1 // Generated file (from: depthwise_conv2d_float_large_weights_as_inputs.mod.py). Do not edit
CreateModel(Model * model)2 void CreateModel(Model *model) {
3 OperandType type2(Type::INT32, {});
4 OperandType type3(Type::TENSOR_FLOAT32, {1, 1, 1, 2});
5 OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
6 OperandType type1(Type::TENSOR_FLOAT32, {2});
7 // Phase 1, operands
8 auto op1 = model->addOperand(&type0);
9 auto op2 = model->addOperand(&type0);
10 auto op3 = model->addOperand(&type1);
11 auto pad0 = model->addOperand(&type2);
12 auto act = model->addOperand(&type2);
13 auto stride = model->addOperand(&type2);
14 auto channelMultiplier = model->addOperand(&type2);
15 auto op4 = model->addOperand(&type3);
16 // Phase 2, operations
17 static int32_t pad0_init[] = {0};
18 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
19 static int32_t act_init[] = {0};
20 model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
21 static int32_t stride_init[] = {1};
22 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
23 static int32_t channelMultiplier_init[] = {1};
24 model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
26 // Phase 3, inputs and outputs
27 model->identifyInputsAndOutputs(
28 {op1, op2, op3},
29 {op4});
30 assert(model->isValid());
31 }
32
is_ignored(int i)33 bool is_ignored(int i) {
34 static std::set<int> ignore = {};
35 return ignore.find(i) != ignore.end();
36 }
37