1 // clang-format off
2 // Generated file (from: conv_quant8_large.mod.py). Do not edit
CreateModel(Model * model)3 void CreateModel(Model *model) {
4 OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 2, 3, 3}, 0.5f, 0);
5 OperandType type1(Type::TENSOR_QUANT8_ASYMM, {3, 1, 1, 3}, 0.5f, 0);
6 OperandType type2(Type::TENSOR_INT32, {3}, 0.25f, 0);
7 OperandType type3(Type::INT32, {});
8 OperandType type4(Type::TENSOR_QUANT8_ASYMM, {1, 2, 3, 3}, 1.0f, 0);
9 // Phase 1, operands
10 auto op1 = model->addOperand(&type0);
11 auto op2 = model->addOperand(&type1);
12 auto op3 = model->addOperand(&type2);
13 auto pad0 = model->addOperand(&type3);
14 auto stride = model->addOperand(&type3);
15 auto act = model->addOperand(&type3);
16 auto op4 = model->addOperand(&type4);
17 // Phase 2, operations
18 static uint8_t op2_init[] = {1, 4, 7, 2, 5, 8, 3, 6, 9};
19 model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 9);
20 static int32_t op3_init[] = {0, 0, 0};
21 model->setOperandValue(op3, op3_init, sizeof(int32_t) * 3);
22 static int32_t pad0_init[] = {0};
23 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
24 static int32_t stride_init[] = {1};
25 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
26 static int32_t act_init[] = {0};
27 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
28 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
29 // Phase 3, inputs and outputs
30 model->identifyInputsAndOutputs(
31 {op1},
32 {op4});
33 assert(model->isValid());
34 }
35
is_ignored(int i)36 inline bool is_ignored(int i) {
37 static std::set<int> ignore = {};
38 return ignore.find(i) != ignore.end();
39 }
40
CreateModel_dynamic_output_shape(Model * model)41 void CreateModel_dynamic_output_shape(Model *model) {
42 OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 2, 3, 3}, 0.5f, 0);
43 OperandType type1(Type::TENSOR_QUANT8_ASYMM, {3, 1, 1, 3}, 0.5f, 0);
44 OperandType type2(Type::TENSOR_INT32, {3}, 0.25f, 0);
45 OperandType type3(Type::INT32, {});
46 OperandType type5(Type::TENSOR_QUANT8_ASYMM, {0, 0, 0, 0}, 1.0f, 0);
47 // Phase 1, operands
48 auto op1 = model->addOperand(&type0);
49 auto op2 = model->addOperand(&type1);
50 auto op3 = model->addOperand(&type2);
51 auto pad0 = model->addOperand(&type3);
52 auto stride = model->addOperand(&type3);
53 auto act = model->addOperand(&type3);
54 auto op4 = model->addOperand(&type5);
55 // Phase 2, operations
56 static uint8_t op2_init[] = {1, 4, 7, 2, 5, 8, 3, 6, 9};
57 model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 9);
58 static int32_t op3_init[] = {0, 0, 0};
59 model->setOperandValue(op3, op3_init, sizeof(int32_t) * 3);
60 static int32_t pad0_init[] = {0};
61 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
62 static int32_t stride_init[] = {1};
63 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
64 static int32_t act_init[] = {0};
65 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
66 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
67 // Phase 3, inputs and outputs
68 model->identifyInputsAndOutputs(
69 {op1},
70 {op4});
71 assert(model->isValid());
72 }
73
is_ignored_dynamic_output_shape(int i)74 inline bool is_ignored_dynamic_output_shape(int i) {
75 static std::set<int> ignore = {};
76 return ignore.find(i) != ignore.end();
77 }
78
79