1 // clang-format off
2 // Generated file (from: conv_float_2.mod.py). Do not edit
CreateModel(Model * model)3 void CreateModel(Model *model) {
4 OperandType type0(Type::TENSOR_FLOAT32, {1, 3, 4, 1});
5 OperandType type1(Type::TENSOR_FLOAT32, {1, 3, 3, 1});
6 OperandType type2(Type::TENSOR_FLOAT32, {1});
7 OperandType type3(Type::INT32, {});
8 // Phase 1, operands
9 auto op1 = model->addOperand(&type0);
10 auto op2 = model->addOperand(&type1);
11 auto op3 = model->addOperand(&type2);
12 auto pad_same = model->addOperand(&type3);
13 auto stride = model->addOperand(&type3);
14 auto act_relu = model->addOperand(&type3);
15 auto op4 = model->addOperand(&type0);
16 // Phase 2, operations
17 static float op2_init[] = {1.0f, 4.0f, 7.0f, 2.0f, 5.0f, 8.0f, 3.0f, 6.0f, 9.0f};
18 model->setOperandValue(op2, op2_init, sizeof(float) * 9);
19 static float op3_init[] = {-200.0f};
20 model->setOperandValue(op3, op3_init, sizeof(float) * 1);
21 static int32_t pad_same_init[] = {1};
22 model->setOperandValue(pad_same, pad_same_init, sizeof(int32_t) * 1);
23 static int32_t stride_init[] = {1};
24 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
25 static int32_t act_relu_init[] = {1};
26 model->setOperandValue(act_relu, act_relu_init, sizeof(int32_t) * 1);
27 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad_same, stride, stride, act_relu}, {op4});
28 // Phase 3, inputs and outputs
29 model->identifyInputsAndOutputs(
30 {op1},
31 {op4});
32 assert(model->isValid());
33 }
34
is_ignored(int i)35 inline bool is_ignored(int i) {
36 static std::set<int> ignore = {};
37 return ignore.find(i) != ignore.end();
38 }
39
CreateModel_dynamic_output_shape(Model * model)40 void CreateModel_dynamic_output_shape(Model *model) {
41 OperandType type0(Type::TENSOR_FLOAT32, {1, 3, 4, 1});
42 OperandType type1(Type::TENSOR_FLOAT32, {1, 3, 3, 1});
43 OperandType type2(Type::TENSOR_FLOAT32, {1});
44 OperandType type3(Type::INT32, {});
45 OperandType type4(Type::TENSOR_FLOAT32, {0, 0, 0, 0});
46 // Phase 1, operands
47 auto op1 = model->addOperand(&type0);
48 auto op2 = model->addOperand(&type1);
49 auto op3 = model->addOperand(&type2);
50 auto pad_same = model->addOperand(&type3);
51 auto stride = model->addOperand(&type3);
52 auto act_relu = model->addOperand(&type3);
53 auto op4 = model->addOperand(&type4);
54 // Phase 2, operations
55 static float op2_init[] = {1.0f, 4.0f, 7.0f, 2.0f, 5.0f, 8.0f, 3.0f, 6.0f, 9.0f};
56 model->setOperandValue(op2, op2_init, sizeof(float) * 9);
57 static float op3_init[] = {-200.0f};
58 model->setOperandValue(op3, op3_init, sizeof(float) * 1);
59 static int32_t pad_same_init[] = {1};
60 model->setOperandValue(pad_same, pad_same_init, sizeof(int32_t) * 1);
61 static int32_t stride_init[] = {1};
62 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
63 static int32_t act_relu_init[] = {1};
64 model->setOperandValue(act_relu, act_relu_init, sizeof(int32_t) * 1);
65 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad_same, stride, stride, act_relu}, {op4});
66 // Phase 3, inputs and outputs
67 model->identifyInputsAndOutputs(
68 {op1},
69 {op4});
70 assert(model->isValid());
71 }
72
is_ignored_dynamic_output_shape(int i)73 inline bool is_ignored_dynamic_output_shape(int i) {
74 static std::set<int> ignore = {};
75 return ignore.find(i) != ignore.end();
76 }
77
78