1 // clang-format off
2 // Generated file (from: depthwise_conv2d_float_large.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 float op2_init[] = {0.25f, 0.0f, 0.25f, 1.0f, 0.25f, 0.0f, 0.25f, 1.0f};
19 model->setOperandValue(op2, op2_init, sizeof(float) * 8);
20 static float op3_init[] = {100.0f, 200.0f};
21 model->setOperandValue(op3, op3_init, sizeof(float) * 2);
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 channelMultiplier_init[] = {1};
27 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
28 static int32_t act_init[] = {0};
29 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
30 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
31 // Phase 3, inputs and outputs
32 model->identifyInputsAndOutputs(
33 {op1},
34 {op4});
35 assert(model->isValid());
36 }
37
is_ignored(int i)38 inline bool is_ignored(int i) {
39 static std::set<int> ignore = {};
40 return ignore.find(i) != ignore.end();
41 }
42
CreateModel_dynamic_output_shape(Model * model)43 void CreateModel_dynamic_output_shape(Model *model) {
44 OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
45 OperandType type1(Type::TENSOR_FLOAT32, {2});
46 OperandType type2(Type::INT32, {});
47 OperandType type4(Type::TENSOR_FLOAT32, {0, 0, 0, 0});
48 // Phase 1, operands
49 auto op1 = model->addOperand(&type0);
50 auto op2 = model->addOperand(&type0);
51 auto op3 = model->addOperand(&type1);
52 auto pad0 = model->addOperand(&type2);
53 auto stride = model->addOperand(&type2);
54 auto channelMultiplier = model->addOperand(&type2);
55 auto act = model->addOperand(&type2);
56 auto op4 = model->addOperand(&type4);
57 // Phase 2, operations
58 static float op2_init[] = {0.25f, 0.0f, 0.25f, 1.0f, 0.25f, 0.0f, 0.25f, 1.0f};
59 model->setOperandValue(op2, op2_init, sizeof(float) * 8);
60 static float op3_init[] = {100.0f, 200.0f};
61 model->setOperandValue(op3, op3_init, sizeof(float) * 2);
62 static int32_t pad0_init[] = {0};
63 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
64 static int32_t stride_init[] = {1};
65 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
66 static int32_t channelMultiplier_init[] = {1};
67 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
68 static int32_t act_init[] = {0};
69 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
70 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
71 // Phase 3, inputs and outputs
72 model->identifyInputsAndOutputs(
73 {op1},
74 {op4});
75 assert(model->isValid());
76 }
77
is_ignored_dynamic_output_shape(int i)78 inline bool is_ignored_dynamic_output_shape(int i) {
79 static std::set<int> ignore = {};
80 return ignore.find(i) != ignore.end();
81 }
82
83