1 // clang-format off
2 // Generated file (from: conv_3_h3_w2_SAME_relaxed.mod.py). Do not edit
CreateModel(Model * model)3 void CreateModel(Model *model) {
4 OperandType type0(Type::INT32, {});
5 OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3});
6 OperandType type2(Type::TENSOR_FLOAT32, {3, 3, 2, 3});
7 OperandType type3(Type::TENSOR_FLOAT32, {3});
8 // Phase 1, operands
9 auto op2 = model->addOperand(&type1);
10 auto op0 = model->addOperand(&type2);
11 auto op1 = model->addOperand(&type3);
12 auto b4 = model->addOperand(&type0);
13 auto b5 = model->addOperand(&type0);
14 auto b6 = model->addOperand(&type0);
15 auto b7 = model->addOperand(&type0);
16 auto op3 = model->addOperand(&type1);
17 // Phase 2, operations
18 static float op0_init[] = {-0.966213f, -0.579455f, -0.684259f, 0.738216f, 0.184325f, 0.0973683f, -0.176863f, -0.23936f, -0.000233404f, 0.055546f, -0.232658f, -0.316404f, -0.012904f, 0.320705f, -0.326657f, -0.919674f, 0.868081f, -0.824608f, -0.467474f, 0.0278809f, 0.563238f, 0.386045f, -0.270568f, -0.941308f, -0.779227f, -0.261492f, -0.774804f, -0.79665f, 0.22473f, -0.414312f, 0.685897f, -0.327792f, 0.77395f, -0.714578f, -0.972365f, 0.0696099f, -0.82203f, -0.79946f, 0.37289f, -0.917775f, 0.82236f, -0.144706f, -0.167188f, 0.268062f, 0.702641f, -0.412223f, 0.755759f, 0.721547f, -0.43637f, -0.274905f, -0.269165f, 0.16102f, 0.819857f, -0.312008f};
19 model->setOperandValue(op0, op0_init, sizeof(float) * 54);
20 static float op1_init[] = {0.0f, 0.0f, 0.0f};
21 model->setOperandValue(op1, op1_init, sizeof(float) * 3);
22 static int32_t b4_init[] = {1};
23 model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1);
24 static int32_t b5_init[] = {1};
25 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1);
26 static int32_t b6_init[] = {1};
27 model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1);
28 static int32_t b7_init[] = {0};
29 model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1);
30 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3});
31 // Phase 3, inputs and outputs
32 model->identifyInputsAndOutputs(
33 {op2},
34 {op3});
35 // Phase 4: set relaxed execution
36 model->relaxComputationFloat32toFloat16(true);
37 assert(model->isValid());
38 }
39
is_ignored(int i)40 inline bool is_ignored(int i) {
41 static std::set<int> ignore = {};
42 return ignore.find(i) != ignore.end();
43 }
44
CreateModel_dynamic_output_shape(Model * model)45 void CreateModel_dynamic_output_shape(Model *model) {
46 OperandType type0(Type::INT32, {});
47 OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3});
48 OperandType type2(Type::TENSOR_FLOAT32, {3, 3, 2, 3});
49 OperandType type3(Type::TENSOR_FLOAT32, {3});
50 OperandType type4(Type::TENSOR_FLOAT32, {0, 0, 0, 0});
51 // Phase 1, operands
52 auto op2 = model->addOperand(&type1);
53 auto op0 = model->addOperand(&type2);
54 auto op1 = model->addOperand(&type3);
55 auto b4 = model->addOperand(&type0);
56 auto b5 = model->addOperand(&type0);
57 auto b6 = model->addOperand(&type0);
58 auto b7 = model->addOperand(&type0);
59 auto op3 = model->addOperand(&type4);
60 // Phase 2, operations
61 static float op0_init[] = {-0.966213f, -0.579455f, -0.684259f, 0.738216f, 0.184325f, 0.0973683f, -0.176863f, -0.23936f, -0.000233404f, 0.055546f, -0.232658f, -0.316404f, -0.012904f, 0.320705f, -0.326657f, -0.919674f, 0.868081f, -0.824608f, -0.467474f, 0.0278809f, 0.563238f, 0.386045f, -0.270568f, -0.941308f, -0.779227f, -0.261492f, -0.774804f, -0.79665f, 0.22473f, -0.414312f, 0.685897f, -0.327792f, 0.77395f, -0.714578f, -0.972365f, 0.0696099f, -0.82203f, -0.79946f, 0.37289f, -0.917775f, 0.82236f, -0.144706f, -0.167188f, 0.268062f, 0.702641f, -0.412223f, 0.755759f, 0.721547f, -0.43637f, -0.274905f, -0.269165f, 0.16102f, 0.819857f, -0.312008f};
62 model->setOperandValue(op0, op0_init, sizeof(float) * 54);
63 static float op1_init[] = {0.0f, 0.0f, 0.0f};
64 model->setOperandValue(op1, op1_init, sizeof(float) * 3);
65 static int32_t b4_init[] = {1};
66 model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1);
67 static int32_t b5_init[] = {1};
68 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1);
69 static int32_t b6_init[] = {1};
70 model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1);
71 static int32_t b7_init[] = {0};
72 model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1);
73 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3});
74 // Phase 3, inputs and outputs
75 model->identifyInputsAndOutputs(
76 {op2},
77 {op3});
78 // Phase 4: set relaxed execution
79 model->relaxComputationFloat32toFloat16(true);
80 assert(model->isValid());
81 }
82
is_ignored_dynamic_output_shape(int i)83 inline bool is_ignored_dynamic_output_shape(int i) {
84 static std::set<int> ignore = {};
85 return ignore.find(i) != ignore.end();
86 }
87
CreateModel_2(Model * model)88 void CreateModel_2(Model *model) {
89 OperandType type0(Type::INT32, {});
90 OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3});
91 OperandType type2(Type::TENSOR_FLOAT32, {3, 3, 2, 3});
92 OperandType type3(Type::TENSOR_FLOAT32, {3});
93 // Phase 1, operands
94 auto op2 = model->addOperand(&type1);
95 auto op0 = model->addOperand(&type2);
96 auto op1 = model->addOperand(&type3);
97 auto b4 = model->addOperand(&type0);
98 auto b5 = model->addOperand(&type0);
99 auto b6 = model->addOperand(&type0);
100 auto b7 = model->addOperand(&type0);
101 auto op3 = model->addOperand(&type1);
102 // Phase 2, operations
103 static float op0_init[] = {-0.966213f, -0.579455f, -0.684259f, 0.738216f, 0.184325f, 0.0973683f, -0.176863f, -0.23936f, -0.000233404f, 0.055546f, -0.232658f, -0.316404f, -0.012904f, 0.320705f, -0.326657f, -0.919674f, 0.868081f, -0.824608f, -0.467474f, 0.0278809f, 0.563238f, 0.386045f, -0.270568f, -0.941308f, -0.779227f, -0.261492f, -0.774804f, -0.79665f, 0.22473f, -0.414312f, 0.685897f, -0.327792f, 0.77395f, -0.714578f, -0.972365f, 0.0696099f, -0.82203f, -0.79946f, 0.37289f, -0.917775f, 0.82236f, -0.144706f, -0.167188f, 0.268062f, 0.702641f, -0.412223f, 0.755759f, 0.721547f, -0.43637f, -0.274905f, -0.269165f, 0.16102f, 0.819857f, -0.312008f};
104 model->setOperandValue(op0, op0_init, sizeof(float) * 54);
105 static float op1_init[] = {0.0f, 0.0f, 0.0f};
106 model->setOperandValue(op1, op1_init, sizeof(float) * 3);
107 static int32_t b4_init[] = {1};
108 model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1);
109 static int32_t b5_init[] = {1};
110 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1);
111 static int32_t b6_init[] = {1};
112 model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1);
113 static int32_t b7_init[] = {0};
114 model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1);
115 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3});
116 // Phase 3, inputs and outputs
117 model->identifyInputsAndOutputs(
118 {op2},
119 {op3});
120 // Phase 4: set relaxed execution
121 model->relaxComputationFloat32toFloat16(true);
122 assert(model->isValid());
123 }
124
is_ignored_2(int i)125 inline bool is_ignored_2(int i) {
126 static std::set<int> ignore = {};
127 return ignore.find(i) != ignore.end();
128 }
129
CreateModel_dynamic_output_shape_2(Model * model)130 void CreateModel_dynamic_output_shape_2(Model *model) {
131 OperandType type0(Type::INT32, {});
132 OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3});
133 OperandType type2(Type::TENSOR_FLOAT32, {3, 3, 2, 3});
134 OperandType type3(Type::TENSOR_FLOAT32, {3});
135 OperandType type4(Type::TENSOR_FLOAT32, {0, 0, 0, 0});
136 // Phase 1, operands
137 auto op2 = model->addOperand(&type1);
138 auto op0 = model->addOperand(&type2);
139 auto op1 = model->addOperand(&type3);
140 auto b4 = model->addOperand(&type0);
141 auto b5 = model->addOperand(&type0);
142 auto b6 = model->addOperand(&type0);
143 auto b7 = model->addOperand(&type0);
144 auto op3 = model->addOperand(&type4);
145 // Phase 2, operations
146 static float op0_init[] = {-0.966213f, -0.579455f, -0.684259f, 0.738216f, 0.184325f, 0.0973683f, -0.176863f, -0.23936f, -0.000233404f, 0.055546f, -0.232658f, -0.316404f, -0.012904f, 0.320705f, -0.326657f, -0.919674f, 0.868081f, -0.824608f, -0.467474f, 0.0278809f, 0.563238f, 0.386045f, -0.270568f, -0.941308f, -0.779227f, -0.261492f, -0.774804f, -0.79665f, 0.22473f, -0.414312f, 0.685897f, -0.327792f, 0.77395f, -0.714578f, -0.972365f, 0.0696099f, -0.82203f, -0.79946f, 0.37289f, -0.917775f, 0.82236f, -0.144706f, -0.167188f, 0.268062f, 0.702641f, -0.412223f, 0.755759f, 0.721547f, -0.43637f, -0.274905f, -0.269165f, 0.16102f, 0.819857f, -0.312008f};
147 model->setOperandValue(op0, op0_init, sizeof(float) * 54);
148 static float op1_init[] = {0.0f, 0.0f, 0.0f};
149 model->setOperandValue(op1, op1_init, sizeof(float) * 3);
150 static int32_t b4_init[] = {1};
151 model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1);
152 static int32_t b5_init[] = {1};
153 model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1);
154 static int32_t b6_init[] = {1};
155 model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1);
156 static int32_t b7_init[] = {0};
157 model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1);
158 model->addOperation(ANEURALNETWORKS_CONV_2D, {op2, op0, op1, b4, b5, b6, b7}, {op3});
159 // Phase 3, inputs and outputs
160 model->identifyInputsAndOutputs(
161 {op2},
162 {op3});
163 // Phase 4: set relaxed execution
164 model->relaxComputationFloat32toFloat16(true);
165 assert(model->isValid());
166 }
167
is_ignored_dynamic_output_shape_2(int i)168 inline bool is_ignored_dynamic_output_shape_2(int i) {
169 static std::set<int> ignore = {};
170 return ignore.find(i) != ignore.end();
171 }
172
173