1 // clang-format off
2 // Generated file (from: avg_pool_float_2_relaxed.mod.py). Do not edit
CreateModel(Model * model)3 void CreateModel(Model *model) {
4 OperandType type0(Type::TENSOR_FLOAT32, {5, 52, 60, 3});
5 OperandType type1(Type::INT32, {});
6 OperandType type2(Type::TENSOR_FLOAT32, {5, 16, 18, 3});
7 // Phase 1, operands
8 auto i0 = model->addOperand(&type0);
9 auto padding = model->addOperand(&type1);
10 auto stride = model->addOperand(&type1);
11 auto filter = model->addOperand(&type1);
12 auto activation = model->addOperand(&type1);
13 auto output = model->addOperand(&type2);
14 // Phase 2, operations
15 static int32_t padding_init[] = {30};
16 model->setOperandValue(padding, padding_init, sizeof(int32_t) * 1);
17 static int32_t stride_init[] = {5};
18 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
19 static int32_t filter_init[] = {35};
20 model->setOperandValue(filter, filter_init, sizeof(int32_t) * 1);
21 static int32_t activation_init[] = {0};
22 model->setOperandValue(activation, activation_init, sizeof(int32_t) * 1);
23 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
24 // Phase 3, inputs and outputs
25 model->identifyInputsAndOutputs(
26 {i0},
27 {output});
28 // Phase 4: set relaxed execution
29 model->relaxComputationFloat32toFloat16(true);
30 assert(model->isValid());
31 }
32
is_ignored(int i)33 inline bool is_ignored(int i) {
34 static std::set<int> ignore = {};
35 return ignore.find(i) != ignore.end();
36 }
37
CreateModel_dynamic_output_shape(Model * model)38 void CreateModel_dynamic_output_shape(Model *model) {
39 OperandType type0(Type::TENSOR_FLOAT32, {5, 52, 60, 3});
40 OperandType type1(Type::INT32, {});
41 OperandType type3(Type::TENSOR_FLOAT32, {0, 0, 0, 0});
42 // Phase 1, operands
43 auto i0 = model->addOperand(&type0);
44 auto padding = model->addOperand(&type1);
45 auto stride = model->addOperand(&type1);
46 auto filter = model->addOperand(&type1);
47 auto activation = model->addOperand(&type1);
48 auto output = model->addOperand(&type3);
49 // Phase 2, operations
50 static int32_t padding_init[] = {30};
51 model->setOperandValue(padding, padding_init, sizeof(int32_t) * 1);
52 static int32_t stride_init[] = {5};
53 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
54 static int32_t filter_init[] = {35};
55 model->setOperandValue(filter, filter_init, sizeof(int32_t) * 1);
56 static int32_t activation_init[] = {0};
57 model->setOperandValue(activation, activation_init, sizeof(int32_t) * 1);
58 model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
59 // Phase 3, inputs and outputs
60 model->identifyInputsAndOutputs(
61 {i0},
62 {output});
63 // Phase 4: set relaxed execution
64 model->relaxComputationFloat32toFloat16(true);
65 assert(model->isValid());
66 }
67
is_ignored_dynamic_output_shape(int i)68 inline bool is_ignored_dynamic_output_shape(int i) {
69 static std::set<int> ignore = {};
70 return ignore.find(i) != ignore.end();
71 }
72
73