1 // clang-format off 2 // Generated file (from: conv_float_large.mod.py). Do not edit 3 void CreateModel(Model *model) { 4 OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 3, 3}); 5 OperandType type1(Type::TENSOR_FLOAT32, {3, 1, 1, 3}); 6 OperandType type2(Type::TENSOR_FLOAT32, {3}); 7 OperandType type3(Type::INT32, {}); 8 // Phase 1, operands 9 auto op1 = model->addOperand(&type0); 10 auto op2 = model->addOperand(&type1); 11 auto op3 = model->addOperand(&type2); 12 auto pad0 = model->addOperand(&type3); 13 auto stride = model->addOperand(&type3); 14 auto act = model->addOperand(&type3); 15 auto op4 = model->addOperand(&type0); 16 // Phase 2, operations 17 static float op2_init[] = {1.0f, 4.0f, 7.0f, 2.0f, 5.0f, 8.0f, 3.0f, 6.0f, 9.0f}; 18 model->setOperandValue(op2, op2_init, sizeof(float) * 9); 19 static float op3_init[] = {0.0f, 0.0f, 0.0f}; 20 model->setOperandValue(op3, op3_init, sizeof(float) * 3); 21 static int32_t pad0_init[] = {0}; 22 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 23 static int32_t stride_init[] = {1}; 24 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 25 static int32_t act_init[] = {0}; 26 model->setOperandValue(act, act_init, sizeof(int32_t) * 1); 27 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4}); 28 // Phase 3, inputs and outputs 29 model->identifyInputsAndOutputs( 30 {op1}, 31 {op4}); 32 assert(model->isValid()); 33 } 34 35 inline bool is_ignored(int i) { 36 static std::set<int> ignore = {}; 37 return ignore.find(i) != ignore.end(); 38 } 39 40 void CreateModel_dynamic_output_shape(Model *model) { 41 OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 3, 3}); 42 OperandType type1(Type::TENSOR_FLOAT32, {3, 1, 1, 3}); 43 OperandType type2(Type::TENSOR_FLOAT32, {3}); 44 OperandType type3(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(&type1); 49 auto op3 = model->addOperand(&type2); 50 auto pad0 = model->addOperand(&type3); 51 auto stride = model->addOperand(&type3); 52 auto act = model->addOperand(&type3); 53 auto op4 = model->addOperand(&type4); 54 // Phase 2, operations 55 static float op2_init[] = {1.0f, 4.0f, 7.0f, 2.0f, 5.0f, 8.0f, 3.0f, 6.0f, 9.0f}; 56 model->setOperandValue(op2, op2_init, sizeof(float) * 9); 57 static float op3_init[] = {0.0f, 0.0f, 0.0f}; 58 model->setOperandValue(op3, op3_init, sizeof(float) * 3); 59 static int32_t pad0_init[] = {0}; 60 model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); 61 static int32_t stride_init[] = {1}; 62 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1); 63 static int32_t act_init[] = {0}; 64 model->setOperandValue(act, act_init, sizeof(int32_t) * 1); 65 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4}); 66 // Phase 3, inputs and outputs 67 model->identifyInputsAndOutputs( 68 {op1}, 69 {op4}); 70 assert(model->isValid()); 71 } 72 73 inline bool is_ignored_dynamic_output_shape(int i) { 74 static std::set<int> ignore = {}; 75 return ignore.find(i) != ignore.end(); 76 } 77 78
