1 // clang-format off
2 // Generated file (from: dequantize_v1_2.mod.py). Do not edit
CreateModel(Model * model)3 void CreateModel(Model *model) {
4 OperandType type0(Type::TENSOR_QUANT8_ASYMM, {10}, 0.5f, 127);
5 OperandType type1(Type::TENSOR_FLOAT32, {10});
6 // Phase 1, operands
7 auto input0 = model->addOperand(&type0);
8 auto output0 = model->addOperand(&type1);
9 // Phase 2, operations
10 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input0}, {output0});
11 // Phase 3, inputs and outputs
12 model->identifyInputsAndOutputs(
13 {input0},
14 {output0});
15 assert(model->isValid());
16 }
17
is_ignored(int i)18 inline bool is_ignored(int i) {
19 static std::set<int> ignore = {};
20 return ignore.find(i) != ignore.end();
21 }
22
CreateModel_relaxed(Model * model)23 void CreateModel_relaxed(Model *model) {
24 OperandType type0(Type::TENSOR_QUANT8_ASYMM, {10}, 0.5f, 127);
25 OperandType type1(Type::TENSOR_FLOAT32, {10});
26 // Phase 1, operands
27 auto input0 = model->addOperand(&type0);
28 auto output0 = model->addOperand(&type1);
29 // Phase 2, operations
30 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input0}, {output0});
31 // Phase 3, inputs and outputs
32 model->identifyInputsAndOutputs(
33 {input0},
34 {output0});
35 // Phase 4: set relaxed execution
36 model->relaxComputationFloat32toFloat16(true);
37 assert(model->isValid());
38 }
39
is_ignored_relaxed(int i)40 inline bool is_ignored_relaxed(int i) {
41 static std::set<int> ignore = {};
42 return ignore.find(i) != ignore.end();
43 }
44
CreateModel_float16(Model * model)45 void CreateModel_float16(Model *model) {
46 OperandType type0(Type::TENSOR_QUANT8_ASYMM, {10}, 0.5f, 127);
47 OperandType type25(Type::TENSOR_FLOAT16, {10});
48 // Phase 1, operands
49 auto input0 = model->addOperand(&type0);
50 auto output0 = model->addOperand(&type25);
51 // Phase 2, operations
52 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input0}, {output0});
53 // Phase 3, inputs and outputs
54 model->identifyInputsAndOutputs(
55 {input0},
56 {output0});
57 assert(model->isValid());
58 }
59
is_ignored_float16(int i)60 inline bool is_ignored_float16(int i) {
61 static std::set<int> ignore = {};
62 return ignore.find(i) != ignore.end();
63 }
64
CreateModel_dynamic_output_shape(Model * model)65 void CreateModel_dynamic_output_shape(Model *model) {
66 OperandType type0(Type::TENSOR_QUANT8_ASYMM, {10}, 0.5f, 127);
67 OperandType type26(Type::TENSOR_FLOAT32, {0});
68 // Phase 1, operands
69 auto input0 = model->addOperand(&type0);
70 auto output0 = model->addOperand(&type26);
71 // Phase 2, operations
72 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input0}, {output0});
73 // Phase 3, inputs and outputs
74 model->identifyInputsAndOutputs(
75 {input0},
76 {output0});
77 assert(model->isValid());
78 }
79
is_ignored_dynamic_output_shape(int i)80 inline bool is_ignored_dynamic_output_shape(int i) {
81 static std::set<int> ignore = {};
82 return ignore.find(i) != ignore.end();
83 }
84
CreateModel_dynamic_output_shape_relaxed(Model * model)85 void CreateModel_dynamic_output_shape_relaxed(Model *model) {
86 OperandType type0(Type::TENSOR_QUANT8_ASYMM, {10}, 0.5f, 127);
87 OperandType type26(Type::TENSOR_FLOAT32, {0});
88 // Phase 1, operands
89 auto input0 = model->addOperand(&type0);
90 auto output0 = model->addOperand(&type26);
91 // Phase 2, operations
92 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input0}, {output0});
93 // Phase 3, inputs and outputs
94 model->identifyInputsAndOutputs(
95 {input0},
96 {output0});
97 // Phase 4: set relaxed execution
98 model->relaxComputationFloat32toFloat16(true);
99 assert(model->isValid());
100 }
101
is_ignored_dynamic_output_shape_relaxed(int i)102 inline bool is_ignored_dynamic_output_shape_relaxed(int i) {
103 static std::set<int> ignore = {};
104 return ignore.find(i) != ignore.end();
105 }
106
CreateModel_dynamic_output_shape_float16(Model * model)107 void CreateModel_dynamic_output_shape_float16(Model *model) {
108 OperandType type0(Type::TENSOR_QUANT8_ASYMM, {10}, 0.5f, 127);
109 OperandType type27(Type::TENSOR_FLOAT16, {0});
110 // Phase 1, operands
111 auto input0 = model->addOperand(&type0);
112 auto output0 = model->addOperand(&type27);
113 // Phase 2, operations
114 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input0}, {output0});
115 // Phase 3, inputs and outputs
116 model->identifyInputsAndOutputs(
117 {input0},
118 {output0});
119 assert(model->isValid());
120 }
121
is_ignored_dynamic_output_shape_float16(int i)122 inline bool is_ignored_dynamic_output_shape_float16(int i) {
123 static std::set<int> ignore = {};
124 return ignore.find(i) != ignore.end();
125 }
126
CreateModel_2(Model * model)127 void CreateModel_2(Model *model) {
128 OperandType type2(Type::TENSOR_QUANT8_ASYMM, {2, 5}, 0.5f, 127);
129 OperandType type3(Type::TENSOR_FLOAT32, {2, 5});
130 // Phase 1, operands
131 auto input01 = model->addOperand(&type2);
132 auto output01 = model->addOperand(&type3);
133 // Phase 2, operations
134 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input01}, {output01});
135 // Phase 3, inputs and outputs
136 model->identifyInputsAndOutputs(
137 {input01},
138 {output01});
139 assert(model->isValid());
140 }
141
is_ignored_2(int i)142 inline bool is_ignored_2(int i) {
143 static std::set<int> ignore = {};
144 return ignore.find(i) != ignore.end();
145 }
146
CreateModel_relaxed_2(Model * model)147 void CreateModel_relaxed_2(Model *model) {
148 OperandType type2(Type::TENSOR_QUANT8_ASYMM, {2, 5}, 0.5f, 127);
149 OperandType type3(Type::TENSOR_FLOAT32, {2, 5});
150 // Phase 1, operands
151 auto input01 = model->addOperand(&type2);
152 auto output01 = model->addOperand(&type3);
153 // Phase 2, operations
154 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input01}, {output01});
155 // Phase 3, inputs and outputs
156 model->identifyInputsAndOutputs(
157 {input01},
158 {output01});
159 // Phase 4: set relaxed execution
160 model->relaxComputationFloat32toFloat16(true);
161 assert(model->isValid());
162 }
163
is_ignored_relaxed_2(int i)164 inline bool is_ignored_relaxed_2(int i) {
165 static std::set<int> ignore = {};
166 return ignore.find(i) != ignore.end();
167 }
168
CreateModel_float16_2(Model * model)169 void CreateModel_float16_2(Model *model) {
170 OperandType type2(Type::TENSOR_QUANT8_ASYMM, {2, 5}, 0.5f, 127);
171 OperandType type28(Type::TENSOR_FLOAT16, {2, 5});
172 // Phase 1, operands
173 auto input01 = model->addOperand(&type2);
174 auto output01 = model->addOperand(&type28);
175 // Phase 2, operations
176 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input01}, {output01});
177 // Phase 3, inputs and outputs
178 model->identifyInputsAndOutputs(
179 {input01},
180 {output01});
181 assert(model->isValid());
182 }
183
is_ignored_float16_2(int i)184 inline bool is_ignored_float16_2(int i) {
185 static std::set<int> ignore = {};
186 return ignore.find(i) != ignore.end();
187 }
188
CreateModel_dynamic_output_shape_2(Model * model)189 void CreateModel_dynamic_output_shape_2(Model *model) {
190 OperandType type2(Type::TENSOR_QUANT8_ASYMM, {2, 5}, 0.5f, 127);
191 OperandType type29(Type::TENSOR_FLOAT32, {0, 0});
192 // Phase 1, operands
193 auto input01 = model->addOperand(&type2);
194 auto output01 = model->addOperand(&type29);
195 // Phase 2, operations
196 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input01}, {output01});
197 // Phase 3, inputs and outputs
198 model->identifyInputsAndOutputs(
199 {input01},
200 {output01});
201 assert(model->isValid());
202 }
203
is_ignored_dynamic_output_shape_2(int i)204 inline bool is_ignored_dynamic_output_shape_2(int i) {
205 static std::set<int> ignore = {};
206 return ignore.find(i) != ignore.end();
207 }
208
CreateModel_dynamic_output_shape_relaxed_2(Model * model)209 void CreateModel_dynamic_output_shape_relaxed_2(Model *model) {
210 OperandType type2(Type::TENSOR_QUANT8_ASYMM, {2, 5}, 0.5f, 127);
211 OperandType type29(Type::TENSOR_FLOAT32, {0, 0});
212 // Phase 1, operands
213 auto input01 = model->addOperand(&type2);
214 auto output01 = model->addOperand(&type29);
215 // Phase 2, operations
216 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input01}, {output01});
217 // Phase 3, inputs and outputs
218 model->identifyInputsAndOutputs(
219 {input01},
220 {output01});
221 // Phase 4: set relaxed execution
222 model->relaxComputationFloat32toFloat16(true);
223 assert(model->isValid());
224 }
225
is_ignored_dynamic_output_shape_relaxed_2(int i)226 inline bool is_ignored_dynamic_output_shape_relaxed_2(int i) {
227 static std::set<int> ignore = {};
228 return ignore.find(i) != ignore.end();
229 }
230
CreateModel_dynamic_output_shape_float16_2(Model * model)231 void CreateModel_dynamic_output_shape_float16_2(Model *model) {
232 OperandType type2(Type::TENSOR_QUANT8_ASYMM, {2, 5}, 0.5f, 127);
233 OperandType type30(Type::TENSOR_FLOAT16, {0, 0});
234 // Phase 1, operands
235 auto input01 = model->addOperand(&type2);
236 auto output01 = model->addOperand(&type30);
237 // Phase 2, operations
238 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input01}, {output01});
239 // Phase 3, inputs and outputs
240 model->identifyInputsAndOutputs(
241 {input01},
242 {output01});
243 assert(model->isValid());
244 }
245
is_ignored_dynamic_output_shape_float16_2(int i)246 inline bool is_ignored_dynamic_output_shape_float16_2(int i) {
247 static std::set<int> ignore = {};
248 return ignore.find(i) != ignore.end();
249 }
250
CreateModel_3(Model * model)251 void CreateModel_3(Model *model) {
252 OperandType type4(Type::TENSOR_QUANT8_SYMM, {2, 2, 2}, 0.5f, 0);
253 OperandType type5(Type::TENSOR_FLOAT32, {2, 2, 2});
254 // Phase 1, operands
255 auto input02 = model->addOperand(&type4);
256 auto output02 = model->addOperand(&type5);
257 // Phase 2, operations
258 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input02}, {output02});
259 // Phase 3, inputs and outputs
260 model->identifyInputsAndOutputs(
261 {input02},
262 {output02});
263 assert(model->isValid());
264 }
265
is_ignored_3(int i)266 inline bool is_ignored_3(int i) {
267 static std::set<int> ignore = {};
268 return ignore.find(i) != ignore.end();
269 }
270
CreateModel_relaxed_3(Model * model)271 void CreateModel_relaxed_3(Model *model) {
272 OperandType type4(Type::TENSOR_QUANT8_SYMM, {2, 2, 2}, 0.5f, 0);
273 OperandType type5(Type::TENSOR_FLOAT32, {2, 2, 2});
274 // Phase 1, operands
275 auto input02 = model->addOperand(&type4);
276 auto output02 = model->addOperand(&type5);
277 // Phase 2, operations
278 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input02}, {output02});
279 // Phase 3, inputs and outputs
280 model->identifyInputsAndOutputs(
281 {input02},
282 {output02});
283 // Phase 4: set relaxed execution
284 model->relaxComputationFloat32toFloat16(true);
285 assert(model->isValid());
286 }
287
is_ignored_relaxed_3(int i)288 inline bool is_ignored_relaxed_3(int i) {
289 static std::set<int> ignore = {};
290 return ignore.find(i) != ignore.end();
291 }
292
CreateModel_float16_3(Model * model)293 void CreateModel_float16_3(Model *model) {
294 OperandType type31(Type::TENSOR_FLOAT16, {2, 2, 2});
295 OperandType type4(Type::TENSOR_QUANT8_SYMM, {2, 2, 2}, 0.5f, 0);
296 // Phase 1, operands
297 auto input02 = model->addOperand(&type4);
298 auto output02 = model->addOperand(&type31);
299 // Phase 2, operations
300 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input02}, {output02});
301 // Phase 3, inputs and outputs
302 model->identifyInputsAndOutputs(
303 {input02},
304 {output02});
305 assert(model->isValid());
306 }
307
is_ignored_float16_3(int i)308 inline bool is_ignored_float16_3(int i) {
309 static std::set<int> ignore = {};
310 return ignore.find(i) != ignore.end();
311 }
312
CreateModel_dynamic_output_shape_3(Model * model)313 void CreateModel_dynamic_output_shape_3(Model *model) {
314 OperandType type32(Type::TENSOR_FLOAT32, {0, 0, 0});
315 OperandType type4(Type::TENSOR_QUANT8_SYMM, {2, 2, 2}, 0.5f, 0);
316 // Phase 1, operands
317 auto input02 = model->addOperand(&type4);
318 auto output02 = model->addOperand(&type32);
319 // Phase 2, operations
320 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input02}, {output02});
321 // Phase 3, inputs and outputs
322 model->identifyInputsAndOutputs(
323 {input02},
324 {output02});
325 assert(model->isValid());
326 }
327
is_ignored_dynamic_output_shape_3(int i)328 inline bool is_ignored_dynamic_output_shape_3(int i) {
329 static std::set<int> ignore = {};
330 return ignore.find(i) != ignore.end();
331 }
332
CreateModel_dynamic_output_shape_relaxed_3(Model * model)333 void CreateModel_dynamic_output_shape_relaxed_3(Model *model) {
334 OperandType type32(Type::TENSOR_FLOAT32, {0, 0, 0});
335 OperandType type4(Type::TENSOR_QUANT8_SYMM, {2, 2, 2}, 0.5f, 0);
336 // Phase 1, operands
337 auto input02 = model->addOperand(&type4);
338 auto output02 = model->addOperand(&type32);
339 // Phase 2, operations
340 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input02}, {output02});
341 // Phase 3, inputs and outputs
342 model->identifyInputsAndOutputs(
343 {input02},
344 {output02});
345 // Phase 4: set relaxed execution
346 model->relaxComputationFloat32toFloat16(true);
347 assert(model->isValid());
348 }
349
is_ignored_dynamic_output_shape_relaxed_3(int i)350 inline bool is_ignored_dynamic_output_shape_relaxed_3(int i) {
351 static std::set<int> ignore = {};
352 return ignore.find(i) != ignore.end();
353 }
354
CreateModel_dynamic_output_shape_float16_3(Model * model)355 void CreateModel_dynamic_output_shape_float16_3(Model *model) {
356 OperandType type33(Type::TENSOR_FLOAT16, {0, 0, 0});
357 OperandType type4(Type::TENSOR_QUANT8_SYMM, {2, 2, 2}, 0.5f, 0);
358 // Phase 1, operands
359 auto input02 = model->addOperand(&type4);
360 auto output02 = model->addOperand(&type33);
361 // Phase 2, operations
362 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input02}, {output02});
363 // Phase 3, inputs and outputs
364 model->identifyInputsAndOutputs(
365 {input02},
366 {output02});
367 assert(model->isValid());
368 }
369
is_ignored_dynamic_output_shape_float16_3(int i)370 inline bool is_ignored_dynamic_output_shape_float16_3(int i) {
371 static std::set<int> ignore = {};
372 return ignore.find(i) != ignore.end();
373 }
374
CreateModel_4(Model * model)375 void CreateModel_4(Model *model) {
376 OperandType type6(Type::TENSOR_QUANT8_SYMM, {2, 1, 2, 2}, 0.5f, 0);
377 OperandType type7(Type::TENSOR_FLOAT32, {2, 1, 2, 2});
378 // Phase 1, operands
379 auto input03 = model->addOperand(&type6);
380 auto output03 = model->addOperand(&type7);
381 // Phase 2, operations
382 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input03}, {output03});
383 // Phase 3, inputs and outputs
384 model->identifyInputsAndOutputs(
385 {input03},
386 {output03});
387 assert(model->isValid());
388 }
389
is_ignored_4(int i)390 inline bool is_ignored_4(int i) {
391 static std::set<int> ignore = {};
392 return ignore.find(i) != ignore.end();
393 }
394
CreateModel_relaxed_4(Model * model)395 void CreateModel_relaxed_4(Model *model) {
396 OperandType type6(Type::TENSOR_QUANT8_SYMM, {2, 1, 2, 2}, 0.5f, 0);
397 OperandType type7(Type::TENSOR_FLOAT32, {2, 1, 2, 2});
398 // Phase 1, operands
399 auto input03 = model->addOperand(&type6);
400 auto output03 = model->addOperand(&type7);
401 // Phase 2, operations
402 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input03}, {output03});
403 // Phase 3, inputs and outputs
404 model->identifyInputsAndOutputs(
405 {input03},
406 {output03});
407 // Phase 4: set relaxed execution
408 model->relaxComputationFloat32toFloat16(true);
409 assert(model->isValid());
410 }
411
is_ignored_relaxed_4(int i)412 inline bool is_ignored_relaxed_4(int i) {
413 static std::set<int> ignore = {};
414 return ignore.find(i) != ignore.end();
415 }
416
CreateModel_float16_4(Model * model)417 void CreateModel_float16_4(Model *model) {
418 OperandType type34(Type::TENSOR_FLOAT16, {2, 1, 2, 2});
419 OperandType type6(Type::TENSOR_QUANT8_SYMM, {2, 1, 2, 2}, 0.5f, 0);
420 // Phase 1, operands
421 auto input03 = model->addOperand(&type6);
422 auto output03 = model->addOperand(&type34);
423 // Phase 2, operations
424 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input03}, {output03});
425 // Phase 3, inputs and outputs
426 model->identifyInputsAndOutputs(
427 {input03},
428 {output03});
429 assert(model->isValid());
430 }
431
is_ignored_float16_4(int i)432 inline bool is_ignored_float16_4(int i) {
433 static std::set<int> ignore = {};
434 return ignore.find(i) != ignore.end();
435 }
436
CreateModel_dynamic_output_shape_4(Model * model)437 void CreateModel_dynamic_output_shape_4(Model *model) {
438 OperandType type35(Type::TENSOR_FLOAT32, {0, 0, 0, 0});
439 OperandType type6(Type::TENSOR_QUANT8_SYMM, {2, 1, 2, 2}, 0.5f, 0);
440 // Phase 1, operands
441 auto input03 = model->addOperand(&type6);
442 auto output03 = model->addOperand(&type35);
443 // Phase 2, operations
444 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input03}, {output03});
445 // Phase 3, inputs and outputs
446 model->identifyInputsAndOutputs(
447 {input03},
448 {output03});
449 assert(model->isValid());
450 }
451
is_ignored_dynamic_output_shape_4(int i)452 inline bool is_ignored_dynamic_output_shape_4(int i) {
453 static std::set<int> ignore = {};
454 return ignore.find(i) != ignore.end();
455 }
456
CreateModel_dynamic_output_shape_relaxed_4(Model * model)457 void CreateModel_dynamic_output_shape_relaxed_4(Model *model) {
458 OperandType type35(Type::TENSOR_FLOAT32, {0, 0, 0, 0});
459 OperandType type6(Type::TENSOR_QUANT8_SYMM, {2, 1, 2, 2}, 0.5f, 0);
460 // Phase 1, operands
461 auto input03 = model->addOperand(&type6);
462 auto output03 = model->addOperand(&type35);
463 // Phase 2, operations
464 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input03}, {output03});
465 // Phase 3, inputs and outputs
466 model->identifyInputsAndOutputs(
467 {input03},
468 {output03});
469 // Phase 4: set relaxed execution
470 model->relaxComputationFloat32toFloat16(true);
471 assert(model->isValid());
472 }
473
is_ignored_dynamic_output_shape_relaxed_4(int i)474 inline bool is_ignored_dynamic_output_shape_relaxed_4(int i) {
475 static std::set<int> ignore = {};
476 return ignore.find(i) != ignore.end();
477 }
478
CreateModel_dynamic_output_shape_float16_4(Model * model)479 void CreateModel_dynamic_output_shape_float16_4(Model *model) {
480 OperandType type36(Type::TENSOR_FLOAT16, {0, 0, 0, 0});
481 OperandType type6(Type::TENSOR_QUANT8_SYMM, {2, 1, 2, 2}, 0.5f, 0);
482 // Phase 1, operands
483 auto input03 = model->addOperand(&type6);
484 auto output03 = model->addOperand(&type36);
485 // Phase 2, operations
486 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input03}, {output03});
487 // Phase 3, inputs and outputs
488 model->identifyInputsAndOutputs(
489 {input03},
490 {output03});
491 assert(model->isValid());
492 }
493
is_ignored_dynamic_output_shape_float16_4(int i)494 inline bool is_ignored_dynamic_output_shape_float16_4(int i) {
495 static std::set<int> ignore = {};
496 return ignore.find(i) != ignore.end();
497 }
498
CreateModel_5(Model * model)499 void CreateModel_5(Model *model) {
500 OperandType type8(Type::TENSOR_QUANT8_SYMM_PER_CHANNEL, {2, 3, 4}, 0.0f, 0, SymmPerChannelQuantParams({2.0f, 0.5f},0));
501 OperandType type9(Type::TENSOR_FLOAT32, {2, 3, 4});
502 // Phase 1, operands
503 auto input04 = model->addOperand(&type8);
504 auto output04 = model->addOperand(&type9);
505 // Phase 2, operations
506 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input04}, {output04});
507 // Phase 3, inputs and outputs
508 model->identifyInputsAndOutputs(
509 {input04},
510 {output04});
511 assert(model->isValid());
512 }
513
is_ignored_5(int i)514 inline bool is_ignored_5(int i) {
515 static std::set<int> ignore = {};
516 return ignore.find(i) != ignore.end();
517 }
518
CreateModel_relaxed_5(Model * model)519 void CreateModel_relaxed_5(Model *model) {
520 OperandType type8(Type::TENSOR_QUANT8_SYMM_PER_CHANNEL, {2, 3, 4}, 0.0f, 0, SymmPerChannelQuantParams({2.0f, 0.5f},0));
521 OperandType type9(Type::TENSOR_FLOAT32, {2, 3, 4});
522 // Phase 1, operands
523 auto input04 = model->addOperand(&type8);
524 auto output04 = model->addOperand(&type9);
525 // Phase 2, operations
526 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input04}, {output04});
527 // Phase 3, inputs and outputs
528 model->identifyInputsAndOutputs(
529 {input04},
530 {output04});
531 // Phase 4: set relaxed execution
532 model->relaxComputationFloat32toFloat16(true);
533 assert(model->isValid());
534 }
535
is_ignored_relaxed_5(int i)536 inline bool is_ignored_relaxed_5(int i) {
537 static std::set<int> ignore = {};
538 return ignore.find(i) != ignore.end();
539 }
540
CreateModel_float16_5(Model * model)541 void CreateModel_float16_5(Model *model) {
542 OperandType type37(Type::TENSOR_FLOAT16, {2, 3, 4});
543 OperandType type8(Type::TENSOR_QUANT8_SYMM_PER_CHANNEL, {2, 3, 4}, 0.0f, 0, SymmPerChannelQuantParams({2.0f, 0.5f},0));
544 // Phase 1, operands
545 auto input04 = model->addOperand(&type8);
546 auto output04 = model->addOperand(&type37);
547 // Phase 2, operations
548 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input04}, {output04});
549 // Phase 3, inputs and outputs
550 model->identifyInputsAndOutputs(
551 {input04},
552 {output04});
553 assert(model->isValid());
554 }
555
is_ignored_float16_5(int i)556 inline bool is_ignored_float16_5(int i) {
557 static std::set<int> ignore = {};
558 return ignore.find(i) != ignore.end();
559 }
560
CreateModel_dynamic_output_shape_5(Model * model)561 void CreateModel_dynamic_output_shape_5(Model *model) {
562 OperandType type32(Type::TENSOR_FLOAT32, {0, 0, 0});
563 OperandType type8(Type::TENSOR_QUANT8_SYMM_PER_CHANNEL, {2, 3, 4}, 0.0f, 0, SymmPerChannelQuantParams({2.0f, 0.5f},0));
564 // Phase 1, operands
565 auto input04 = model->addOperand(&type8);
566 auto output04 = model->addOperand(&type32);
567 // Phase 2, operations
568 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input04}, {output04});
569 // Phase 3, inputs and outputs
570 model->identifyInputsAndOutputs(
571 {input04},
572 {output04});
573 assert(model->isValid());
574 }
575
is_ignored_dynamic_output_shape_5(int i)576 inline bool is_ignored_dynamic_output_shape_5(int i) {
577 static std::set<int> ignore = {};
578 return ignore.find(i) != ignore.end();
579 }
580
CreateModel_dynamic_output_shape_relaxed_5(Model * model)581 void CreateModel_dynamic_output_shape_relaxed_5(Model *model) {
582 OperandType type32(Type::TENSOR_FLOAT32, {0, 0, 0});
583 OperandType type8(Type::TENSOR_QUANT8_SYMM_PER_CHANNEL, {2, 3, 4}, 0.0f, 0, SymmPerChannelQuantParams({2.0f, 0.5f},0));
584 // Phase 1, operands
585 auto input04 = model->addOperand(&type8);
586 auto output04 = model->addOperand(&type32);
587 // Phase 2, operations
588 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input04}, {output04});
589 // Phase 3, inputs and outputs
590 model->identifyInputsAndOutputs(
591 {input04},
592 {output04});
593 // Phase 4: set relaxed execution
594 model->relaxComputationFloat32toFloat16(true);
595 assert(model->isValid());
596 }
597
is_ignored_dynamic_output_shape_relaxed_5(int i)598 inline bool is_ignored_dynamic_output_shape_relaxed_5(int i) {
599 static std::set<int> ignore = {};
600 return ignore.find(i) != ignore.end();
601 }
602
CreateModel_dynamic_output_shape_float16_5(Model * model)603 void CreateModel_dynamic_output_shape_float16_5(Model *model) {
604 OperandType type33(Type::TENSOR_FLOAT16, {0, 0, 0});
605 OperandType type8(Type::TENSOR_QUANT8_SYMM_PER_CHANNEL, {2, 3, 4}, 0.0f, 0, SymmPerChannelQuantParams({2.0f, 0.5f},0));
606 // Phase 1, operands
607 auto input04 = model->addOperand(&type8);
608 auto output04 = model->addOperand(&type33);
609 // Phase 2, operations
610 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input04}, {output04});
611 // Phase 3, inputs and outputs
612 model->identifyInputsAndOutputs(
613 {input04},
614 {output04});
615 assert(model->isValid());
616 }
617
is_ignored_dynamic_output_shape_float16_5(int i)618 inline bool is_ignored_dynamic_output_shape_float16_5(int i) {
619 static std::set<int> ignore = {};
620 return ignore.find(i) != ignore.end();
621 }
622
CreateModel_6(Model * model)623 void CreateModel_6(Model *model) {
624 OperandType type10(Type::TENSOR_QUANT8_SYMM_PER_CHANNEL, {2, 3, 4}, 0.0f, 0, SymmPerChannelQuantParams({2.0f, 1.0f, 0.5f},1));
625 OperandType type9(Type::TENSOR_FLOAT32, {2, 3, 4});
626 // Phase 1, operands
627 auto input05 = model->addOperand(&type10);
628 auto output05 = model->addOperand(&type9);
629 // Phase 2, operations
630 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input05}, {output05});
631 // Phase 3, inputs and outputs
632 model->identifyInputsAndOutputs(
633 {input05},
634 {output05});
635 assert(model->isValid());
636 }
637
is_ignored_6(int i)638 inline bool is_ignored_6(int i) {
639 static std::set<int> ignore = {};
640 return ignore.find(i) != ignore.end();
641 }
642
CreateModel_relaxed_6(Model * model)643 void CreateModel_relaxed_6(Model *model) {
644 OperandType type10(Type::TENSOR_QUANT8_SYMM_PER_CHANNEL, {2, 3, 4}, 0.0f, 0, SymmPerChannelQuantParams({2.0f, 1.0f, 0.5f},1));
645 OperandType type9(Type::TENSOR_FLOAT32, {2, 3, 4});
646 // Phase 1, operands
647 auto input05 = model->addOperand(&type10);
648 auto output05 = model->addOperand(&type9);
649 // Phase 2, operations
650 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input05}, {output05});
651 // Phase 3, inputs and outputs
652 model->identifyInputsAndOutputs(
653 {input05},
654 {output05});
655 // Phase 4: set relaxed execution
656 model->relaxComputationFloat32toFloat16(true);
657 assert(model->isValid());
658 }
659
is_ignored_relaxed_6(int i)660 inline bool is_ignored_relaxed_6(int i) {
661 static std::set<int> ignore = {};
662 return ignore.find(i) != ignore.end();
663 }
664
CreateModel_float16_6(Model * model)665 void CreateModel_float16_6(Model *model) {
666 OperandType type10(Type::TENSOR_QUANT8_SYMM_PER_CHANNEL, {2, 3, 4}, 0.0f, 0, SymmPerChannelQuantParams({2.0f, 1.0f, 0.5f},1));
667 OperandType type37(Type::TENSOR_FLOAT16, {2, 3, 4});
668 // Phase 1, operands
669 auto input05 = model->addOperand(&type10);
670 auto output05 = model->addOperand(&type37);
671 // Phase 2, operations
672 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input05}, {output05});
673 // Phase 3, inputs and outputs
674 model->identifyInputsAndOutputs(
675 {input05},
676 {output05});
677 assert(model->isValid());
678 }
679
is_ignored_float16_6(int i)680 inline bool is_ignored_float16_6(int i) {
681 static std::set<int> ignore = {};
682 return ignore.find(i) != ignore.end();
683 }
684
CreateModel_dynamic_output_shape_6(Model * model)685 void CreateModel_dynamic_output_shape_6(Model *model) {
686 OperandType type10(Type::TENSOR_QUANT8_SYMM_PER_CHANNEL, {2, 3, 4}, 0.0f, 0, SymmPerChannelQuantParams({2.0f, 1.0f, 0.5f},1));
687 OperandType type32(Type::TENSOR_FLOAT32, {0, 0, 0});
688 // Phase 1, operands
689 auto input05 = model->addOperand(&type10);
690 auto output05 = model->addOperand(&type32);
691 // Phase 2, operations
692 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input05}, {output05});
693 // Phase 3, inputs and outputs
694 model->identifyInputsAndOutputs(
695 {input05},
696 {output05});
697 assert(model->isValid());
698 }
699
is_ignored_dynamic_output_shape_6(int i)700 inline bool is_ignored_dynamic_output_shape_6(int i) {
701 static std::set<int> ignore = {};
702 return ignore.find(i) != ignore.end();
703 }
704
CreateModel_dynamic_output_shape_relaxed_6(Model * model)705 void CreateModel_dynamic_output_shape_relaxed_6(Model *model) {
706 OperandType type10(Type::TENSOR_QUANT8_SYMM_PER_CHANNEL, {2, 3, 4}, 0.0f, 0, SymmPerChannelQuantParams({2.0f, 1.0f, 0.5f},1));
707 OperandType type32(Type::TENSOR_FLOAT32, {0, 0, 0});
708 // Phase 1, operands
709 auto input05 = model->addOperand(&type10);
710 auto output05 = model->addOperand(&type32);
711 // Phase 2, operations
712 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input05}, {output05});
713 // Phase 3, inputs and outputs
714 model->identifyInputsAndOutputs(
715 {input05},
716 {output05});
717 // Phase 4: set relaxed execution
718 model->relaxComputationFloat32toFloat16(true);
719 assert(model->isValid());
720 }
721
is_ignored_dynamic_output_shape_relaxed_6(int i)722 inline bool is_ignored_dynamic_output_shape_relaxed_6(int i) {
723 static std::set<int> ignore = {};
724 return ignore.find(i) != ignore.end();
725 }
726
CreateModel_dynamic_output_shape_float16_6(Model * model)727 void CreateModel_dynamic_output_shape_float16_6(Model *model) {
728 OperandType type10(Type::TENSOR_QUANT8_SYMM_PER_CHANNEL, {2, 3, 4}, 0.0f, 0, SymmPerChannelQuantParams({2.0f, 1.0f, 0.5f},1));
729 OperandType type33(Type::TENSOR_FLOAT16, {0, 0, 0});
730 // Phase 1, operands
731 auto input05 = model->addOperand(&type10);
732 auto output05 = model->addOperand(&type33);
733 // Phase 2, operations
734 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {input05}, {output05});
735 // Phase 3, inputs and outputs
736 model->identifyInputsAndOutputs(
737 {input05},
738 {output05});
739 assert(model->isValid());
740 }
741
is_ignored_dynamic_output_shape_float16_6(int i)742 inline bool is_ignored_dynamic_output_shape_float16_6(int i) {
743 static std::set<int> ignore = {};
744 return ignore.find(i) != ignore.end();
745 }
746
CreateModel_7(Model * model)747 void CreateModel_7(Model *model) {
748 OperandType type11(Type::TENSOR_QUANT8_ASYMM, {1, 2, 2, 1}, 1.0f, 0);
749 OperandType type12(Type::TENSOR_FLOAT16, {1, 2, 2, 1});
750 // Phase 1, operands
751 auto op1 = model->addOperand(&type11);
752 auto op2 = model->addOperand(&type12);
753 // Phase 2, operations
754 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {op1}, {op2});
755 // Phase 3, inputs and outputs
756 model->identifyInputsAndOutputs(
757 {op1},
758 {op2});
759 assert(model->isValid());
760 }
761
is_ignored_7(int i)762 inline bool is_ignored_7(int i) {
763 static std::set<int> ignore = {};
764 return ignore.find(i) != ignore.end();
765 }
766
CreateModel_dynamic_output_shape_7(Model * model)767 void CreateModel_dynamic_output_shape_7(Model *model) {
768 OperandType type11(Type::TENSOR_QUANT8_ASYMM, {1, 2, 2, 1}, 1.0f, 0);
769 OperandType type36(Type::TENSOR_FLOAT16, {0, 0, 0, 0});
770 // Phase 1, operands
771 auto op1 = model->addOperand(&type11);
772 auto op2 = model->addOperand(&type36);
773 // Phase 2, operations
774 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {op1}, {op2});
775 // Phase 3, inputs and outputs
776 model->identifyInputsAndOutputs(
777 {op1},
778 {op2});
779 assert(model->isValid());
780 }
781
is_ignored_dynamic_output_shape_7(int i)782 inline bool is_ignored_dynamic_output_shape_7(int i) {
783 static std::set<int> ignore = {};
784 return ignore.find(i) != ignore.end();
785 }
786
CreateModel_zero_sized(Model * model)787 void CreateModel_zero_sized(Model *model) {
788 OperandType type13(Type::TENSOR_QUANT8_ASYMM, {1, 2}, 0.1f, 128);
789 OperandType type14(Type::TENSOR_QUANT16_ASYMM, {1, 8}, 0.125f, 0);
790 OperandType type15(Type::TENSOR_QUANT8_ASYMM, {0}, 0.1f, 128);
791 OperandType type16(Type::TENSOR_INT32, {0});
792 OperandType type17(Type::TENSOR_QUANT16_ASYMM, {0, 4}, 0.125f, 0);
793 OperandType type18(Type::TENSOR_INT32, {1});
794 OperandType type19(Type::FLOAT32, {});
795 OperandType type20(Type::INT32, {});
796 OperandType type21(Type::BOOL, {});
797 OperandType type22(Type::TENSOR_QUANT8_ASYMM, {1, 1, 1, 1}, 0.1f, 128);
798 OperandType type23(Type::TENSOR_QUANT8_ASYMM, {0, 2, 2, 1}, 0.1f, 128);
799 OperandType type24(Type::TENSOR_FLOAT32, {0, 2, 2, 1});
800 // Phase 1, operands
801 auto scores = model->addOperand(&type13);
802 auto roi = model->addOperand(&type14);
803 auto param = model->addOperand(&type18);
804 auto param1 = model->addOperand(&type19);
805 auto param2 = model->addOperand(&type20);
806 auto param3 = model->addOperand(&type20);
807 auto param4 = model->addOperand(&type19);
808 auto param5 = model->addOperand(&type19);
809 auto param6 = model->addOperand(&type19);
810 auto scoresOut = model->addOperand(&type15);
811 auto roiOut = model->addOperand(&type17);
812 auto classesOut = model->addOperand(&type16);
813 auto batchSplitOut = model->addOperand(&type16);
814 auto in = model->addOperand(&type22);
815 auto param7 = model->addOperand(&type20);
816 auto param8 = model->addOperand(&type20);
817 auto param9 = model->addOperand(&type19);
818 auto param10 = model->addOperand(&type19);
819 auto param11 = model->addOperand(&type20);
820 auto param12 = model->addOperand(&type20);
821 auto layout = model->addOperand(&type21);
822 auto featureMap = model->addOperand(&type23);
823 auto out = model->addOperand(&type24);
824 // Phase 2, operations
825 static uint8_t scores_init[] = {137, 129};
826 model->setOperandValue(scores, scores_init, sizeof(uint8_t) * 2);
827 static uint16_t roi_init[] = {8, 8, 80, 80, 0, 0, 80, 80};
828 model->setOperandValue(roi, roi_init, sizeof(uint16_t) * 8);
829 static int32_t param_init[] = {0};
830 model->setOperandValue(param, param_init, sizeof(int32_t) * 1);
831 static float param1_init[] = {0.3f};
832 model->setOperandValue(param1, param1_init, sizeof(float) * 1);
833 static int32_t param2_init[] = {-1};
834 model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1);
835 static int32_t param3_init[] = {0};
836 model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1);
837 static float param4_init[] = {0.4f};
838 model->setOperandValue(param4, param4_init, sizeof(float) * 1);
839 static float param5_init[] = {1.0f};
840 model->setOperandValue(param5, param5_init, sizeof(float) * 1);
841 static float param6_init[] = {0.3f};
842 model->setOperandValue(param6, param6_init, sizeof(float) * 1);
843 static int32_t param7_init[] = {2};
844 model->setOperandValue(param7, param7_init, sizeof(int32_t) * 1);
845 static int32_t param8_init[] = {2};
846 model->setOperandValue(param8, param8_init, sizeof(int32_t) * 1);
847 static float param9_init[] = {2.0f};
848 model->setOperandValue(param9, param9_init, sizeof(float) * 1);
849 static float param10_init[] = {2.0f};
850 model->setOperandValue(param10, param10_init, sizeof(float) * 1);
851 static int32_t param11_init[] = {4};
852 model->setOperandValue(param11, param11_init, sizeof(int32_t) * 1);
853 static int32_t param12_init[] = {4};
854 model->setOperandValue(param12, param12_init, sizeof(int32_t) * 1);
855 static bool8 layout_init[] = {false};
856 model->setOperandValue(layout, layout_init, sizeof(bool8) * 1);
857 model->addOperation(ANEURALNETWORKS_BOX_WITH_NMS_LIMIT, {scores, roi, param, param1, param2, param3, param4, param5, param6}, {scoresOut, roiOut, classesOut, batchSplitOut});
858 model->addOperation(ANEURALNETWORKS_ROI_ALIGN, {in, roiOut, batchSplitOut, param7, param8, param9, param10, param11, param12, layout}, {featureMap});
859 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {featureMap}, {out});
860 // Phase 3, inputs and outputs
861 model->identifyInputsAndOutputs(
862 {in},
863 {scoresOut, classesOut, out});
864 assert(model->isValid());
865 }
866
is_ignored_zero_sized(int i)867 inline bool is_ignored_zero_sized(int i) {
868 static std::set<int> ignore = {};
869 return ignore.find(i) != ignore.end();
870 }
871
CreateModel_zero_sized_relaxed(Model * model)872 void CreateModel_zero_sized_relaxed(Model *model) {
873 OperandType type13(Type::TENSOR_QUANT8_ASYMM, {1, 2}, 0.1f, 128);
874 OperandType type14(Type::TENSOR_QUANT16_ASYMM, {1, 8}, 0.125f, 0);
875 OperandType type15(Type::TENSOR_QUANT8_ASYMM, {0}, 0.1f, 128);
876 OperandType type16(Type::TENSOR_INT32, {0});
877 OperandType type17(Type::TENSOR_QUANT16_ASYMM, {0, 4}, 0.125f, 0);
878 OperandType type18(Type::TENSOR_INT32, {1});
879 OperandType type19(Type::FLOAT32, {});
880 OperandType type20(Type::INT32, {});
881 OperandType type21(Type::BOOL, {});
882 OperandType type22(Type::TENSOR_QUANT8_ASYMM, {1, 1, 1, 1}, 0.1f, 128);
883 OperandType type23(Type::TENSOR_QUANT8_ASYMM, {0, 2, 2, 1}, 0.1f, 128);
884 OperandType type24(Type::TENSOR_FLOAT32, {0, 2, 2, 1});
885 // Phase 1, operands
886 auto scores = model->addOperand(&type13);
887 auto roi = model->addOperand(&type14);
888 auto param = model->addOperand(&type18);
889 auto param1 = model->addOperand(&type19);
890 auto param2 = model->addOperand(&type20);
891 auto param3 = model->addOperand(&type20);
892 auto param4 = model->addOperand(&type19);
893 auto param5 = model->addOperand(&type19);
894 auto param6 = model->addOperand(&type19);
895 auto scoresOut = model->addOperand(&type15);
896 auto roiOut = model->addOperand(&type17);
897 auto classesOut = model->addOperand(&type16);
898 auto batchSplitOut = model->addOperand(&type16);
899 auto in = model->addOperand(&type22);
900 auto param7 = model->addOperand(&type20);
901 auto param8 = model->addOperand(&type20);
902 auto param9 = model->addOperand(&type19);
903 auto param10 = model->addOperand(&type19);
904 auto param11 = model->addOperand(&type20);
905 auto param12 = model->addOperand(&type20);
906 auto layout = model->addOperand(&type21);
907 auto featureMap = model->addOperand(&type23);
908 auto out = model->addOperand(&type24);
909 // Phase 2, operations
910 static uint8_t scores_init[] = {137, 129};
911 model->setOperandValue(scores, scores_init, sizeof(uint8_t) * 2);
912 static uint16_t roi_init[] = {8, 8, 80, 80, 0, 0, 80, 80};
913 model->setOperandValue(roi, roi_init, sizeof(uint16_t) * 8);
914 static int32_t param_init[] = {0};
915 model->setOperandValue(param, param_init, sizeof(int32_t) * 1);
916 static float param1_init[] = {0.3f};
917 model->setOperandValue(param1, param1_init, sizeof(float) * 1);
918 static int32_t param2_init[] = {-1};
919 model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1);
920 static int32_t param3_init[] = {0};
921 model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1);
922 static float param4_init[] = {0.4f};
923 model->setOperandValue(param4, param4_init, sizeof(float) * 1);
924 static float param5_init[] = {1.0f};
925 model->setOperandValue(param5, param5_init, sizeof(float) * 1);
926 static float param6_init[] = {0.3f};
927 model->setOperandValue(param6, param6_init, sizeof(float) * 1);
928 static int32_t param7_init[] = {2};
929 model->setOperandValue(param7, param7_init, sizeof(int32_t) * 1);
930 static int32_t param8_init[] = {2};
931 model->setOperandValue(param8, param8_init, sizeof(int32_t) * 1);
932 static float param9_init[] = {2.0f};
933 model->setOperandValue(param9, param9_init, sizeof(float) * 1);
934 static float param10_init[] = {2.0f};
935 model->setOperandValue(param10, param10_init, sizeof(float) * 1);
936 static int32_t param11_init[] = {4};
937 model->setOperandValue(param11, param11_init, sizeof(int32_t) * 1);
938 static int32_t param12_init[] = {4};
939 model->setOperandValue(param12, param12_init, sizeof(int32_t) * 1);
940 static bool8 layout_init[] = {false};
941 model->setOperandValue(layout, layout_init, sizeof(bool8) * 1);
942 model->addOperation(ANEURALNETWORKS_BOX_WITH_NMS_LIMIT, {scores, roi, param, param1, param2, param3, param4, param5, param6}, {scoresOut, roiOut, classesOut, batchSplitOut});
943 model->addOperation(ANEURALNETWORKS_ROI_ALIGN, {in, roiOut, batchSplitOut, param7, param8, param9, param10, param11, param12, layout}, {featureMap});
944 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {featureMap}, {out});
945 // Phase 3, inputs and outputs
946 model->identifyInputsAndOutputs(
947 {in},
948 {scoresOut, classesOut, out});
949 // Phase 4: set relaxed execution
950 model->relaxComputationFloat32toFloat16(true);
951 assert(model->isValid());
952 }
953
is_ignored_zero_sized_relaxed(int i)954 inline bool is_ignored_zero_sized_relaxed(int i) {
955 static std::set<int> ignore = {};
956 return ignore.find(i) != ignore.end();
957 }
958
CreateModel_zero_sized_float16(Model * model)959 void CreateModel_zero_sized_float16(Model *model) {
960 OperandType type13(Type::TENSOR_QUANT8_ASYMM, {1, 2}, 0.1f, 128);
961 OperandType type14(Type::TENSOR_QUANT16_ASYMM, {1, 8}, 0.125f, 0);
962 OperandType type15(Type::TENSOR_QUANT8_ASYMM, {0}, 0.1f, 128);
963 OperandType type16(Type::TENSOR_INT32, {0});
964 OperandType type17(Type::TENSOR_QUANT16_ASYMM, {0, 4}, 0.125f, 0);
965 OperandType type18(Type::TENSOR_INT32, {1});
966 OperandType type19(Type::FLOAT32, {});
967 OperandType type20(Type::INT32, {});
968 OperandType type21(Type::BOOL, {});
969 OperandType type22(Type::TENSOR_QUANT8_ASYMM, {1, 1, 1, 1}, 0.1f, 128);
970 OperandType type23(Type::TENSOR_QUANT8_ASYMM, {0, 2, 2, 1}, 0.1f, 128);
971 OperandType type38(Type::TENSOR_FLOAT16, {0, 2, 2, 1});
972 // Phase 1, operands
973 auto scores = model->addOperand(&type13);
974 auto roi = model->addOperand(&type14);
975 auto param = model->addOperand(&type18);
976 auto param1 = model->addOperand(&type19);
977 auto param2 = model->addOperand(&type20);
978 auto param3 = model->addOperand(&type20);
979 auto param4 = model->addOperand(&type19);
980 auto param5 = model->addOperand(&type19);
981 auto param6 = model->addOperand(&type19);
982 auto scoresOut = model->addOperand(&type15);
983 auto roiOut = model->addOperand(&type17);
984 auto classesOut = model->addOperand(&type16);
985 auto batchSplitOut = model->addOperand(&type16);
986 auto in = model->addOperand(&type22);
987 auto param7 = model->addOperand(&type20);
988 auto param8 = model->addOperand(&type20);
989 auto param9 = model->addOperand(&type19);
990 auto param10 = model->addOperand(&type19);
991 auto param11 = model->addOperand(&type20);
992 auto param12 = model->addOperand(&type20);
993 auto layout = model->addOperand(&type21);
994 auto featureMap = model->addOperand(&type23);
995 auto out = model->addOperand(&type38);
996 // Phase 2, operations
997 static uint8_t scores_init[] = {137, 129};
998 model->setOperandValue(scores, scores_init, sizeof(uint8_t) * 2);
999 static uint16_t roi_init[] = {8, 8, 80, 80, 0, 0, 80, 80};
1000 model->setOperandValue(roi, roi_init, sizeof(uint16_t) * 8);
1001 static int32_t param_init[] = {0};
1002 model->setOperandValue(param, param_init, sizeof(int32_t) * 1);
1003 static float param1_init[] = {0.3f};
1004 model->setOperandValue(param1, param1_init, sizeof(float) * 1);
1005 static int32_t param2_init[] = {-1};
1006 model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1);
1007 static int32_t param3_init[] = {0};
1008 model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1);
1009 static float param4_init[] = {0.4f};
1010 model->setOperandValue(param4, param4_init, sizeof(float) * 1);
1011 static float param5_init[] = {1.0f};
1012 model->setOperandValue(param5, param5_init, sizeof(float) * 1);
1013 static float param6_init[] = {0.3f};
1014 model->setOperandValue(param6, param6_init, sizeof(float) * 1);
1015 static int32_t param7_init[] = {2};
1016 model->setOperandValue(param7, param7_init, sizeof(int32_t) * 1);
1017 static int32_t param8_init[] = {2};
1018 model->setOperandValue(param8, param8_init, sizeof(int32_t) * 1);
1019 static float param9_init[] = {2.0f};
1020 model->setOperandValue(param9, param9_init, sizeof(float) * 1);
1021 static float param10_init[] = {2.0f};
1022 model->setOperandValue(param10, param10_init, sizeof(float) * 1);
1023 static int32_t param11_init[] = {4};
1024 model->setOperandValue(param11, param11_init, sizeof(int32_t) * 1);
1025 static int32_t param12_init[] = {4};
1026 model->setOperandValue(param12, param12_init, sizeof(int32_t) * 1);
1027 static bool8 layout_init[] = {false};
1028 model->setOperandValue(layout, layout_init, sizeof(bool8) * 1);
1029 model->addOperation(ANEURALNETWORKS_BOX_WITH_NMS_LIMIT, {scores, roi, param, param1, param2, param3, param4, param5, param6}, {scoresOut, roiOut, classesOut, batchSplitOut});
1030 model->addOperation(ANEURALNETWORKS_ROI_ALIGN, {in, roiOut, batchSplitOut, param7, param8, param9, param10, param11, param12, layout}, {featureMap});
1031 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {featureMap}, {out});
1032 // Phase 3, inputs and outputs
1033 model->identifyInputsAndOutputs(
1034 {in},
1035 {scoresOut, classesOut, out});
1036 assert(model->isValid());
1037 }
1038
is_ignored_zero_sized_float16(int i)1039 inline bool is_ignored_zero_sized_float16(int i) {
1040 static std::set<int> ignore = {};
1041 return ignore.find(i) != ignore.end();
1042 }
1043
CreateModel_zero_sized_dynamic_output_shape(Model * model)1044 void CreateModel_zero_sized_dynamic_output_shape(Model *model) {
1045 OperandType type13(Type::TENSOR_QUANT8_ASYMM, {1, 2}, 0.1f, 128);
1046 OperandType type14(Type::TENSOR_QUANT16_ASYMM, {1, 8}, 0.125f, 0);
1047 OperandType type15(Type::TENSOR_QUANT8_ASYMM, {0}, 0.1f, 128);
1048 OperandType type16(Type::TENSOR_INT32, {0});
1049 OperandType type17(Type::TENSOR_QUANT16_ASYMM, {0, 4}, 0.125f, 0);
1050 OperandType type18(Type::TENSOR_INT32, {1});
1051 OperandType type19(Type::FLOAT32, {});
1052 OperandType type20(Type::INT32, {});
1053 OperandType type21(Type::BOOL, {});
1054 OperandType type22(Type::TENSOR_QUANT8_ASYMM, {1, 1, 1, 1}, 0.1f, 128);
1055 OperandType type23(Type::TENSOR_QUANT8_ASYMM, {0, 2, 2, 1}, 0.1f, 128);
1056 OperandType type35(Type::TENSOR_FLOAT32, {0, 0, 0, 0});
1057 // Phase 1, operands
1058 auto scores = model->addOperand(&type13);
1059 auto roi = model->addOperand(&type14);
1060 auto param = model->addOperand(&type18);
1061 auto param1 = model->addOperand(&type19);
1062 auto param2 = model->addOperand(&type20);
1063 auto param3 = model->addOperand(&type20);
1064 auto param4 = model->addOperand(&type19);
1065 auto param5 = model->addOperand(&type19);
1066 auto param6 = model->addOperand(&type19);
1067 auto scoresOut = model->addOperand(&type15);
1068 auto roiOut = model->addOperand(&type17);
1069 auto classesOut = model->addOperand(&type16);
1070 auto batchSplitOut = model->addOperand(&type16);
1071 auto in = model->addOperand(&type22);
1072 auto param7 = model->addOperand(&type20);
1073 auto param8 = model->addOperand(&type20);
1074 auto param9 = model->addOperand(&type19);
1075 auto param10 = model->addOperand(&type19);
1076 auto param11 = model->addOperand(&type20);
1077 auto param12 = model->addOperand(&type20);
1078 auto layout = model->addOperand(&type21);
1079 auto featureMap = model->addOperand(&type23);
1080 auto out = model->addOperand(&type35);
1081 // Phase 2, operations
1082 static uint8_t scores_init[] = {137, 129};
1083 model->setOperandValue(scores, scores_init, sizeof(uint8_t) * 2);
1084 static uint16_t roi_init[] = {8, 8, 80, 80, 0, 0, 80, 80};
1085 model->setOperandValue(roi, roi_init, sizeof(uint16_t) * 8);
1086 static int32_t param_init[] = {0};
1087 model->setOperandValue(param, param_init, sizeof(int32_t) * 1);
1088 static float param1_init[] = {0.3f};
1089 model->setOperandValue(param1, param1_init, sizeof(float) * 1);
1090 static int32_t param2_init[] = {-1};
1091 model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1);
1092 static int32_t param3_init[] = {0};
1093 model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1);
1094 static float param4_init[] = {0.4f};
1095 model->setOperandValue(param4, param4_init, sizeof(float) * 1);
1096 static float param5_init[] = {1.0f};
1097 model->setOperandValue(param5, param5_init, sizeof(float) * 1);
1098 static float param6_init[] = {0.3f};
1099 model->setOperandValue(param6, param6_init, sizeof(float) * 1);
1100 static int32_t param7_init[] = {2};
1101 model->setOperandValue(param7, param7_init, sizeof(int32_t) * 1);
1102 static int32_t param8_init[] = {2};
1103 model->setOperandValue(param8, param8_init, sizeof(int32_t) * 1);
1104 static float param9_init[] = {2.0f};
1105 model->setOperandValue(param9, param9_init, sizeof(float) * 1);
1106 static float param10_init[] = {2.0f};
1107 model->setOperandValue(param10, param10_init, sizeof(float) * 1);
1108 static int32_t param11_init[] = {4};
1109 model->setOperandValue(param11, param11_init, sizeof(int32_t) * 1);
1110 static int32_t param12_init[] = {4};
1111 model->setOperandValue(param12, param12_init, sizeof(int32_t) * 1);
1112 static bool8 layout_init[] = {false};
1113 model->setOperandValue(layout, layout_init, sizeof(bool8) * 1);
1114 model->addOperation(ANEURALNETWORKS_BOX_WITH_NMS_LIMIT, {scores, roi, param, param1, param2, param3, param4, param5, param6}, {scoresOut, roiOut, classesOut, batchSplitOut});
1115 model->addOperation(ANEURALNETWORKS_ROI_ALIGN, {in, roiOut, batchSplitOut, param7, param8, param9, param10, param11, param12, layout}, {featureMap});
1116 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {featureMap}, {out});
1117 // Phase 3, inputs and outputs
1118 model->identifyInputsAndOutputs(
1119 {in},
1120 {scoresOut, classesOut, out});
1121 assert(model->isValid());
1122 }
1123
is_ignored_zero_sized_dynamic_output_shape(int i)1124 inline bool is_ignored_zero_sized_dynamic_output_shape(int i) {
1125 static std::set<int> ignore = {};
1126 return ignore.find(i) != ignore.end();
1127 }
1128
CreateModel_zero_sized_dynamic_output_shape_relaxed(Model * model)1129 void CreateModel_zero_sized_dynamic_output_shape_relaxed(Model *model) {
1130 OperandType type13(Type::TENSOR_QUANT8_ASYMM, {1, 2}, 0.1f, 128);
1131 OperandType type14(Type::TENSOR_QUANT16_ASYMM, {1, 8}, 0.125f, 0);
1132 OperandType type15(Type::TENSOR_QUANT8_ASYMM, {0}, 0.1f, 128);
1133 OperandType type16(Type::TENSOR_INT32, {0});
1134 OperandType type17(Type::TENSOR_QUANT16_ASYMM, {0, 4}, 0.125f, 0);
1135 OperandType type18(Type::TENSOR_INT32, {1});
1136 OperandType type19(Type::FLOAT32, {});
1137 OperandType type20(Type::INT32, {});
1138 OperandType type21(Type::BOOL, {});
1139 OperandType type22(Type::TENSOR_QUANT8_ASYMM, {1, 1, 1, 1}, 0.1f, 128);
1140 OperandType type23(Type::TENSOR_QUANT8_ASYMM, {0, 2, 2, 1}, 0.1f, 128);
1141 OperandType type35(Type::TENSOR_FLOAT32, {0, 0, 0, 0});
1142 // Phase 1, operands
1143 auto scores = model->addOperand(&type13);
1144 auto roi = model->addOperand(&type14);
1145 auto param = model->addOperand(&type18);
1146 auto param1 = model->addOperand(&type19);
1147 auto param2 = model->addOperand(&type20);
1148 auto param3 = model->addOperand(&type20);
1149 auto param4 = model->addOperand(&type19);
1150 auto param5 = model->addOperand(&type19);
1151 auto param6 = model->addOperand(&type19);
1152 auto scoresOut = model->addOperand(&type15);
1153 auto roiOut = model->addOperand(&type17);
1154 auto classesOut = model->addOperand(&type16);
1155 auto batchSplitOut = model->addOperand(&type16);
1156 auto in = model->addOperand(&type22);
1157 auto param7 = model->addOperand(&type20);
1158 auto param8 = model->addOperand(&type20);
1159 auto param9 = model->addOperand(&type19);
1160 auto param10 = model->addOperand(&type19);
1161 auto param11 = model->addOperand(&type20);
1162 auto param12 = model->addOperand(&type20);
1163 auto layout = model->addOperand(&type21);
1164 auto featureMap = model->addOperand(&type23);
1165 auto out = model->addOperand(&type35);
1166 // Phase 2, operations
1167 static uint8_t scores_init[] = {137, 129};
1168 model->setOperandValue(scores, scores_init, sizeof(uint8_t) * 2);
1169 static uint16_t roi_init[] = {8, 8, 80, 80, 0, 0, 80, 80};
1170 model->setOperandValue(roi, roi_init, sizeof(uint16_t) * 8);
1171 static int32_t param_init[] = {0};
1172 model->setOperandValue(param, param_init, sizeof(int32_t) * 1);
1173 static float param1_init[] = {0.3f};
1174 model->setOperandValue(param1, param1_init, sizeof(float) * 1);
1175 static int32_t param2_init[] = {-1};
1176 model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1);
1177 static int32_t param3_init[] = {0};
1178 model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1);
1179 static float param4_init[] = {0.4f};
1180 model->setOperandValue(param4, param4_init, sizeof(float) * 1);
1181 static float param5_init[] = {1.0f};
1182 model->setOperandValue(param5, param5_init, sizeof(float) * 1);
1183 static float param6_init[] = {0.3f};
1184 model->setOperandValue(param6, param6_init, sizeof(float) * 1);
1185 static int32_t param7_init[] = {2};
1186 model->setOperandValue(param7, param7_init, sizeof(int32_t) * 1);
1187 static int32_t param8_init[] = {2};
1188 model->setOperandValue(param8, param8_init, sizeof(int32_t) * 1);
1189 static float param9_init[] = {2.0f};
1190 model->setOperandValue(param9, param9_init, sizeof(float) * 1);
1191 static float param10_init[] = {2.0f};
1192 model->setOperandValue(param10, param10_init, sizeof(float) * 1);
1193 static int32_t param11_init[] = {4};
1194 model->setOperandValue(param11, param11_init, sizeof(int32_t) * 1);
1195 static int32_t param12_init[] = {4};
1196 model->setOperandValue(param12, param12_init, sizeof(int32_t) * 1);
1197 static bool8 layout_init[] = {false};
1198 model->setOperandValue(layout, layout_init, sizeof(bool8) * 1);
1199 model->addOperation(ANEURALNETWORKS_BOX_WITH_NMS_LIMIT, {scores, roi, param, param1, param2, param3, param4, param5, param6}, {scoresOut, roiOut, classesOut, batchSplitOut});
1200 model->addOperation(ANEURALNETWORKS_ROI_ALIGN, {in, roiOut, batchSplitOut, param7, param8, param9, param10, param11, param12, layout}, {featureMap});
1201 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {featureMap}, {out});
1202 // Phase 3, inputs and outputs
1203 model->identifyInputsAndOutputs(
1204 {in},
1205 {scoresOut, classesOut, out});
1206 // Phase 4: set relaxed execution
1207 model->relaxComputationFloat32toFloat16(true);
1208 assert(model->isValid());
1209 }
1210
is_ignored_zero_sized_dynamic_output_shape_relaxed(int i)1211 inline bool is_ignored_zero_sized_dynamic_output_shape_relaxed(int i) {
1212 static std::set<int> ignore = {};
1213 return ignore.find(i) != ignore.end();
1214 }
1215
CreateModel_zero_sized_dynamic_output_shape_float16(Model * model)1216 void CreateModel_zero_sized_dynamic_output_shape_float16(Model *model) {
1217 OperandType type13(Type::TENSOR_QUANT8_ASYMM, {1, 2}, 0.1f, 128);
1218 OperandType type14(Type::TENSOR_QUANT16_ASYMM, {1, 8}, 0.125f, 0);
1219 OperandType type15(Type::TENSOR_QUANT8_ASYMM, {0}, 0.1f, 128);
1220 OperandType type16(Type::TENSOR_INT32, {0});
1221 OperandType type17(Type::TENSOR_QUANT16_ASYMM, {0, 4}, 0.125f, 0);
1222 OperandType type18(Type::TENSOR_INT32, {1});
1223 OperandType type19(Type::FLOAT32, {});
1224 OperandType type20(Type::INT32, {});
1225 OperandType type21(Type::BOOL, {});
1226 OperandType type22(Type::TENSOR_QUANT8_ASYMM, {1, 1, 1, 1}, 0.1f, 128);
1227 OperandType type23(Type::TENSOR_QUANT8_ASYMM, {0, 2, 2, 1}, 0.1f, 128);
1228 OperandType type36(Type::TENSOR_FLOAT16, {0, 0, 0, 0});
1229 // Phase 1, operands
1230 auto scores = model->addOperand(&type13);
1231 auto roi = model->addOperand(&type14);
1232 auto param = model->addOperand(&type18);
1233 auto param1 = model->addOperand(&type19);
1234 auto param2 = model->addOperand(&type20);
1235 auto param3 = model->addOperand(&type20);
1236 auto param4 = model->addOperand(&type19);
1237 auto param5 = model->addOperand(&type19);
1238 auto param6 = model->addOperand(&type19);
1239 auto scoresOut = model->addOperand(&type15);
1240 auto roiOut = model->addOperand(&type17);
1241 auto classesOut = model->addOperand(&type16);
1242 auto batchSplitOut = model->addOperand(&type16);
1243 auto in = model->addOperand(&type22);
1244 auto param7 = model->addOperand(&type20);
1245 auto param8 = model->addOperand(&type20);
1246 auto param9 = model->addOperand(&type19);
1247 auto param10 = model->addOperand(&type19);
1248 auto param11 = model->addOperand(&type20);
1249 auto param12 = model->addOperand(&type20);
1250 auto layout = model->addOperand(&type21);
1251 auto featureMap = model->addOperand(&type23);
1252 auto out = model->addOperand(&type36);
1253 // Phase 2, operations
1254 static uint8_t scores_init[] = {137, 129};
1255 model->setOperandValue(scores, scores_init, sizeof(uint8_t) * 2);
1256 static uint16_t roi_init[] = {8, 8, 80, 80, 0, 0, 80, 80};
1257 model->setOperandValue(roi, roi_init, sizeof(uint16_t) * 8);
1258 static int32_t param_init[] = {0};
1259 model->setOperandValue(param, param_init, sizeof(int32_t) * 1);
1260 static float param1_init[] = {0.3f};
1261 model->setOperandValue(param1, param1_init, sizeof(float) * 1);
1262 static int32_t param2_init[] = {-1};
1263 model->setOperandValue(param2, param2_init, sizeof(int32_t) * 1);
1264 static int32_t param3_init[] = {0};
1265 model->setOperandValue(param3, param3_init, sizeof(int32_t) * 1);
1266 static float param4_init[] = {0.4f};
1267 model->setOperandValue(param4, param4_init, sizeof(float) * 1);
1268 static float param5_init[] = {1.0f};
1269 model->setOperandValue(param5, param5_init, sizeof(float) * 1);
1270 static float param6_init[] = {0.3f};
1271 model->setOperandValue(param6, param6_init, sizeof(float) * 1);
1272 static int32_t param7_init[] = {2};
1273 model->setOperandValue(param7, param7_init, sizeof(int32_t) * 1);
1274 static int32_t param8_init[] = {2};
1275 model->setOperandValue(param8, param8_init, sizeof(int32_t) * 1);
1276 static float param9_init[] = {2.0f};
1277 model->setOperandValue(param9, param9_init, sizeof(float) * 1);
1278 static float param10_init[] = {2.0f};
1279 model->setOperandValue(param10, param10_init, sizeof(float) * 1);
1280 static int32_t param11_init[] = {4};
1281 model->setOperandValue(param11, param11_init, sizeof(int32_t) * 1);
1282 static int32_t param12_init[] = {4};
1283 model->setOperandValue(param12, param12_init, sizeof(int32_t) * 1);
1284 static bool8 layout_init[] = {false};
1285 model->setOperandValue(layout, layout_init, sizeof(bool8) * 1);
1286 model->addOperation(ANEURALNETWORKS_BOX_WITH_NMS_LIMIT, {scores, roi, param, param1, param2, param3, param4, param5, param6}, {scoresOut, roiOut, classesOut, batchSplitOut});
1287 model->addOperation(ANEURALNETWORKS_ROI_ALIGN, {in, roiOut, batchSplitOut, param7, param8, param9, param10, param11, param12, layout}, {featureMap});
1288 model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {featureMap}, {out});
1289 // Phase 3, inputs and outputs
1290 model->identifyInputsAndOutputs(
1291 {in},
1292 {scoresOut, classesOut, out});
1293 assert(model->isValid());
1294 }
1295
is_ignored_zero_sized_dynamic_output_shape_float16(int i)1296 inline bool is_ignored_zero_sized_dynamic_output_shape_float16(int i) {
1297 static std::set<int> ignore = {};
1298 return ignore.find(i) != ignore.end();
1299 }
1300
1301