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1 // clang-format off
2 // Generated file (from: conv_float_channels.mod.py). Do not edit
CreateModel(Model * model)3 void CreateModel(Model *model) {
4   OperandType type0(Type::TENSOR_FLOAT32, {1, 1, 1, 3});
5   OperandType type1(Type::TENSOR_FLOAT32, {3, 1, 1, 3});
6   OperandType type2(Type::TENSOR_FLOAT32, {3});
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 pad0 = model->addOperand(&type3);
13   auto stride = model->addOperand(&type3);
14   auto act = model->addOperand(&type3);
15   auto op4 = model->addOperand(&type0);
16   // Phase 2, operations
17   static float op2_init[] = {1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f, 3.0f, 3.0f, 3.0f};
18   model->setOperandValue(op2, op2_init, sizeof(float) * 9);
19   static float op3_init[] = {0.0f, 0.0f, 0.0f};
20   model->setOperandValue(op3, op3_init, sizeof(float) * 3);
21   static int32_t pad0_init[] = {0};
22   model->setOperandValue(pad0, pad0_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_init[] = {0};
26   model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
27   model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {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, 1, 1, 3});
42   OperandType type1(Type::TENSOR_FLOAT32, {3, 1, 1, 3});
43   OperandType type2(Type::TENSOR_FLOAT32, {3});
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 pad0 = model->addOperand(&type3);
51   auto stride = model->addOperand(&type3);
52   auto act = model->addOperand(&type3);
53   auto op4 = model->addOperand(&type4);
54   // Phase 2, operations
55   static float op2_init[] = {1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f, 3.0f, 3.0f, 3.0f};
56   model->setOperandValue(op2, op2_init, sizeof(float) * 9);
57   static float op3_init[] = {0.0f, 0.0f, 0.0f};
58   model->setOperandValue(op3, op3_init, sizeof(float) * 3);
59   static int32_t pad0_init[] = {0};
60   model->setOperandValue(pad0, pad0_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_init[] = {0};
64   model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
65   model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {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