wrap_array = *tensor_wrap_array_ref;
161 tensor_wrap_array->size = tensor_wrap_size;
162 return tensor_wrap_array;
163}
164
165void ccv_nnc_set_tensor_wraps(ccv_nnc_graph_tensor_wrap_t** const tensor_wraps, ccv_nnc_tensor_t* const* const tensors, const int tensor_size)
166{
167 int i;
168 for (i = 0; i < tensor_size; i++)
169 if (tensors[i])
170 {
171 if (CCV_IS_TENSOR_MULTIVIEW(tensors[i])((*(int*)(tensors[i])) & CCV_TENSOR_MULTIVIEW) &&
172 ((ccv_nnc_tensor_multiview_t*)tensors[i])->anchor != CCV_NNC_MULTIVIEW_PHI(intptr_t)0x1)
173 {
174 if (!tensor_wraps[i] || tensors[i] != tensor_wraps[i]->tensors[0])
175 {
176 if (tensor_wraps[i])
177 _ccv_nnc_graph_tensor_wrap_free(tensor_wraps[i]);
178 tensor_wraps[i] = _ccv_nnc_graph_tensor_wrap_new((ccv_nnc_tensor_multiview_t*)tensors[i]);
179 }
180 } else {
181 if (tensor_wraps[i])
182 _ccv_nnc_graph_tensor_wrap_free(tensor_wraps[i]);
183 tensor_wraps[i] = 0;
184 }
185 }
186}
187
188void ccv_nnc_graph_register_tensor_wraps(ccv_nnc_graph_t* graph, const int tensor_wraps_ref_d)
189{
190 ccv_nnc_graph_t* p = graph;
191 const ccv_nnc_graph_tensor_wraps_ref_t tensor_wraps_ref = {
192 .d = tensor_wraps_ref_d,
193 .graph = graph,
194 };
195 do {
196 if (!p->tensor_wraps_refs)
197 {
198 p->tensor_wraps_refs = ccv_array_new(sizeof(ccv_nnc_graph_tensor_wraps_ref_t), 0, 0);
199 ccv_array_push(p->tensor_wraps_refs, &tensor_wraps_ref);
200 } else {
201 int i;
202 int has_tensor_wraps_ref = 0;
203 for (i = 0; !has_tensor_wraps_ref && i < p->tensor_wraps_refs->rnum; i++)
204 {
205 ccv_nnc_graph_tensor_wraps_ref_t* tensor_wraps_ref = (ccv_nnc_graph_tensor_wraps_ref_t*)ccv_array_get(p->tensor_wraps_refs, i)((void*)(((char*)((p->tensor_wraps_refs)->data)) + (size_t
)(p->tensor_wraps_refs)->rsize * (size_t)(i)));
206 has_tensor_wraps_ref = (tensor_wraps_ref->d == tensor_wraps_ref_d && tensor_wraps_ref->graph == graph);
207 }
208 if (!has_tensor_wraps_ref)
209 ccv_array_push(p->tensor_wraps_refs, &tensor_wraps_ref);
210 }
211 p = p->p;
212 } while (p);
213}
214
215static void _ccv_nnc_graph_redo_tensor_wraps(ccv_nnc_graph_exec_info_t* const info, ccv_nnc_graph_t* const graph)
216{
217 int i;
218 const int has_wrap = ccv_nnc_tensors_have_wraps(info->inputs, info->input_size) ||
219 ccv_nnc_tensors_have_wraps(info->outputs, info->output_size) ||
220 ccv_nnc_tensors_have_wraps(info->updates, info->update_size);
221 if (has_wrap)
222 {
223 const int tensor_wrap_size = info->input_size + info->output_size + info->update_size;
224 ccv_nnc_graph_tensor_wrap_array_t* const tensor_wrap_array = ccv_nnc_get_tensor_wrap_array(graph, tensor_wrap_size, &info->tensor_wraps_ref);
225 ccv_nnc_set_tensor_wraps(tensor_wrap_array->tensor_wraps, info->inputs, info->input_size);
226 const int d = info->input_size;
227 ccv_nnc_set_tensor_wraps(tensor_wrap_array->tensor_wraps + d, info->outputs, info->output_size);
228 const int dd = info->input_size + info->output_size;
229 ccv_nnc_set_tensor_wraps(tensor_wrap_array->tensor_wraps + dd, info->updates, info->update_size);
230 } else if (info->tensor_wraps_ref) {
231 ccv_nnc_graph_tensor_wrap_array_t** tensor_wrap_array_ref = (ccv_nnc_graph_tensor_wrap_array_t**)ccv_array_get(graph->tensor_wraps, info->tensor_wraps_ref - 1)((void*)(((char*)((graph->tensor_wraps)->data)) + (size_t
)(graph->tensor_wraps)->rsize * (size_t)(info->tensor_wraps_ref
- 1)));
232 ccv_nnc_graph_tensor_wrap_array_t* const tensor_wrap_array = *tensor_wrap_array_ref;
233 if (tensor_wrap_array)
234 {
235 for (i = 0; i < tensor_wrap_array->size; i++)
236 if (tensor_wrap_array->tensor_wraps[i])
237 _ccv_nnc_graph_tensor_wrap_free(tensor_wrap_array->tensor_wraps[i]);
238 ccfreefree(tensor_wrap_array);
239 *tensor_wrap_array_ref = 0;
240 info->tensor_wraps_ref = 0;
241 }
242 }
243}
244
245static void _ccv_nnc_graph_deregister_tensor_wraps(ccv_nnc_graph_t* graph, const int tensor_wraps_ref_d)
246{
247 ccv_nnc_graph_t* p = graph;
248 do {
249 int i;
250 // Remove from the array.
251 if (p->tensor_wraps_refs)
252 for (i = 0; i < p->tensor_wraps_refs->rnum; i++)
253 {
254 ccv_nnc_graph_tensor_wraps_ref_t* const tensor_wraps_ref = (ccv_nnc_graph_tensor_wraps_ref_t*)ccv_array_get(p->tensor_wraps_refs, i)((void*)(((char*)((p->tensor_wraps_refs)->data)) + (size_t
)(p->tensor_wraps_refs)->rsize * (size_t)(i)));
255 if (tensor_wraps_ref->d == tensor_wraps_ref_d && tensor_wraps_ref->graph == graph)
256 {
257 --p->tensor_wraps_refs->rnum;
258 if (i < p->tensor_wraps_refs->rnum)
259 memcpy(tensor_wraps_ref, tensor_wraps_ref + 1, sizeof(ccv_nnc_graph_exec_t) * (p->tensor_wraps_refs->rnum - i));
260 break;
261 }
262 }
263 p = p->p;
264 } while (p);
265}
266
267void ccv_nnc_graph_exec_set_io_flags(ccv_nnc_graph_t* const graph, const ccv_nnc_graph_exec_t exec, const int* const input_flags, const int input_flag_size, const int* const output_flags, const int output_flag_size)
268{
269 assert(exec.d < graph->exec_info->rnum)((void) sizeof ((exec.d < graph->exec_info->rnum) ? 1
: 0), __extension__ ({ if (exec.d < graph->exec_info->
rnum) ; else __assert_fail ("exec.d < graph->exec_info->rnum"
, "ccv_nnc_graph.c", 269, __extension__ __PRETTY_FUNCTION__);
}));
270 assert(exec.graph == graph)((void) sizeof ((exec.graph == graph) ? 1 : 0), __extension__
({ if (exec.graph == graph) ; else __assert_fail ("exec.graph == graph"
, "ccv_nnc_graph.c", 270, __extension__ __PRETTY_FUNCTION__);
}));
271 ccv_nnc_graph_exec_info_t* const info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, exec.d)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(exec.d)));
272 assert(input_flag_size <= info->input_size)((void) sizeof ((input_flag_size <= info->input_size) ?
1 : 0), __extension__ ({ if (input_flag_size <= info->
input_size) ; else __assert_fail ("input_flag_size <= info->input_size"
, "ccv_nnc_graph.c", 272, __extension__ __PRETTY_FUNCTION__);
}));
273 assert(output_flag_size <= info->output_size)((void) sizeof ((output_flag_size <= info->output_size)
? 1 : 0), __extension__ ({ if (output_flag_size <= info->
output_size) ; else __assert_fail ("output_flag_size <= info->output_size"
, "ccv_nnc_graph.c", 273, __extension__ __PRETTY_FUNCTION__);
}));
274 if (info->input_size + info->output_size == 0)
275 return;
276 if (!info->input_flags)
277 {
278 info->input_flags = (int*)cccalloccalloc(info->input_size + info->output_size, sizeof(int));
279 info->output_flags = info->input_flags + info->input_size;
280 }
281 if (input_flag_size > 0)
282 memcpy(info->input_flags, input_flags, sizeof(int) * input_flag_size);
283 if (output_flag_size > 0)
284 memcpy(info->output_flags, output_flags, sizeof(int) * output_flag_size);
285}
286
287void ccv_nnc_graph_exec_pair_with(ccv_nnc_graph_t* const graph, const ccv_nnc_graph_exec_t exec, const ccv_nnc_graph_exec_t pair_exec)
288{
289 assert(exec.graph == graph)((void) sizeof ((exec.graph == graph) ? 1 : 0), __extension__
({ if (exec.graph == graph) ; else __assert_fail ("exec.graph == graph"
, "ccv_nnc_graph.c", 289, __extension__ __PRETTY_FUNCTION__);
}));
290 assert(exec.d >= 0)((void) sizeof ((exec.d >= 0) ? 1 : 0), __extension__ ({ if
(exec.d >= 0) ; else __assert_fail ("exec.d >= 0", "ccv_nnc_graph.c"
, 290, __extension__ __PRETTY_FUNCTION__); }));
291 assert(exec.d < graph->exec_info->rnum)((void) sizeof ((exec.d < graph->exec_info->rnum) ? 1
: 0), __extension__ ({ if (exec.d < graph->exec_info->
rnum) ; else __assert_fail ("exec.d < graph->exec_info->rnum"
, "ccv_nnc_graph.c", 291, __extension__ __PRETTY_FUNCTION__);
}));
292 assert(pair_exec.graph == graph || pair_exec.graph == graph->pair)((void) sizeof ((pair_exec.graph == graph || pair_exec.graph ==
graph->pair) ? 1 : 0), __extension__ ({ if (pair_exec.graph
== graph || pair_exec.graph == graph->pair) ; else __assert_fail
("pair_exec.graph == graph || pair_exec.graph == graph->pair"
, "ccv_nnc_graph.c", 292, __extension__ __PRETTY_FUNCTION__);
}));
293 assert(pair_exec.d >= 0)((void) sizeof ((pair_exec.d >= 0) ? 1 : 0), __extension__
({ if (pair_exec.d >= 0) ; else __assert_fail ("pair_exec.d >= 0"
, "ccv_nnc_graph.c", 293, __extension__ __PRETTY_FUNCTION__);
}));
294 if (pair_exec.graph == graph)
295 { assert(pair_exec.d < graph->exec_info->rnum)((void) sizeof ((pair_exec.d < graph->exec_info->rnum
) ? 1 : 0), __extension__ ({ if (pair_exec.d < graph->exec_info
->rnum) ; else __assert_fail ("pair_exec.d < graph->exec_info->rnum"
, "ccv_nnc_graph.c", 295, __extension__ __PRETTY_FUNCTION__);
})); }
296 else
297 { assert(pair_exec.d < graph->pair->exec_info->rnum)((void) sizeof ((pair_exec.d < graph->pair->exec_info
->rnum) ? 1 : 0), __extension__ ({ if (pair_exec.d < graph
->pair->exec_info->rnum) ; else __assert_fail ("pair_exec.d < graph->pair->exec_info->rnum"
, "ccv_nnc_graph.c", 297, __extension__ __PRETTY_FUNCTION__);
})); }
298 ccv_nnc_graph_exec_info_t* const exec_info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, exec.d)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(exec.d)));
299 exec_info->pair_ref = pair_exec.d + 1;
300}
301
302static ccv_nnc_tensor_t* _ccv_nnc_any_tensor_from_tensor_multiview(ccv_nnc_tensor_multiview_t* const mv)
303{
304 ccv_nnc_tensor_t* tensor = (ccv_nnc_tensor_t*)mv;
305 while (CCV_IS_TENSOR_MULTIVIEW(tensor)((*(int*)(tensor)) & CCV_TENSOR_MULTIVIEW))
306 {
307 ccv_nnc_tensor_multiview_t* mv = (ccv_nnc_tensor_multiview_t*)tensor;
308 const int count = 0;
309 const int off = mv->kind;
310 const int mod = mv->repeat;
311 // If reached the root.
312 tensor = CCV_NNC_MULTIVIEW_DATA(mv)((mv)->_heap_data ? (mv)->_heap_data : (mv)->_inline_data
)[count >= off ? ((count - off) % mod) + off : count]; // Unwrap.
313 }
314 return tensor;
315}
316
317void ccv_nnc_graph_exec_set_io(ccv_nnc_graph_t* const graph, const ccv_nnc_graph_exec_t exec, ccv_nnc_tensor_t* const* const inputs, const int input_size, ccv_nnc_tensor_t* const* const outputs, const int output_size)
318{
319 assert(exec.d < graph->exec_info->rnum)((void) sizeof ((exec.d < graph->exec_info->rnum) ? 1
: 0), __extension__ ({ if (exec.d < graph->exec_info->
rnum) ; else __assert_fail ("exec.d < graph->exec_info->rnum"
, "ccv_nnc_graph.c", 319, __extension__ __PRETTY_FUNCTION__);
}));
320 assert(exec.graph == graph)((void) sizeof ((exec.graph == graph) ? 1 : 0), __extension__
({ if (exec.graph == graph) ; else __assert_fail ("exec.graph == graph"
, "ccv_nnc_graph.c", 320, __extension__ __PRETTY_FUNCTION__);
}));
321 ccv_nnc_graph_exec_info_t* const info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, exec.d)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(exec.d)));
322 // De-register from the graph if it contains multiview tensors.
323 if (info->tensor_wraps_ref)
324 _ccv_nnc_graph_deregister_tensor_wraps(graph, info->tensor_wraps_ref - 1);
325 // In case it is already executed, rewind.
326 _ccv_nnc_graph_exec_rewind(info, graph);
327 if (input_size == 0 && output_size == 0)
328 {
329 if (info->input_size > 0 || info->output_size > 0)
330 ccfreefree(info->inputs);
331 info->inputs = 0;
332 info->outputs = 0;
333 info->input_size = 0;
334 info->output_size = 0;
335 _ccv_nnc_graph_redo_tensor_wraps(info, graph);
336 if (info->tensor_wraps_ref)
337 ccv_nnc_graph_register_tensor_wraps(graph, info->tensor_wraps_ref - 1);
338 return;
339 }
340 if (info->inputs)
341 info->inputs = (ccv_nnc_tensor_t**)ccreallocrealloc(info->inputs, sizeof(ccv_nnc_tensor_t*) * (input_size + output_size));
342 else
343 info->inputs = (ccv_nnc_tensor_t**)ccmallocmalloc(sizeof(ccv_nnc_tensor_t*) * (input_size + output_size));
344 info->outputs = info->inputs + input_size;
345 if (inputs)
346 memcpy(info->inputs, inputs, sizeof(ccv_nnc_tensor_t*) * input_size);
347 if (outputs)
348 memcpy(info->outputs, outputs, sizeof(ccv_nnc_tensor_t*) * output_size);
349 int i;
350 int tensor_memory = 0, tensor_formats = 0, tensor_datatypes = 0;
351 for (i = 0; i < input_size + output_size; i++)
352 if (info->inputs[i])
353 {
354 ccv_nnc_tensor_t* const tensor = CCV_IS_TENSOR_MULTIVIEW(info->inputs[i])((*(int*)(info->inputs[i])) & CCV_TENSOR_MULTIVIEW) ? _ccv_nnc_any_tensor_from_tensor_multiview((ccv_nnc_tensor_multiview_t*)info->inputs[i]) : info->inputs[i];
355 tensor_memory |= CCV_TENSOR_GET_MEMORY(tensor->info.type)((tensor->info.type) & 0x3), tensor_formats |= tensor->info.format, tensor_datatypes |= CCV_GET_DATA_TYPE(tensor->info.datatype)((tensor->info.datatype) & 0xFF000);
356 }
357 info->cmd.backend = ccv_nnc_cmd_find_backend(info->cmd, tensor_memory, tensor_formats, tensor_datatypes);
358 info->input_size = input_size;
359 info->output_size = output_size;
360 _ccv_nnc_graph_redo_tensor_wraps(info, graph);
361 // Register again if the tensor wraps exist.
362 if (info->tensor_wraps_ref)
363 ccv_nnc_graph_register_tensor_wraps(graph, info->tensor_wraps_ref - 1);
364 // Free flags.
365 if (info->input_flags)
366 {
367 ccfreefree(info->input_flags);
368 info->input_flags = info->output_flags = 0;
369 }
370}
371
372void ccv_nnc_graph_exec_add_as_affected(ccv_nnc_graph_t* const graph, const ccv_nnc_graph_exec_t exec, ccv_nnc_tensor_t* const update)
373{
374 assert(CCV_IS_TENSOR_MULTIVIEW(update))((void) sizeof ((((*(int*)(update)) & CCV_TENSOR_MULTIVIEW
)) ? 1 : 0), __extension__ ({ if (((*(int*)(update)) & CCV_TENSOR_MULTIVIEW
)) ; else __assert_fail ("CCV_IS_TENSOR_MULTIVIEW(update)", "ccv_nnc_graph.c"
, 374, __extension__ __PRETTY_FUNCTION__); }));
375 assert(exec.d < graph->exec_info->rnum)((void) sizeof ((exec.d < graph->exec_info->rnum) ? 1
: 0), __extension__ ({ if (exec.d < graph->exec_info->
rnum) ; else __assert_fail ("exec.d < graph->exec_info->rnum"
, "ccv_nnc_graph.c", 375, __extension__ __PRETTY_FUNCTION__);
}));
376 assert(exec.graph == graph)((void) sizeof ((exec.graph == graph) ? 1 : 0), __extension__
({ if (exec.graph == graph) ; else __assert_fail ("exec.graph == graph"
, "ccv_nnc_graph.c", 376, __extension__ __PRETTY_FUNCTION__);
}));
377 ccv_nnc_graph_exec_info_t* const info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, exec.d)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(exec.d)));
378 const int register_tensor_wraps = !info->tensor_wraps_ref;
379 const int update_index = info->update_size;
380 ++info->update_size;
381 if (info->updates)
382 info->updates = (ccv_nnc_tensor_t**)ccreallocrealloc(info->updates, sizeof(ccv_nnc_tensor_t*) * info->update_size);
383 else
384 info->updates = (ccv_nnc_tensor_t**)ccmallocmalloc(sizeof(ccv_nnc_tensor_t*) * info->update_size);
385 info->updates[update_index] = update;
386 _ccv_nnc_graph_redo_tensor_wraps(info, graph);
387 if (register_tensor_wraps)
388 ccv_nnc_graph_register_tensor_wraps(graph, info->tensor_wraps_ref - 1);
389}
390
391ccv_nnc_graph_exec_t ccv_nnc_graph_exec_new(ccv_nnc_graph_t* const graph, const ccv_nnc_cmd_t cmd, const ccv_nnc_hint_t hint, ccv_nnc_tensor_t* const* const inputs, const int input_size, ccv_nnc_tensor_t* const* const outputs, const int output_size)
392{
393 int d = graph->exec_info->rnum;
394 ccv_nnc_graph_exec_info_t info = {
395 .cmd = cmd,
396 .hint = hint,
397 .input_size = input_size,
398 .output_size = output_size,
399 };
400 assert(inputs || input_size == 0)((void) sizeof ((inputs || input_size == 0) ? 1 : 0), __extension__
({ if (inputs || input_size == 0) ; else __assert_fail ("inputs || input_size == 0"
, "ccv_nnc_graph.c", 400, __extension__ __PRETTY_FUNCTION__);
}));
401 assert(outputs || output_size == 0)((void) sizeof ((outputs || output_size == 0) ? 1 : 0), __extension__
({ if (outputs || output_size == 0) ; else __assert_fail ("outputs || output_size == 0"
, "ccv_nnc_graph.c", 401, __extension__ __PRETTY_FUNCTION__);
}));
402 if (input_size > 0 || output_size > 0)
403 {
404 info.inputs = (ccv_nnc_tensor_t**)ccmallocmalloc(sizeof(ccv_nnc_tensor_t*) * (input_size + output_size));
405 info.outputs = info.inputs + input_size;
406 if (inputs)
407 memcpy(info.inputs, inputs, sizeof(ccv_nnc_tensor_t*) * input_size);
408 if (outputs)
409 memcpy(info.outputs, outputs, sizeof(ccv_nnc_tensor_t*) * output_size);
410 info.input_size = input_size;
411 info.output_size = output_size;
412 int i;
413 int tensor_memory = 0, tensor_formats = 0, tensor_datatypes = 0;
414 for (i = 0; i < input_size + output_size; i++)
415 if (info.inputs[i])
416 {
417 ccv_nnc_tensor_t* const tensor = CCV_IS_TENSOR_MULTIVIEW(info.inputs[i])((*(int*)(info.inputs[i])) & CCV_TENSOR_MULTIVIEW) ? _ccv_nnc_any_tensor_from_tensor_multiview((ccv_nnc_tensor_multiview_t*)info.inputs[i]) : info.inputs[i];
418 tensor_memory |= CCV_TENSOR_GET_MEMORY(tensor->info.type)((tensor->info.type) & 0x3), tensor_formats |= tensor->info.format, tensor_datatypes |= CCV_GET_DATA_TYPE(tensor->info.datatype)((tensor->info.datatype) & 0xFF000);
419 }
420 info.cmd.backend = ccv_nnc_cmd_find_backend(info.cmd, tensor_memory, tensor_formats, tensor_datatypes);
421 }
422 _ccv_nnc_graph_redo_tensor_wraps(&info, graph);
423 // Add itself to the graph's wraps array, this will help the run time when we run the graph and do unwrapping.
424 if (info.tensor_wraps_ref)
425 ccv_nnc_graph_register_tensor_wraps(graph, info.tensor_wraps_ref - 1);
426 ccv_array_push(graph->exec_info, &info);
427 return (ccv_nnc_graph_exec_t){
428 .d = d,
429 .graph = graph,
430 };
431}
432
433void ccv_nnc_graph_add_carry_over(ccv_nnc_graph_t* const graph, const ccv_nnc_tensor_t* const from, const ccv_nnc_tensor_t* const to)
434{
435 ccv_nnc_graph_tensor_carry_over_t carry_over = {
436 .from = _ccv_nnc_graph_tensor_wrap_new((ccv_nnc_tensor_multiview_t*)from),
437 .to = _ccv_nnc_graph_tensor_wrap_new((ccv_nnc_tensor_multiview_t*)to)
438 };
439 if (!graph->carry_overs)
440 graph->carry_overs = ccv_array_new(sizeof(ccv_nnc_graph_tensor_carry_over_t), 0, 0);
441 ccv_array_push(graph->carry_overs, &carry_over);
442}
443
444int ccv_nnc_graph_exec_concat(ccv_nnc_graph_t* const graph, const ccv_nnc_graph_exec_t source, const ccv_nnc_graph_exec_t destination)
445{
446 assert(graph == source.graph)((void) sizeof ((graph == source.graph) ? 1 : 0), __extension__
({ if (graph == source.graph) ; else __assert_fail ("graph == source.graph"
, "ccv_nnc_graph.c", 446, __extension__ __PRETTY_FUNCTION__);
}));
447 assert(graph == destination.graph)((void) sizeof ((graph == destination.graph) ? 1 : 0), __extension__
({ if (graph == destination.graph) ; else __assert_fail ("graph == destination.graph"
, "ccv_nnc_graph.c", 447, __extension__ __PRETTY_FUNCTION__);
}));
448 assert(source.d < graph->exec_info->rnum)((void) sizeof ((source.d < graph->exec_info->rnum) ?
1 : 0), __extension__ ({ if (source.d < graph->exec_info
->rnum) ; else __assert_fail ("source.d < graph->exec_info->rnum"
, "ccv_nnc_graph.c", 448, __extension__ __PRETTY_FUNCTION__);
}));
449 assert(destination.d < graph->exec_info->rnum)((void) sizeof ((destination.d < graph->exec_info->rnum
) ? 1 : 0), __extension__ ({ if (destination.d < graph->
exec_info->rnum) ; else __assert_fail ("destination.d < graph->exec_info->rnum"
, "ccv_nnc_graph.c", 449, __extension__ __PRETTY_FUNCTION__);
}));
450 ccv_nnc_graph_exec_info_t* src_info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, source.d)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(source.d)));
451 if (src_info->outgoings == 0)
452 src_info->outgoings = ccv_array_new(sizeof(int32_t), 1, 0);
453 else {
454 int i;
455 // Check if this is already connected, if so, skip.
456 for (i = 0; i < src_info->outgoings->rnum; i++)
457 if (*(int*)ccv_array_get(src_info->outgoings, i)((void*)(((char*)((src_info->outgoings)->data)) + (size_t
)(src_info->outgoings)->rsize * (size_t)(i))) == destination.d)
458 return -1;
459 }
460 ccv_array_push(src_info->outgoings, &destination.d);
461 graph->topsorted = 0;
462 return 0;
463}
464
465int ccv_nnc_graph_exec_disjoin(ccv_nnc_graph_t* const graph, const ccv_nnc_graph_exec_t source, const ccv_nnc_graph_exec_t destination)
466{
467 assert(graph == source.graph)((void) sizeof ((graph == source.graph) ? 1 : 0), __extension__
({ if (graph == source.graph) ; else __assert_fail ("graph == source.graph"
, "ccv_nnc_graph.c", 467, __extension__ __PRETTY_FUNCTION__);
}));
468 assert(graph == destination.graph)((void) sizeof ((graph == destination.graph) ? 1 : 0), __extension__
({ if (graph == destination.graph) ; else __assert_fail ("graph == destination.graph"
, "ccv_nnc_graph.c", 468, __extension__ __PRETTY_FUNCTION__);
}));
469 assert(source.d < graph->exec_info->rnum)((void) sizeof ((source.d < graph->exec_info->rnum) ?
1 : 0), __extension__ ({ if (source.d < graph->exec_info
->rnum) ; else __assert_fail ("source.d < graph->exec_info->rnum"
, "ccv_nnc_graph.c", 469, __extension__ __PRETTY_FUNCTION__);
}));
470 assert(destination.d < graph->exec_info->rnum)((void) sizeof ((destination.d < graph->exec_info->rnum
) ? 1 : 0), __extension__ ({ if (destination.d < graph->
exec_info->rnum) ; else __assert_fail ("destination.d < graph->exec_info->rnum"
, "ccv_nnc_graph.c", 470, __extension__ __PRETTY_FUNCTION__);
}));
471 ccv_nnc_graph_exec_info_t* src_info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, source.d)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(source.d)));
472 if (!src_info->outgoings)
473 return -1;
474 int i;
475 // Check if this is already connected, if so, skip.
476 for (i = 0; i < src_info->outgoings->rnum; i++)
477 if (*(int*)ccv_array_get(src_info->outgoings, i)((void*)(((char*)((src_info->outgoings)->data)) + (size_t
)(src_info->outgoings)->rsize * (size_t)(i))) == destination.d)
478 {
479 if (i < src_info->outgoings->rnum - 1)
480 *(int*)ccv_array_get(src_info->outgoings, i)((void*)(((char*)((src_info->outgoings)->data)) + (size_t
)(src_info->outgoings)->rsize * (size_t)(i))) = *(int*)ccv_array_get(src_info->outgoings, src_info->outgoings->rnum - 1)((void*)(((char*)((src_info->outgoings)->data)) + (size_t
)(src_info->outgoings)->rsize * (size_t)(src_info->outgoings
->rnum - 1)));
481 --src_info->outgoings->rnum;
482 graph->topsorted = 0;
483 return 0;
484 }
485 return -1;
486}
487
488int ccv_nnc_graph_exec_count(const ccv_nnc_graph_t* const graph)
489{
490 return graph->exec_info ? graph->exec_info->rnum : 0;
491}
492
493void* ccv_nnc_graph_buffer(ccv_nnc_graph_t* const graph, int size)
494{
495 if (graph->buffer_size >= size)
496 return graph->buffer;
497 graph->buffer_size = size;
498 graph->buffer = (graph->buffer) ? ccreallocrealloc(graph->buffer, size) : ccmallocmalloc(size);
499 return graph->buffer;
500}
501
502void ccv_nnc_graph_topsort(ccv_nnc_graph_t* const graph, int* const exec_cvt, const int exec_cvt_size)
503{
504 if (exec_cvt_size == 0 && graph->exec_info->rnum == 0)
505 {
506 graph->topsorted = 1;
507 return;
508 }
509 assert(exec_cvt_size == graph->exec_info->rnum)((void) sizeof ((exec_cvt_size == graph->exec_info->rnum
) ? 1 : 0), __extension__ ({ if (exec_cvt_size == graph->exec_info
->rnum) ; else __assert_fail ("exec_cvt_size == graph->exec_info->rnum"
, "ccv_nnc_graph.c", 509, __extension__ __PRETTY_FUNCTION__);
}));
510 assert(graph->sources && graph->sources->rnum)((void) sizeof ((graph->sources && graph->sources
->rnum) ? 1 : 0), __extension__ ({ if (graph->sources &&
graph->sources->rnum) ; else __assert_fail ("graph->sources && graph->sources->rnum"
, "ccv_nnc_graph.c", 510, __extension__ __PRETTY_FUNCTION__);
}));
511 assert(graph->destinations && graph->destinations->rnum)((void) sizeof ((graph->destinations && graph->
destinations->rnum) ? 1 : 0), __extension__ ({ if (graph->
destinations && graph->destinations->rnum) ; else
__assert_fail ("graph->destinations && graph->destinations->rnum"
, "ccv_nnc_graph.c", 511, __extension__ __PRETTY_FUNCTION__);
}));
512 int i, j;
513 for (i = 0; i < exec_cvt_size; i++)
514 exec_cvt[i] = -1;
515 ccv_array_t* exec_info = ccv_array_new(sizeof(ccv_nnc_graph_exec_info_t), graph->exec_info->rnum, 0);
516 // If there are breakpoints, it is more complicated, we first start to the breakpoints, and then continue from the breakpoints to the destinations.
517 if (graph->breakpoint_size)
518 {
519 ccv_nnc_graph_visit_t* visit = ccv_nnc_graph_visit_new(graph, (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, 0), graph->exec_info->rnum, (ccv_nnc_graph_exec_t*)ccv_array_get(graph->sources, 0), graph->sources->rnum, graph->breakpoints, graph->breakpoint_size, 0)({ ccv_nnc_graph_visit_t* _visit_ = (ccv_nnc_graph_visit_t*)malloc
(sizeof(ccv_nnc_graph_visit_t) + sizeof(_visit_->node[0]) *
((graph->exec_info->rnum) - 1)); _visit_->size = 0;
do { typedef struct { int8_t d; int8_t r; uint16_t c; int32_t
edges; } ccv_nnc_incoming_t; int _i_, _j_; int _incoming_edges_
= 0; for (_i_ = 0; _i_ < (graph->exec_info->rnum); _i_
++) _incoming_edges_ += (((ccv_nnc_graph_exec_info_t*)((void*
)(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_i_].outgoings) ? ((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_i_].outgoings
->rnum : 0; const int _heap_mem_ = ((graph->exec_info->
rnum) + _incoming_edges_ > 1024); ccv_nnc_incoming_t* _incomings_
; if (_heap_mem_) _incomings_ = (ccv_nnc_incoming_t*)malloc(sizeof
(ccv_nnc_incoming_t) * (graph->exec_info->rnum) + sizeof
(int32_t) * ((graph->exec_info->rnum) * 2 + _incoming_edges_
)); else _incomings_ = (ccv_nnc_incoming_t*)__builtin_alloca (
sizeof(ccv_nnc_incoming_t) * (graph->exec_info->rnum) +
sizeof(int32_t) * ((graph->exec_info->rnum) * 2 + _incoming_edges_
)); memset(_incomings_, 0, sizeof(ccv_nnc_incoming_t) * (graph
->exec_info->rnum)); int32_t* _exists_[2] = { (int32_t*
)(_incomings_ + (graph->exec_info->rnum)), (int32_t*)(_incomings_
+ (graph->exec_info->rnum)) + (graph->exec_info->
rnum), }; int32_t* const _edges_ = _exists_[1] + (graph->exec_info
->rnum); for (_i_ = 0; _i_ < (graph->sources->rnum
); _i_++) { ((void) sizeof ((((ccv_nnc_graph_exec_t*)((void*)
(((char*)((graph->sources)->data)) + (size_t)(graph->
sources)->rsize * (size_t)(0))))[_i_].graph == graph) ? 1 :
0), __extension__ ({ if (((ccv_nnc_graph_exec_t*)((void*)(((
char*)((graph->sources)->data)) + (size_t)(graph->sources
)->rsize * (size_t)(0))))[_i_].graph == graph) ; else __assert_fail
("((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->sources)->data)) + (size_t)(graph->sources)->rsize * (size_t)(0))))[_i_].graph == graph"
, "ccv_nnc_graph.c", 519, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[((ccv_nnc_graph_exec_t*)((void*)(((char*)((
graph->sources)->data)) + (size_t)(graph->sources)->
rsize * (size_t)(0))))[_i_].d].r = 1; _exists_[0][_i_] = ((ccv_nnc_graph_exec_t
*)((void*)(((char*)((graph->sources)->data)) + (size_t)
(graph->sources)->rsize * (size_t)(0))))[_i_].d; } int _exist_size_
[2] = { (graph->sources->rnum), 0, }; int _p_ = 0, _q_ =
1; while (_exist_size_[_p_] > 0) { _exist_size_[_q_] = 0;
for (_i_ = 0; _i_ < _exist_size_[_p_]; _i_++) { const int32_t
_idx_ = _exists_[_p_][_i_]; if (_incomings_[_idx_].r != 1) continue
; _incomings_[_idx_].r = 2; if (((ccv_nnc_graph_exec_info_t*)
((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
) for (_j_ = 0; _j_ < ((ccv_nnc_graph_exec_info_t*)((void*
)(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings->rnum
; _j_++) { const int d = *(int*)((void*)(((char*)((((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
)->data)) + (size_t)(((ccv_nnc_graph_exec_info_t*)((void*)
(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings)->rsize
* (size_t)(_j_))); ++_incomings_[d].c; if (_incomings_[d].r !=
0) continue; _incomings_[d].r = 1; ((void) sizeof ((_exist_size_
[_q_] < (graph->exec_info->rnum)) ? 1 : 0), __extension__
({ if (_exist_size_[_q_] < (graph->exec_info->rnum)
) ; else __assert_fail ("_exist_size_[_q_] < (graph->exec_info->rnum)"
, "ccv_nnc_graph.c", 519, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_)); } for (
_i_ = 0; _i_ < (graph->sources->rnum); _i_++) { ((void
) sizeof ((((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->
sources)->data)) + (size_t)(graph->sources)->rsize *
(size_t)(0))))[_i_].graph == graph) ? 1 : 0), __extension__ (
{ if (((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->sources
)->data)) + (size_t)(graph->sources)->rsize * (size_t
)(0))))[_i_].graph == graph) ; else __assert_fail ("((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->sources)->data)) + (size_t)(graph->sources)->rsize * (size_t)(0))))[_i_].graph == graph"
, "ccv_nnc_graph.c", 519, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[((ccv_nnc_graph_exec_t*)((void*)(((char*)((
graph->sources)->data)) + (size_t)(graph->sources)->
rsize * (size_t)(0))))[_i_].d].r = 3; _exists_[0][_i_] = ((ccv_nnc_graph_exec_t
*)((void*)(((char*)((graph->sources)->data)) + (size_t)
(graph->sources)->rsize * (size_t)(0))))[_i_].d; } _exist_size_
[0] = (graph->sources->rnum); _exist_size_[1] = 0; _p_ =
0, _q_ = 1; int _bump_ = 1; while (_exist_size_[_p_] > 0)
{ _exist_size_[_q_] = 0; for (_i_ = 0; _i_ < _exist_size_
[_p_]; _i_++) { const int32_t _idx_ = _exists_[_p_][_i_]; if (
_incomings_[_idx_].r != 3) continue; _incomings_[_idx_].r = 4
; if (((ccv_nnc_graph_exec_info_t*)((void*)(((char*)((graph->
exec_info)->data)) + (size_t)(graph->exec_info)->rsize
* (size_t)(0))))[_idx_].outgoings) for (_j_ = 0; _j_ < ((
ccv_nnc_graph_exec_info_t*)((void*)(((char*)((graph->exec_info
)->data)) + (size_t)(graph->exec_info)->rsize * (size_t
)(0))))[_idx_].outgoings->rnum; _j_++) { const int d = *(int
*)((void*)(((char*)((((ccv_nnc_graph_exec_info_t*)((void*)(((
char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings)->data
)) + (size_t)(((ccv_nnc_graph_exec_info_t*)((void*)(((char*)(
(graph->exec_info)->data)) + (size_t)(graph->exec_info
)->rsize * (size_t)(0))))[_idx_].outgoings)->rsize * (size_t
)(_j_))); if (_incomings_[d].edges == 0) { _incomings_[d].edges
= _bump_; _bump_ += _incomings_[d].c; _incomings_[d].c = 0; }
_edges_[_incomings_[d].edges - 1 + _incomings_[d].c] = _idx_
; ++_incomings_[d].c; if (_incomings_[d].r != 2) continue; _incomings_
[d].r = 3; ((void) sizeof ((_exist_size_[_q_] < (graph->
exec_info->rnum)) ? 1 : 0), __extension__ ({ if (_exist_size_
[_q_] < (graph->exec_info->rnum)) ; else __assert_fail
("_exist_size_[_q_] < (graph->exec_info->rnum)", "ccv_nnc_graph.c"
, 519, __extension__ __PRETTY_FUNCTION__); })); _exists_[_q_]
[_exist_size_[_q_]] = d; ++_exist_size_[_q_]; } } ((_i_) = (_p_
), (_p_) = (_q_), (_q_) = (_i_)); } for (_i_ = 0; _i_ < (graph
->breakpoint_size); _i_++) { ((void) sizeof (((graph->breakpoints
)[_i_].graph == graph) ? 1 : 0), __extension__ ({ if ((graph->
breakpoints)[_i_].graph == graph) ; else __assert_fail ("(graph->breakpoints)[_i_].graph == graph"
, "ccv_nnc_graph.c", 519, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[(graph->breakpoints)[_i_].d].r = 5; _exists_
[0][_i_] = (graph->breakpoints)[_i_].d; } _exist_size_[0] =
(graph->breakpoint_size); _exist_size_[1] = 0; _p_ = 0, _q_
= 1; while (_exist_size_[_p_] > 0) { _exist_size_[_q_] = 0
; for (_i_ = 0; _i_ < _exist_size_[_p_]; _i_++) { const int32_t
_idx_ = _exists_[_p_][_i_]; if (_incomings_[_idx_].r != 5) continue
; _incomings_[_idx_].r = 6; if (_incomings_[_idx_].edges >
0) for (_j_ = 0; _j_ < _incomings_[_idx_].c; _j_++) { const
int d = _edges_[_incomings_[_idx_].edges - 1 + _j_]; if (_incomings_
[d].r != 4) continue; _incomings_[d].r = 5; ((void) sizeof ((
_exist_size_[_q_] < (graph->exec_info->rnum)) ? 1 : 0
), __extension__ ({ if (_exist_size_[_q_] < (graph->exec_info
->rnum)) ; else __assert_fail ("_exist_size_[_q_] < (graph->exec_info->rnum)"
, "ccv_nnc_graph.c", 519, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_)); } for (
_i_ = 0; _i_ < (graph->breakpoint_size); _i_++) { ((void
) sizeof (((graph->breakpoints)[_i_].graph == graph) ? 1 :
0), __extension__ ({ if ((graph->breakpoints)[_i_].graph ==
graph) ; else __assert_fail ("(graph->breakpoints)[_i_].graph == graph"
, "ccv_nnc_graph.c", 519, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[(graph->breakpoints)[_i_].d].d = 1; } for
(_i_ = 0; _i_ < (graph->sources->rnum); _i_++) { ((
void) sizeof ((((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph
->sources)->data)) + (size_t)(graph->sources)->rsize
* (size_t)(0))))[_i_].graph == graph) ? 1 : 0), __extension__
({ if (((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->
sources)->data)) + (size_t)(graph->sources)->rsize *
(size_t)(0))))[_i_].graph == graph) ; else __assert_fail ("((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->sources)->data)) + (size_t)(graph->sources)->rsize * (size_t)(0))))[_i_].graph == graph"
, "ccv_nnc_graph.c", 519, __extension__ __PRETTY_FUNCTION__);
})); _exists_[0][_i_] = ((ccv_nnc_graph_exec_t*)((void*)(((char
*)((graph->sources)->data)) + (size_t)(graph->sources
)->rsize * (size_t)(0))))[_i_].d; } _p_ = 0; _q_ = 1; _exist_size_
[0] = (graph->sources->rnum); _exist_size_[1] = 0; int _d_
= 0; while (_exist_size_[_p_] > 0) { _exist_size_[_q_] = 0
; for (_i_ = 0; _i_ < _exist_size_[_p_];) { const int32_t _idx_
= _exists_[_p_][_i_]; _visit_->node[_visit_->size].index
= ((_idx_)); _visit_->node[_visit_->size].term = ((_incomings_
[_idx_].d)); ++_visit_->size;; if (_incomings_[_idx_].d) {
++_d_; _incomings_[_idx_].r = 7; } if (((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
) { if (((ccv_nnc_graph_exec_info_t*)((void*)(((char*)((graph
->exec_info)->data)) + (size_t)(graph->exec_info)->
rsize * (size_t)(0))))[_idx_].outgoings->rnum == 1) { const
int d = *(int*)((void*)(((char*)((((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
)->data)) + (size_t)(((ccv_nnc_graph_exec_info_t*)((void*)
(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings)->rsize
* (size_t)(0))); --_incomings_[d].c; if (_incomings_[d].c ==
0 && _incomings_[d].r == 6 && _d_ < (graph
->breakpoint_size)) { _exists_[_p_][_i_] = d; continue; } }
else for (_j_ = 0; _j_ < ((ccv_nnc_graph_exec_info_t*)((void
*)(((char*)((graph->exec_info)->data)) + (size_t)(graph
->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings->
rnum; _j_++) { const int d = *(int*)((void*)(((char*)((((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
)->data)) + (size_t)(((ccv_nnc_graph_exec_info_t*)((void*)
(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings)->rsize
* (size_t)(_j_))); --_incomings_[d].c; if (_incomings_[d].c ==
0 && _incomings_[d].r == 6 && _d_ < (graph
->breakpoint_size)) { ((void) sizeof ((_exist_size_[_q_] <
(graph->exec_info->rnum)) ? 1 : 0), __extension__ ({ if
(_exist_size_[_q_] < (graph->exec_info->rnum)) ; else
__assert_fail ("_exist_size_[_q_] < (graph->exec_info->rnum)"
, "ccv_nnc_graph.c", 519, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } } ++_i_; } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_
)); } for (_i_ = 0; _i_ < (graph->breakpoint_size); _i_
++) { ((void) sizeof (((graph->breakpoints)[_i_].graph == graph
) ? 1 : 0), __extension__ ({ if ((graph->breakpoints)[_i_]
.graph == graph) ; else __assert_fail ("(graph->breakpoints)[_i_].graph == graph"
, "ccv_nnc_graph.c", 519, __extension__ __PRETTY_FUNCTION__);
})); if (_incomings_[(graph->breakpoints)[_i_].d].r == 7)
continue; if (!(0)) { ((void) sizeof ((_incomings_[(graph->
breakpoints)[_i_].d].c == 0) ? 1 : 0), __extension__ ({ if (_incomings_
[(graph->breakpoints)[_i_].d].c == 0) ; else __assert_fail
("_incomings_[(graph->breakpoints)[_i_].d].c == 0", "ccv_nnc_graph.c"
, 519, __extension__ __PRETTY_FUNCTION__); })); } else if (_incomings_
[(graph->breakpoints)[_i_].d].c > 0) continue; _visit_->
node[_visit_->size].index = (((graph->breakpoints)[_i_]
.d)); _visit_->node[_visit_->size].term = ((_incomings_
[(graph->breakpoints)[_i_].d].d)); ++_visit_->size;; } if
(_heap_mem_) free(_incomings_); } while (0);; ((void) sizeof
((_visit_->size <= (graph->exec_info->rnum)) ? 1
: 0), __extension__ ({ if (_visit_->size <= (graph->
exec_info->rnum)) ; else __assert_fail ("_visit_->size <= (graph->exec_info->rnum)"
, "ccv_nnc_graph.c", 519, __extension__ __PRETTY_FUNCTION__);
})); _visit_; });
520 for (i = 0; i < graph->breakpoint_size; i++)
521 exec_cvt[graph->breakpoints[i].d] = -2; // Mark this as breakpoints, so we will skip the first round.
522 ccv_nnc_graph_visit_for(visit, (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, 0), node, idx){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int _node_unused_ __attribute__((unused)) = (visit)->
node[_i_].term; typeof (((ccv_nnc_graph_exec_info_t*)((void*)
(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))) const node __attribute__
((unused)) = ((ccv_nnc_graph_exec_info_t*)((void*)(((char*)((
graph->exec_info)->data)) + (size_t)(graph->exec_info
)->rsize * (size_t)(0)))) + idx; {
523 assert(!node->pair_ref)((void) sizeof ((!node->pair_ref) ? 1 : 0), __extension__ (
{ if (!node->pair_ref) ; else __assert_fail ("!node->pair_ref"
, "ccv_nnc_graph.c", 523, __extension__ __PRETTY_FUNCTION__);
})); // If node has a pair ref, we cannot fix it up.
524 if (exec_cvt[idx] == -2) // Skip breakpoint.
525 continue;
526 // Loop over node and push to the array.
527 ccv_array_push(exec_info, node);
528 // Go to its sub-graph to fix exec_idx
529 for (i = 0; i < node->graph_ref_size; i++)
530 {
531 const int graph_ref = CCV_NNC_GRAPH_REF(node)((node)->_heap_graph_ref ? (node)->_heap_graph_ref : (node
)->_inline_graph_ref)[i] - 1;
532 if (graph_ref >= 0)
533 {
534 ccv_nnc_graph_t* const sub_graph = *(ccv_nnc_graph_t**)ccv_array_get(graph->sub_graphs, graph_ref)((void*)(((char*)((graph->sub_graphs)->data)) + (size_t
)(graph->sub_graphs)->rsize * (size_t)(graph_ref)));
535 sub_graph->exec_idx = exec_info->rnum;
536 }
537 }
538 exec_cvt[idx] = exec_info->rnum - 1;
539 } ccv_nnc_graph_visit_endfor} }
540 ccv_nnc_graph_visit_free(visit);
541 graph->breakpoint_offset = exec_info->rnum;
542 visit = ccv_nnc_graph_visit_new(graph, (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, 0), graph->exec_info->rnum, graph->breakpoints, graph->breakpoint_size, (ccv_nnc_graph_exec_t*)ccv_array_get(graph->destinations, 0), graph->destinations->rnum, 0)({ ccv_nnc_graph_visit_t* _visit_ = (ccv_nnc_graph_visit_t*)malloc
(sizeof(ccv_nnc_graph_visit_t) + sizeof(_visit_->node[0]) *
((graph->exec_info->rnum) - 1)); _visit_->size = 0;
do { typedef struct { int8_t d; int8_t r; uint16_t c; int32_t
edges; } ccv_nnc_incoming_t; int _i_, _j_; int _incoming_edges_
= 0; for (_i_ = 0; _i_ < (graph->exec_info->rnum); _i_
++) _incoming_edges_ += (((ccv_nnc_graph_exec_info_t*)((void*
)(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_i_].outgoings) ? ((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_i_].outgoings
->rnum : 0; const int _heap_mem_ = ((graph->exec_info->
rnum) + _incoming_edges_ > 1024); ccv_nnc_incoming_t* _incomings_
; if (_heap_mem_) _incomings_ = (ccv_nnc_incoming_t*)malloc(sizeof
(ccv_nnc_incoming_t) * (graph->exec_info->rnum) + sizeof
(int32_t) * ((graph->exec_info->rnum) * 2 + _incoming_edges_
)); else _incomings_ = (ccv_nnc_incoming_t*)__builtin_alloca (
sizeof(ccv_nnc_incoming_t) * (graph->exec_info->rnum) +
sizeof(int32_t) * ((graph->exec_info->rnum) * 2 + _incoming_edges_
)); memset(_incomings_, 0, sizeof(ccv_nnc_incoming_t) * (graph
->exec_info->rnum)); int32_t* _exists_[2] = { (int32_t*
)(_incomings_ + (graph->exec_info->rnum)), (int32_t*)(_incomings_
+ (graph->exec_info->rnum)) + (graph->exec_info->
rnum), }; int32_t* const _edges_ = _exists_[1] + (graph->exec_info
->rnum); for (_i_ = 0; _i_ < (graph->breakpoint_size
); _i_++) { ((void) sizeof (((graph->breakpoints)[_i_].graph
== graph) ? 1 : 0), __extension__ ({ if ((graph->breakpoints
)[_i_].graph == graph) ; else __assert_fail ("(graph->breakpoints)[_i_].graph == graph"
, "ccv_nnc_graph.c", 542, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[(graph->breakpoints)[_i_].d].r = 1; _exists_
[0][_i_] = (graph->breakpoints)[_i_].d; } int _exist_size_
[2] = { (graph->breakpoint_size), 0, }; int _p_ = 0, _q_ =
1; while (_exist_size_[_p_] > 0) { _exist_size_[_q_] = 0;
for (_i_ = 0; _i_ < _exist_size_[_p_]; _i_++) { const int32_t
_idx_ = _exists_[_p_][_i_]; if (_incomings_[_idx_].r != 1) continue
; _incomings_[_idx_].r = 2; if (((ccv_nnc_graph_exec_info_t*)
((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
) for (_j_ = 0; _j_ < ((ccv_nnc_graph_exec_info_t*)((void*
)(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings->rnum
; _j_++) { const int d = *(int*)((void*)(((char*)((((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
)->data)) + (size_t)(((ccv_nnc_graph_exec_info_t*)((void*)
(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings)->rsize
* (size_t)(_j_))); ++_incomings_[d].c; if (_incomings_[d].r !=
0) continue; _incomings_[d].r = 1; ((void) sizeof ((_exist_size_
[_q_] < (graph->exec_info->rnum)) ? 1 : 0), __extension__
({ if (_exist_size_[_q_] < (graph->exec_info->rnum)
) ; else __assert_fail ("_exist_size_[_q_] < (graph->exec_info->rnum)"
, "ccv_nnc_graph.c", 542, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_)); } for (
_i_ = 0; _i_ < (graph->breakpoint_size); _i_++) { ((void
) sizeof (((graph->breakpoints)[_i_].graph == graph) ? 1 :
0), __extension__ ({ if ((graph->breakpoints)[_i_].graph ==
graph) ; else __assert_fail ("(graph->breakpoints)[_i_].graph == graph"
, "ccv_nnc_graph.c", 542, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[(graph->breakpoints)[_i_].d].r = 3; _exists_
[0][_i_] = (graph->breakpoints)[_i_].d; } _exist_size_[0] =
(graph->breakpoint_size); _exist_size_[1] = 0; _p_ = 0, _q_
= 1; int _bump_ = 1; while (_exist_size_[_p_] > 0) { _exist_size_
[_q_] = 0; for (_i_ = 0; _i_ < _exist_size_[_p_]; _i_++) {
const int32_t _idx_ = _exists_[_p_][_i_]; if (_incomings_[_idx_
].r != 3) continue; _incomings_[_idx_].r = 4; if (((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
) for (_j_ = 0; _j_ < ((ccv_nnc_graph_exec_info_t*)((void*
)(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings->rnum
; _j_++) { const int d = *(int*)((void*)(((char*)((((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
)->data)) + (size_t)(((ccv_nnc_graph_exec_info_t*)((void*)
(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings)->rsize
* (size_t)(_j_))); if (_incomings_[d].edges == 0) { _incomings_
[d].edges = _bump_; _bump_ += _incomings_[d].c; _incomings_[d
].c = 0; } _edges_[_incomings_[d].edges - 1 + _incomings_[d].
c] = _idx_; ++_incomings_[d].c; if (_incomings_[d].r != 2) continue
; _incomings_[d].r = 3; ((void) sizeof ((_exist_size_[_q_] <
(graph->exec_info->rnum)) ? 1 : 0), __extension__ ({ if
(_exist_size_[_q_] < (graph->exec_info->rnum)) ; else
__assert_fail ("_exist_size_[_q_] < (graph->exec_info->rnum)"
, "ccv_nnc_graph.c", 542, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_)); } for (
_i_ = 0; _i_ < (graph->destinations->rnum); _i_++) {
((void) sizeof ((((ccv_nnc_graph_exec_t*)((void*)(((char*)((
graph->destinations)->data)) + (size_t)(graph->destinations
)->rsize * (size_t)(0))))[_i_].graph == graph) ? 1 : 0), __extension__
({ if (((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->
destinations)->data)) + (size_t)(graph->destinations)->
rsize * (size_t)(0))))[_i_].graph == graph) ; else __assert_fail
("((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->destinations)->data)) + (size_t)(graph->destinations)->rsize * (size_t)(0))))[_i_].graph == graph"
, "ccv_nnc_graph.c", 542, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[((ccv_nnc_graph_exec_t*)((void*)(((char*)((
graph->destinations)->data)) + (size_t)(graph->destinations
)->rsize * (size_t)(0))))[_i_].d].r = 5; _exists_[0][_i_] =
((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->destinations
)->data)) + (size_t)(graph->destinations)->rsize * (
size_t)(0))))[_i_].d; } _exist_size_[0] = (graph->destinations
->rnum); _exist_size_[1] = 0; _p_ = 0, _q_ = 1; while (_exist_size_
[_p_] > 0) { _exist_size_[_q_] = 0; for (_i_ = 0; _i_ <
_exist_size_[_p_]; _i_++) { const int32_t _idx_ = _exists_[_p_
][_i_]; if (_incomings_[_idx_].r != 5) continue; _incomings_[
_idx_].r = 6; if (_incomings_[_idx_].edges > 0) for (_j_ =
0; _j_ < _incomings_[_idx_].c; _j_++) { const int d = _edges_
[_incomings_[_idx_].edges - 1 + _j_]; if (_incomings_[d].r !=
4) continue; _incomings_[d].r = 5; ((void) sizeof ((_exist_size_
[_q_] < (graph->exec_info->rnum)) ? 1 : 0), __extension__
({ if (_exist_size_[_q_] < (graph->exec_info->rnum)
) ; else __assert_fail ("_exist_size_[_q_] < (graph->exec_info->rnum)"
, "ccv_nnc_graph.c", 542, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_)); } for (
_i_ = 0; _i_ < (graph->destinations->rnum); _i_++) {
((void) sizeof ((((ccv_nnc_graph_exec_t*)((void*)(((char*)((
graph->destinations)->data)) + (size_t)(graph->destinations
)->rsize * (size_t)(0))))[_i_].graph == graph) ? 1 : 0), __extension__
({ if (((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->
destinations)->data)) + (size_t)(graph->destinations)->
rsize * (size_t)(0))))[_i_].graph == graph) ; else __assert_fail
("((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->destinations)->data)) + (size_t)(graph->destinations)->rsize * (size_t)(0))))[_i_].graph == graph"
, "ccv_nnc_graph.c", 542, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[((ccv_nnc_graph_exec_t*)((void*)(((char*)((
graph->destinations)->data)) + (size_t)(graph->destinations
)->rsize * (size_t)(0))))[_i_].d].d = 1; } for (_i_ = 0; _i_
< (graph->breakpoint_size); _i_++) { ((void) sizeof ((
(graph->breakpoints)[_i_].graph == graph) ? 1 : 0), __extension__
({ if ((graph->breakpoints)[_i_].graph == graph) ; else __assert_fail
("(graph->breakpoints)[_i_].graph == graph", "ccv_nnc_graph.c"
, 542, __extension__ __PRETTY_FUNCTION__); })); _exists_[0][_i_
] = (graph->breakpoints)[_i_].d; } _p_ = 0; _q_ = 1; _exist_size_
[0] = (graph->breakpoint_size); _exist_size_[1] = 0; int _d_
= 0; while (_exist_size_[_p_] > 0) { _exist_size_[_q_] = 0
; for (_i_ = 0; _i_ < _exist_size_[_p_];) { const int32_t _idx_
= _exists_[_p_][_i_]; _visit_->node[_visit_->size].index
= ((_idx_)); _visit_->node[_visit_->size].term = ((_incomings_
[_idx_].d)); ++_visit_->size;; if (_incomings_[_idx_].d) {
++_d_; _incomings_[_idx_].r = 7; } if (((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
) { if (((ccv_nnc_graph_exec_info_t*)((void*)(((char*)((graph
->exec_info)->data)) + (size_t)(graph->exec_info)->
rsize * (size_t)(0))))[_idx_].outgoings->rnum == 1) { const
int d = *(int*)((void*)(((char*)((((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
)->data)) + (size_t)(((ccv_nnc_graph_exec_info_t*)((void*)
(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings)->rsize
* (size_t)(0))); --_incomings_[d].c; if (_incomings_[d].c ==
0 && _incomings_[d].r == 6 && _d_ < (graph
->destinations->rnum)) { _exists_[_p_][_i_] = d; continue
; } } else for (_j_ = 0; _j_ < ((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
->rnum; _j_++) { const int d = *(int*)((void*)(((char*)(((
(ccv_nnc_graph_exec_info_t*)((void*)(((char*)((graph->exec_info
)->data)) + (size_t)(graph->exec_info)->rsize * (size_t
)(0))))[_idx_].outgoings)->data)) + (size_t)(((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
)->rsize * (size_t)(_j_))); --_incomings_[d].c; if (_incomings_
[d].c == 0 && _incomings_[d].r == 6 && _d_ <
(graph->destinations->rnum)) { ((void) sizeof ((_exist_size_
[_q_] < (graph->exec_info->rnum)) ? 1 : 0), __extension__
({ if (_exist_size_[_q_] < (graph->exec_info->rnum)
) ; else __assert_fail ("_exist_size_[_q_] < (graph->exec_info->rnum)"
, "ccv_nnc_graph.c", 542, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } } ++_i_; } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_
)); } for (_i_ = 0; _i_ < (graph->destinations->rnum
); _i_++) { ((void) sizeof ((((ccv_nnc_graph_exec_t*)((void*)
(((char*)((graph->destinations)->data)) + (size_t)(graph
->destinations)->rsize * (size_t)(0))))[_i_].graph == graph
) ? 1 : 0), __extension__ ({ if (((ccv_nnc_graph_exec_t*)((void
*)(((char*)((graph->destinations)->data)) + (size_t)(graph
->destinations)->rsize * (size_t)(0))))[_i_].graph == graph
) ; else __assert_fail ("((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->destinations)->data)) + (size_t)(graph->destinations)->rsize * (size_t)(0))))[_i_].graph == graph"
, "ccv_nnc_graph.c", 542, __extension__ __PRETTY_FUNCTION__);
})); if (_incomings_[((ccv_nnc_graph_exec_t*)((void*)(((char
*)((graph->destinations)->data)) + (size_t)(graph->destinations
)->rsize * (size_t)(0))))[_i_].d].r == 7) continue; if (!(
0)) { ((void) sizeof ((_incomings_[((ccv_nnc_graph_exec_t*)((
void*)(((char*)((graph->destinations)->data)) + (size_t
)(graph->destinations)->rsize * (size_t)(0))))[_i_].d].
c == 0) ? 1 : 0), __extension__ ({ if (_incomings_[((ccv_nnc_graph_exec_t
*)((void*)(((char*)((graph->destinations)->data)) + (size_t
)(graph->destinations)->rsize * (size_t)(0))))[_i_].d].
c == 0) ; else __assert_fail ("_incomings_[((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->destinations)->data)) + (size_t)(graph->destinations)->rsize * (size_t)(0))))[_i_].d].c == 0"
, "ccv_nnc_graph.c", 542, __extension__ __PRETTY_FUNCTION__);
})); } else if (_incomings_[((ccv_nnc_graph_exec_t*)((void*)
(((char*)((graph->destinations)->data)) + (size_t)(graph
->destinations)->rsize * (size_t)(0))))[_i_].d].c > 0
) continue; _visit_->node[_visit_->size].index = ((((ccv_nnc_graph_exec_t
*)((void*)(((char*)((graph->destinations)->data)) + (size_t
)(graph->destinations)->rsize * (size_t)(0))))[_i_].d))
; _visit_->node[_visit_->size].term = ((_incomings_[((ccv_nnc_graph_exec_t
*)((void*)(((char*)((graph->destinations)->data)) + (size_t
)(graph->destinations)->rsize * (size_t)(0))))[_i_].d].
d)); ++_visit_->size;; } if (_heap_mem_) free(_incomings_)
; } while (0);; ((void) sizeof ((_visit_->size <= (graph
->exec_info->rnum)) ? 1 : 0), __extension__ ({ if (_visit_
->size <= (graph->exec_info->rnum)) ; else __assert_fail
("_visit_->size <= (graph->exec_info->rnum)", "ccv_nnc_graph.c"
, 542, __extension__ __PRETTY_FUNCTION__); })); _visit_; });
543 ccv_nnc_graph_visit_for(visit, (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, 0), node, idx){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int _node_unused_ __attribute__((unused)) = (visit)->
node[_i_].term; typeof (((ccv_nnc_graph_exec_info_t*)((void*)
(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))) const node __attribute__
((unused)) = ((ccv_nnc_graph_exec_info_t*)((void*)(((char*)((
graph->exec_info)->data)) + (size_t)(graph->exec_info
)->rsize * (size_t)(0)))) + idx; {
544 assert(!node->pair_ref)((void) sizeof ((!node->pair_ref) ? 1 : 0), __extension__ (
{ if (!node->pair_ref) ; else __assert_fail ("!node->pair_ref"
, "ccv_nnc_graph.c", 544, __extension__ __PRETTY_FUNCTION__);
})); // If node has a pair ref, we cannot fix it up.
545 // Loop over node and push to the array.
546 ccv_array_push(exec_info, node);
547 // Go to its sub-graph to fix exec_idx
548 for (i = 0; i < node->graph_ref_size; i++)
549 {
550 const int graph_ref = CCV_NNC_GRAPH_REF(node)((node)->_heap_graph_ref ? (node)->_heap_graph_ref : (node
)->_inline_graph_ref)[i] - 1;
551 if (graph_ref >= 0)
552 {
553 ccv_nnc_graph_t* const sub_graph = *(ccv_nnc_graph_t**)ccv_array_get(graph->sub_graphs, graph_ref)((void*)(((char*)((graph->sub_graphs)->data)) + (size_t
)(graph->sub_graphs)->rsize * (size_t)(graph_ref)));
554 sub_graph->exec_idx = exec_info->rnum;
555 }
556 }
557 exec_cvt[idx] = exec_info->rnum - 1;
558 } ccv_nnc_graph_visit_endfor} }
559 ccv_nnc_graph_visit_free(visit);
560 for (i = 0; i < graph->breakpoint_size; i++)
561 { assert(exec_cvt[graph->breakpoints[i].d] >= 0)((void) sizeof ((exec_cvt[graph->breakpoints[i].d] >= 0
) ? 1 : 0), __extension__ ({ if (exec_cvt[graph->breakpoints
[i].d] >= 0) ; else __assert_fail ("exec_cvt[graph->breakpoints[i].d] >= 0"
, "ccv_nnc_graph.c", 561, __extension__ __PRETTY_FUNCTION__);
})); } // All breakpoints should be assigned.
562 } else {
563 ccv_nnc_graph_visit_t* visit = ccv_nnc_graph_visit_new(graph, (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, 0), graph->exec_info->rnum, (ccv_nnc_graph_exec_t*)ccv_array_get(graph->sources, 0), graph->sources->rnum, (ccv_nnc_graph_exec_t*)ccv_array_get(graph->destinations, 0), graph->destinations->rnum, 0)({ ccv_nnc_graph_visit_t* _visit_ = (ccv_nnc_graph_visit_t*)malloc
(sizeof(ccv_nnc_graph_visit_t) + sizeof(_visit_->node[0]) *
((graph->exec_info->rnum) - 1)); _visit_->size = 0;
do { typedef struct { int8_t d; int8_t r; uint16_t c; int32_t
edges; } ccv_nnc_incoming_t; int _i_, _j_; int _incoming_edges_
= 0; for (_i_ = 0; _i_ < (graph->exec_info->rnum); _i_
++) _incoming_edges_ += (((ccv_nnc_graph_exec_info_t*)((void*
)(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_i_].outgoings) ? ((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_i_].outgoings
->rnum : 0; const int _heap_mem_ = ((graph->exec_info->
rnum) + _incoming_edges_ > 1024); ccv_nnc_incoming_t* _incomings_
; if (_heap_mem_) _incomings_ = (ccv_nnc_incoming_t*)malloc(sizeof
(ccv_nnc_incoming_t) * (graph->exec_info->rnum) + sizeof
(int32_t) * ((graph->exec_info->rnum) * 2 + _incoming_edges_
)); else _incomings_ = (ccv_nnc_incoming_t*)__builtin_alloca (
sizeof(ccv_nnc_incoming_t) * (graph->exec_info->rnum) +
sizeof(int32_t) * ((graph->exec_info->rnum) * 2 + _incoming_edges_
)); memset(_incomings_, 0, sizeof(ccv_nnc_incoming_t) * (graph
->exec_info->rnum)); int32_t* _exists_[2] = { (int32_t*
)(_incomings_ + (graph->exec_info->rnum)), (int32_t*)(_incomings_
+ (graph->exec_info->rnum)) + (graph->exec_info->
rnum), }; int32_t* const _edges_ = _exists_[1] + (graph->exec_info
->rnum); for (_i_ = 0; _i_ < (graph->sources->rnum
); _i_++) { ((void) sizeof ((((ccv_nnc_graph_exec_t*)((void*)
(((char*)((graph->sources)->data)) + (size_t)(graph->
sources)->rsize * (size_t)(0))))[_i_].graph == graph) ? 1 :
0), __extension__ ({ if (((ccv_nnc_graph_exec_t*)((void*)(((
char*)((graph->sources)->data)) + (size_t)(graph->sources
)->rsize * (size_t)(0))))[_i_].graph == graph) ; else __assert_fail
("((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->sources)->data)) + (size_t)(graph->sources)->rsize * (size_t)(0))))[_i_].graph == graph"
, "ccv_nnc_graph.c", 563, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[((ccv_nnc_graph_exec_t*)((void*)(((char*)((
graph->sources)->data)) + (size_t)(graph->sources)->
rsize * (size_t)(0))))[_i_].d].r = 1; _exists_[0][_i_] = ((ccv_nnc_graph_exec_t
*)((void*)(((char*)((graph->sources)->data)) + (size_t)
(graph->sources)->rsize * (size_t)(0))))[_i_].d; } int _exist_size_
[2] = { (graph->sources->rnum), 0, }; int _p_ = 0, _q_ =
1; while (_exist_size_[_p_] > 0) { _exist_size_[_q_] = 0;
for (_i_ = 0; _i_ < _exist_size_[_p_]; _i_++) { const int32_t
_idx_ = _exists_[_p_][_i_]; if (_incomings_[_idx_].r != 1) continue
; _incomings_[_idx_].r = 2; if (((ccv_nnc_graph_exec_info_t*)
((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
) for (_j_ = 0; _j_ < ((ccv_nnc_graph_exec_info_t*)((void*
)(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings->rnum
; _j_++) { const int d = *(int*)((void*)(((char*)((((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
)->data)) + (size_t)(((ccv_nnc_graph_exec_info_t*)((void*)
(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings)->rsize
* (size_t)(_j_))); ++_incomings_[d].c; if (_incomings_[d].r !=
0) continue; _incomings_[d].r = 1; ((void) sizeof ((_exist_size_
[_q_] < (graph->exec_info->rnum)) ? 1 : 0), __extension__
({ if (_exist_size_[_q_] < (graph->exec_info->rnum)
) ; else __assert_fail ("_exist_size_[_q_] < (graph->exec_info->rnum)"
, "ccv_nnc_graph.c", 563, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_)); } for (
_i_ = 0; _i_ < (graph->sources->rnum); _i_++) { ((void
) sizeof ((((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->
sources)->data)) + (size_t)(graph->sources)->rsize *
(size_t)(0))))[_i_].graph == graph) ? 1 : 0), __extension__ (
{ if (((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->sources
)->data)) + (size_t)(graph->sources)->rsize * (size_t
)(0))))[_i_].graph == graph) ; else __assert_fail ("((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->sources)->data)) + (size_t)(graph->sources)->rsize * (size_t)(0))))[_i_].graph == graph"
, "ccv_nnc_graph.c", 563, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[((ccv_nnc_graph_exec_t*)((void*)(((char*)((
graph->sources)->data)) + (size_t)(graph->sources)->
rsize * (size_t)(0))))[_i_].d].r = 3; _exists_[0][_i_] = ((ccv_nnc_graph_exec_t
*)((void*)(((char*)((graph->sources)->data)) + (size_t)
(graph->sources)->rsize * (size_t)(0))))[_i_].d; } _exist_size_
[0] = (graph->sources->rnum); _exist_size_[1] = 0; _p_ =
0, _q_ = 1; int _bump_ = 1; while (_exist_size_[_p_] > 0)
{ _exist_size_[_q_] = 0; for (_i_ = 0; _i_ < _exist_size_
[_p_]; _i_++) { const int32_t _idx_ = _exists_[_p_][_i_]; if (
_incomings_[_idx_].r != 3) continue; _incomings_[_idx_].r = 4
; if (((ccv_nnc_graph_exec_info_t*)((void*)(((char*)((graph->
exec_info)->data)) + (size_t)(graph->exec_info)->rsize
* (size_t)(0))))[_idx_].outgoings) for (_j_ = 0; _j_ < ((
ccv_nnc_graph_exec_info_t*)((void*)(((char*)((graph->exec_info
)->data)) + (size_t)(graph->exec_info)->rsize * (size_t
)(0))))[_idx_].outgoings->rnum; _j_++) { const int d = *(int
*)((void*)(((char*)((((ccv_nnc_graph_exec_info_t*)((void*)(((
char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings)->data
)) + (size_t)(((ccv_nnc_graph_exec_info_t*)((void*)(((char*)(
(graph->exec_info)->data)) + (size_t)(graph->exec_info
)->rsize * (size_t)(0))))[_idx_].outgoings)->rsize * (size_t
)(_j_))); if (_incomings_[d].edges == 0) { _incomings_[d].edges
= _bump_; _bump_ += _incomings_[d].c; _incomings_[d].c = 0; }
_edges_[_incomings_[d].edges - 1 + _incomings_[d].c] = _idx_
; ++_incomings_[d].c; if (_incomings_[d].r != 2) continue; _incomings_
[d].r = 3; ((void) sizeof ((_exist_size_[_q_] < (graph->
exec_info->rnum)) ? 1 : 0), __extension__ ({ if (_exist_size_
[_q_] < (graph->exec_info->rnum)) ; else __assert_fail
("_exist_size_[_q_] < (graph->exec_info->rnum)", "ccv_nnc_graph.c"
, 563, __extension__ __PRETTY_FUNCTION__); })); _exists_[_q_]
[_exist_size_[_q_]] = d; ++_exist_size_[_q_]; } } ((_i_) = (_p_
), (_p_) = (_q_), (_q_) = (_i_)); } for (_i_ = 0; _i_ < (graph
->destinations->rnum); _i_++) { ((void) sizeof ((((ccv_nnc_graph_exec_t
*)((void*)(((char*)((graph->destinations)->data)) + (size_t
)(graph->destinations)->rsize * (size_t)(0))))[_i_].graph
== graph) ? 1 : 0), __extension__ ({ if (((ccv_nnc_graph_exec_t
*)((void*)(((char*)((graph->destinations)->data)) + (size_t
)(graph->destinations)->rsize * (size_t)(0))))[_i_].graph
== graph) ; else __assert_fail ("((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->destinations)->data)) + (size_t)(graph->destinations)->rsize * (size_t)(0))))[_i_].graph == graph"
, "ccv_nnc_graph.c", 563, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[((ccv_nnc_graph_exec_t*)((void*)(((char*)((
graph->destinations)->data)) + (size_t)(graph->destinations
)->rsize * (size_t)(0))))[_i_].d].r = 5; _exists_[0][_i_] =
((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->destinations
)->data)) + (size_t)(graph->destinations)->rsize * (
size_t)(0))))[_i_].d; } _exist_size_[0] = (graph->destinations
->rnum); _exist_size_[1] = 0; _p_ = 0, _q_ = 1; while (_exist_size_
[_p_] > 0) { _exist_size_[_q_] = 0; for (_i_ = 0; _i_ <
_exist_size_[_p_]; _i_++) { const int32_t _idx_ = _exists_[_p_
][_i_]; if (_incomings_[_idx_].r != 5) continue; _incomings_[
_idx_].r = 6; if (_incomings_[_idx_].edges > 0) for (_j_ =
0; _j_ < _incomings_[_idx_].c; _j_++) { const int d = _edges_
[_incomings_[_idx_].edges - 1 + _j_]; if (_incomings_[d].r !=
4) continue; _incomings_[d].r = 5; ((void) sizeof ((_exist_size_
[_q_] < (graph->exec_info->rnum)) ? 1 : 0), __extension__
({ if (_exist_size_[_q_] < (graph->exec_info->rnum)
) ; else __assert_fail ("_exist_size_[_q_] < (graph->exec_info->rnum)"
, "ccv_nnc_graph.c", 563, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_)); } for (
_i_ = 0; _i_ < (graph->destinations->rnum); _i_++) {
((void) sizeof ((((ccv_nnc_graph_exec_t*)((void*)(((char*)((
graph->destinations)->data)) + (size_t)(graph->destinations
)->rsize * (size_t)(0))))[_i_].graph == graph) ? 1 : 0), __extension__
({ if (((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->
destinations)->data)) + (size_t)(graph->destinations)->
rsize * (size_t)(0))))[_i_].graph == graph) ; else __assert_fail
("((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->destinations)->data)) + (size_t)(graph->destinations)->rsize * (size_t)(0))))[_i_].graph == graph"
, "ccv_nnc_graph.c", 563, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[((ccv_nnc_graph_exec_t*)((void*)(((char*)((
graph->destinations)->data)) + (size_t)(graph->destinations
)->rsize * (size_t)(0))))[_i_].d].d = 1; } for (_i_ = 0; _i_
< (graph->sources->rnum); _i_++) { ((void) sizeof (
(((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->sources
)->data)) + (size_t)(graph->sources)->rsize * (size_t
)(0))))[_i_].graph == graph) ? 1 : 0), __extension__ ({ if ((
(ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->sources)->
data)) + (size_t)(graph->sources)->rsize * (size_t)(0))
))[_i_].graph == graph) ; else __assert_fail ("((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->sources)->data)) + (size_t)(graph->sources)->rsize * (size_t)(0))))[_i_].graph == graph"
, "ccv_nnc_graph.c", 563, __extension__ __PRETTY_FUNCTION__);
})); _exists_[0][_i_] = ((ccv_nnc_graph_exec_t*)((void*)(((char
*)((graph->sources)->data)) + (size_t)(graph->sources
)->rsize * (size_t)(0))))[_i_].d; } _p_ = 0; _q_ = 1; _exist_size_
[0] = (graph->sources->rnum); _exist_size_[1] = 0; int _d_
= 0; while (_exist_size_[_p_] > 0) { _exist_size_[_q_] = 0
; for (_i_ = 0; _i_ < _exist_size_[_p_];) { const int32_t _idx_
= _exists_[_p_][_i_]; _visit_->node[_visit_->size].index
= ((_idx_)); _visit_->node[_visit_->size].term = ((_incomings_
[_idx_].d)); ++_visit_->size;; if (_incomings_[_idx_].d) {
++_d_; _incomings_[_idx_].r = 7; } if (((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
) { if (((ccv_nnc_graph_exec_info_t*)((void*)(((char*)((graph
->exec_info)->data)) + (size_t)(graph->exec_info)->
rsize * (size_t)(0))))[_idx_].outgoings->rnum == 1) { const
int d = *(int*)((void*)(((char*)((((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
)->data)) + (size_t)(((ccv_nnc_graph_exec_info_t*)((void*)
(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings)->rsize
* (size_t)(0))); --_incomings_[d].c; if (_incomings_[d].c ==
0 && _incomings_[d].r == 6 && _d_ < (graph
->destinations->rnum)) { _exists_[_p_][_i_] = d; continue
; } } else for (_j_ = 0; _j_ < ((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
->rnum; _j_++) { const int d = *(int*)((void*)(((char*)(((
(ccv_nnc_graph_exec_info_t*)((void*)(((char*)((graph->exec_info
)->data)) + (size_t)(graph->exec_info)->rsize * (size_t
)(0))))[_idx_].outgoings)->data)) + (size_t)(((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
)->rsize * (size_t)(_j_))); --_incomings_[d].c; if (_incomings_
[d].c == 0 && _incomings_[d].r == 6 && _d_ <
(graph->destinations->rnum)) { ((void) sizeof ((_exist_size_
[_q_] < (graph->exec_info->rnum)) ? 1 : 0), __extension__
({ if (_exist_size_[_q_] < (graph->exec_info->rnum)
) ; else __assert_fail ("_exist_size_[_q_] < (graph->exec_info->rnum)"
, "ccv_nnc_graph.c", 563, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } } ++_i_; } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_
)); } for (_i_ = 0; _i_ < (graph->destinations->rnum
); _i_++) { ((void) sizeof ((((ccv_nnc_graph_exec_t*)((void*)
(((char*)((graph->destinations)->data)) + (size_t)(graph
->destinations)->rsize * (size_t)(0))))[_i_].graph == graph
) ? 1 : 0), __extension__ ({ if (((ccv_nnc_graph_exec_t*)((void
*)(((char*)((graph->destinations)->data)) + (size_t)(graph
->destinations)->rsize * (size_t)(0))))[_i_].graph == graph
) ; else __assert_fail ("((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->destinations)->data)) + (size_t)(graph->destinations)->rsize * (size_t)(0))))[_i_].graph == graph"
, "ccv_nnc_graph.c", 563, __extension__ __PRETTY_FUNCTION__);
})); if (_incomings_[((ccv_nnc_graph_exec_t*)((void*)(((char
*)((graph->destinations)->data)) + (size_t)(graph->destinations
)->rsize * (size_t)(0))))[_i_].d].r == 7) continue; if (!(
0)) { ((void) sizeof ((_incomings_[((ccv_nnc_graph_exec_t*)((
void*)(((char*)((graph->destinations)->data)) + (size_t
)(graph->destinations)->rsize * (size_t)(0))))[_i_].d].
c == 0) ? 1 : 0), __extension__ ({ if (_incomings_[((ccv_nnc_graph_exec_t
*)((void*)(((char*)((graph->destinations)->data)) + (size_t
)(graph->destinations)->rsize * (size_t)(0))))[_i_].d].
c == 0) ; else __assert_fail ("_incomings_[((ccv_nnc_graph_exec_t*)((void*)(((char*)((graph->destinations)->data)) + (size_t)(graph->destinations)->rsize * (size_t)(0))))[_i_].d].c == 0"
, "ccv_nnc_graph.c", 563, __extension__ __PRETTY_FUNCTION__);
})); } else if (_incomings_[((ccv_nnc_graph_exec_t*)((void*)
(((char*)((graph->destinations)->data)) + (size_t)(graph
->destinations)->rsize * (size_t)(0))))[_i_].d].c > 0
) continue; _visit_->node[_visit_->size].index = ((((ccv_nnc_graph_exec_t
*)((void*)(((char*)((graph->destinations)->data)) + (size_t
)(graph->destinations)->rsize * (size_t)(0))))[_i_].d))
; _visit_->node[_visit_->size].term = ((_incomings_[((ccv_nnc_graph_exec_t
*)((void*)(((char*)((graph->destinations)->data)) + (size_t
)(graph->destinations)->rsize * (size_t)(0))))[_i_].d].
d)); ++_visit_->size;; } if (_heap_mem_) free(_incomings_)
; } while (0);; ((void) sizeof ((_visit_->size <= (graph
->exec_info->rnum)) ? 1 : 0), __extension__ ({ if (_visit_
->size <= (graph->exec_info->rnum)) ; else __assert_fail
("_visit_->size <= (graph->exec_info->rnum)", "ccv_nnc_graph.c"
, 563, __extension__ __PRETTY_FUNCTION__); })); _visit_; });
564 ccv_nnc_graph_visit_for(visit, (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, 0), node, idx){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int _node_unused_ __attribute__((unused)) = (visit)->
node[_i_].term; typeof (((ccv_nnc_graph_exec_info_t*)((void*)
(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))) const node __attribute__
((unused)) = ((ccv_nnc_graph_exec_info_t*)((void*)(((char*)((
graph->exec_info)->data)) + (size_t)(graph->exec_info
)->rsize * (size_t)(0)))) + idx; {
565 assert(!node->pair_ref)((void) sizeof ((!node->pair_ref) ? 1 : 0), __extension__ (
{ if (!node->pair_ref) ; else __assert_fail ("!node->pair_ref"
, "ccv_nnc_graph.c", 565, __extension__ __PRETTY_FUNCTION__);
})); // If node has a pair ref, we cannot fix it up.
566 // Loop over node and push to the array.
567 ccv_array_push(exec_info, node);
568 // Go to its sub-graph to fix exec_idx
569 for (i = 0; i < node->graph_ref_size; i++)
570 {
571 const int graph_ref = CCV_NNC_GRAPH_REF(node)((node)->_heap_graph_ref ? (node)->_heap_graph_ref : (node
)->_inline_graph_ref)[i] - 1;
572 if (graph_ref >= 0)
573 {
574 ccv_nnc_graph_t* const sub_graph = *(ccv_nnc_graph_t**)ccv_array_get(graph->sub_graphs, graph_ref)((void*)(((char*)((graph->sub_graphs)->data)) + (size_t
)(graph->sub_graphs)->rsize * (size_t)(graph_ref)));
575 sub_graph->exec_idx = exec_info->rnum;
576 }
577 }
578 exec_cvt[idx] = exec_info->rnum - 1;
579 } ccv_nnc_graph_visit_endfor} }
580 ccv_nnc_graph_visit_free(visit);
581 }
582 assert(graph->exec_info->rnum == exec_info->rnum)((void) sizeof ((graph->exec_info->rnum == exec_info->
rnum) ? 1 : 0), __extension__ ({ if (graph->exec_info->
rnum == exec_info->rnum) ; else __assert_fail ("graph->exec_info->rnum == exec_info->rnum"
, "ccv_nnc_graph.c", 582, __extension__ __PRETTY_FUNCTION__);
}));
583 ccv_array_free(graph->exec_info);
584 graph->exec_info = exec_info;
585 for (i = 0; i < graph->sources->rnum; i++)
586 {
587 ccv_nnc_graph_exec_t* const source = (ccv_nnc_graph_exec_t*)ccv_array_get(graph->sources, i)((void*)(((char*)((graph->sources)->data)) + (size_t)(graph
->sources)->rsize * (size_t)(i)));
588 source->d = exec_cvt[source->d];
589 }
590 for (i = 0; i < graph->destinations->rnum; i++)
591 {
592 ccv_nnc_graph_exec_t* const destination = (ccv_nnc_graph_exec_t*)ccv_array_get(graph->destinations, i)((void*)(((char*)((graph->destinations)->data)) + (size_t
)(graph->destinations)->rsize * (size_t)(i)));
593 destination->d = exec_cvt[destination->d];
594 }
595 // Update all outgoings to reflect the latest.
596 for (i = 0; i < exec_info->rnum; i++)
597 {
598 ccv_nnc_graph_exec_info_t* const info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(exec_info, i)((void*)(((char*)((exec_info)->data)) + (size_t)(exec_info
)->rsize * (size_t)(i)));
599 if (info->outgoings)
600 for (j = 0; j < info->outgoings->rnum; j++)
601 *(int*)ccv_array_get(info->outgoings, j)((void*)(((char*)((info->outgoings)->data)) + (size_t)(
info->outgoings)->rsize * (size_t)(j))) = exec_cvt[*(int*)ccv_array_get(info->outgoings, j)((void*)(((char*)((info->outgoings)->data)) + (size_t)(
info->outgoings)->rsize * (size_t)(j)))];
602 }
603 graph->topsorted = 1;
604}
605
606typedef struct {
607 int device_id;
608 int exec_idx;
609 ccv_array_t* signal_set;
610 ccv_array_t* command_set; // The set of command executed in this stream. In case there is a tie (on rank). We will check this.
611} ccv_nnc_stream_data_t;
612
613static void _ccv_nnc_graph_schedule_assign_signals(ccv_array_t* const incoming, ccv_nnc_graph_exec_schedule_t* const node, ccv_array_t* const stream_data, int* const signal_size, ccv_nnc_graph_exec_schedule_t* const exec_info, const int exec_info_size)
614{
615 assert(incoming->rnum > 0)((void) sizeof ((incoming->rnum > 0) ? 1 : 0), __extension__
({ if (incoming->rnum > 0) ; else __assert_fail ("incoming->rnum > 0"
, "ccv_nnc_graph.c", 615, __extension__ __PRETTY_FUNCTION__);
}));
616 int i, j, k;
617 int wait_size = 0, max_wait_size = 0;
618 for (i = 0; i < incoming->rnum; i++)
619 {
620 const int incoming_idx = *(int*)ccv_array_get(incoming, i)((void*)(((char*)((incoming)->data)) + (size_t)(incoming)->
rsize * (size_t)(i)));
621 ccv_nnc_graph_exec_schedule_t* const incoming_exec_info = exec_info + incoming_idx;
622 assert(incoming_exec_info->stream_size > 0)((void) sizeof ((incoming_exec_info->stream_size > 0) ?
1 : 0), __extension__ ({ if (incoming_exec_info->stream_size
> 0) ; else __assert_fail ("incoming_exec_info->stream_size > 0"
, "ccv_nnc_graph.c", 622, __extension__ __PRETTY_FUNCTION__);
}));
623 max_wait_size += incoming_exec_info->stream_size;
624 }
625 int waits[ccv_max(1, max_wait_size)({ typeof (1) _a = (1); typeof (max_wait_size) _b = (max_wait_size
); (_a > _b) ? _a : _b; })];
626 assert(node->stream_size > 0)((void) sizeof ((node->stream_size > 0) ? 1 : 0), __extension__
({ if (node->stream_size > 0) ; else __assert_fail ("node->stream_size > 0"
, "ccv_nnc_graph.c", 626, __extension__ __PRETTY_FUNCTION__);
}));
627 for (i = 0; i < incoming->rnum; i++)
628 {
629 const int incoming_idx = *(int*)ccv_array_get(incoming, i)((void*)(((char*)((incoming)->data)) + (size_t)(incoming)->
rsize * (size_t)(i)));
630 assert(incoming_idx < exec_info_size)((void) sizeof ((incoming_idx < exec_info_size) ? 1 : 0), __extension__
({ if (incoming_idx < exec_info_size) ; else __assert_fail
("incoming_idx < exec_info_size", "ccv_nnc_graph.c", 630,
__extension__ __PRETTY_FUNCTION__); }));
631 assert(incoming_idx >= 0)((void) sizeof ((incoming_idx >= 0) ? 1 : 0), __extension__
({ if (incoming_idx >= 0) ; else __assert_fail ("incoming_idx >= 0"
, "ccv_nnc_graph.c", 631, __extension__ __PRETTY_FUNCTION__);
}));
632 ccv_nnc_graph_exec_schedule_t* const incoming_exec_info = exec_info + incoming_idx;
633 assert(incoming_exec_info->stream_size > 0)((void) sizeof ((incoming_exec_info->stream_size > 0) ?
1 : 0), __extension__ ({ if (incoming_exec_info->stream_size
> 0) ; else __assert_fail ("incoming_exec_info->stream_size > 0"
, "ccv_nnc_graph.c", 633, __extension__ __PRETTY_FUNCTION__);
}));
634 int stream_synced = 1;
635 // If the current node's stream is a subset of the incoming node's stream, there
636 // is no need to sync with signal, because we are already synced with the incoming.
637 for (j = 0; stream_synced && j < node->stream_size; j++)
638 {
639 const int s = SCHEDULE_STREAMS(*node)((*node).stream_size <= 1 ? (*node)._inline_streams : (*node
)._heap_streams)[j];
640 assert(s >= 0)((void) sizeof ((s >= 0) ? 1 : 0), __extension__ ({ if (s >=
0) ; else __assert_fail ("s >= 0", "ccv_nnc_graph.c", 640
, __extension__ __PRETTY_FUNCTION__); }));
641 int flag = 0;
642 for (k = 0; !flag && k < incoming_exec_info->stream_size; k++)
643 flag = (SCHEDULE_STREAMS(*incoming_exec_info)((*incoming_exec_info).stream_size <= 1 ? (*incoming_exec_info
)._inline_streams : (*incoming_exec_info)._heap_streams)[k] == s);
644 stream_synced = flag;
645 }
646 if (stream_synced)
647 continue;
648 // Otherwise, find the streams we need to sync with, and create signals for these.
649 for (j = 0; j < incoming_exec_info->stream_size; j++)
650 {
651 const int s = SCHEDULE_STREAMS(*incoming_exec_info)((*incoming_exec_info).stream_size <= 1 ? (*incoming_exec_info
)._inline_streams : (*incoming_exec_info)._heap_streams)[j];
652 assert(s >= 0)((void) sizeof ((s >= 0) ? 1 : 0), __extension__ ({ if (s >=
0) ; else __assert_fail ("s >= 0", "ccv_nnc_graph.c", 652
, __extension__ __PRETTY_FUNCTION__); }));
653 int flag = 0;
654 for (k = 0; !flag && k < node->stream_size; k++)
655 flag = (SCHEDULE_STREAMS(*node)((*node).stream_size <= 1 ? (*node)._inline_streams : (*node
)._heap_streams)[k] == s);
656 if (!flag) // Need to have a signal.
657 {
658 if (SCHEDULE_SIGNALS(*incoming_exec_info)((*incoming_exec_info).stream_size <= 1 ? (*incoming_exec_info
)._inline_signals : (*incoming_exec_info)._heap_signals)[j] < 0)
659 SCHEDULE_SIGNALS(*incoming_exec_info)((*incoming_exec_info).stream_size <= 1 ? (*incoming_exec_info
)._inline_signals : (*incoming_exec_info)._heap_signals)[j] = (*signal_size)++;
660 else {
661 int flag = 0;
662 // If any of the stream the current node has already seen this signal, we are good already.
663 for (k = 0; !flag && k < node->stream_size; k++)
664 {
665 assert(SCHEDULE_STREAMS(*node)[k] >= 0)((void) sizeof ((((*node).stream_size <= 1 ? (*node)._inline_streams
: (*node)._heap_streams)[k] >= 0) ? 1 : 0), __extension__
({ if (((*node).stream_size <= 1 ? (*node)._inline_streams
: (*node)._heap_streams)[k] >= 0) ; else __assert_fail ("SCHEDULE_STREAMS(*node)[k] >= 0"
, "ccv_nnc_graph.c", 665, __extension__ __PRETTY_FUNCTION__);
}));
666 ccv_nnc_stream_data_t* const data = (ccv_nnc_stream_data_t*)ccv_array_get(stream_data, SCHEDULE_STREAMS(*node)[k])((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(((*node).stream_size <= 1 ? (*node)
._inline_streams : (*node)._heap_streams)[k])));
667 flag = (data->signal_set && ccv_array_find_int(data->signal_set, SCHEDULE_SIGNALS(*incoming_exec_info)((*incoming_exec_info).stream_size <= 1 ? (*incoming_exec_info
)._inline_signals : (*incoming_exec_info)._heap_signals)[j]));
668 }
669 if (flag)
670 continue;
671 }
672 // Otherwise, we need to wait for this. Currently, our granularity is about wait on all streams.
673 waits[wait_size++] = SCHEDULE_SIGNALS(*incoming_exec_info)((*incoming_exec_info).stream_size <= 1 ? (*incoming_exec_info
)._inline_signals : (*incoming_exec_info)._heap_signals)[j];
674 // All streams on this node have seen this signal.
675 for (k = 0; k < node->stream_size; k++)
676 {
677 ccv_nnc_stream_data_t* const data = (ccv_nnc_stream_data_t*)ccv_array_get(stream_data, SCHEDULE_STREAMS(*node)[k])((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(((*node).stream_size <= 1 ? (*node)
._inline_streams : (*node)._heap_streams)[k])));
678 if (!data->signal_set)
679 data->signal_set = ccv_array_new(sizeof(int), 0, 0);
680 ccv_array_push(data->signal_set, &SCHEDULE_SIGNALS(*incoming_exec_info)((*incoming_exec_info).stream_size <= 1 ? (*incoming_exec_info
)._inline_signals : (*incoming_exec_info)._heap_signals)[j]);
681 }
682 }
683 }
684 }
685 node->wait_size = wait_size;
686 if (wait_size > 0)
687 {
688 node->waits = node->waits ? ccreallocrealloc(node->waits, sizeof(int) * wait_size) : ccmallocmalloc(sizeof(int) * wait_size);
689 memcpy(node->waits, waits, sizeof(int) * wait_size);
690 }
691}
692
693typedef struct {
694 int rank;
695 ccv_array_t* outgoings;
696} ccv_nnc_incoming_t;
697
698static int _ccv_nnc_device_ids_for_stream_data(ccv_nnc_graph_exec_info_t* const node, const int device_id, ccv_array_t* const stream_data, int* const device_ids, const int max_device_id_size)
699{
700 // TODO: I need to re-think whether this is GPU only or not.
701 int device_id_size = ccv_nnc_device_ids_for_io(node->inputs, node->input_size, node->outputs, node->output_size, CCV_TENSOR_GPU_MEMORY, device_ids, max_device_id_size);
702 if (device_id_size == 0)
703 {
704 // If there is a default data, use that device id. Otherwise, use the device id passed in (this will be the default data device id).
705 if (stream_data->rnum > 0)
706 {
707 ccv_nnc_stream_data_t* const default_data = (ccv_nnc_stream_data_t*)ccv_array_get(stream_data, 0)((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(0)));
708 device_ids[0] = default_data->device_id;
709 } else
710 device_ids[0] = device_id >= 0 ? device_id : 0;
711 device_id_size = 1;
712 }
713 return device_id_size;
714}
715
716void ccv_nnc_graph_static_schedule_free(ccv_nnc_graph_static_schedule_t* const schedule)
717{
718 int i;
719 ccv_nnc_graph_exec_schedule_t* const schd_info = schedule->exec_info;
720 for (i = 0; i < schedule->exec_info_size; i++)
721 {
722 if (schd_info[i].stream_size > 1)
723 ccfreefree(schd_info[i]._heap_streams);
724 if (schd_info[i].waits)
725 ccfreefree(schd_info[i].waits);
726 }
727 if (schedule->stream_1s)
728 ccfreefree(schedule->stream_1s);
729 if (schedule->waits)
730 ccfreefree(schedule->waits);
731 if (schedule->psort)
732 ccfreefree(schedule->psort);
733 if (schedule->begin)
734 ccv_nnc_stream_signal_free(schedule->begin);
735 if (schedule->end)
736 ccv_nnc_stream_signal_free(schedule->end);
737 ccfreefree(schedule);
738}
739
740static ccv_nnc_graph_static_schedule_t* _ccv_nnc_graph_static_schedule_new(ccv_nnc_graph_t* const graph, const int stream_type, const int device_id, const int max_stream_count, ccv_nnc_stream_context_t* const stream_context, const ccv_nnc_graph_exec_t* const _sources, const int _source_size, const ccv_nnc_graph_exec_t* const _destinations, const int _destination_size)
741{
742 assert(graph->sources && graph->sources->rnum)((void) sizeof ((graph->sources && graph->sources
->rnum) ? 1 : 0), __extension__ ({ if (graph->sources &&
graph->sources->rnum) ; else __assert_fail ("graph->sources && graph->sources->rnum"
, "ccv_nnc_graph.c", 742, __extension__ __PRETTY_FUNCTION__);
}));
1
Assuming field 'sources' is non-null
→
2
←
Assuming field 'rnum' is not equal to 0
→
3
←
Taking true branch
→
743 assert(graph->destinations && graph->destinations->rnum)((void) sizeof ((graph->destinations && graph->
destinations->rnum) ? 1 : 0), __extension__ ({ if (graph->
destinations && graph->destinations->rnum) ; else
__assert_fail ("graph->destinations && graph->destinations->rnum"
, "ccv_nnc_graph.c", 743, __extension__ __PRETTY_FUNCTION__);
}));
4
←
Assuming field 'destinations' is non-null
→
5
←
Assuming field 'rnum' is not equal to 0
→
6
←
Taking true branch
→
744 assert(graph->topsorted)((void) sizeof ((graph->topsorted) ? 1 : 0), __extension__
({ if (graph->topsorted) ; else __assert_fail ("graph->topsorted"
, "ccv_nnc_graph.c", 744, __extension__ __PRETTY_FUNCTION__);
})); // Only support this on a topsorted graph.
7
←
Assuming field 'topsorted' is not equal to 0
→
8
←
Taking true branch
→
745 const int exec_info_size = graph->exec_info->rnum;
746 assert(exec_info_size > 0)((void) sizeof ((exec_info_size > 0) ? 1 : 0), __extension__
({ if (exec_info_size > 0) ; else __assert_fail ("exec_info_size > 0"
, "ccv_nnc_graph.c", 746, __extension__ __PRETTY_FUNCTION__);
}));
9
←
Assuming 'exec_info_size' is > 0
→
10
←
Taking true branch
→
747 const ccv_nnc_graph_exec_t* const sources = _sources == 0 ? (ccv_nnc_graph_exec_t*)ccv_array_get(graph->sources, 0)((void*)(((char*)((graph->sources)->data)) + (size_t)(graph
->sources)->rsize * (size_t)(0))) : _sources;
11
←
Assuming '_sources' is not equal to null
→
12
←
'?' condition is false
→
748 const int source_size = _sources
12.1
'_sources' is not equal to null
 == 0 ? graph->sources->rnum : _source_size;
13
←
'?' condition is false
→
749 if (!_sources
13.1
'_sources' is non-null
)
750 { assert(_source_size == 0)((void) sizeof ((_source_size == 0) ? 1 : 0), __extension__ (
{ if (_source_size == 0) ; else __assert_fail ("_source_size == 0"
, "ccv_nnc_graph.c", 750, __extension__ __PRETTY_FUNCTION__);
})); }
751 const ccv_nnc_graph_exec_t* const destinations = _destinations == 0 ? (ccv_nnc_graph_exec_t*)ccv_array_get(graph->destinations, 0)((void*)(((char*)((graph->destinations)->data)) + (size_t
)(graph->destinations)->rsize * (size_t)(0))) : _destinations;
14
←
Taking false branch
→
15
←
Assuming '_destinations' is not equal to null
→
16
←
'?' condition is false
→
752 const int destination_size = _destinations
16.1
'_destinations' is not equal to null
 == 0 ? graph->destinations->rnum : _destination_size;
17
←
'?' condition is false
→
753 if (!_destinations
17.1
'_destinations' is non-null
)
754 { assert(_destination_size == 0)((void) sizeof ((_destination_size == 0) ? 1 : 0), __extension__
({ if (_destination_size == 0) ; else __assert_fail ("_destination_size == 0"
, "ccv_nnc_graph.c", 754, __extension__ __PRETTY_FUNCTION__);
})); }
755 const int root_schedule = (_sources
17.2
'_sources' is not equal to null
 == 0 && _destinations == 0);
756 ccv_nnc_graph_static_schedule_t* const schedule = cccalloccalloc(1, sizeof(ccv_nnc_graph_static_schedule_t) + sizeof(ccv_nnc_graph_exec_schedule_t) * (exec_info_size - 1));
757 schedule->exec_info_size = exec_info_size;
758 ccv_nnc_graph_exec_schedule_t* const schd_info = schedule->exec_info;
759 ccv_nnc_graph_exec_info_t* const exec_info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, 0)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(0)));
760 ccv_nnc_graph_visit_t* visit = ccv_nnc_graph_visit_new(graph, exec_info, exec_info_size, sources, source_size, destinations, destination_size, 0)({ ccv_nnc_graph_visit_t* _visit_ = (ccv_nnc_graph_visit_t*)malloc
(sizeof(ccv_nnc_graph_visit_t) + sizeof(_visit_->node[0]) *
((exec_info_size) - 1)); _visit_->size = 0; do { typedef struct
{ int8_t d; int8_t r; uint16_t c; int32_t edges; } ccv_nnc_incoming_t
; int _i_, _j_; int _incoming_edges_ = 0; for (_i_ = 0; _i_ <
(exec_info_size); _i_++) _incoming_edges_ += ((exec_info)[_i_
].outgoings) ? (exec_info)[_i_].outgoings->rnum : 0; const
int _heap_mem_ = ((exec_info_size) + _incoming_edges_ > 1024
); ccv_nnc_incoming_t* _incomings_; if (_heap_mem_) _incomings_
= (ccv_nnc_incoming_t*)malloc(sizeof(ccv_nnc_incoming_t) * (
exec_info_size) + sizeof(int32_t) * ((exec_info_size) * 2 + _incoming_edges_
)); else _incomings_ = (ccv_nnc_incoming_t*)__builtin_alloca (
sizeof(ccv_nnc_incoming_t) * (exec_info_size) + sizeof(int32_t
) * ((exec_info_size) * 2 + _incoming_edges_)); memset(_incomings_
, 0, sizeof(ccv_nnc_incoming_t) * (exec_info_size)); int32_t*
_exists_[2] = { (int32_t*)(_incomings_ + (exec_info_size)), (
int32_t*)(_incomings_ + (exec_info_size)) + (exec_info_size),
}; int32_t* const _edges_ = _exists_[1] + (exec_info_size); for
(_i_ = 0; _i_ < (source_size); _i_++) { ((void) sizeof ((
(sources)[_i_].graph == graph) ? 1 : 0), __extension__ ({ if (
(sources)[_i_].graph == graph) ; else __assert_fail ("(sources)[_i_].graph == graph"
, "ccv_nnc_graph.c", 760, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[(sources)[_i_].d].r = 1; _exists_[0][_i_] =
(sources)[_i_].d; } int _exist_size_[2] = { (source_size), 0
, }; int _p_ = 0, _q_ = 1; while (_exist_size_[_p_] > 0) {
_exist_size_[_q_] = 0; for (_i_ = 0; _i_ < _exist_size_[_p_
]; _i_++) { const int32_t _idx_ = _exists_[_p_][_i_]; if (_incomings_
[_idx_].r != 1) continue; _incomings_[_idx_].r = 2; if ((exec_info
)[_idx_].outgoings) for (_j_ = 0; _j_ < (exec_info)[_idx_]
.outgoings->rnum; _j_++) { const int d = *(int*)((void*)((
(char*)(((exec_info)[_idx_].outgoings)->data)) + (size_t)(
(exec_info)[_idx_].outgoings)->rsize * (size_t)(_j_))); ++
_incomings_[d].c; if (_incomings_[d].r != 0) continue; _incomings_
[d].r = 1; ((void) sizeof ((_exist_size_[_q_] < (exec_info_size
)) ? 1 : 0), __extension__ ({ if (_exist_size_[_q_] < (exec_info_size
)) ; else __assert_fail ("_exist_size_[_q_] < (exec_info_size)"
, "ccv_nnc_graph.c", 760, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_)); } for (
_i_ = 0; _i_ < (source_size); _i_++) { ((void) sizeof (((sources
)[_i_].graph == graph) ? 1 : 0), __extension__ ({ if ((sources
)[_i_].graph == graph) ; else __assert_fail ("(sources)[_i_].graph == graph"
, "ccv_nnc_graph.c", 760, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[(sources)[_i_].d].r = 3; _exists_[0][_i_] =
(sources)[_i_].d; } _exist_size_[0] = (source_size); _exist_size_
[1] = 0; _p_ = 0, _q_ = 1; int _bump_ = 1; while (_exist_size_
[_p_] > 0) { _exist_size_[_q_] = 0; for (_i_ = 0; _i_ <
_exist_size_[_p_]; _i_++) { const int32_t _idx_ = _exists_[_p_
][_i_]; if (_incomings_[_idx_].r != 3) continue; _incomings_[
_idx_].r = 4; if ((exec_info)[_idx_].outgoings) for (_j_ = 0;
_j_ < (exec_info)[_idx_].outgoings->rnum; _j_++) { const
int d = *(int*)((void*)(((char*)(((exec_info)[_idx_].outgoings
)->data)) + (size_t)((exec_info)[_idx_].outgoings)->rsize
* (size_t)(_j_))); if (_incomings_[d].edges == 0) { _incomings_
[d].edges = _bump_; _bump_ += _incomings_[d].c; _incomings_[d
].c = 0; } _edges_[_incomings_[d].edges - 1 + _incomings_[d].
c] = _idx_; ++_incomings_[d].c; if (_incomings_[d].r != 2) continue
; _incomings_[d].r = 3; ((void) sizeof ((_exist_size_[_q_] <
(exec_info_size)) ? 1 : 0), __extension__ ({ if (_exist_size_
[_q_] < (exec_info_size)) ; else __assert_fail ("_exist_size_[_q_] < (exec_info_size)"
, "ccv_nnc_graph.c", 760, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_)); } for (
_i_ = 0; _i_ < (destination_size); _i_++) { ((void) sizeof
(((destinations)[_i_].graph == graph) ? 1 : 0), __extension__
({ if ((destinations)[_i_].graph == graph) ; else __assert_fail
("(destinations)[_i_].graph == graph", "ccv_nnc_graph.c", 760
, __extension__ __PRETTY_FUNCTION__); })); _incomings_[(destinations
)[_i_].d].r = 5; _exists_[0][_i_] = (destinations)[_i_].d; } _exist_size_
[0] = (destination_size); _exist_size_[1] = 0; _p_ = 0, _q_ =
1; while (_exist_size_[_p_] > 0) { _exist_size_[_q_] = 0;
for (_i_ = 0; _i_ < _exist_size_[_p_]; _i_++) { const int32_t
_idx_ = _exists_[_p_][_i_]; if (_incomings_[_idx_].r != 5) continue
; _incomings_[_idx_].r = 6; if (_incomings_[_idx_].edges >
0) for (_j_ = 0; _j_ < _incomings_[_idx_].c; _j_++) { const
int d = _edges_[_incomings_[_idx_].edges - 1 + _j_]; if (_incomings_
[d].r != 4) continue; _incomings_[d].r = 5; ((void) sizeof ((
_exist_size_[_q_] < (exec_info_size)) ? 1 : 0), __extension__
({ if (_exist_size_[_q_] < (exec_info_size)) ; else __assert_fail
("_exist_size_[_q_] < (exec_info_size)", "ccv_nnc_graph.c"
, 760, __extension__ __PRETTY_FUNCTION__); })); _exists_[_q_]
[_exist_size_[_q_]] = d; ++_exist_size_[_q_]; } } ((_i_) = (_p_
), (_p_) = (_q_), (_q_) = (_i_)); } for (_i_ = 0; _i_ < (destination_size
); _i_++) { ((void) sizeof (((destinations)[_i_].graph == graph
) ? 1 : 0), __extension__ ({ if ((destinations)[_i_].graph ==
graph) ; else __assert_fail ("(destinations)[_i_].graph == graph"
, "ccv_nnc_graph.c", 760, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[(destinations)[_i_].d].d = 1; } for (_i_ = 0
; _i_ < (source_size); _i_++) { ((void) sizeof (((sources)
[_i_].graph == graph) ? 1 : 0), __extension__ ({ if ((sources
)[_i_].graph == graph) ; else __assert_fail ("(sources)[_i_].graph == graph"
, "ccv_nnc_graph.c", 760, __extension__ __PRETTY_FUNCTION__);
})); _exists_[0][_i_] = (sources)[_i_].d; } _p_ = 0; _q_ = 1
; _exist_size_[0] = (source_size); _exist_size_[1] = 0; int _d_
= 0; while (_exist_size_[_p_] > 0) { _exist_size_[_q_] = 0
; for (_i_ = 0; _i_ < _exist_size_[_p_];) { const int32_t _idx_
= _exists_[_p_][_i_]; _visit_->node[_visit_->size].index
= ((_idx_)); _visit_->node[_visit_->size].term = ((_incomings_
[_idx_].d)); ++_visit_->size;; if (_incomings_[_idx_].d) {
++_d_; _incomings_[_idx_].r = 7; } if ((exec_info)[_idx_].outgoings
) { if ((exec_info)[_idx_].outgoings->rnum == 1) { const int
d = *(int*)((void*)(((char*)(((exec_info)[_idx_].outgoings)->
data)) + (size_t)((exec_info)[_idx_].outgoings)->rsize * (
size_t)(0))); --_incomings_[d].c; if (_incomings_[d].c == 0 &&
_incomings_[d].r == 6 && _d_ < (destination_size)
) { _exists_[_p_][_i_] = d; continue; } } else for (_j_ = 0; _j_
< (exec_info)[_idx_].outgoings->rnum; _j_++) { const int
d = *(int*)((void*)(((char*)(((exec_info)[_idx_].outgoings)->
data)) + (size_t)((exec_info)[_idx_].outgoings)->rsize * (
size_t)(_j_))); --_incomings_[d].c; if (_incomings_[d].c == 0
&& _incomings_[d].r == 6 && _d_ < (destination_size
)) { ((void) sizeof ((_exist_size_[_q_] < (exec_info_size)
) ? 1 : 0), __extension__ ({ if (_exist_size_[_q_] < (exec_info_size
)) ; else __assert_fail ("_exist_size_[_q_] < (exec_info_size)"
, "ccv_nnc_graph.c", 760, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } } ++_i_; } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_
)); } for (_i_ = 0; _i_ < (destination_size); _i_++) { ((void
) sizeof (((destinations)[_i_].graph == graph) ? 1 : 0), __extension__
({ if ((destinations)[_i_].graph == graph) ; else __assert_fail
("(destinations)[_i_].graph == graph", "ccv_nnc_graph.c", 760
, __extension__ __PRETTY_FUNCTION__); })); if (_incomings_[(destinations
)[_i_].d].r == 7) continue; if (!(0)) { ((void) sizeof ((_incomings_
[(destinations)[_i_].d].c == 0) ? 1 : 0), __extension__ ({ if
(_incomings_[(destinations)[_i_].d].c == 0) ; else __assert_fail
("_incomings_[(destinations)[_i_].d].c == 0", "ccv_nnc_graph.c"
, 760, __extension__ __PRETTY_FUNCTION__); })); } else if (_incomings_
[(destinations)[_i_].d].c > 0) continue; _visit_->node[
_visit_->size].index = (((destinations)[_i_].d)); _visit_->
node[_visit_->size].term = ((_incomings_[(destinations)[_i_
].d].d)); ++_visit_->size;; } if (_heap_mem_) free(_incomings_
); } while (0);; ((void) sizeof ((_visit_->size <= (exec_info_size
)) ? 1 : 0), __extension__ ({ if (_visit_->size <= (exec_info_size
)) ; else __assert_fail ("_visit_->size <= (exec_info_size)"
, "ccv_nnc_graph.c", 760, __extension__ __PRETTY_FUNCTION__);
})); _visit_; });
18
←
Loop condition is true. Entering loop body
→
19
←
Assuming field 'outgoings' is null
→
20
←
'?' condition is false
→
21
←
Assuming '_i_' is >= 'exec_info_size'
→
22
←
Loop condition is false. Execution continues on line 760
→
23
←
Taking false branch
→
24
←
Assuming '_i_' is >= 'source_size'
→
25
←
Loop condition is false. Execution continues on line 760
→
26
←
Loop condition is false. Execution continues on line 760
→
27
←
Loop condition is false. Execution continues on line 760
→
28
←
Loop condition is false. Execution continues on line 760
→
29
←
Assuming '_i_' is >= 'destination_size'
→
30
←
Loop condition is false. Execution continues on line 760
→
31
←
Loop condition is false. Execution continues on line 760
→
32
←
Loop condition is false. Execution continues on line 760
→
33
←
Loop condition is false. Execution continues on line 760
→
34
←
Loop condition is false. Execution continues on line 760
→
35
←
Loop condition is false. Execution continues on line 760
→
36
←
Taking false branch
→
37
←
Loop condition is false. Exiting loop
→
38
←
Taking true branch
→
761 if (!root_schedule
38.1
'root_schedule' is 0
)
39
←
Taking true branch
→
762 {
763 // If this is not a root schedule, we need to do partial topsort.
764 int psort_size = 0;
765 ccv_nnc_graph_visit_for(visit, exec_info, node, idx){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int _node_unused_ __attribute__((unused)) = (visit)->
node[_i_].term; typeof ((exec_info)) const node __attribute__
((unused)) = (exec_info) + idx; {
40
←
Loop condition is false. Execution continues on line 768
→
766 ++psort_size;
767 } ccv_nnc_graph_visit_endfor} }
768 schedule->psort = (int*)ccmallocmalloc(sizeof(int) * psort_size);
769 schedule->psort_size = psort_size;
770 psort_size = 0;
771 ccv_nnc_graph_visit_for(visit, exec_info, node, idx){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int _node_unused_ __attribute__((unused)) = (visit)->
node[_i_].term; typeof ((exec_info)) const node __attribute__
((unused)) = (exec_info) + idx; {
41
←
Loop condition is false. Execution continues on line 775
→
772 schedule->psort[psort_size++] = idx;
773 } ccv_nnc_graph_visit_endfor} }
774 }
775 int i, j, k;
776 // Generate exec dependencies (or, in other words, partial ordering of executions).
777 ccv_sparse_matrix_t* exec_dep = ccv_sparse_matrix_new(exec_info_size, exec_info_size, CCV_32S | CCV_C1, CCV_SPARSE_ROW_MAJOR, 0);
778 int* buf = (int*)ccmallocmalloc(sizeof(int) * exec_info_size * 2);
779 int buf_size;
780#define for_block(x, val) \
781 do { \
782 if (((int32_t*)val)[0] > 0) \
783 { \
784 buf[buf_size * 2] = x; \
785 buf[buf_size * 2 + 1] = ((int32_t*)val)[0] + 1; \
786 ++buf_size; \
787 } \
788 } while (0)
789 for (i = 0; i < exec_info_size; i++)
42
←
Loop condition is true. Entering loop body
→
43
←
Loop condition is false. Execution continues on line 791
→
790 schd_info[i].stream_size = -1;
791 ccv_nnc_graph_visit_for(visit, exec_info, node, idx, term){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int term __attribute__((unused)) = (visit)->node[_i_
].term; typeof ((exec_info)) const node __attribute__((unused
)) = (exec_info) + idx; {
44
←
Loop condition is false. Execution continues on line 823
→
792 buf_size = 0; /* save all its parent deps to this buffer */
793 ccv_sparse_matrix_vector_t* vector = ccv_get_sparse_matrix_vector(exec_dep, idx);
794 schd_info[idx].stream_size = 0;
795 if (vector)
796 CCV_SPARSE_VECTOR_FOREACH(exec_dep, vector, for_block)do { switch ((((exec_dep)->type) & 0xFF000)) { case CCV_32S
: { do { int _i_; __attribute__((unused)) const size_t _c_ = (
((exec_dep)->type) & 0xFFF); if ((exec_dep)->type &
CCV_DENSE_VECTOR) { for (_i_ = 0; _i_ < (vector)->size
; _i_++) { for_block((_i_), ((vector)->data.i32 + (_i_ * _c_
))); } } else { const size_t _idx_size_ = sizeof(ccv_sparse_matrix_index_t
) + ((_ccv_get_data_type_size[(((exec_dep)->type) & 0xFF000
) >> 12] * (((exec_dep)->type) & 0xFFF) + 3) &
-4); uint8_t* const _vidx_ = (uint8_t*)(vector)->index; for
(_i_ = 0; _i_ < (vector)->size; _i_++) { ccv_sparse_matrix_index_t
* const _idx_i_ = (ccv_sparse_matrix_index_t*)(_vidx_ + _idx_size_
* _i_); if (_idx_i_->ifbit <= 1) continue; ccv_numeric_data_t
_d_ = { .u8 = (uint8_t*)(_idx_i_ + 1) }; for_block((_idx_i_->
i), (_d_.i32 + (0))); } } } while (0); break; } case CCV_32F:
{ do { int _i_; __attribute__((unused)) const size_t _c_ = (
((exec_dep)->type) & 0xFFF); if ((exec_dep)->type &
CCV_DENSE_VECTOR) { for (_i_ = 0; _i_ < (vector)->size
; _i_++) { for_block((_i_), ((vector)->data.f32 + (_i_ * _c_
))); } } else { const size_t _idx_size_ = sizeof(ccv_sparse_matrix_index_t
) + ((_ccv_get_data_type_size[(((exec_dep)->type) & 0xFF000
) >> 12] * (((exec_dep)->type) & 0xFFF) + 3) &
-4); uint8_t* const _vidx_ = (uint8_t*)(vector)->index; for
(_i_ = 0; _i_ < (vector)->size; _i_++) { ccv_sparse_matrix_index_t
* const _idx_i_ = (ccv_sparse_matrix_index_t*)(_vidx_ + _idx_size_
* _i_); if (_idx_i_->ifbit <= 1) continue; ccv_numeric_data_t
_d_ = { .u8 = (uint8_t*)(_idx_i_ + 1) }; for_block((_idx_i_->
i), (_d_.f32 + (0))); } } } while (0); break; } case CCV_64S:
{ do { int _i_; __attribute__((unused)) const size_t _c_ = (
((exec_dep)->type) & 0xFFF); if ((exec_dep)->type &
CCV_DENSE_VECTOR) { for (_i_ = 0; _i_ < (vector)->size
; _i_++) { for_block((_i_), ((vector)->data.i64 + (_i_ * _c_
))); } } else { const size_t _idx_size_ = sizeof(ccv_sparse_matrix_index_t
) + ((_ccv_get_data_type_size[(((exec_dep)->type) & 0xFF000
) >> 12] * (((exec_dep)->type) & 0xFFF) + 3) &
-4); uint8_t* const _vidx_ = (uint8_t*)(vector)->index; for
(_i_ = 0; _i_ < (vector)->size; _i_++) { ccv_sparse_matrix_index_t
* const _idx_i_ = (ccv_sparse_matrix_index_t*)(_vidx_ + _idx_size_
* _i_); if (_idx_i_->ifbit <= 1) continue; ccv_numeric_data_t
_d_ = { .u8 = (uint8_t*)(_idx_i_ + 1) }; for_block((_idx_i_->
i), (_d_.i64 + (0))); } } } while (0); break; } case CCV_64F:
{ do { int _i_; __attribute__((unused)) const size_t _c_ = (
((exec_dep)->type) & 0xFFF); if ((exec_dep)->type &
CCV_DENSE_VECTOR) { for (_i_ = 0; _i_ < (vector)->size
; _i_++) { for_block((_i_), ((vector)->data.f64 + (_i_ * _c_
))); } } else { const size_t _idx_size_ = sizeof(ccv_sparse_matrix_index_t
) + ((_ccv_get_data_type_size[(((exec_dep)->type) & 0xFF000
) >> 12] * (((exec_dep)->type) & 0xFFF) + 3) &
-4); uint8_t* const _vidx_ = (uint8_t*)(vector)->index; for
(_i_ = 0; _i_ < (vector)->size; _i_++) { ccv_sparse_matrix_index_t
* const _idx_i_ = (ccv_sparse_matrix_index_t*)(_vidx_ + _idx_size_
* _i_); if (_idx_i_->ifbit <= 1) continue; ccv_numeric_data_t
_d_ = { .u8 = (uint8_t*)(_idx_i_ + 1) }; for_block((_idx_i_->
i), (_d_.f64 + (0))); } } } while (0); break; } default: { do
{ int _i_; __attribute__((unused)) const size_t _c_ = (((exec_dep
)->type) & 0xFFF); if ((exec_dep)->type & CCV_DENSE_VECTOR
) { for (_i_ = 0; _i_ < (vector)->size; _i_++) { for_block
((_i_), ((vector)->data.u8 + (_i_ * _c_))); } } else { const
size_t _idx_size_ = sizeof(ccv_sparse_matrix_index_t) + ((_ccv_get_data_type_size
[(((exec_dep)->type) & 0xFF000) >> 12] * (((exec_dep
)->type) & 0xFFF) + 3) & -4); uint8_t* const _vidx_
= (uint8_t*)(vector)->index; for (_i_ = 0; _i_ < (vector
)->size; _i_++) { ccv_sparse_matrix_index_t* const _idx_i_
= (ccv_sparse_matrix_index_t*)(_vidx_ + _idx_size_ * _i_); if
(_idx_i_->ifbit <= 1) continue; ccv_numeric_data_t _d_
= { .u8 = (uint8_t*)(_idx_i_ + 1) }; for_block((_idx_i_->
i), (_d_.u8 + (0))); } } } while (0); } } } while (0);
797 if (!node->outgoings)
798 continue;
799 for (i = 0; i < node->outgoings->rnum; i++)
800 {
801 int outgoing = *(int*)ccv_array_get(node->outgoings, i)((void*)(((char*)((node->outgoings)->data)) + (size_t)(
node->outgoings)->rsize * (size_t)(i)));
802 const int32_t one = 1;
803 ccv_numeric_data_t cell = ccv_get_sparse_matrix_cell(exec_dep, outgoing, idx);
804 /* If not found, set, if the current node is the destination node, no need
805 * set itself as parent of subsequent nodes because its terminal nature. */
806 if (!term && (!cell.i32 || cell.i32[0] == 0))
807 ccv_set_sparse_matrix_cell(exec_dep, outgoing, idx, &one);
808 for (j = 0; j < buf_size; j++) /* set with all idx's dependencies as well */
809 {
810 ccv_numeric_data_t cell = ccv_get_sparse_matrix_cell(exec_dep, outgoing, buf[j * 2]);
811 /* If not found, set */
812 if (!cell.i32 || cell.i32[0] == 0)
813 ccv_set_sparse_matrix_cell(exec_dep, outgoing, buf[j * 2], &buf[j * 2 + 1]);
814 else {
815 /* Otherwise, set to the longest one */
816 int32_t dep = ccv_max(cell.i32[0], buf[j * 2 + 1])({ typeof (cell.i32[0]) _a = (cell.i32[0]); typeof (buf[j * 2
+ 1]) _b = (buf[j * 2 + 1]); (_a > _b) ? _a : _b; });
817 ccv_set_sparse_matrix_cell(exec_dep, outgoing, buf[j * 2], &dep);
818 }
819 }
820 }
821 } ccv_nnc_graph_visit_endfor} }
822#undef for_block
823 ccfreefree(buf);
824 // Algorithm to allocate signals and streams for this graph.
825 ccv_array_t* const stream_data = ccv_array_new(sizeof(ccv_nnc_stream_data_t), 0, 0);
826 ccv_array_t** const outgoings = cccalloccalloc(exec_info_size, sizeof(ccv_array_t*));
827 ccv_nnc_incoming_t* const incomings = cccalloccalloc(exec_info_size, sizeof(ccv_nnc_incoming_t));
828 int max_device_id_size = 1;
829 // Filter out outgoing nodes that we will be able to access it afterwards anyway.
830 ccv_nnc_graph_visit_for(visit, exec_info, node, idx){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int _node_unused_ __attribute__((unused)) = (visit)->
node[_i_].term; typeof ((exec_info)) const node __attribute__
((unused)) = (exec_info) + idx; {
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831 max_device_id_size = ccv_max(node->input_size + node->output_size, max_device_id_size)({ typeof (node->input_size + node->output_size) _a = (
node->input_size + node->output_size); typeof (max_device_id_size
) _b = (max_device_id_size); (_a > _b) ? _a : _b; });
832 if (node->outgoings)
833 {
834 outgoings[idx] = ccv_array_new(sizeof(int), 0, 0);
835 for (i = 0; i < node->outgoings->rnum; i++)
836 {
837 const int di = *(int*)ccv_array_get(node->outgoings, i)((void*)(((char*)((node->outgoings)->data)) + (size_t)(
node->outgoings)->rsize * (size_t)(i)));
838 // Skip if we haven't accessed this exec.
839 if (schd_info[di].stream_size < 0)
840 continue;
841 int flag = 0;
842 for (j = 0; !flag && j < node->outgoings->rnum; j++)
843 {
844 if (j != i)
845 {
846 const int dj = *(int*)ccv_array_get(node->outgoings, j)((void*)(((char*)((node->outgoings)->data)) + (size_t)(
node->outgoings)->rsize * (size_t)(j)));
847 ccv_numeric_data_t cell = ccv_get_sparse_matrix_cell(exec_dep, di, dj);
848 flag = (cell.i32 && cell.i32[0]);
849 }
850 }
851 if (!flag)
852 {
853 ccv_array_push(outgoings[idx], &di);
854 if (!incomings[di].outgoings)
855 incomings[di].outgoings = ccv_array_new(sizeof(int), 1, 0);
856 ccv_array_push(incomings[di].outgoings, &idx);
857 }
858 }
859 }
860 } ccv_nnc_graph_visit_endfor} }
861#define visitor(node, idx, _) \
862 if (node->outgoings) \
863 for (i = 0; i < node->outgoings->rnum; i++) \
864 { \
865 const int d = *(int*)ccv_array_get(node->outgoings, i)((void*)(((char*)((node->outgoings)->data)) + (size_t)(
node->outgoings)->rsize * (size_t)(i))); \
866 node->rank = ccv_max(incomings[d].rank + 1, node->rank)({ typeof (incomings[d].rank + 1) _a = (incomings[d].rank + 1
); typeof (node->rank) _b = (node->rank); (_a > _b) ?
_a : _b; }); \
867 }
868 CCV_NNC_GRAPH_VISIT(graph, incomings, exec_info_size, destinations, destination_size, sources, source_size, 0, visitor)do { typedef struct { int8_t d; int8_t r; uint16_t c; int32_t
edges; } ccv_nnc_incoming_t; int _i_, _j_; int _incoming_edges_
= 0; for (_i_ = 0; _i_ < (exec_info_size); _i_++) _incoming_edges_
+= ((incomings)[_i_].outgoings) ? (incomings)[_i_].outgoings
->rnum : 0; const int _heap_mem_ = ((exec_info_size) + _incoming_edges_
> 1024); ccv_nnc_incoming_t* _incomings_; if (_heap_mem_)
_incomings_ = (ccv_nnc_incoming_t*)malloc(sizeof(ccv_nnc_incoming_t
) * (exec_info_size) + sizeof(int32_t) * ((exec_info_size) * 2
+ _incoming_edges_)); else _incomings_ = (ccv_nnc_incoming_t
*)__builtin_alloca (sizeof(ccv_nnc_incoming_t) * (exec_info_size
) + sizeof(int32_t) * ((exec_info_size) * 2 + _incoming_edges_
)); memset(_incomings_, 0, sizeof(ccv_nnc_incoming_t) * (exec_info_size
)); int32_t* _exists_[2] = { (int32_t*)(_incomings_ + (exec_info_size
)), (int32_t*)(_incomings_ + (exec_info_size)) + (exec_info_size
), }; int32_t* const _edges_ = _exists_[1] + (exec_info_size)
; for (_i_ = 0; _i_ < (destination_size); _i_++) { ((void)
sizeof (((destinations)[_i_].graph == graph) ? 1 : 0), __extension__
({ if ((destinations)[_i_].graph == graph) ; else __assert_fail
("(destinations)[_i_].graph == graph", "ccv_nnc_graph.c", 868
, __extension__ __PRETTY_FUNCTION__); })); _incomings_[(destinations
)[_i_].d].r = 1; _exists_[0][_i_] = (destinations)[_i_].d; } int
_exist_size_[2] = { (destination_size), 0, }; int _p_ = 0, _q_
= 1; while (_exist_size_[_p_] > 0) { _exist_size_[_q_] = 0
; for (_i_ = 0; _i_ < _exist_size_[_p_]; _i_++) { const int32_t
_idx_ = _exists_[_p_][_i_]; if (_incomings_[_idx_].r != 1) continue
; _incomings_[_idx_].r = 2; if ((incomings)[_idx_].outgoings)
for (_j_ = 0; _j_ < (incomings)[_idx_].outgoings->rnum
; _j_++) { const int d = *(int*)((void*)(((char*)(((incomings
)[_idx_].outgoings)->data)) + (size_t)((incomings)[_idx_].
outgoings)->rsize * (size_t)(_j_))); ++_incomings_[d].c; if
(_incomings_[d].r != 0) continue; _incomings_[d].r = 1; ((void
) sizeof ((_exist_size_[_q_] < (exec_info_size)) ? 1 : 0),
__extension__ ({ if (_exist_size_[_q_] < (exec_info_size)
) ; else __assert_fail ("_exist_size_[_q_] < (exec_info_size)"
, "ccv_nnc_graph.c", 868, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_)); } for (
_i_ = 0; _i_ < (destination_size); _i_++) { ((void) sizeof
(((destinations)[_i_].graph == graph) ? 1 : 0), __extension__
({ if ((destinations)[_i_].graph == graph) ; else __assert_fail
("(destinations)[_i_].graph == graph", "ccv_nnc_graph.c", 868
, __extension__ __PRETTY_FUNCTION__); })); _incomings_[(destinations
)[_i_].d].r = 3; _exists_[0][_i_] = (destinations)[_i_].d; } _exist_size_
[0] = (destination_size); _exist_size_[1] = 0; _p_ = 0, _q_ =
1; int _bump_ = 1; while (_exist_size_[_p_] > 0) { _exist_size_
[_q_] = 0; for (_i_ = 0; _i_ < _exist_size_[_p_]; _i_++) {
const int32_t _idx_ = _exists_[_p_][_i_]; if (_incomings_[_idx_
].r != 3) continue; _incomings_[_idx_].r = 4; if ((incomings)
[_idx_].outgoings) for (_j_ = 0; _j_ < (incomings)[_idx_].
outgoings->rnum; _j_++) { const int d = *(int*)((void*)(((
char*)(((incomings)[_idx_].outgoings)->data)) + (size_t)((
incomings)[_idx_].outgoings)->rsize * (size_t)(_j_))); if (
_incomings_[d].edges == 0) { _incomings_[d].edges = _bump_; _bump_
+= _incomings_[d].c; _incomings_[d].c = 0; } _edges_[_incomings_
[d].edges - 1 + _incomings_[d].c] = _idx_; ++_incomings_[d].c
; if (_incomings_[d].r != 2) continue; _incomings_[d].r = 3; (
(void) sizeof ((_exist_size_[_q_] < (exec_info_size)) ? 1 :
0), __extension__ ({ if (_exist_size_[_q_] < (exec_info_size
)) ; else __assert_fail ("_exist_size_[_q_] < (exec_info_size)"
, "ccv_nnc_graph.c", 868, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_)); } for (
_i_ = 0; _i_ < (source_size); _i_++) { ((void) sizeof (((sources
)[_i_].graph == graph) ? 1 : 0), __extension__ ({ if ((sources
)[_i_].graph == graph) ; else __assert_fail ("(sources)[_i_].graph == graph"
, "ccv_nnc_graph.c", 868, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[(sources)[_i_].d].r = 5; _exists_[0][_i_] =
(sources)[_i_].d; } _exist_size_[0] = (source_size); _exist_size_
[1] = 0; _p_ = 0, _q_ = 1; while (_exist_size_[_p_] > 0) {
_exist_size_[_q_] = 0; for (_i_ = 0; _i_ < _exist_size_[_p_
]; _i_++) { const int32_t _idx_ = _exists_[_p_][_i_]; if (_incomings_
[_idx_].r != 5) continue; _incomings_[_idx_].r = 6; if (_incomings_
[_idx_].edges > 0) for (_j_ = 0; _j_ < _incomings_[_idx_
].c; _j_++) { const int d = _edges_[_incomings_[_idx_].edges -
1 + _j_]; if (_incomings_[d].r != 4) continue; _incomings_[d
].r = 5; ((void) sizeof ((_exist_size_[_q_] < (exec_info_size
)) ? 1 : 0), __extension__ ({ if (_exist_size_[_q_] < (exec_info_size
)) ; else __assert_fail ("_exist_size_[_q_] < (exec_info_size)"
, "ccv_nnc_graph.c", 868, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_)); } for (
_i_ = 0; _i_ < (source_size); _i_++) { ((void) sizeof (((sources
)[_i_].graph == graph) ? 1 : 0), __extension__ ({ if ((sources
)[_i_].graph == graph) ; else __assert_fail ("(sources)[_i_].graph == graph"
, "ccv_nnc_graph.c", 868, __extension__ __PRETTY_FUNCTION__);
})); _incomings_[(sources)[_i_].d].d = 1; } for (_i_ = 0; _i_
< (destination_size); _i_++) { ((void) sizeof (((destinations
)[_i_].graph == graph) ? 1 : 0), __extension__ ({ if ((destinations
)[_i_].graph == graph) ; else __assert_fail ("(destinations)[_i_].graph == graph"
, "ccv_nnc_graph.c", 868, __extension__ __PRETTY_FUNCTION__);
})); _exists_[0][_i_] = (destinations)[_i_].d; } _p_ = 0; _q_
= 1; _exist_size_[0] = (destination_size); _exist_size_[1] =
0; int _d_ = 0; while (_exist_size_[_p_] > 0) { _exist_size_
[_q_] = 0; for (_i_ = 0; _i_ < _exist_size_[_p_];) { const
int32_t _idx_ = _exists_[_p_][_i_]; visitor(((incomings) + _idx_
), (_idx_), (_incomings_[_idx_].d)); if (_incomings_[_idx_].d
) { ++_d_; _incomings_[_idx_].r = 7; } if ((incomings)[_idx_]
.outgoings) { if ((incomings)[_idx_].outgoings->rnum == 1)
{ const int d = *(int*)((void*)(((char*)(((incomings)[_idx_]
.outgoings)->data)) + (size_t)((incomings)[_idx_].outgoings
)->rsize * (size_t)(0))); --_incomings_[d].c; if (_incomings_
[d].c == 0 && _incomings_[d].r == 6 && _d_ <
(source_size)) { _exists_[_p_][_i_] = d; continue; } } else for
(_j_ = 0; _j_ < (incomings)[_idx_].outgoings->rnum; _j_
++) { const int d = *(int*)((void*)(((char*)(((incomings)[_idx_
].outgoings)->data)) + (size_t)((incomings)[_idx_].outgoings
)->rsize * (size_t)(_j_))); --_incomings_[d].c; if (_incomings_
[d].c == 0 && _incomings_[d].r == 6 && _d_ <
(source_size)) { ((void) sizeof ((_exist_size_[_q_] < (exec_info_size
)) ? 1 : 0), __extension__ ({ if (_exist_size_[_q_] < (exec_info_size
)) ; else __assert_fail ("_exist_size_[_q_] < (exec_info_size)"
, "ccv_nnc_graph.c", 868, __extension__ __PRETTY_FUNCTION__);
})); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } } ++_i_; } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_
)); } for (_i_ = 0; _i_ < (source_size); _i_++) { ((void) sizeof
(((sources)[_i_].graph == graph) ? 1 : 0), __extension__ ({ if
((sources)[_i_].graph == graph) ; else __assert_fail ("(sources)[_i_].graph == graph"
, "ccv_nnc_graph.c", 868, __extension__ __PRETTY_FUNCTION__);
})); if (_incomings_[(sources)[_i_].d].r == 7) continue; if (
!(0)) { ((void) sizeof ((_incomings_[(sources)[_i_].d].c == 0
) ? 1 : 0), __extension__ ({ if (_incomings_[(sources)[_i_].d
].c == 0) ; else __assert_fail ("_incomings_[(sources)[_i_].d].c == 0"
, "ccv_nnc_graph.c", 868, __extension__ __PRETTY_FUNCTION__);
})); } else if (_incomings_[(sources)[_i_].d].c > 0) continue
; visitor(((incomings) + (sources)[_i_].d), ((sources)[_i_].d
), (_incomings_[(sources)[_i_].d].d)); } if (_heap_mem_) free
(_incomings_); } while (0);;
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869#undef visitor
870 int device_ids[max_device_id_size];
871 int outgoing_device_ids[max_device_id_size];
872 int signal_size = 0;
873 ccv_nnc_graph_visit_for(visit, exec_info, node, idx){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int _node_unused_ __attribute__((unused)) = (visit)->
node[_i_].term; typeof ((exec_info)) const node __attribute__
((unused)) = (exec_info) + idx; {
62
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874 // Go through the incomings.
875 const int device_id_size = _ccv_nnc_device_ids_for_stream_data(node, device_id, stream_data, device_ids, max_device_id_size);
876 if (schd_info[idx].stream_size == 0)
877 {
878 schd_info[idx].stream_size = device_id_size; // At least at the same size as the device_id_size.
879 if (device_id_size > 1)
880 {
881 schd_info[idx]._heap_streams = (int*)ccmallocmalloc(sizeof(int) * device_id_size * 2);
882 schd_info[idx]._heap_signals = (schd_info[idx]._heap_streams + device_id_size);
883 }
884 for (i = 0; i < device_id_size; i++)
885 SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[i] = -1, SCHEDULE_SIGNALS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_signals
: (schd_info[idx])._heap_signals)[i] = -1;
886 }
887 for (i = 0; i < device_id_size; i++)
888 // Go through until the end to assign streams.
889 if (SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[i] < 0)
890 {
891 int stream_idx = -1;
892 int stream_has_command = 0;
893 // First, find a good stream in stream data (the stream is good if it can be recycled, and it has the same command).
894 // Otherwise, we prefer a usable stream (it doesn't have the command, but it can be recycled).
895 for (j = 0; (stream_idx < 0 || !stream_has_command) && j < stream_data->rnum; j++)
896 {
897 ccv_nnc_stream_data_t* const data = (ccv_nnc_stream_data_t*)ccv_array_get(stream_data, j)((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(j)));
898 if (data->device_id == device_ids[i])
899 {
900 const ccv_numeric_data_t cell = ccv_get_sparse_matrix_cell(exec_dep, idx, data->exec_idx);
901 // If there is a path to conclude that exec_idx is before idx, then we can reuse
902 // this stream. Otherwise the work in this "empty stream" could still be ongoing,
903 // and we may delay the following work unnecessarily.
904 if (cell.i32 && cell.i32[0] > 0)
905 {
906 if (ccv_array_find_uint(data->command_set, node->cmd.cmd))
907 stream_idx = j, stream_has_command = 1;
908 else if (stream_idx < 0) // Otherwise, only assign the stream idx if it is not assigned yet.
909 stream_idx = j;
910 }
911 }
912 }
913 if (stream_idx < 0)
914 {
915 // Note that the max stream count is a "soft" limit. Even we have different devices, our compute allocation has to be on different streams.
916 if (stream_data->rnum >= max_stream_count && max_stream_count > 0)
917 {
918 // If we are already at out limit, go through again to see if a stream is available, if the stream has command, and also its exec_idx is not preceding this execution.
919 for (j = 0; (stream_idx < 0 || !stream_has_command) && j < stream_data->rnum; j++)
920 {
921 ccv_nnc_stream_data_t* const data = (ccv_nnc_stream_data_t*)ccv_array_get(stream_data, j)((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(j)));
922 if (data->device_id == device_ids[i])
923 {
924 const ccv_numeric_data_t cell = ccv_get_sparse_matrix_cell(exec_dep, data->exec_idx, idx);
925 // There must be no path from idx to exec_idx otherwise we already have stream_idx. Now we just to verify
926 // there is no path from exec_idx to idx as well.
927 if (!cell.i32 || cell.i32[0] == 0)
928 {
929 if (ccv_array_find_uint(data->command_set, node->cmd.cmd))
930 stream_idx = j, stream_has_command = 1;
931 else if (stream_idx < 0) // Otherwise, only assign the stream idx if it is not assigned yet.
932 stream_idx = j;
933 }
934 }
935 }
936 if (stream_idx >= 0)
937 {
938 // Now need to mark exec_idx is after idx, so we can avoid A -> B -> A deadlock.
939 ccv_nnc_stream_data_t* const data = (ccv_nnc_stream_data_t*)ccv_array_get(stream_data, stream_idx)((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(stream_idx)));
940 const int32_t one = 1;
941 ccv_set_sparse_matrix_cell(exec_dep, idx, data->exec_idx, &one);
942 }
943 }
944 if (stream_idx < 0)
945 {
946 stream_idx = stream_data->rnum;
947 const ccv_nnc_stream_data_t data = {
948 .device_id = device_ids[i],
949 };
950 ccv_array_push(stream_data, &data);
951 }
952 }
953 assert(stream_idx >= 0)((void) sizeof ((stream_idx >= 0) ? 1 : 0), __extension__ (
{ if (stream_idx >= 0) ; else __assert_fail ("stream_idx >= 0"
, "ccv_nnc_graph.c", 953, __extension__ __PRETTY_FUNCTION__);
}));
954 ccv_nnc_stream_data_t* const data = (ccv_nnc_stream_data_t*)ccv_array_get(stream_data, stream_idx)((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(stream_idx)));
955 if (!data->command_set)
956 data->command_set = ccv_array_new(sizeof(uint32_t), 1, 0);
957 SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[i] = stream_idx;
958 ccv_array_add_unique_uint(data->command_set, node->cmd.cmd);
959 // Assign all subsequent node to use this stream.
960 int outgoing_idx = idx;
961 // if we want to enforce the stream count is only 1, we certainly don't want to the greedy approach.
962 // With the greedy approach, the current stream will go all the way down and certainly conflict with
963 // other streams. We'd prefer to interleaving the execution instead in this case.
964 if (max_stream_count != 1)
965 while (outgoings[outgoing_idx] && outgoings[outgoing_idx]->rnum)
966 {
967 int highest_rank = -1;
968 int highest_idx = -1;
969 int stream_n = -1;
970 int stream_has_command = 0;
971 for (j = 0; j < outgoings[outgoing_idx]->rnum; j++)
972 {
973 const int d = *(int*)ccv_array_get(outgoings[outgoing_idx], j)((void*)(((char*)((outgoings[outgoing_idx])->data)) + (size_t
)(outgoings[outgoing_idx])->rsize * (size_t)(j)));
974 // This is not outside of our scope at this point.
975 assert(schd_info[d].stream_size >= 0)((void) sizeof ((schd_info[d].stream_size >= 0) ? 1 : 0), __extension__
({ if (schd_info[d].stream_size >= 0) ; else __assert_fail
("schd_info[d].stream_size >= 0", "ccv_nnc_graph.c", 975,
__extension__ __PRETTY_FUNCTION__); }));
976 ccv_nnc_graph_exec_info_t* const outgoing_node = exec_info + d;
977 const int outgoing_device_id_size = _ccv_nnc_device_ids_for_stream_data(outgoing_node, device_id, stream_data, outgoing_device_ids, max_device_id_size);
978 if (schd_info[d].stream_size == 0)
979 {
980 schd_info[d].stream_size = outgoing_device_id_size; // At least at the same size as the device_id_size.
981 if (outgoing_device_id_size > 1)
982 {
983 schd_info[d]._heap_streams = (int*)ccmallocmalloc(sizeof(int) * outgoing_device_id_size * 2);
984 schd_info[d]._heap_signals = (schd_info[d]._heap_streams + outgoing_device_id_size);
985 }
986 for (k = 0; k < outgoing_device_id_size; k++)
987 SCHEDULE_STREAMS(schd_info[d])((schd_info[d]).stream_size <= 1 ? (schd_info[d])._inline_streams
: (schd_info[d])._heap_streams)[k] = -1, SCHEDULE_SIGNALS(schd_info[d])((schd_info[d]).stream_size <= 1 ? (schd_info[d])._inline_signals
: (schd_info[d])._heap_signals)[k] = -1;
988 }
989 assert(schd_info[d].stream_size == outgoing_device_id_size)((void) sizeof ((schd_info[d].stream_size == outgoing_device_id_size
) ? 1 : 0), __extension__ ({ if (schd_info[d].stream_size == outgoing_device_id_size
) ; else __assert_fail ("schd_info[d].stream_size == outgoing_device_id_size"
, "ccv_nnc_graph.c", 989, __extension__ __PRETTY_FUNCTION__);
}));
990 for (k = 0; k < outgoing_device_id_size; k++)
991 // If it should be on the same device and the stream is not assign, potentially.
992 if (outgoing_device_ids[k] == device_ids[i] &&
993 SCHEDULE_STREAMS(schd_info[d])((schd_info[d]).stream_size <= 1 ? (schd_info[d])._inline_streams
: (schd_info[d])._heap_streams)[k] < 0 &&
994 (incomings[d].rank > highest_rank ||
995 (incomings[d].rank == highest_rank &&
996 !stream_has_command && ccv_array_find_uint(data->command_set, outgoing_node->cmd.cmd))))
997 {
998 highest_rank = incomings[d].rank;
999 highest_idx = d;
1000 stream_n = k;
1001 // This is 1 if rank is the same (thus, I must break the tie already), if the rank is not the same, we need to compute this.
1002 stream_has_command = (incomings[d].rank == highest_rank || ccv_array_find_uint(data->command_set, outgoing_node->cmd.cmd));
1003 }
1004 }
1005 if (highest_idx >= 0)
1006 {
1007 outgoing_idx = highest_idx;
1008 ccv_nnc_graph_exec_info_t* const outgoing_node = exec_info + outgoing_idx;
1009 assert(stream_n >= 0)((void) sizeof ((stream_n >= 0) ? 1 : 0), __extension__ ({
if (stream_n >= 0) ; else __assert_fail ("stream_n >= 0"
, "ccv_nnc_graph.c", 1009, __extension__ __PRETTY_FUNCTION__)
; }));
1010 SCHEDULE_STREAMS(schd_info[outgoing_idx])((schd_info[outgoing_idx]).stream_size <= 1 ? (schd_info[outgoing_idx
])._inline_streams : (schd_info[outgoing_idx])._heap_streams)[stream_n] = stream_idx;
1011 ccv_array_add_unique_uint(data->command_set, outgoing_node->cmd.cmd);
1012 } else
1013 break;
1014 }
1015 data->exec_idx = outgoing_idx;
1016 }
1017 } ccv_nnc_graph_visit_endfor} }
1018 // Go through to assign signals when necessary.
1019 ccv_nnc_graph_visit_for(visit, exec_info, node, idx){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int _node_unused_ __attribute__((unused)) = (visit)->
node[_i_].term; typeof ((exec_info)) const node __attribute__
((unused)) = (exec_info) + idx; {
63
←
Loop condition is false. Execution continues on line 1023
→
1020 if (incomings[idx].outgoings && incomings[idx].outgoings->rnum)
1021 _ccv_nnc_graph_schedule_assign_signals(incomings[idx].outgoings, schd_info + idx, stream_data, &signal_size, schd_info, exec_info_size);
1022 } ccv_nnc_graph_visit_endfor} }
1023 for (i = 0; i < exec_info_size; i++)
64
←
Loop condition is true. Entering loop body
→
66
←
Loop condition is false. Execution continues on line 1026
→
1024 if (outgoings[i])
65
←
Taking false branch
→
1025 ccv_array_free(outgoings[i]);
1026 ccfreefree(outgoings);
1027 ccv_matrix_free(exec_dep);
1028 ccv_nnc_stream_data_t* const default_data = (ccv_nnc_stream_data_t*)ccv_array_get(stream_data, 0)((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(0)));
1029 if (device_id >= 0)
67
←
Assuming 'device_id' is < 0
→
68
←
Taking false branch
→
1030 {
1031 // If the default stream (stream 0) is not the same as desired stream, swap with the one that is.
1032 if (default_data->device_id != device_id)
1033 {
1034 int exchange_stream_idx = -1;
1035 // Find the stream idx to exchange.
1036 ccv_nnc_graph_visit_for(visit, exec_info, node, idx){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int _node_unused_ __attribute__((unused)) = (visit)->
node[_i_].term; typeof ((exec_info)) const node __attribute__
((unused)) = (exec_info) + idx; {
1037 int flag = 0;
1038 for(i = 0; !flag && i < schd_info[idx].stream_size; i++)
1039 {
1040 const int stream_idx = SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[i];
1041 ccv_nnc_stream_data_t* const data = (ccv_nnc_stream_data_t*)ccv_array_get(stream_data, stream_idx)((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(stream_idx)));
1042 if (data->device_id == device_id)
1043 {
1044 exchange_stream_idx = stream_idx;
1045 flag = 1;
1046 }
1047 }
1048 if (flag)
1049 break;
1050 } ccv_nnc_graph_visit_endfor} }
1051 assert(exchange_stream_idx >= 0)((void) sizeof ((exchange_stream_idx >= 0) ? 1 : 0), __extension__
({ if (exchange_stream_idx >= 0) ; else __assert_fail ("exchange_stream_idx >= 0"
, "ccv_nnc_graph.c", 1051, __extension__ __PRETTY_FUNCTION__)
; }));
1052 ccv_nnc_graph_visit_for(visit, exec_info, node, idx){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int _node_unused_ __attribute__((unused)) = (visit)->
node[_i_].term; typeof ((exec_info)) const node __attribute__
((unused)) = (exec_info) + idx; {
1053 for (i = 0; i < schd_info[idx].stream_size; i++)
1054 if (SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[i] == 0)
1055 SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[i] = -1;
1056 } ccv_nnc_graph_visit_endfor} }
1057 ccv_nnc_graph_visit_for(visit, exec_info, node, idx){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int _node_unused_ __attribute__((unused)) = (visit)->
node[_i_].term; typeof ((exec_info)) const node __attribute__
((unused)) = (exec_info) + idx; {
1058 for (i = 0; i < schd_info[idx].stream_size; i++)
1059 if (SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[i] == exchange_stream_idx)
1060 SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[i] = 0;
1061 } ccv_nnc_graph_visit_endfor} }
1062 ccv_nnc_graph_visit_for(visit, exec_info, node, idx){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int _node_unused_ __attribute__((unused)) = (visit)->
node[_i_].term; typeof ((exec_info)) const node __attribute__
((unused)) = (exec_info) + idx; {
1063 for (i = 0; i < schd_info[idx].stream_size; i++)
1064 if (SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[i] == -1)
1065 SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[i] = exchange_stream_idx;
1066 } ccv_nnc_graph_visit_endfor} }
1067 ((ccv_nnc_stream_data_t*)ccv_array_get(stream_data, exchange_stream_idx)((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(exchange_stream_idx))))->device_id = default_data->device_id;
1068 default_data->device_id = device_id;
1069 }
1070 }
1071 int graph_stream_1_size = 0;
1072 for (i = 0; i
68.1
'i' is >= 'source_size'
 < source_size; i++)
69
←
Loop condition is false. Execution continues on line 1093
→
1073 {
1074 const int idx = sources[i].d;
1075 // If it has incoming nodes, check whether these are on stream 0.
1076 if (incomings[idx].outgoings && incomings[idx].outgoings->rnum)
1077 {
1078 int flag = 0;
1079 const ccv_array_t* const incoming = incomings[idx].outgoings;
1080 for (j = 0; !flag && j < incoming->rnum; j++)
1081 {
1082 const int incoming_idx = *(int*)ccv_array_get(incoming, j)((void*)(((char*)((incoming)->data)) + (size_t)(incoming)->
rsize * (size_t)(j)));
1083 for (k = 0; !flag && k < schd_info[incoming_idx].stream_size; k++)
1084 flag = (SCHEDULE_STREAMS(schd_info[incoming_idx])((schd_info[incoming_idx]).stream_size <= 1 ? (schd_info[incoming_idx
])._inline_streams : (schd_info[incoming_idx])._heap_streams)[k] == 0); // If this is the default stream, we already have a good start.
1085 }
1086 if (flag)
1087 continue;
1088 }
1089 for (j = 0; j < schd_info[idx].stream_size; j++)
1090 if (SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[j] != 0) // If this is not the default stream, we need explicit begin signal to start.
1091 ++graph_stream_1_size;
1092 }
1093 if (graph_stream_1_size
69.1
'graph_stream_1_size' is <= 0
 > 0)
70
←
Taking false branch
→
1094 {
1095 schedule->stream_1s = ccmallocmalloc(sizeof(int) * graph_stream_1_size);
1096 graph_stream_1_size = 0;
1097 for (i = 0; i < source_size; i++)
1098 {
1099 const int idx = sources[i].d;
1100 // If it has incoming nodes, check whether these are on stream 0.
1101 if (incomings[idx].outgoings && incomings[idx].outgoings->rnum)
1102 {
1103 int flag = 0;
1104 const ccv_array_t* const incoming = incomings[idx].outgoings;
1105 for (j = 0; !flag && j < incoming->rnum; j++)
1106 {
1107 const int incoming_idx = *(int*)ccv_array_get(incoming, j)((void*)(((char*)((incoming)->data)) + (size_t)(incoming)->
rsize * (size_t)(j)));
1108 for (k = 0; !flag && k < schd_info[incoming_idx].stream_size; k++)
1109 flag = (SCHEDULE_STREAMS(schd_info[incoming_idx])((schd_info[incoming_idx]).stream_size <= 1 ? (schd_info[incoming_idx
])._inline_streams : (schd_info[incoming_idx])._heap_streams)[k] == 0); // If this is the default stream, we already have a good start.
1110 }
1111 if (flag)
1112 continue;
1113 }
1114 for (j = 0; j < schd_info[idx].stream_size; j++)
1115 if (SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[j] != 0) // If this is not the default stream, we need explicit begin signal to start.
1116 {
1117 const int stream_idx = SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[j];
1118 int flag = 0;
1119 for (k = 0; !flag && k < graph_stream_1_size; k++)
1120 flag = (stream_idx == schedule->stream_1s[k]);
1121 if (!flag)
1122 schedule->stream_1s[graph_stream_1_size++] = stream_idx;
1123 }
1124 }
1125 schedule->stream_1_size = graph_stream_1_size;
1126 }
1127 for (i = 0; i < exec_info_size; i++)
71
←
Loop condition is true. Entering loop body
→
73
←
Loop condition is false. Execution continues on line 1130
→
1128 if (incomings[i].outgoings
71.1
Field 'outgoings' is null
)
72
←
Taking false branch
→
1129 ccv_array_free(incomings[i].outgoings);
1130 ccfreefree(incomings);
1131 int graph_wait_size = 0;
1132 for (i = 0; i
73.1
'i' is >= 'destination_size'
 < destination_size; i++)
74
←
Loop condition is false. Execution continues on line 1139
→
1133 {
1134 const int idx = destinations[i].d;
1135 for (j = 0; j < schd_info[idx].stream_size; j++)
1136 if (SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[j] != 0) // If this exec_info doesn't end with default stream, we need to wait.
1137 ++graph_wait_size;
1138 }
1139 if (graph_wait_size
74.1
'graph_wait_size' is <= 0
 > 0)
75
←
Taking false branch
→
1140 {
1141 schedule->waits = ccmallocmalloc(sizeof(int) * graph_wait_size);
1142 graph_wait_size = 0;
1143 for (i = 0; i < destination_size; i++)
1144 {
1145 const int idx = destinations[i].d;
1146 for (j = 0; j < schd_info[idx].stream_size; j++)
1147 if (SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[j] != 0) // If this exec_info doesn't end with default stream, we need to wait.
1148 {
1149 ccv_nnc_stream_data_t* const default_stream_data = (ccv_nnc_stream_data_t*)ccv_array_get(stream_data, 0)((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(0)));
1150 if (SCHEDULE_SIGNALS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_signals
: (schd_info[idx])._heap_signals)[j] < 0)
1151 SCHEDULE_SIGNALS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_signals
: (schd_info[idx])._heap_signals)[j] = signal_size++;
1152 else if (default_stream_data->signal_set && ccv_array_find_int(default_stream_data->signal_set, SCHEDULE_SIGNALS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_signals
: (schd_info[idx])._heap_signals)[j]))
1153 continue;
1154 schedule->waits[graph_wait_size++] = SCHEDULE_SIGNALS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_signals
: (schd_info[idx])._heap_signals)[j];
1155 }
1156 }
1157 schedule->wait_size = graph_wait_size;
1158 }
1159 for (i = 0; i < stream_data->rnum; i++)
76
←
Assuming 'i' is >= field 'rnum'
→
77
←
Loop condition is false. Execution continues on line 1168
→
1160 {
1161 ccv_nnc_stream_data_t* const data = (ccv_nnc_stream_data_t*)ccv_array_get(stream_data, i)((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(i)));
1162 if (data->signal_set)
1163 ccv_array_free(data->signal_set);
1164 assert(data->command_set)((void) sizeof ((data->command_set) ? 1 : 0), __extension__
({ if (data->command_set) ; else __assert_fail ("data->command_set"
, "ccv_nnc_graph.c", 1164, __extension__ __PRETTY_FUNCTION__)
; }));
1165 ccv_array_free(data->command_set);
1166 }
1167 // Allocate streams & signals
1168 int default_stream_type = stream_type;
1169 CCV_STREAM_SET_DEVICE_ID(default_stream_type, default_data->device_id)(default_stream_type) = (((default_stream_type) & ~0xfff00
) | (((default_data->device_id) & 0xfff) << 8));
1170 if (root_schedule
77.1
'root_schedule' is 0
)
78
←
Taking false branch
→
1171 {
1172 assert(!graph->streams)((void) sizeof ((!graph->streams) ? 1 : 0), __extension__ (
{ if (!graph->streams) ; else __assert_fail ("!graph->streams"
, "ccv_nnc_graph.c", 1172, __extension__ __PRETTY_FUNCTION__)
; }));
1173 graph->stream_size = stream_data->rnum;
1174 graph->streams = (ccv_nnc_stream_context_t**)ccmallocmalloc(sizeof(ccv_nnc_stream_context_t*) * graph->stream_size);
1175 graph->block_stream_tasks = (co_routine_t**)cccalloccalloc(graph->stream_size, sizeof(co_routine_t*));
1176 if (stream_context)
1177 graph->streams[0] = stream_context;
1178 for (i = (stream_context ? 1 : 0); i < stream_data->rnum; i++)
1179 {
1180 ccv_nnc_stream_data_t* const data = (ccv_nnc_stream_data_t*)ccv_array_get(stream_data, i)((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(i)));
1181 int type = stream_type;
1182 CCV_STREAM_SET_DEVICE_ID(type, data->device_id)(type) = (((type) & ~0xfff00) | (((data->device_id) &
0xfff) << 8));
1183 graph->streams[i] = ccv_nnc_stream_context_new(type);
1184 }
1185 graph->signal_size = signal_size;
1186 graph->signals = (ccv_nnc_stream_signal_t**)cccalloccalloc(signal_size, sizeof(ccv_nnc_stream_signal_t*));
1187 ccv_nnc_graph_visit_for(visit, exec_info, node, idx){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int _node_unused_ __attribute__((unused)) = (visit)->
node[_i_].term; typeof ((exec_info)) const node __attribute__
((unused)) = (exec_info) + idx; {
1188 for (i = 0; i < schd_info[idx].stream_size; i++)
1189 if (SCHEDULE_SIGNALS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_signals
: (schd_info[idx])._heap_signals)[i] >= 0)
1190 {
1191 const int signal = SCHEDULE_SIGNALS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_signals
: (schd_info[idx])._heap_signals)[i];
1192 if (!graph->signals[signal])
1193 {
1194 const ccv_nnc_stream_data_t* const data = (ccv_nnc_stream_data_t*)ccv_array_get(stream_data, SCHEDULE_STREAMS(schd_info[idx])[i])((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(((schd_info[idx]).stream_size <= 1 ?
(schd_info[idx])._inline_streams : (schd_info[idx])._heap_streams
)[i])));
1195 int type = stream_type;
1196 CCV_STREAM_SET_DEVICE_ID(type, data->device_id)(type) = (((type) & ~0xfff00) | (((data->device_id) &
0xfff) << 8));
1197 graph->signals[signal] = ccv_nnc_stream_signal_new(type);
1198 }
1199 }
1200 } ccv_nnc_graph_visit_endfor} }
1201 } else {
1202 assert(graph->streams)((void) sizeof ((graph->streams) ? 1 : 0), __extension__ (
{ if (graph->streams) ; else __assert_fail ("graph->streams"
, "ccv_nnc_graph.c", 1202, __extension__ __PRETTY_FUNCTION__)
; }));
79
←
Assuming field 'streams' is non-null
→
80
←
Taking true branch
→
1203 assert(graph->stream_size >= stream_data->rnum)((void) sizeof ((graph->stream_size >= stream_data->
rnum) ? 1 : 0), __extension__ ({ if (graph->stream_size >=
stream_data->rnum) ; else __assert_fail ("graph->stream_size >= stream_data->rnum"
, "ccv_nnc_graph.c", 1203, __extension__ __PRETTY_FUNCTION__)
; }));
81
←
Assuming field 'stream_size' is >= field 'rnum'
→
82
←
Taking true branch
→
1204 // Find streams to proper allocated stream based on the type we need.
1205 int* const stream_idxs = (int*)ccmallocmalloc(sizeof(int) * (stream_data->rnum + signal_size));
83
←
Storing uninitialized value
→
1206 uint64_t* const stream_used = (uint64_t*)cccalloccalloc(((graph->stream_size + 63) >> 6) + ((graph->signal_size + 63) >> 6), sizeof(uint64_t));
1207 for (i = 0; i
83.1
'i' is >= field 'rnum'
 < stream_data->rnum; i++)
84
←
Loop condition is false. Execution continues on line 1224
→
1208 {
1209 ccv_nnc_stream_data_t* const data = (ccv_nnc_stream_data_t*)ccv_array_get(stream_data, i)((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(i)));
1210 int type = stream_type;
1211 CCV_STREAM_SET_DEVICE_ID(type, data->device_id)(type) = (((type) & ~0xfff00) | (((data->device_id) &
0xfff) << 8));
1212 for (j = 0; j < graph->stream_size; j++)
1213 if (!(stream_used[j >> 6] & ((uint64_t)1 << (j & 63))))
1214 {
1215 const int stream_type = ccv_nnc_stream_context_type(graph->streams[j]);
1216 if (stream_type == type)
1217 {
1218 stream_idxs[i] = j;
1219 stream_used[j >> 6] |= ((uint64_t)1 << (j & 63));
1220 break;
1221 }
1222 }
1223 }
1224 assert(graph->signal_size >= signal_size)((void) sizeof ((graph->signal_size >= signal_size) ? 1
: 0), __extension__ ({ if (graph->signal_size >= signal_size
) ; else __assert_fail ("graph->signal_size >= signal_size"
, "ccv_nnc_graph.c", 1224, __extension__ __PRETTY_FUNCTION__)
; }));
85
←
Assuming 'signal_size' is <= field 'signal_size'
→
86
←
Taking true branch
→
1225 // Find signals to proper allocated signal based on the type we need.
1226 int* const signal_idxs = stream_idxs + stream_data->rnum;
1227 uint64_t* const signal_used = stream_used + ((graph->stream_size + 63) >> 6);
1228 for (i = 0; i < signal_size; i++)
87
←
Loop condition is false. Execution continues on line 1230
→
1229 signal_idxs[i] = -1;
1230 ccv_nnc_graph_visit_for(visit, exec_info, node, idx){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int _node_unused_ __attribute__((unused)) = (visit)->
node[_i_].term; typeof ((exec_info)) const node __attribute__
((unused)) = (exec_info) + idx; {
88
←
Loop condition is false. Execution continues on line 1255
→
1231 for (i = 0; i < schd_info[idx].stream_size; i++)
1232 if (SCHEDULE_SIGNALS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_signals
: (schd_info[idx])._heap_signals)[i] >= 0)
1233 {
1234 const int signal = SCHEDULE_SIGNALS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_signals
: (schd_info[idx])._heap_signals)[i];
1235 if (signal_idxs[signal] < 0)
1236 {
1237 const ccv_nnc_stream_data_t* const data = (ccv_nnc_stream_data_t*)ccv_array_get(stream_data, SCHEDULE_STREAMS(schd_info[idx])[i])((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(((schd_info[idx]).stream_size <= 1 ?
(schd_info[idx])._inline_streams : (schd_info[idx])._heap_streams
)[i])));
1238 int type = stream_type;
1239 CCV_STREAM_SET_DEVICE_ID(type, data->device_id)(type) = (((type) & ~0xfff00) | (((data->device_id) &
0xfff) << 8));
1240 for (j = 0; j < graph->signal_size; j++)
1241 if (!(signal_used[j >> 6] & ((uint64_t)1 << (j & 63))))
1242 {
1243 const int signal_type = ccv_nnc_stream_signal_type(graph->signals[j]);
1244 if (signal_type == type)
1245 {
1246 signal_idxs[signal] = j;
1247 signal_used[j >> 6] |= ((uint64_t)1 << (j & 63));
1248 break;
1249 }
1250 }
1251 }
1252 }
1253 } ccv_nnc_graph_visit_endfor} }
1254 // Now rebind streams and signals from the schedule.
1255 ccv_nnc_graph_visit_for(visit, exec_info, node, idx){ int _i_; for (_i_ = 0; _i_ < (visit)->size; _i_++) { const
int idx __attribute__((unused)) = (visit)->node[_i_].index
; const int _node_unused_ __attribute__((unused)) = (visit)->
node[_i_].term; typeof ((exec_info)) const node __attribute__
((unused)) = (exec_info) + idx; {
89
←
Loop condition is false. Execution continues on line 1265
→
1256 for (i = 0; i < schd_info[idx].stream_size; i++)
1257 {
1258 SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[i] = stream_idxs[SCHEDULE_STREAMS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_streams
: (schd_info[idx])._heap_streams)[i]];
1259 if (SCHEDULE_SIGNALS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_signals
: (schd_info[idx])._heap_signals)[i] >= 0)
1260 SCHEDULE_SIGNALS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_signals
: (schd_info[idx])._heap_signals)[i] = signal_idxs[SCHEDULE_SIGNALS(schd_info[idx])((schd_info[idx]).stream_size <= 1 ? (schd_info[idx])._inline_signals
: (schd_info[idx])._heap_signals)[i]];
1261 }
1262 for (i = 0; i < schd_info[idx].wait_size; i++)
1263 schd_info[idx].waits[i] = signal_idxs[schd_info[idx].waits[i]];
1264 } ccv_nnc_graph_visit_endfor} }
1265 for (i = 0; i < schedule->stream_1_size; i++)
90
←
Loop condition is false. Execution continues on line 1267
→
1266 schedule->stream_1s[i] = stream_idxs[schedule->stream_1s[i]];
1267 for (i = 0; i < schedule->wait_size; i++)
91
←
Loop condition is false. Execution continues on line 1270
→
1268 schedule->waits[i] = signal_idxs[schedule->waits[i]];
1269 // Rebind who is the stream 0 (default stream).
1270 schedule->stream_0 = stream_idxs[0];
92
←
Assigned value is garbage or undefined
1271 ccfreefree(stream_used);
1272 ccfreefree(stream_idxs);
1273 }
1274 assert(graph->streams)((void) sizeof ((graph->streams) ? 1 : 0), __extension__ (
{ if (graph->streams) ; else __assert_fail ("graph->streams"
, "ccv_nnc_graph.c", 1274, __extension__ __PRETTY_FUNCTION__)
; }));
1275 ccv_nnc_graph_visit_free(visit);
1276 for (i = 0; i < signal_size; i++)
1277 { assert(graph->signals[i])((void) sizeof ((graph->signals[i]) ? 1 : 0), __extension__
({ if (graph->signals[i]) ; else __assert_fail ("graph->signals[i]"
, "ccv_nnc_graph.c", 1277, __extension__ __PRETTY_FUNCTION__)
; })); }
1278 if (schedule->stream_1_size)
1279 schedule->begin = ccv_nnc_stream_signal_new(default_stream_type);
1280 schedule->end = ccv_nnc_stream_signal_new(default_stream_type);
1281 // Do this recursively for its sub graphs.
1282 if (graph->sub_graphs)
1283 for (i = 0; i < graph->sub_graphs->rnum; i++)
1284 {
1285 ccv_nnc_graph_t* const sub_graph = *(ccv_nnc_graph_t**)ccv_array_get(graph->sub_graphs, i)((void*)(((char*)((graph->sub_graphs)->data)) + (size_t
)(graph->sub_graphs)->rsize * (size_t)(i)));
1286 if (sub_graph && !sub_graph->default_schedule)
1287 {
1288 const int exec_idx = sub_graph->exec_idx - 1;
1289 assert(schd_info[exec_idx].stream_size == 1)((void) sizeof ((schd_info[exec_idx].stream_size == 1) ? 1 : 0
), __extension__ ({ if (schd_info[exec_idx].stream_size == 1)
; else __assert_fail ("schd_info[exec_idx].stream_size == 1"
, "ccv_nnc_graph.c", 1289, __extension__ __PRETTY_FUNCTION__)
; }));
1290 const int stream_idx = SCHEDULE_STREAMS(schd_info[exec_idx])((schd_info[exec_idx]).stream_size <= 1 ? (schd_info[exec_idx
])._inline_streams : (schd_info[exec_idx])._heap_streams)[0];
1291 const int device_id = ((ccv_nnc_stream_data_t*)ccv_array_get(stream_data, stream_idx)((void*)(((char*)((stream_data)->data)) + (size_t)(stream_data
)->rsize * (size_t)(stream_idx))))->device_id;
1292 sub_graph->default_schedule = _ccv_nnc_graph_static_schedule_new(sub_graph, stream_type, device_id, max_stream_count, graph->streams[stream_idx], 0, 0, 0, 0);
1293 }
1294 }
1295 ccv_array_free(stream_data);
1296 return schedule;
1297}
1298void ccv_nnc_graph_set_default_static_schedule(ccv_nnc_graph_t* const graph, const int stream_type, const int max_stream_count)
1299{
1300 assert(graph->p == 0)((void) sizeof ((graph->p == 0) ? 1 : 0), __extension__ ({
if (graph->p == 0) ; else __assert_fail ("graph->p == 0"
, "ccv_nnc_graph.c", 1300, __extension__ __PRETTY_FUNCTION__)
; }));
1301 if (graph->default_schedule)
1302 ccv_nnc_graph_static_schedule_free(graph->default_schedule);
1303 graph->default_schedule = _ccv_nnc_graph_static_schedule_new(graph, stream_type, -1, max_stream_count, 0, 0, 0, 0, 0);
1304}
1305
1306ccv_nnc_graph_static_schedule_t* ccv_nnc_graph_static_schedule_new(ccv_nnc_graph_t* const graph, const int stream_type, const int max_stream_count, const ccv_nnc_graph_exec_t* const sources, const int source_size, const ccv_nnc_graph_exec_t* const destinations, const int destination_size)
1307{
1308 assert(graph->p == 0)((void) sizeof ((graph->p == 0) ? 1 : 0), __extension__ ({
if (graph->p == 0) ; else __assert_fail ("graph->p == 0"
, "ccv_nnc_graph.c", 1308, __extension__ __PRETTY_FUNCTION__)
; }));
1309 return _ccv_nnc_graph_static_schedule_new(graph, stream_type, -1, max_stream_count, 0, sources, source_size, destinations, destination_size);
1310}
1311
1312ccv_nnc_stream_context_t* ccv_nnc_graph_default_stream(const ccv_nnc_graph_t* const graph)
1313{
1314 if (graph->streams && graph->stream_size > 0)
1315 return graph->streams[0];
1316 return 0;
1317}
1318
1319static void _ccv_nnc_graph_dot_exec(const int index, const ccv_nnc_graph_exec_info_t* const exec_info, const ccv_nnc_graph_exec_schedule_t* const schd_info, ccv_nnc_stream_context_t** const streams, const int flags, FILE* out)
1320{
1321 if (flags == CCV_NNC_LONG_DOT_GRAPH)
1322 fputc('{', out);
1323 fprintf(out, "node%d", index);
1324 if (flags == CCV_NNC_LONG_DOT_GRAPH)
1325 {
1326 fputs("|Command: ", out);
1327 fputs(ccv_nnc_cmd_name(exec_info->cmd.cmd), out);
1328 if (schd_info)
1329 {
1330 if (schd_info->stream_size > 0)
1331 {
1332 int i, flag = 0;
1333 fputs("|Stream: ", out);
1334 for (i = 0; i < schd_info->stream_size; i++)
1335 {
1336 const int device_id = streams ? CCV_TENSOR_GET_DEVICE_ID(streams[SCHEDULE_STREAMS(*schd_info)[i]]->type)(((streams[((*schd_info).stream_size <= 1 ? (*schd_info)._inline_streams
: (*schd_info)._heap_streams)[i]]->type) & 0xfff00) >>
8) : 0;
1337 if (i == 0)
1338 fprintf(out, "%d (d%d)", SCHEDULE_STREAMS(*schd_info)((*schd_info).stream_size <= 1 ? (*schd_info)._inline_streams
: (*schd_info)._heap_streams)[i], device_id);
1339 else
1340 fprintf(out, ", %d (d%d)", SCHEDULE_STREAMS(*schd_info)((*schd_info).stream_size <= 1 ? (*schd_info)._inline_streams
: (*schd_info)._heap_streams)[i], device_id);
1341 }
1342 for (i = 0; i < schd_info->stream_size; i++)
1343 if (SCHEDULE_SIGNALS(*schd_info)((*schd_info).stream_size <= 1 ? (*schd_info)._inline_signals
: (*schd_info)._heap_signals)[i] >= 0)
1344 {
1345 if (!flag)
1346 {
1347 flag = 1;
1348 fprintf(out, "|Signal: %d", SCHEDULE_SIGNALS(*schd_info)((*schd_info).stream_size <= 1 ? (*schd_info)._inline_signals
: (*schd_info)._heap_signals)[i]);
1349 } else
1350 fprintf(out, ", %d", SCHEDULE_SIGNALS(*schd_info)((*schd_info).stream_size <= 1 ? (*schd_info)._inline_signals
: (*schd_info)._heap_signals)[i]);
1351 }
1352 }
1353 if (schd_info->wait_size > 0)
1354 {
1355 fputs("|Wait: ", out);
1356 int i;
1357 for (i = 0; i < schd_info->wait_size - 1; i++)
1358 fprintf(out, "%d, ", schd_info->waits[i]);
1359 fprintf(out, "%d", schd_info->waits[schd_info->wait_size - 1]);
1360 }
1361 }
1362 fputc('}', out);
1363 }
1364}
1365
1366static void _ccv_nnc_graph_dot_tensor(const int index, const ccv_nnc_tensor_t* const tensor, const int zone, const int flags, const int depth, FILE* out)
1367{
1368 // if it has an alias pointer, or, it is a long form.
1369 if (flags == CCV_NNC_LONG_DOT_GRAPH)
1370 fputc('{', out);
1371 const int is_tensor_view = CCV_IS_TENSOR_VIEW(tensor)((*(int*)(tensor)) & CCV_TENSOR_VIEW);
1372 if (is_tensor_view)
1373 fprintf(out, "tensorview%d", index);
1374 else
1375 fprintf(out, "tensor%d", index);
1376 int i;
1377 for (i = 0; i < depth; i++) // Print subscription to denote depth.
1378 fputc('\'', out);
1379 if (CCV_GET_TAPE_ALLOC(tensor->type)((tensor->type) & CCV_TAPE_ALLOC))
1380 fputs(" (t)", out);
1381 if (flags == CCV_NNC_LONG_DOT_GRAPH)
1382 {
1383 const int device_id = CCV_TENSOR_GET_DEVICE_ID(tensor->info.type)(((tensor->info.type) & 0xfff00) >> 8);
1384 fprintf(out, "|d%d|zone%d", device_id, zone);
1385 for (i = 0; i < depth; i++) // Print subscription to denote depth.
1386 fputc('\'', out);
1387 uintptr_t aptr = (uintptr_t)tensor->data.u8;
1388 size_t tensor_size;
1389 if (is_tensor_view)
1390 tensor_size = (size_t)((ccv_nnc_tensor_view_t*)(tensor))->stride[0] * tensor->info.dim[0] * CCV_GET_DATA_TYPE_SIZE(tensor->type)_ccv_get_data_type_size[((tensor->type) & 0xFF000) >>
12];
1391 else
1392 tensor_size = ccv_nnc_dimension_count(tensor->info.dim) * CCV_GET_DATA_TYPE_SIZE(tensor->type)_ccv_get_data_type_size[((tensor->type) & 0xFF000) >>
12];
1393 // Print out the range as well.
1394 fprintf(out, "|{%#010x|%#010x}|%d", (uint32_t)aptr, (uint32_t)(aptr + tensor_size - 1), tensor->info.dim[0]);
1395 for (i = 1; i < CCV_NNC_MAX_DIM_ALLOC(12) && tensor->info.dim[i]; i++)
1396 fprintf(out, "x%d", tensor->info.dim[i]);
1397 fputc('}', out);
1398 }
1399}
1400
1401typedef struct {
1402 int index;
1403 int name;
1404 int zone;
1405 uintptr_t tensor_ref;
1406 uintptr_t start_ptr;
1407 uintptr_t end_ptr;
1408} ccv_nnc_tensor_dot_t;
1409
1410typedef struct {
1411 ccv_nnc_tensor_dot_t* dots;
1412 int* remap;
1413 int* rename_zone;
1414 int* rename_index;
1415} ccv_nnc_tensor_dot_recovery_t;
1416
1417// First sort by start_ptr, then sort by tensor ptr (so that we will have the same tensor sorted to one cluster).
1418#define less_than(i1, i2, aux) ((i1).start_ptr < (i2).start_ptr || ((i1).start_ptr == (i2).start_ptr && (i1).tensor_ref < (i2).tensor_ref))
1419static CCV_IMPLEMENT_QSORT(_ccv_nnc_tensor_dot_sort_by_ptr, ccv_nnc_tensor_dot_t, less_than)void _ccv_nnc_tensor_dot_sort_by_ptr(ccv_nnc_tensor_dot_t *array
, size_t total, int aux) { int isort_thresh = 7; ccv_nnc_tensor_dot_t
t; int sp = 0; struct { ccv_nnc_tensor_dot_t *lb; ccv_nnc_tensor_dot_t
*ub; } stack[48]; if( total <= 1 ) return; stack[0].lb = array
; stack[0].ub = array + (total - 1); while( sp >= 0 ) { ccv_nnc_tensor_dot_t
* left = stack[sp].lb; ccv_nnc_tensor_dot_t* right = stack[sp
--].ub; for(;;) { int i, n = (int)(right - left) + 1, m; ccv_nnc_tensor_dot_t
* ptr; ccv_nnc_tensor_dot_t* ptr2; if( n <= isort_thresh )
{ insert_sort: for( ptr = left + 1; ptr <= right; ptr++ )
{ for( ptr2 = ptr; ptr2 > left && less_than(ptr2[
0],ptr2[-1], aux); ptr2--) (((t)) = ((ptr2[0])), ((ptr2[0])) =
((ptr2[-1])), ((ptr2[-1])) = ((t))); } break; } else { ccv_nnc_tensor_dot_t
* left0; ccv_nnc_tensor_dot_t* left1; ccv_nnc_tensor_dot_t* right0
; ccv_nnc_tensor_dot_t* right1; ccv_nnc_tensor_dot_t* pivot; ccv_nnc_tensor_dot_t
* a; ccv_nnc_tensor_dot_t* b; ccv_nnc_tensor_dot_t* c; int swap_cnt
= 0; left0 = left; right0 = right; pivot = left + (n/2); if(
n > 40 ) { int d = n / 8; a = left, b = left + d, c = left
+ 2*d; left = less_than(*a, *b, aux) ? (less_than(*b, *c, aux
) ? b : (less_than(*a, *c, aux) ? c : a)) : (less_than(*c, *b
, aux) ? b : (less_than(*a, *c, aux) ? a : c)); a = pivot - d
, b = pivot, c = pivot + d; pivot = less_than(*a, *b, aux) ? (
less_than(*b, *c, aux) ? b : (less_than(*a, *c, aux) ? c : a)
) : (less_than(*c, *b, aux) ? b : (less_than(*a, *c, aux) ? a
: c)); a = right - 2*d, b = right - d, c = right; right = less_than
(*a, *b, aux) ? (less_than(*b, *c, aux) ? b : (less_than(*a, *
c, aux) ? c : a)) : (less_than(*c, *b, aux) ? b : (less_than(
*a, *c, aux) ? a : c)); } a = left, b = pivot, c = right; pivot
= less_than(*a, *b, aux) ? (less_than(*b, *c, aux) ? b : (less_than
(*a, *c, aux) ? c : a)) : (less_than(*c, *b, aux) ? b : (less_than
(*a, *c, aux) ? a : c)); if( pivot != left0 ) { (((t)) = ((*pivot
)), ((*pivot)) = ((*left0)), ((*left0)) = ((t))); pivot = left0
; } left = left1 = left0 + 1; right = right1 = right0; for(;;
) { while( left <= right && !less_than(*pivot, *left
, aux) ) { if( !less_than(*left, *pivot, aux) ) { if( left >
left1 ) (((t)) = ((*left1)), ((*left1)) = ((*left)), ((*left
)) = ((t))); swap_cnt = 1; left1++; } left++; } while( left <=
right && !less_than(*right, *pivot, aux) ) { if( !less_than
(*pivot, *right, aux) ) { if( right < right1 ) (((t)) = ((
*right1)), ((*right1)) = ((*right)), ((*right)) = ((t))); swap_cnt
= 1; right1--; } right--; } if( left > right ) break; (((
t)) = ((*left)), ((*left)) = ((*right)), ((*right)) = ((t)));
swap_cnt = 1; left++; right--; } if( swap_cnt == 0 ) { left =
left0, right = right0; goto insert_sort; } n = ({ typeof ((int
)(left1 - left0)) _a = ((int)(left1 - left0)); typeof ((int)(
left - left1)) _b = ((int)(left - left1)); (_a < _b) ? _a :
_b; }); for( i = 0; i < n; i++ ) (((t)) = ((left0[i])), (
(left0[i])) = ((left[i-n])), ((left[i-n])) = ((t))); n = ({ typeof
((int)(right0 - right1)) _a = ((int)(right0 - right1)); typeof
((int)(right1 - right)) _b = ((int)(right1 - right)); (_a <
_b) ? _a : _b; }); for( i = 0; i < n; i++ ) (((t)) = ((left
[i])), ((left[i])) = ((right0[i-n+1])), ((right0[i-n+1])) = (
(t))); n = (int)(left - left1); m = (int)(right1 - right); if
( n > 1 ) { if( m > 1 ) { if( n > m ) { stack[++sp].
lb = left0; stack[sp].ub = left0 + n - 1; left = right0 - m +
1, right = right0; } else { stack[++sp].lb = right0 - m + 1;
stack[sp].ub = right0; left = left0, right = left0 + n - 1; }
} else left = left0, right = left0 + n - 1; } else if( m >
1 ) left = right0 - m + 1, right = right0; else break; } } }
}
1420#undef less_than
1421
1422static int _ccv_nnc_graph_dot_tensor_multiview_count(const ccv_nnc_tensor_multiview_t* const mv)
1423{
1424 if (!CCV_IS_TENSOR_MULTIVIEW(mv)((*(int*)(mv)) & CCV_TENSOR_MULTIVIEW))
1425 return 1;
1426 const int count = mv->kind + mv->repeat;
1427 int i, c = 0;
1428 for (i = 0; i < count; i++)
1429 c += _ccv_nnc_graph_dot_tensor_multiview_count((ccv_nnc_tensor_multiview_t*)CCV_NNC_MULTIVIEW_DATA(mv)((mv)->_heap_data ? (mv)->_heap_data : (mv)->_inline_data
)[i]);
1430 return c;
1431}
1432
1433static void _ccv_nnc_graph_dot_tensor_multiview_tensor_dots(const ccv_nnc_tensor_multiview_t* const mv, ccv_nnc_tensor_dot_t* const tensor_dots, int* tensor_index)
1434{
1435 const int count = mv->kind + mv->repeat;
1436 int i;
1437 for (i = 0; i < count; i++)
1438 if (CCV_IS_TENSOR_MULTIVIEW(CCV_NNC_MULTIVIEW_DATA(mv)[i])((*(int*)(((mv)->_heap_data ? (mv)->_heap_data : (mv)->
_inline_data)[i])) & CCV_TENSOR_MULTIVIEW))
1439 _ccv_nnc_graph_dot_tensor_multiview_tensor_dots((ccv_nnc_tensor_multiview_t*)CCV_NNC_MULTIVIEW_DATA(mv)((mv)->_heap_data ? (mv)->_heap_data : (mv)->_inline_data
)[i], tensor_dots, tensor_index);
1440 else {
1441 tensor_dots[*tensor_index].name = *tensor_index;
1442 tensor_dots[*tensor_index].start_ptr = (uintptr_t)CCV_NNC_MULTIVIEW_DATA(mv)((mv)->_heap_data ? (mv)->_heap_data : (mv)->_inline_data
)[i]->data.u8;
1443 // Because tv's pointer will get updated, it is not correct in this case to have one tensor_ref.
1444 tensor_dots[*tensor_index].tensor_ref = tensor_dots[*tensor_index].start_ptr;
1445 const size_t dim_size = ccv_nnc_dimension_count(CCV_NNC_MULTIVIEW_DATA(mv)((mv)->_heap_data ? (mv)->_heap_data : (mv)->_inline_data
)[i]->info.dim) * CCV_GET_DATA_TYPE_SIZE(CCV_NNC_MULTIVIEW_DATA(mv)[i]->type)_ccv_get_data_type_size[((((mv)->_heap_data ? (mv)->_heap_data
: (mv)->_inline_data)[i]->type) & 0xFF000) >>
12];
1446 tensor_dots[*tensor_index].end_ptr = tensor_dots[*tensor_index].start_ptr + dim_size - 1;
1447 ++(*tensor_index);
1448 }
1449}
1450
1451static ccv_nnc_tensor_dot_recovery_t _ccv_nnc_graph_tensor_dot_recovery(const ccv_nnc_graph_t* const graph)
1452{
1453 int i, j;
1454 // Recover tensor relationships for all tensors referenced in the graph.
1455 // Most notably, we have to give these indexes, and find if they point to
1456 // the same memory region, and whether they overlap. These information
1457 // are lost since we converted from symbolic form to the execution form.
1458 // and here we do our best to recover because that is easier to understand
1459 // if we want to present the graph visually (also, we don't want to put this
1460 // information into the tensor or execution graph to avoid overhead, thus,
1461 // recovering is the best we can do).
1462 int tensor_count = 0;
1463 for (i = 0; i < graph->exec_info->rnum; i++)
1464 {
1465 ccv_nnc_graph_exec_info_t* exec_info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, i)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(i)));
1466 for (j = 0; j < exec_info->input_size; j++)
1467 if (exec_info->inputs[j])
1468 tensor_count += CCV_IS_TENSOR_MULTIVIEW(exec_info->inputs[j])((*(int*)(exec_info->inputs[j])) & CCV_TENSOR_MULTIVIEW
) ? _ccv_nnc_graph_dot_tensor_multiview_count((ccv_nnc_tensor_multiview_t*)exec_info->inputs[j]) : 1;
1469 for (j = 0; j < exec_info->output_size; j++)
1470 if (exec_info->outputs[j])
1471 tensor_count += CCV_IS_TENSOR_MULTIVIEW(exec_info->outputs[j])((*(int*)(exec_info->outputs[j])) & CCV_TENSOR_MULTIVIEW
) ? _ccv_nnc_graph_dot_tensor_multiview_count((ccv_nnc_tensor_multiview_t*)exec_info->outputs[j]) : 1;
1472 }
1473 ccv_nnc_tensor_dot_t* tensor_dots = tensor_count > 0 ? (ccv_nnc_tensor_dot_t*)ccmallocmalloc(sizeof(ccv_nnc_tensor_dot_t) * tensor_count) : 0;
1474 int k = 0;
1475 for (i = 0; i < graph->exec_info->rnum; i++)
1476 {
1477 ccv_nnc_graph_exec_info_t* exec_info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, i)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(i)));
1478 for (j = 0; j < exec_info->input_size; j++)
1479 {
1480 ccv_nnc_tensor_t* tensor = exec_info->inputs[j];
1481 if (!tensor)
1482 continue;
1483 if (CCV_IS_TENSOR_MULTIVIEW(tensor)((*(int*)(tensor)) & CCV_TENSOR_MULTIVIEW))
1484 _ccv_nnc_graph_dot_tensor_multiview_tensor_dots((ccv_nnc_tensor_multiview_t*)tensor, tensor_dots, &k);
1485 else {
1486 tensor_dots[k].name = k;
1487 tensor_dots[k].tensor_ref = (uintptr_t)tensor;
1488 tensor_dots[k].start_ptr = (uintptr_t)tensor->data.u8;
1489 size_t tensor_size;
1490 if (CCV_IS_TENSOR_VIEW(tensor)((*(int*)(tensor)) & CCV_TENSOR_VIEW))
1491 tensor_size = (size_t)((ccv_nnc_tensor_view_t*)(tensor))->stride[0] * tensor->info.dim[0] * CCV_GET_DATA_TYPE_SIZE(tensor->type)_ccv_get_data_type_size[((tensor->type) & 0xFF000) >>
12];
1492 else
1493 tensor_size = ccv_nnc_dimension_count(tensor->info.dim) * CCV_GET_DATA_TYPE_SIZE(tensor->type)_ccv_get_data_type_size[((tensor->type) & 0xFF000) >>
12];
1494 tensor_dots[k].end_ptr = tensor_dots[k].start_ptr + tensor_size - 1;
1495 ++k;
1496 }
1497 }
1498 for (j = 0; j < exec_info->output_size; j++)
1499 {
1500 ccv_nnc_tensor_t* tensor = exec_info->outputs[j];
1501 if (!tensor)
1502 continue;
1503 if (CCV_IS_TENSOR_MULTIVIEW(tensor)((*(int*)(tensor)) & CCV_TENSOR_MULTIVIEW))
1504 _ccv_nnc_graph_dot_tensor_multiview_tensor_dots((ccv_nnc_tensor_multiview_t*)tensor, tensor_dots, &k);
1505 else {
1506 tensor_dots[k].name = k;
1507 tensor_dots[k].tensor_ref = (uintptr_t)tensor;
1508 tensor_dots[k].start_ptr = (uintptr_t)tensor->data.u8;
1509 size_t tensor_size;
1510 if (CCV_IS_TENSOR_VIEW(tensor)((*(int*)(tensor)) & CCV_TENSOR_VIEW))
1511 tensor_size = (size_t)((ccv_nnc_tensor_view_t*)(tensor))->stride[0] * tensor->info.dim[0] * CCV_GET_DATA_TYPE_SIZE(tensor->type)_ccv_get_data_type_size[((tensor->type) & 0xFF000) >>
12];
1512 else
1513 tensor_size = ccv_nnc_dimension_count(tensor->info.dim) * CCV_GET_DATA_TYPE_SIZE(tensor->type)_ccv_get_data_type_size[((tensor->type) & 0xFF000) >>
12];
1514 tensor_dots[k].end_ptr = tensor_dots[k].start_ptr + tensor_size - 1;
1515 ++k;
1516 }
1517 }
1518 }
1519 tensor_count = k; // We may over count, now shrink.
1520 // To group overlap memory into one zone, we sort it by start ptr first (secondary by the tensor pointer).
1521 _ccv_nnc_tensor_dot_sort_by_ptr(tensor_dots, tensor_count, 0);
1522 int index = 0, zone = 0;
1523 uintptr_t tensor_ref = tensor_count > 0 ? tensor_dots[0].tensor_ref : 0;
1524 uintptr_t end_ptr = tensor_count > 0 ? tensor_dots[0].end_ptr : 0;
1525 // Then, it is trivial, we go by end ptr. If the next start ptr is still within the end ptr (start ptr <= end ptr),
1526 // they are the same zone.
1527 for (i = 0; i < tensor_count; i++)
1528 {
1529 if (tensor_dots[i].tensor_ref != tensor_ref)
1530 {
1531 tensor_ref = tensor_dots[i].tensor_ref;
1532 ++index;
1533 }
1534 if (tensor_dots[i].start_ptr > end_ptr)
1535 {
1536 end_ptr = ccv_max(end_ptr, tensor_dots[i].end_ptr)({ typeof (end_ptr) _a = (end_ptr); typeof (tensor_dots[i].end_ptr
) _b = (tensor_dots[i].end_ptr); (_a > _b) ? _a : _b; });
1537 ++zone;
1538 }
1539 tensor_dots[i].index = index;
1540 tensor_dots[i].zone = zone;
1541 }
1542 // We already have index and zone assigned, but the problem is that these are not very human interpretable (because
1543 // it follows the pointer from low to high, not the tensor creation order). The following code renamed both the index
1544 // and the zone so that it is much more understandable.
1545 const int index_count = index + 1;
1546 const int zone_count = zone + 1;
1547 int* remap = (int*)ccmallocmalloc(sizeof(int) * (tensor_count + index_count + zone_count));
1548 int* rename_index = remap + tensor_count;
1549 int* rename_zone = rename_index + index_count;
1550 for (i = 0; i < tensor_count; i++)
1551 remap[tensor_dots[i].name] = i;
1552 for (i = 0; i < index_count; i++)
1553 rename_index[i] = -1;
1554 for (i = 0; i < zone_count; i++)
1555 rename_zone[i] = -1;
1556 index = 0;
1557 zone = 0;
1558 for (i = 0; i < tensor_count; i++)
1559 {
1560 ccv_nnc_tensor_dot_t* tensor_dot = tensor_dots + remap[i];
1561 if (rename_index[tensor_dot->index] == -1)
1562 rename_index[tensor_dot->index] = index++;
1563 if (rename_zone[tensor_dot->zone] == -1)
1564 rename_zone[tensor_dot->zone] = zone++;
1565 }
1566 ccv_nnc_tensor_dot_recovery_t recovery = {
1567 .dots = tensor_dots,
1568 .remap = remap,
1569 .rename_index = rename_index,
1570 .rename_zone = rename_zone,
1571 };
1572 return recovery;
1573}
1574
1575static void _ccv_nnc_graph_tensor_dot_recovery_free(const ccv_nnc_tensor_dot_recovery_t recovery)
1576{
1577 ccfreefree(recovery.dots);
1578 ccfreefree(recovery.remap);
1579}
1580
1581static void _ccv_nnc_graph_dot_tensor_multiview_one(const ccv_nnc_tensor_multiview_t* const mv, const ccv_nnc_tensor_dot_recovery_t recovery, const int depth, int* tensor_index, FILE* out)
1582{
1583 const int count = mv->kind + mv->repeat;
1584 int i, j;
1585 fputs("|{", out);
1586 for (i = 0; i < count; i++)
1587 if (CCV_IS_TENSOR_MULTIVIEW(CCV_NNC_MULTIVIEW_DATA(mv)[i])((*(int*)(((mv)->_heap_data ? (mv)->_heap_data : (mv)->
_inline_data)[i])) & CCV_TENSOR_MULTIVIEW))
1588 {
1589 fprintf(out, "{%d", i);
1590 if (mv->kind == CCV_NNC_MULTIVIEW_K0N || (mv->kind == CCV_NNC_MULTIVIEW_K1N && i > 0))
1591 fputc('*', out); // Denotes that we loop on this.
1592 _ccv_nnc_graph_dot_tensor_multiview_one((ccv_nnc_tensor_multiview_t*)CCV_NNC_MULTIVIEW_DATA(mv)((mv)->_heap_data ? (mv)->_heap_data : (mv)->_inline_data
)[i], recovery, depth, tensor_index, out);
1593 if (i == count - 1)
1594 fputc('}', out);
1595 else
1596 fputs("}|", out);
1597 } else {
1598 fprintf(out, "{%d", i);
1599 if (mv->kind == CCV_NNC_MULTIVIEW_K0N || (mv->kind == CCV_NNC_MULTIVIEW_K1N && i > 0))
1600 fputc('*', out); // Denotes that we loop on this.
1601 const ccv_nnc_tensor_dot_t* const tensor_dot = recovery.dots + recovery.remap[*tensor_index];
1602 fprintf(out, "|zone%d", recovery.rename_zone[tensor_dot->zone]);
1603 for (j = 0; j < depth; j++)
1604 fputc('\'', out);
1605 uintptr_t aptr = (uintptr_t)CCV_NNC_MULTIVIEW_DATA(mv)((mv)->_heap_data ? (mv)->_heap_data : (mv)->_inline_data
)[i]->data.u8;
1606 // For the last one, we don't extend to full ainc.
1607 size_t dim_size = ccv_nnc_dimension_count(CCV_NNC_MULTIVIEW_DATA(mv)((mv)->_heap_data ? (mv)->_heap_data : (mv)->_inline_data
)[i]->info.dim) * CCV_GET_DATA_TYPE_SIZE(CCV_NNC_MULTIVIEW_DATA(mv)[i]->type)_ccv_get_data_type_size[((((mv)->_heap_data ? (mv)->_heap_data
: (mv)->_inline_data)[i]->type) & 0xFF000) >>
12];
1608 // Print out the range as well.
1609 fprintf(out, "|{%#010x|%#010x}", (uint32_t)aptr, (uint32_t)(aptr + dim_size - 1));
1610 ++(*tensor_index);
1611 if (i == count - 1)
1612 fputc('}', out);
1613 else
1614 fputs("}|", out);
1615 }
1616 fputc('}', out);
1617}
1618
1619static void _ccv_nnc_graph_dot_tensor_multiview(const ccv_nnc_tensor_multiview_t* const mv, const ccv_nnc_tensor_dot_recovery_t recovery, const int flags, const int depth, int* tensor_index, FILE* out)
1620{
1621 // if it has an alias pointer, or, it is a long form.
1622 if (flags == CCV_NNC_LONG_DOT_GRAPH)
1623 fputc('{', out);
1624 const ccv_nnc_tensor_dot_t* const tensor_dot = recovery.dots + recovery.remap[*tensor_index];
1625 fprintf(out, "multiview%d", recovery.rename_index[tensor_dot->index]);
1626 int i;
1627 for (i = 0; i < depth; i++) // Print subscription to denote depth.
1628 fputc('\'', out);
1629 if (CCV_GET_TAPE_ALLOC(mv->type)((mv->type) & CCV_TAPE_ALLOC))
1630 fputs(" (t)", out);
1631 if (flags == CCV_NNC_LONG_DOT_GRAPH)
1632 {
1633 _ccv_nnc_graph_dot_tensor_multiview_one(mv, recovery, depth, tensor_index, out);
1634 const ccv_nnc_tensor_t* root = (ccv_nnc_tensor_t*)mv;
1635 while (CCV_IS_TENSOR_MULTIVIEW(root)((*(int*)(root)) & CCV_TENSOR_MULTIVIEW))
1636 root = CCV_NNC_MULTIVIEW_DATA((ccv_nnc_tensor_multiview_t*)root)(((ccv_nnc_tensor_multiview_t*)root)->_heap_data ? ((ccv_nnc_tensor_multiview_t
*)root)->_heap_data : ((ccv_nnc_tensor_multiview_t*)root)->
_inline_data)[0];
1637 fprintf(out, "|%d", root->info.dim[0]);
1638 for (i = 1; i < CCV_NNC_MAX_DIM_ALLOC(12) && root->info.dim[i]; i++)
1639 fprintf(out, "x%d", root->info.dim[i]);
1640 fputc('}', out);
1641 } else
1642 *tensor_index += _ccv_nnc_graph_dot_tensor_multiview_count(mv);
1643}
1644
1645static void _ccv_nnc_graph_dot_node(const ccv_nnc_graph_exec_info_t* const exec_info, const ccv_nnc_graph_exec_schedule_t* const schd_info, const int exec_index, ccv_nnc_stream_context_t** const streams, const ccv_nnc_tensor_dot_recovery_t recovery, const int flags, const int depth, FILE* out, int* const tensor_index)
1646{
1647 fprintf(out, "node%d [shape=record,label=\"", exec_index);
1648 _ccv_nnc_graph_dot_exec(exec_index, exec_info, schd_info, streams, flags, out);
1649 int i;
1650 int k = *tensor_index;
1651 if (exec_info->input_size > 0)
1652 {
1653 fputs("|{Input", out);
1654 for (i = 0; i < exec_info->input_size; i++)
1655 if (exec_info->inputs[i])
1656 {
1657 fputc('|', out);
1658 if (CCV_IS_TENSOR_MULTIVIEW(exec_info->inputs[i])((*(int*)(exec_info->inputs[i])) & CCV_TENSOR_MULTIVIEW
))
1659 _ccv_nnc_graph_dot_tensor_multiview((ccv_nnc_tensor_multiview_t*)exec_info->inputs[i], recovery, flags, depth, &k, out);
1660 else {
1661 const ccv_nnc_tensor_dot_t* const tensor_dot = recovery.dots + recovery.remap[k];
1662 _ccv_nnc_graph_dot_tensor(recovery.rename_index[tensor_dot->index], exec_info->inputs[i], recovery.rename_zone[tensor_dot->zone], flags, depth, out);
1663 ++k;
1664 }
1665 } else
1666 fputs("|-", out);
1667 fputc('}', out);
1668 }
1669 if (exec_info->output_size > 0)
1670 {
1671 fputs("|{Output", out);
1672 for (i = 0; i < exec_info->output_size; i++)
1673 if (exec_info->outputs[i])
1674 {
1675 fputc('|', out);
1676 if (CCV_IS_TENSOR_MULTIVIEW(exec_info->outputs[i])((*(int*)(exec_info->outputs[i])) & CCV_TENSOR_MULTIVIEW
))
1677 _ccv_nnc_graph_dot_tensor_multiview((ccv_nnc_tensor_multiview_t*)exec_info->outputs[i], recovery, flags, depth, &k, out);
1678 else {
1679 const ccv_nnc_tensor_dot_t* const tensor_dot = recovery.dots + recovery.remap[k];
1680 _ccv_nnc_graph_dot_tensor(recovery.rename_index[tensor_dot->index], exec_info->outputs[i], recovery.rename_zone[tensor_dot->zone], flags, depth, out);
1681 ++k;
1682 }
1683 } else
1684 fputs("|-", out);
1685 fputc('}', out);
1686 }
1687 fputs("\"];\n", out);
1688 *tensor_index = k;
1689}
1690
1691static void _ccv_nnc_graph_dot_while_label(const ccv_nnc_graph_exec_info_t* const exec_info, const int exec_index, const ccv_nnc_tensor_dot_recovery_t recovery, const ccv_nnc_graph_t* const while_graph, const int flags, const int depth, FILE* out, int* tensor_index)
1692{
1693 int i;
1694 fprintf(out, "label=<<b>while%d </b>Command: ", exec_index);
1695 fputs(ccv_nnc_cmd_name(exec_info->cmd.cmd), out);
1696 fputs(">;\n", out);
1697 fprintf(out, "label%d [shape=record,label=\"{", exec_index);
1698 int k = *tensor_index;
1699 if (exec_info->input_size > 0)
1700 {
1701 fputs("{Input|{", out);
1702 for (i = 0; i < exec_info->input_size; i++)
1703 {
1704 if (i > 0)
1705 fputc('|', out);
1706 if (exec_info->inputs[i])
1707 {
1708 if (CCV_IS_TENSOR_MULTIVIEW(exec_info->inputs[i])((*(int*)(exec_info->inputs[i])) & CCV_TENSOR_MULTIVIEW
))
1709 _ccv_nnc_graph_dot_tensor_multiview((ccv_nnc_tensor_multiview_t*)exec_info->inputs[i], recovery, flags, depth, &k, out);
1710 else {
1711 const ccv_nnc_tensor_dot_t* const tensor_dot = recovery.dots + recovery.remap[k];
1712 _ccv_nnc_graph_dot_tensor(recovery.rename_index[tensor_dot->index], exec_info->inputs[i], recovery.rename_zone[tensor_dot->zone], flags, depth, out);
1713 ++k;
1714 }
1715 } else
1716 fputc('-', out);
1717 }
1718 fputs("}}", out);
1719 }
1720 if (exec_info->output_size > 0)
1721 {
1722 if (exec_info->input_size > 0)
1723 fputs("|", out);
1724 fputs("{Output|{", out);
1725 for (i = 0; i < exec_info->output_size; i++)
1726 {
1727 if (i > 0)
1728 fputc('|', out);
1729 if (exec_info->outputs[i])
1730 {
1731 if (CCV_IS_TENSOR_MULTIVIEW(exec_info->outputs[i])((*(int*)(exec_info->outputs[i])) & CCV_TENSOR_MULTIVIEW
))
1732 _ccv_nnc_graph_dot_tensor_multiview((ccv_nnc_tensor_multiview_t*)exec_info->outputs[i], recovery, flags, depth, &k, out);
1733 else {
1734 const ccv_nnc_tensor_dot_t* const tensor_dot = recovery.dots + recovery.remap[k];
1735 _ccv_nnc_graph_dot_tensor(recovery.rename_index[tensor_dot->index], exec_info->outputs[i], recovery.rename_zone[tensor_dot->zone], flags, depth, out);
1736 ++k;
1737 }
1738 } else
1739 fputc('-', out);
1740 }
1741 fputs("}}", out);
1742 }
1743 fputs("}\"];\n", out);
1744 *tensor_index = k;
1745}
1746
1747static void _ccv_nnc_graph_dot_case_of_label(const ccv_nnc_graph_exec_info_t* const exec_info, const int exec_index, const ccv_nnc_tensor_dot_recovery_t recovery, const int flags, const int depth, FILE* out, int* tensor_index)
1748{
1749 int i;
1750 fprintf(out, "label=<<b>caseof%d </b>Command: ", exec_index);
1751 fputs(ccv_nnc_cmd_name(exec_info->cmd.cmd), out);
1752 fputs(">;\n", out);
1753 fprintf(out, "label%d [shape=record,label=\"{", exec_index);
1754 int k = *tensor_index;
1755 if (exec_info->input_size > 0)
1756 {
1757 fputs("{Input|{", out);
1758 for (i = 0; i < exec_info->input_size; i++)
1759 {
1760 if (i > 0)
1761 fputc('|', out);
1762 if (exec_info->inputs[i])
1763 {
1764 if (CCV_IS_TENSOR_MULTIVIEW(exec_info->inputs[i])((*(int*)(exec_info->inputs[i])) & CCV_TENSOR_MULTIVIEW
))
1765 _ccv_nnc_graph_dot_tensor_multiview((ccv_nnc_tensor_multiview_t*)exec_info->inputs[i], recovery, flags, depth, &k, out);
1766 else {
1767 const ccv_nnc_tensor_dot_t* const tensor_dot = recovery.dots + recovery.remap[k];
1768 _ccv_nnc_graph_dot_tensor(recovery.rename_index[tensor_dot->index], exec_info->inputs[i], recovery.rename_zone[tensor_dot->zone], flags, depth, out);
1769 ++k;
1770 }
1771 } else
1772 fputc('-', out);
1773 }
1774 fputs("}}", out);
1775 }
1776 if (exec_info->output_size > 0)
1777 {
1778 if (exec_info->input_size > 0)
1779 fputs("|", out);
1780 fputs("{Output|{", out);
1781 for (i = 0; i < exec_info->output_size; i++)
1782 {
1783 if (i > 0)
1784 fputc('|', out);
1785 if (exec_info->outputs[i])
1786 {
1787 if (CCV_IS_TENSOR_MULTIVIEW(exec_info->outputs[i])((*(int*)(exec_info->outputs[i])) & CCV_TENSOR_MULTIVIEW
))
1788 _ccv_nnc_graph_dot_tensor_multiview((ccv_nnc_tensor_multiview_t*)exec_info->outputs[i], recovery, flags, depth, &k, out);
1789 else {
1790 const ccv_nnc_tensor_dot_t* const tensor_dot = recovery.dots + recovery.remap[k];
1791 _ccv_nnc_graph_dot_tensor(recovery.rename_index[tensor_dot->index], exec_info->outputs[i], recovery.rename_zone[tensor_dot->zone], flags, depth, out);
1792 ++k;
1793 }
1794 } else
1795 fputc('-', out);
1796 }
1797 fputs("}}", out);
1798 }
1799 fputs("}\"];\n", out);
1800 *tensor_index = k;
1801}
1802
1803static void _ccv_nnc_graph_dot_sub_graphs(const ccv_nnc_graph_exec_info_t* const exec_info, const ccv_nnc_tensor_dot_recovery_t p_recovery, const ccv_array_t* const sub_graphs, const int flags, const int depth, FILE* out, int* tensor_index, int* exec_index)
1804{
1805 if (exec_info->flags & CCV_NNC_GRAPH_EXEC_P_WHILE)
1806 {
1807 fprintf(out, "subgraph cluster%d {\nstyle=\"rounded\";\nnode%d [style=invisible];\n", *exec_index, *exec_index);
1808 const ccv_nnc_graph_t* const while_graph = *(ccv_nnc_graph_t**)ccv_array_get(sub_graphs, CCV_NNC_GRAPH_REF(exec_info)[0] - 1)((void*)(((char*)((sub_graphs)->data)) + (size_t)(sub_graphs
)->rsize * (size_t)(((exec_info)->_heap_graph_ref ? (exec_info
)->_heap_graph_ref : (exec_info)->_inline_graph_ref)[0]
- 1)));
1809 // Output this node info within this subgraph.
1810 _ccv_nnc_graph_dot_while_label(exec_info, *exec_index, p_recovery, while_graph, flags, depth - 1 /* Label all references to its level above. */, out, tensor_index);
1811 } else if (exec_info->flags & CCV_NNC_GRAPH_EXEC_CASE_OF) {
1812 fprintf(out, "subgraph cluster%d {\nstyle=\"rounded\";\nnode%d [style=invisible];\n", *exec_index, *exec_index);
1813 _ccv_nnc_graph_dot_case_of_label(exec_info, *exec_index, p_recovery, flags, depth - 1 /* Label all references to its level above. */, out, tensor_index);
1814 }
1815 ++(*exec_index);
1816 int p;
1817 for (p = 0; p < exec_info->graph_ref_size; p++)
1818 {
1819 if (exec_info->flags & CCV_NNC_GRAPH_EXEC_CASE_OF)
1820 {
1821 fprintf(out, "subgraph cluster%d {\nstyle=\"rounded\";\nnode%d [style=invisible];\nlabel=\"\"\n", *exec_index, *exec_index);
1822 ++(*exec_index);
1823 }
1824 const ccv_nnc_graph_t* const graph = *(ccv_nnc_graph_t**)ccv_array_get(sub_graphs, CCV_NNC_GRAPH_REF(exec_info)[p] - 1)((void*)(((char*)((sub_graphs)->data)) + (size_t)(sub_graphs
)->rsize * (size_t)(((exec_info)->_heap_graph_ref ? (exec_info
)->_heap_graph_ref : (exec_info)->_inline_graph_ref)[p]
- 1)));
1825 const ccv_nnc_graph_static_schedule_t* const schedule = graph->default_schedule;
1826 ccv_nnc_tensor_dot_recovery_t recovery = _ccv_nnc_graph_tensor_dot_recovery(graph);
1827 int i, j;
1828 int k = 0;
1829 int* node_id = (int*)ccmallocmalloc(sizeof(int) * graph->exec_info->rnum);
1830 // Output styles.
1831 for (i = 0; i < graph->exec_info->rnum; i++)
1832 {
1833 node_id[i] = *exec_index;
1834 ccv_nnc_graph_exec_info_t* exec_info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, i)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(i)));
1835 if (CCV_NNC_GRAPH_REF(exec_info)((exec_info)->_heap_graph_ref ? (exec_info)->_heap_graph_ref
: (exec_info)->_inline_graph_ref)[0])
1836 _ccv_nnc_graph_dot_sub_graphs(exec_info, recovery, graph->sub_graphs, flags, depth + 1, out, &k, exec_index);
1837 else {
1838 _ccv_nnc_graph_dot_node(exec_info,
1839 schedule ? (i < schedule->exec_info_size ? schedule->exec_info + i : 0) : 0,
1840 *exec_index, graph->streams, recovery, flags, depth, out, &k);
1841 ++(*exec_index);
1842 }
1843 }
1844 // Output connections.
1845 for (i = 0; i < graph->exec_info->rnum; i++)
1846 {
1847 ccv_nnc_graph_exec_info_t* exec_info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, i)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(i)));
1848 if (exec_info->outgoings)
1849 for (j = 0; j < exec_info->outgoings->rnum; j++)
1850 {
1851 const int outgoing_idx = *(int*)ccv_array_get(exec_info->outgoings, j)((void*)(((char*)((exec_info->outgoings)->data)) + (size_t
)(exec_info->outgoings)->rsize * (size_t)(j)));
1852 const ccv_nnc_graph_exec_info_t* const outgoing_info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, outgoing_idx)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(outgoing_idx)));
1853 // If both are sub-graphs, have both tail and head specified.
1854 if (CCV_NNC_GRAPH_REF(exec_info)((exec_info)->_heap_graph_ref ? (exec_info)->_heap_graph_ref
: (exec_info)->_inline_graph_ref)[0] && CCV_NNC_GRAPH_REF(outgoing_info)((outgoing_info)->_heap_graph_ref ? (outgoing_info)->_heap_graph_ref
: (outgoing_info)->_inline_graph_ref)[0])
1855 fprintf(out, "node%d -> node%d [ltail=cluster%d,lhead=cluster%d];\n", node_id[i], node_id[outgoing_idx], node_id[i], node_id[outgoing_idx]);
1856 else if (CCV_NNC_GRAPH_REF(exec_info)((exec_info)->_heap_graph_ref ? (exec_info)->_heap_graph_ref
: (exec_info)->_inline_graph_ref)[0] && !CCV_NNC_GRAPH_REF(outgoing_info)((outgoing_info)->_heap_graph_ref ? (outgoing_info)->_heap_graph_ref
: (outgoing_info)->_inline_graph_ref)[0])
1857 fprintf(out, "node%d -> node%d [ltail=cluster%d];\n", node_id[i], node_id[outgoing_idx], node_id[i]);
1858 else if (!CCV_NNC_GRAPH_REF(exec_info)((exec_info)->_heap_graph_ref ? (exec_info)->_heap_graph_ref
: (exec_info)->_inline_graph_ref)[0] && CCV_NNC_GRAPH_REF(outgoing_info)((outgoing_info)->_heap_graph_ref ? (outgoing_info)->_heap_graph_ref
: (outgoing_info)->_inline_graph_ref)[0])
1859 fprintf(out, "node%d -> node%d [lhead=cluster%d];\n", node_id[i], node_id[outgoing_idx], node_id[outgoing_idx]);
1860 else
1861 fprintf(out, "node%d -> node%d;\n", node_id[i], node_id[outgoing_idx]);
1862 }
1863 }
1864 fputs("}\n", out);
1865 _ccv_nnc_graph_tensor_dot_recovery_free(recovery);
1866 ccfreefree(node_id);
1867 }
1868 // Extra subgraph cluster.
1869 if (exec_info->flags & CCV_NNC_GRAPH_EXEC_CASE_OF)
1870 fputs("}\n", out);
1871}
1872
1873void ccv_nnc_graph_dot(const ccv_nnc_graph_t* const graph, const int flags, FILE* out)
1874{
1875 fputs("digraph G {\ncompound=true;\n", out);
1876 ccv_nnc_tensor_dot_recovery_t recovery = _ccv_nnc_graph_tensor_dot_recovery(graph);
1877 int i, j;
1878 int k = 0, c = 0;
1879 int* node_id = (int*)ccmallocmalloc(sizeof(int) * graph->exec_info->rnum);
1880 const ccv_nnc_graph_static_schedule_t* const schedule = graph->default_schedule;
1881 // Output styles.
1882 for (i = 0; i < graph->exec_info->rnum; i++)
1883 {
1884 node_id[i] = c;
1885 ccv_nnc_graph_exec_info_t* exec_info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, i)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(i)));
1886 if (CCV_NNC_GRAPH_REF(exec_info)((exec_info)->_heap_graph_ref ? (exec_info)->_heap_graph_ref
: (exec_info)->_inline_graph_ref)[0])
1887 _ccv_nnc_graph_dot_sub_graphs(exec_info, recovery, graph->sub_graphs, flags, 1, out, &k, &c);
1888 else {
1889 _ccv_nnc_graph_dot_node(exec_info,
1890 schedule ? (i < schedule->exec_info_size ? schedule->exec_info + i : 0) : 0,
1891 c, graph->streams, recovery, flags, 0, out, &k);
1892 ++c;
1893 }
1894 }
1895 // Output connections.
1896 for (i = 0; i < graph->exec_info->rnum; i++)
1897 {
1898 ccv_nnc_graph_exec_info_t* exec_info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, i)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(i)));
1899 if (exec_info->outgoings)
1900 for (j = 0; j < exec_info->outgoings->rnum; j++)
1901 {
1902 const int outgoing_idx = *(int*)ccv_array_get(exec_info->outgoings, j)((void*)(((char*)((exec_info->outgoings)->data)) + (size_t
)(exec_info->outgoings)->rsize * (size_t)(j)));
1903 const ccv_nnc_graph_exec_info_t* const outgoing_info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, outgoing_idx)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(outgoing_idx)));
1904 // If both are sub-graphs, have both tail and head specified.
1905 if (CCV_NNC_GRAPH_REF(exec_info)((exec_info)->_heap_graph_ref ? (exec_info)->_heap_graph_ref
: (exec_info)->_inline_graph_ref)[0] && CCV_NNC_GRAPH_REF(outgoing_info)((outgoing_info)->_heap_graph_ref ? (outgoing_info)->_heap_graph_ref
: (outgoing_info)->_inline_graph_ref)[0])
1906 fprintf(out, "node%d -> node%d [ltail=cluster%d,lhead=cluster%d];\n", node_id[i], node_id[outgoing_idx], node_id[i], node_id[outgoing_idx]);
1907 else if (CCV_NNC_GRAPH_REF(exec_info)((exec_info)->_heap_graph_ref ? (exec_info)->_heap_graph_ref
: (exec_info)->_inline_graph_ref)[0] && !CCV_NNC_GRAPH_REF(outgoing_info)((outgoing_info)->_heap_graph_ref ? (outgoing_info)->_heap_graph_ref
: (outgoing_info)->_inline_graph_ref)[0])
1908 fprintf(out, "node%d -> node%d [ltail=cluster%d];\n", node_id[i], node_id[outgoing_idx], node_id[i]);
1909 else if (!CCV_NNC_GRAPH_REF(exec_info)((exec_info)->_heap_graph_ref ? (exec_info)->_heap_graph_ref
: (exec_info)->_inline_graph_ref)[0] && CCV_NNC_GRAPH_REF(outgoing_info)((outgoing_info)->_heap_graph_ref ? (outgoing_info)->_heap_graph_ref
: (outgoing_info)->_inline_graph_ref)[0])
1910 fprintf(out, "node%d -> node%d [lhead=cluster%d];\n", node_id[i], node_id[outgoing_idx], node_id[outgoing_idx]);
1911 else
1912 fprintf(out, "node%d -> node%d;\n", node_id[i], node_id[outgoing_idx]);
1913 }
1914 }
1915 fputs("}\n", out);
1916 _ccv_nnc_graph_tensor_dot_recovery_free(recovery);
1917 ccfreefree(node_id);
1918}
1919
1920void ccv_nnc_graph_autotune(ccv_nnc_graph_t* const graph, const size_t max_workspace_size, const int flags, const ccv_nnc_graph_exec_t* const sources, const int source_size, const ccv_nnc_graph_exec_t* const destinations, const int destination_size)
1921{
1922 // exec current node, for synchronous CPU execution, no stream unit.
1923 int i;
1924#define visitor(node, idx, ...) \
1925 do { \
1926 if (node->cmd.cmd == CCV_NNC_NOOP) \
1927 continue; \
1928 if (node->cmd.cmd == CCV_NNC_GRAPH_FORWARD || node->cmd.cmd == CCV_NNC_GRAPH_BACKWARD) \
1929 for (i = 0; i < node->graph_ref_size; i++) \
1930 { \
1931 ccv_nnc_graph_t* sub_graph = *(ccv_nnc_graph_t**)ccv_array_get(graph->sub_graphs, CCV_NNC_GRAPH_REF(node)[i] - 1)((void*)(((char*)((graph->sub_graphs)->data)) + (size_t
)(graph->sub_graphs)->rsize * (size_t)(((node)->_heap_graph_ref
? (node)->_heap_graph_ref : (node)->_inline_graph_ref)
[i] - 1))); \
1932 ccv_nnc_graph_autotune(sub_graph, max_workspace_size, flags, 0, 0, 0, 0); \
1933 } \
1934 else { \
1935 /* Need to unwrap these tensors */ \
1936 for (i = 0; i < node->input_size + node->output_size; i++) \
1937 if (node->inputs[i] && CCV_IS_TENSOR_MULTIVIEW(node->inputs[i])((*(int*)(node->inputs[i])) & CCV_TENSOR_MULTIVIEW)) \
1938 node->inputs[i] = _ccv_nnc_any_tensor_from_tensor_multiview((ccv_nnc_tensor_multiview_t*)node->inputs[i]); \
1939 PRINT(CCV_CLI_VERBOSE, "%s [%d]: [%d] -> [%d]\n", ccv_nnc_cmd_name(node->cmd.cmd), idx, node->input_size, node->output_size)do { if ((CCV_CLI_VERBOSE & ccv_cli_get_output_levels()))
{ printf("%s [%d]: [%d] -> [%d]\n", ccv_nnc_cmd_name(node
->cmd.cmd), idx, node->input_size, node->output_size
); fflush(stdout); } } while (0); \
1940 for (i = 0; i < node->input_size; i++) \
1941 { \
1942 PRINT(CCV_CLI_VERBOSE, "|-> %d. %p (%p)", i + 1, node->inputs[i], (node->inputs[i] ? node->inputs[i]->data.u8 : 0))do { if ((CCV_CLI_VERBOSE & ccv_cli_get_output_levels()))
{ printf("|-> %d. %p (%p)", i + 1, node->inputs[i], (node
->inputs[i] ? node->inputs[i]->data.u8 : 0)); fflush
(stdout); } } while (0); \
1943 if (node->inputs[i] && CCV_CLI_OUTPUT_LEVEL_IS(CCV_CLI_VERBOSE)(CCV_CLI_VERBOSE & ccv_cli_get_output_levels())) \
1944 ccv_nnc_print_tensor_shape(node->inputs[i]); \
1945 PRINT(CCV_CLI_VERBOSE, "\n")do { if ((CCV_CLI_VERBOSE & ccv_cli_get_output_levels()))
{ printf("\n"); fflush(stdout); } } while (0); \
1946 } \
1947 for (i = 0; i < node->output_size; i++) \
1948 { \
1949 PRINT(CCV_CLI_VERBOSE, "|<- %d. %p (%p)", i + 1, node->outputs[i], (node->outputs[i] ? node->outputs[i]->data.u8 : 0))do { if ((CCV_CLI_VERBOSE & ccv_cli_get_output_levels()))
{ printf("|<- %d. %p (%p)", i + 1, node->outputs[i], (
node->outputs[i] ? node->outputs[i]->data.u8 : 0)); fflush
(stdout); } } while (0); \
1950 if (node->outputs[i] && CCV_CLI_OUTPUT_LEVEL_IS(CCV_CLI_VERBOSE)(CCV_CLI_VERBOSE & ccv_cli_get_output_levels())) \
1951 ccv_nnc_print_tensor_shape(node->outputs[i]); \
1952 PRINT(CCV_CLI_VERBOSE, "\n")do { if ((CCV_CLI_VERBOSE & ccv_cli_get_output_levels()))
{ printf("\n"); fflush(stdout); } } while (0); \
1953 } \
1954 node->cmd = ccv_nnc_cmd_autotune(node->cmd, max_workspace_size, node->hint, flags, node->inputs, node->input_size, node->outputs, node->output_size, 0); \
1955 } \
1956 } while (0)
1957 const ccv_nnc_graph_exec_t* const graph_sources = sources ? sources : (graph->sources ? (ccv_nnc_graph_exec_t*)ccv_array_get(graph->sources, 0)((void*)(((char*)((graph->sources)->data)) + (size_t)(graph
->sources)->rsize * (size_t)(0))): 0);
1958 const int graph_source_size = source_size ? source_size : (graph->sources ? graph->sources->rnum : 0);
1959 const ccv_nnc_graph_exec_t* const graph_destinations = destinations ? destinations : (graph->destinations ? (ccv_nnc_graph_exec_t*)ccv_array_get(graph->destinations, 0)((void*)(((char*)((graph->destinations)->data)) + (size_t
)(graph->destinations)->rsize * (size_t)(0))) : 0);
1960 const int graph_destination_size = destination_size ? destination_size : (graph->destinations ? graph->destinations->rnum : 0);
1961 CCV_NNC_GRAPH_VISIT(graph, (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, 0), graph->exec_info->rnum, graph_sources, graph_source_size, graph_destinations, graph_destination_size, 0, visitor)do { typedef struct { int8_t d; int8_t r; uint16_t c; int32_t
edges; } ccv_nnc_incoming_t; int _i_, _j_; int _incoming_edges_
= 0; for (_i_ = 0; _i_ < (graph->exec_info->rnum); _i_
++) _incoming_edges_ += (((ccv_nnc_graph_exec_info_t*)((void*
)(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_i_].outgoings) ? ((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_i_].outgoings
->rnum : 0; const int _heap_mem_ = ((graph->exec_info->
rnum) + _incoming_edges_ > 1024); ccv_nnc_incoming_t* _incomings_
; if (_heap_mem_) _incomings_ = (ccv_nnc_incoming_t*)malloc(sizeof
(ccv_nnc_incoming_t) * (graph->exec_info->rnum) + sizeof
(int32_t) * ((graph->exec_info->rnum) * 2 + _incoming_edges_
)); else _incomings_ = (ccv_nnc_incoming_t*)__builtin_alloca (
sizeof(ccv_nnc_incoming_t) * (graph->exec_info->rnum) +
sizeof(int32_t) * ((graph->exec_info->rnum) * 2 + _incoming_edges_
)); memset(_incomings_, 0, sizeof(ccv_nnc_incoming_t) * (graph
->exec_info->rnum)); int32_t* _exists_[2] = { (int32_t*
)(_incomings_ + (graph->exec_info->rnum)), (int32_t*)(_incomings_
+ (graph->exec_info->rnum)) + (graph->exec_info->
rnum), }; int32_t* const _edges_ = _exists_[1] + (graph->exec_info
->rnum); for (_i_ = 0; _i_ < (graph_source_size); _i_++
) { ((void) sizeof (((graph_sources)[_i_].graph == graph) ? 1
: 0), __extension__ ({ if ((graph_sources)[_i_].graph == graph
) ; else __assert_fail ("(graph_sources)[_i_].graph == graph"
, "ccv_nnc_graph.c", 1961, __extension__ __PRETTY_FUNCTION__)
; })); _incomings_[(graph_sources)[_i_].d].r = 1; _exists_[0]
[_i_] = (graph_sources)[_i_].d; } int _exist_size_[2] = { (graph_source_size
), 0, }; int _p_ = 0, _q_ = 1; while (_exist_size_[_p_] > 0
) { _exist_size_[_q_] = 0; for (_i_ = 0; _i_ < _exist_size_
[_p_]; _i_++) { const int32_t _idx_ = _exists_[_p_][_i_]; if (
_incomings_[_idx_].r != 1) continue; _incomings_[_idx_].r = 2
; if (((ccv_nnc_graph_exec_info_t*)((void*)(((char*)((graph->
exec_info)->data)) + (size_t)(graph->exec_info)->rsize
* (size_t)(0))))[_idx_].outgoings) for (_j_ = 0; _j_ < ((
ccv_nnc_graph_exec_info_t*)((void*)(((char*)((graph->exec_info
)->data)) + (size_t)(graph->exec_info)->rsize * (size_t
)(0))))[_idx_].outgoings->rnum; _j_++) { const int d = *(int
*)((void*)(((char*)((((ccv_nnc_graph_exec_info_t*)((void*)(((
char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings)->data
)) + (size_t)(((ccv_nnc_graph_exec_info_t*)((void*)(((char*)(
(graph->exec_info)->data)) + (size_t)(graph->exec_info
)->rsize * (size_t)(0))))[_idx_].outgoings)->rsize * (size_t
)(_j_))); ++_incomings_[d].c; if (_incomings_[d].r != 0) continue
; _incomings_[d].r = 1; ((void) sizeof ((_exist_size_[_q_] <
(graph->exec_info->rnum)) ? 1 : 0), __extension__ ({ if
(_exist_size_[_q_] < (graph->exec_info->rnum)) ; else
__assert_fail ("_exist_size_[_q_] < (graph->exec_info->rnum)"
, "ccv_nnc_graph.c", 1961, __extension__ __PRETTY_FUNCTION__)
; })); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_)); } for (
_i_ = 0; _i_ < (graph_source_size); _i_++) { ((void) sizeof
(((graph_sources)[_i_].graph == graph) ? 1 : 0), __extension__
({ if ((graph_sources)[_i_].graph == graph) ; else __assert_fail
("(graph_sources)[_i_].graph == graph", "ccv_nnc_graph.c", 1961
, __extension__ __PRETTY_FUNCTION__); })); _incomings_[(graph_sources
)[_i_].d].r = 3; _exists_[0][_i_] = (graph_sources)[_i_].d; }
_exist_size_[0] = (graph_source_size); _exist_size_[1] = 0; _p_
= 0, _q_ = 1; int _bump_ = 1; while (_exist_size_[_p_] > 0
) { _exist_size_[_q_] = 0; for (_i_ = 0; _i_ < _exist_size_
[_p_]; _i_++) { const int32_t _idx_ = _exists_[_p_][_i_]; if (
_incomings_[_idx_].r != 3) continue; _incomings_[_idx_].r = 4
; if (((ccv_nnc_graph_exec_info_t*)((void*)(((char*)((graph->
exec_info)->data)) + (size_t)(graph->exec_info)->rsize
* (size_t)(0))))[_idx_].outgoings) for (_j_ = 0; _j_ < ((
ccv_nnc_graph_exec_info_t*)((void*)(((char*)((graph->exec_info
)->data)) + (size_t)(graph->exec_info)->rsize * (size_t
)(0))))[_idx_].outgoings->rnum; _j_++) { const int d = *(int
*)((void*)(((char*)((((ccv_nnc_graph_exec_info_t*)((void*)(((
char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings)->data
)) + (size_t)(((ccv_nnc_graph_exec_info_t*)((void*)(((char*)(
(graph->exec_info)->data)) + (size_t)(graph->exec_info
)->rsize * (size_t)(0))))[_idx_].outgoings)->rsize * (size_t
)(_j_))); if (_incomings_[d].edges == 0) { _incomings_[d].edges
= _bump_; _bump_ += _incomings_[d].c; _incomings_[d].c = 0; }
_edges_[_incomings_[d].edges - 1 + _incomings_[d].c] = _idx_
; ++_incomings_[d].c; if (_incomings_[d].r != 2) continue; _incomings_
[d].r = 3; ((void) sizeof ((_exist_size_[_q_] < (graph->
exec_info->rnum)) ? 1 : 0), __extension__ ({ if (_exist_size_
[_q_] < (graph->exec_info->rnum)) ; else __assert_fail
("_exist_size_[_q_] < (graph->exec_info->rnum)", "ccv_nnc_graph.c"
, 1961, __extension__ __PRETTY_FUNCTION__); })); _exists_[_q_
][_exist_size_[_q_]] = d; ++_exist_size_[_q_]; } } ((_i_) = (
_p_), (_p_) = (_q_), (_q_) = (_i_)); } for (_i_ = 0; _i_ <
(graph_destination_size); _i_++) { ((void) sizeof (((graph_destinations
)[_i_].graph == graph) ? 1 : 0), __extension__ ({ if ((graph_destinations
)[_i_].graph == graph) ; else __assert_fail ("(graph_destinations)[_i_].graph == graph"
, "ccv_nnc_graph.c", 1961, __extension__ __PRETTY_FUNCTION__)
; })); _incomings_[(graph_destinations)[_i_].d].r = 5; _exists_
[0][_i_] = (graph_destinations)[_i_].d; } _exist_size_[0] = (
graph_destination_size); _exist_size_[1] = 0; _p_ = 0, _q_ = 1
; while (_exist_size_[_p_] > 0) { _exist_size_[_q_] = 0; for
(_i_ = 0; _i_ < _exist_size_[_p_]; _i_++) { const int32_t
_idx_ = _exists_[_p_][_i_]; if (_incomings_[_idx_].r != 5) continue
; _incomings_[_idx_].r = 6; if (_incomings_[_idx_].edges >
0) for (_j_ = 0; _j_ < _incomings_[_idx_].c; _j_++) { const
int d = _edges_[_incomings_[_idx_].edges - 1 + _j_]; if (_incomings_
[d].r != 4) continue; _incomings_[d].r = 5; ((void) sizeof ((
_exist_size_[_q_] < (graph->exec_info->rnum)) ? 1 : 0
), __extension__ ({ if (_exist_size_[_q_] < (graph->exec_info
->rnum)) ; else __assert_fail ("_exist_size_[_q_] < (graph->exec_info->rnum)"
, "ccv_nnc_graph.c", 1961, __extension__ __PRETTY_FUNCTION__)
; })); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_)); } for (
_i_ = 0; _i_ < (graph_destination_size); _i_++) { ((void) sizeof
(((graph_destinations)[_i_].graph == graph) ? 1 : 0), __extension__
({ if ((graph_destinations)[_i_].graph == graph) ; else __assert_fail
("(graph_destinations)[_i_].graph == graph", "ccv_nnc_graph.c"
, 1961, __extension__ __PRETTY_FUNCTION__); })); _incomings_[
(graph_destinations)[_i_].d].d = 1; } for (_i_ = 0; _i_ < (
graph_source_size); _i_++) { ((void) sizeof (((graph_sources)
[_i_].graph == graph) ? 1 : 0), __extension__ ({ if ((graph_sources
)[_i_].graph == graph) ; else __assert_fail ("(graph_sources)[_i_].graph == graph"
, "ccv_nnc_graph.c", 1961, __extension__ __PRETTY_FUNCTION__)
; })); _exists_[0][_i_] = (graph_sources)[_i_].d; } _p_ = 0; _q_
= 1; _exist_size_[0] = (graph_source_size); _exist_size_[1] =
0; int _d_ = 0; while (_exist_size_[_p_] > 0) { _exist_size_
[_q_] = 0; for (_i_ = 0; _i_ < _exist_size_[_p_];) { const
int32_t _idx_ = _exists_[_p_][_i_]; visitor((((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0)))) + _idx_), (
_idx_), (_incomings_[_idx_].d)); if (_incomings_[_idx_].d) { ++
_d_; _incomings_[_idx_].r = 7; } if (((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
) { if (((ccv_nnc_graph_exec_info_t*)((void*)(((char*)((graph
->exec_info)->data)) + (size_t)(graph->exec_info)->
rsize * (size_t)(0))))[_idx_].outgoings->rnum == 1) { const
int d = *(int*)((void*)(((char*)((((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
)->data)) + (size_t)(((ccv_nnc_graph_exec_info_t*)((void*)
(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings)->rsize
* (size_t)(0))); --_incomings_[d].c; if (_incomings_[d].c ==
0 && _incomings_[d].r == 6 && _d_ < (graph_destination_size
)) { _exists_[_p_][_i_] = d; continue; } } else for (_j_ = 0;
_j_ < ((ccv_nnc_graph_exec_info_t*)((void*)(((char*)((graph
->exec_info)->data)) + (size_t)(graph->exec_info)->
rsize * (size_t)(0))))[_idx_].outgoings->rnum; _j_++) { const
int d = *(int*)((void*)(((char*)((((ccv_nnc_graph_exec_info_t
*)((void*)(((char*)((graph->exec_info)->data)) + (size_t
)(graph->exec_info)->rsize * (size_t)(0))))[_idx_].outgoings
)->data)) + (size_t)(((ccv_nnc_graph_exec_info_t*)((void*)
(((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0))))[_idx_].outgoings)->rsize
* (size_t)(_j_))); --_incomings_[d].c; if (_incomings_[d].c ==
0 && _incomings_[d].r == 6 && _d_ < (graph_destination_size
)) { ((void) sizeof ((_exist_size_[_q_] < (graph->exec_info
->rnum)) ? 1 : 0), __extension__ ({ if (_exist_size_[_q_] <
(graph->exec_info->rnum)) ; else __assert_fail ("_exist_size_[_q_] < (graph->exec_info->rnum)"
, "ccv_nnc_graph.c", 1961, __extension__ __PRETTY_FUNCTION__)
; })); _exists_[_q_][_exist_size_[_q_]] = d; ++_exist_size_[_q_
]; } } } ++_i_; } ((_i_) = (_p_), (_p_) = (_q_), (_q_) = (_i_
)); } for (_i_ = 0; _i_ < (graph_destination_size); _i_++)
{ ((void) sizeof (((graph_destinations)[_i_].graph == graph)
? 1 : 0), __extension__ ({ if ((graph_destinations)[_i_].graph
== graph) ; else __assert_fail ("(graph_destinations)[_i_].graph == graph"
, "ccv_nnc_graph.c", 1961, __extension__ __PRETTY_FUNCTION__)
; })); if (_incomings_[(graph_destinations)[_i_].d].r == 7) continue
; if (!(0)) { ((void) sizeof ((_incomings_[(graph_destinations
)[_i_].d].c == 0) ? 1 : 0), __extension__ ({ if (_incomings_[
(graph_destinations)[_i_].d].c == 0) ; else __assert_fail ("_incomings_[(graph_destinations)[_i_].d].c == 0"
, "ccv_nnc_graph.c", 1961, __extension__ __PRETTY_FUNCTION__)
; })); } else if (_incomings_[(graph_destinations)[_i_].d].c >
0) continue; visitor((((ccv_nnc_graph_exec_info_t*)((void*)(
((char*)((graph->exec_info)->data)) + (size_t)(graph->
exec_info)->rsize * (size_t)(0)))) + (graph_destinations)[
_i_].d), ((graph_destinations)[_i_].d), (_incomings_[(graph_destinations
)[_i_].d].d)); } if (_heap_mem_) free(_incomings_); } while (
0);;
1962#undef visitor
1963}
1964
1965void ccv_nnc_graph_free(ccv_nnc_graph_t* const graph)
1966{
1967 int i, j;
1968 for (i = 0; i < graph->exec_info->rnum; i++)
1969 {
1970 ccv_nnc_graph_exec_info_t *info = (ccv_nnc_graph_exec_info_t*)ccv_array_get(graph->exec_info, i)((void*)(((char*)((graph->exec_info)->data)) + (size_t)
(graph->exec_info)->rsize * (size_t)(i)));
1971 if (info->_heap_graph_ref)
1972 ccfreefree(info->_heap_graph_ref);
1973 ccv_array_t* outgoings = info->outgoings;
1974 if (outgoings)
1975 ccv_array_free(outgoings);
1976 // We allocate inputs & outputs in continuous fashion, therefore, only need to free the input array.
1977 if (info->inputs)
1978 ccfreefree(info->inputs);
1979 if (info->input_flags)
1980 ccfreefree(info->input_flags);
1981 if (info->updates)
1982 ccfreefree(info->updates);
1983 if ((info->flags & CCV_NNC_GRAPH_EXEC_P_WHILE) && info->p_while.inputs)
1984 ccfreefree(info->p_while.inputs);
1985 }
1986 if (graph->tensor_wraps)
1987 {
1988 for (i = 0; i < graph->tensor_wraps->rnum; i++)
1989 {
1990 ccv_nnc_graph_tensor_wrap_array_t* const tensor_wrap_array = *(ccv_nnc_graph_tensor_wrap_array_t**)ccv_array_get(graph->tensor_wraps, i)((void*)(((char*)((graph->tensor_wraps)->data)) + (size_t
)(graph->tensor_wraps)->rsize * (size_t)(i)));
1991 if (tensor_wrap_array)
1992 {
1993 for (j = 0; j < tensor_wrap_array->size; j++)
1994 _ccv_nnc_graph_tensor_wrap_free(tensor_wrap_array->tensor_wraps[j]);
1995 ccfreefree(tensor_wrap_array);
1996 }
1997 }
1998 ccv_array_free(graph->tensor_wraps);
1999 }
2000 if (graph->tensor_wraps_refs)
2001 ccv_array_free(graph->tensor_wraps_refs);
2002 if (graph->breakpoints)
2003 ccfreefree(graph->breakpoints);
2004 if (graph->sources)
2005 ccv_array_free(graph->sources);
2006 if (graph->destinations)
2007 ccv_array_free(graph->destinations);
2008 if (graph->default_schedule)
2009 ccv_nnc_graph_static_schedule_free(graph->default_schedule);
2010 if (graph->streams)
2011 {
2012 // If the graph has parent graph, the default stream is allocated by the parent graph, we need to skip.
2013 if (!graph->p)
2014 ccv_nnc_stream_context_free(graph->streams[0]);
2015 for (i = 1; i < graph->stream_size; i++)
2016 ccv_nnc_stream_context_free(graph->streams[i]);
2017 ccfreefree(graph->streams);
2018 }
2019 if (graph->block_stream_tasks)
2020 ccfreefree(graph->block_stream_tasks);
2021 if (graph->signals)
2022 {
2023 for (i = 0; i < graph->signal_size; i++)
2024 ccv_nnc_stream_signal_free(graph->signals[i]);
2025 ccfreefree(graph->signals);
2026 }
2027 if (graph->carry_overs)
2028 {
2029 for (i = 0; i < graph->carry_overs->rnum; i++)
2030 {
2031 ccv_nnc_graph_tensor_carry_over_t* const carry_over = (ccv_nnc_graph_tensor_carry_over_t*)ccv_array_get(graph->carry_overs, i)((void*)(((char*)((graph->carry_overs)->data)) + (size_t
)(graph->carry_overs)->rsize * (size_t)(i)));
2032 _ccv_nnc_graph_tensor_wrap_free(carry_over->from);
2033 _ccv_nnc_graph_tensor_wrap_free(carry_over->to);
2034 }
2035 ccv_array_free(graph->carry_overs);
2036 }
2037 if (graph->sub_graphs)
2038 {
2039 for (i = 0; i < graph->sub_graphs->rnum; i++)
2040 ccv_nnc_graph_free(*(ccv_nnc_graph_t**)ccv_array_get(graph->sub_graphs, i)((void*)(((char*)((graph->sub_graphs)->data)) + (size_t
)(graph->sub_graphs)->rsize * (size_t)(i))));
2041 ccv_array_free(graph->sub_graphs);
2042 }
2043 ccv_array_free(graph->exec_info);
2044 if (graph->buffer)
2045 ccfreefree(graph->buffer);
2046 ccfreefree(graph);
2047}