| // Generated file (from: conv_1_h3_w2_SAME.mod.py). Do not edit |
| void CreateModel(Model *model) { |
| OperandType type0(Type::INT32, {1}); |
| OperandType type3(Type::TENSOR_FLOAT32, {1, 3, 2, 3}); |
| OperandType type2(Type::TENSOR_FLOAT32, {1, 8, 8, 1}); |
| OperandType type1(Type::TENSOR_FLOAT32, {1, 8, 8, 3}); |
| OperandType type4(Type::TENSOR_FLOAT32, {1}); |
| // Phase 1, operands |
| auto b4 = model->addOperand(&type0); |
| auto b5 = model->addOperand(&type0); |
| auto b6 = model->addOperand(&type0); |
| auto b7 = model->addOperand(&type0); |
| auto op2 = model->addOperand(&type1); |
| auto op3 = model->addOperand(&type2); |
| auto op0 = model->addOperand(&type3); |
| auto op1 = model->addOperand(&type4); |
| // Phase 2, operations |
| static int32_t b4_init[] = {1}; |
| model->setOperandValue(b4, b4_init, sizeof(int32_t) * 1); |
| static int32_t b5_init[] = {1}; |
| model->setOperandValue(b5, b5_init, sizeof(int32_t) * 1); |
| static int32_t b6_init[] = {1}; |
| model->setOperandValue(b6, b6_init, sizeof(int32_t) * 1); |
| static int32_t b7_init[] = {0}; |
| model->setOperandValue(b7, b7_init, sizeof(int32_t) * 1); |
| static float op0_init[] = {-0.966213f, -0.467474f, -0.82203f, -0.579455f, 0.0278809f, -0.79946f, -0.684259f, 0.563238f, 0.37289f, 0.738216f, 0.386045f, -0.917775f, 0.184325f, -0.270568f, 0.82236f, 0.0973683f, -0.941308f, -0.144706f}; |
| model->setOperandValue(op0, op0_init, sizeof(float) * 18); |
| static float op1_init[] = {0f}; |
| model->setOperandValue(op1, op1_init, sizeof(float) * 1); |
| model->addOperation(ANEURALNETWORKS_CONV, {op2, op0, op1, b4, b5, b6, b7}, {op3}); |
| // Phase 3, inputs and outputs |
| model->setInputsAndOutputs( |
| {op2}, |
| {op3}); |
| assert(model->isValid()); |
| } |