1 // clang-format off
2 // Generated file (from: avg_pool_quant8_3.mod.py). Do not edit
CreateModel(Model * model)3 void CreateModel(Model *model) {
4   OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 100, 100, 1}, 0.5f, 0);
5   OperandType type1(Type::INT32, {});
6   OperandType type2(Type::TENSOR_QUANT8_ASYMM, {1, 23, 23, 1}, 0.5f, 0);
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[] = {0};
16   model->setOperandValue(padding, padding_init, sizeof(int32_t) * 1);
17   static int32_t stride_init[] = {4};
18   model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
19   static int32_t filter_init[] = {10};
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   assert(model->isValid());
29 }
30 
is_ignored(int i)31 inline bool is_ignored(int i) {
32   static std::set<int> ignore = {};
33   return ignore.find(i) != ignore.end();
34 }
35 
CreateModel_dynamic_output_shape(Model * model)36 void CreateModel_dynamic_output_shape(Model *model) {
37   OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 100, 100, 1}, 0.5f, 0);
38   OperandType type1(Type::INT32, {});
39   OperandType type3(Type::TENSOR_QUANT8_ASYMM, {0, 0, 0, 0}, 0.5f, 0);
40   // Phase 1, operands
41   auto i0 = model->addOperand(&type0);
42   auto padding = model->addOperand(&type1);
43   auto stride = model->addOperand(&type1);
44   auto filter = model->addOperand(&type1);
45   auto activation = model->addOperand(&type1);
46   auto output = model->addOperand(&type3);
47   // Phase 2, operations
48   static int32_t padding_init[] = {0};
49   model->setOperandValue(padding, padding_init, sizeof(int32_t) * 1);
50   static int32_t stride_init[] = {4};
51   model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
52   static int32_t filter_init[] = {10};
53   model->setOperandValue(filter, filter_init, sizeof(int32_t) * 1);
54   static int32_t activation_init[] = {0};
55   model->setOperandValue(activation, activation_init, sizeof(int32_t) * 1);
56   model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
57   // Phase 3, inputs and outputs
58   model->identifyInputsAndOutputs(
59     {i0},
60     {output});
61   assert(model->isValid());
62 }
63 
is_ignored_dynamic_output_shape(int i)64 inline bool is_ignored_dynamic_output_shape(int i) {
65   static std::set<int> ignore = {};
66   return ignore.find(i) != ignore.end();
67 }
68 
69