1 // clang-format off
2 // Generated file (from: depthwise_conv2d_float_large_weights_as_inputs_relaxed.mod.py). Do not edit
CreateModel(Model * model)3 void CreateModel(Model *model) {
4 OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
5 OperandType type1(Type::TENSOR_FLOAT32, {2});
6 OperandType type2(Type::INT32, {});
7 OperandType type3(Type::TENSOR_FLOAT32, {1, 1, 1, 2});
8 // Phase 1, operands
9 auto op1 = model->addOperand(&type0);
10 auto op2 = model->addOperand(&type0);
11 auto op3 = model->addOperand(&type1);
12 auto pad0 = model->addOperand(&type2);
13 auto stride = model->addOperand(&type2);
14 auto channelMultiplier = model->addOperand(&type2);
15 auto act = model->addOperand(&type2);
16 auto op4 = model->addOperand(&type3);
17 // Phase 2, operations
18 static int32_t pad0_init[] = {0};
19 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
20 static int32_t stride_init[] = {1};
21 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
22 static int32_t channelMultiplier_init[] = {1};
23 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
24 static int32_t act_init[] = {0};
25 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
26 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
27 // Phase 3, inputs and outputs
28 model->identifyInputsAndOutputs(
29 {op1, op2, op3},
30 {op4});
31 // Phase 4: set relaxed execution
32 model->relaxComputationFloat32toFloat16(true);
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_FLOAT32, {1, 2, 2, 2});
43 OperandType type1(Type::TENSOR_FLOAT32, {2});
44 OperandType type2(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(&type0);
49 auto op3 = model->addOperand(&type1);
50 auto pad0 = model->addOperand(&type2);
51 auto stride = model->addOperand(&type2);
52 auto channelMultiplier = model->addOperand(&type2);
53 auto act = model->addOperand(&type2);
54 auto op4 = model->addOperand(&type4);
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_init[] = {1};
59 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
60 static int32_t channelMultiplier_init[] = {1};
61 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
62 static int32_t act_init[] = {0};
63 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
64 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
65 // Phase 3, inputs and outputs
66 model->identifyInputsAndOutputs(
67 {op1, op2, op3},
68 {op4});
69 // Phase 4: set relaxed execution
70 model->relaxComputationFloat32toFloat16(true);
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