1 // clang-format off
2 // Generated file (from: l2_pool_float_large.mod.py). Do not edit
CreateModel(Model * model)3 void CreateModel(Model *model) {
4 OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 3});
5 OperandType type1(Type::INT32, {});
6 OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 1, 3});
7 // Phase 1, operands
8 auto op1 = model->addOperand(&type0);
9 auto pad0 = model->addOperand(&type1);
10 auto stride_width = model->addOperand(&type1);
11 auto stride_height = model->addOperand(&type1);
12 auto filter_width = model->addOperand(&type1);
13 auto filter_height = model->addOperand(&type1);
14 auto act = model->addOperand(&type1);
15 auto op3 = model->addOperand(&type2);
16 // Phase 2, operations
17 static int32_t pad0_init[] = {0};
18 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
19 static int32_t stride_width_init[] = {1};
20 model->setOperandValue(stride_width, stride_width_init, sizeof(int32_t) * 1);
21 static int32_t stride_height_init[] = {1};
22 model->setOperandValue(stride_height, stride_height_init, sizeof(int32_t) * 1);
23 static int32_t filter_width_init[] = {2};
24 model->setOperandValue(filter_width, filter_width_init, sizeof(int32_t) * 1);
25 static int32_t filter_height_init[] = {2};
26 model->setOperandValue(filter_height, filter_height_init, sizeof(int32_t) * 1);
27 static int32_t act_init[] = {0};
28 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
29 model->addOperation(ANEURALNETWORKS_L2_POOL_2D, {op1, pad0, pad0, pad0, pad0, stride_width, stride_height, filter_width, filter_height, act}, {op3});
30 // Phase 3, inputs and outputs
31 model->identifyInputsAndOutputs(
32 {op1},
33 {op3});
34 assert(model->isValid());
35 }
36
is_ignored(int i)37 inline bool is_ignored(int i) {
38 static std::set<int> ignore = {};
39 return ignore.find(i) != ignore.end();
40 }
41
CreateModel_dynamic_output_shape(Model * model)42 void CreateModel_dynamic_output_shape(Model *model) {
43 OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 3});
44 OperandType type1(Type::INT32, {});
45 OperandType type3(Type::TENSOR_FLOAT32, {0, 0, 0, 0});
46 // Phase 1, operands
47 auto op1 = model->addOperand(&type0);
48 auto pad0 = model->addOperand(&type1);
49 auto stride_width = model->addOperand(&type1);
50 auto stride_height = model->addOperand(&type1);
51 auto filter_width = model->addOperand(&type1);
52 auto filter_height = model->addOperand(&type1);
53 auto act = model->addOperand(&type1);
54 auto op3 = model->addOperand(&type3);
55 // Phase 2, operations
56 static int32_t pad0_init[] = {0};
57 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
58 static int32_t stride_width_init[] = {1};
59 model->setOperandValue(stride_width, stride_width_init, sizeof(int32_t) * 1);
60 static int32_t stride_height_init[] = {1};
61 model->setOperandValue(stride_height, stride_height_init, sizeof(int32_t) * 1);
62 static int32_t filter_width_init[] = {2};
63 model->setOperandValue(filter_width, filter_width_init, sizeof(int32_t) * 1);
64 static int32_t filter_height_init[] = {2};
65 model->setOperandValue(filter_height, filter_height_init, sizeof(int32_t) * 1);
66 static int32_t act_init[] = {0};
67 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
68 model->addOperation(ANEURALNETWORKS_L2_POOL_2D, {op1, pad0, pad0, pad0, pad0, stride_width, stride_height, filter_width, filter_height, act}, {op3});
69 // Phase 3, inputs and outputs
70 model->identifyInputsAndOutputs(
71 {op1},
72 {op3});
73 assert(model->isValid());
74 }
75
is_ignored_dynamic_output_shape(int i)76 inline bool is_ignored_dynamic_output_shape(int i) {
77 static std::set<int> ignore = {};
78 return ignore.find(i) != ignore.end();
79 }
80
81