blob: ee8f889418a4f59f61c577404b4701efaeb9cab6 [file]
// Generated from mul.mod.py
// DO NOT EDIT
// clang-format off
#include "TestGenerated.h"
namespace generated_tests::mul {
void CreateModel(Model *model) {
OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
OperandType type1(Type::INT32, {});
// Phase 1, operands
auto op1 = model->addOperand(&type0);
auto op2 = model->addOperand(&type0);
auto act = model->addOperand(&type1);
auto op3 = model->addOperand(&type0);
// Phase 2, operations
static int32_t act_init[] = {0};
model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
model->addOperation(ANEURALNETWORKS_MUL, {op1, op2, act}, {op3});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op1, op2},
{op3});
assert(model->isValid());
}
bool is_ignored(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
} // namespace generated_tests::mul
namespace generated_tests::mul {
void CreateModel_dynamic_output_shape(Model *model) {
OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
OperandType type1(Type::INT32, {});
OperandType type2(Type::TENSOR_FLOAT32, {0, 0, 0, 0});
// Phase 1, operands
auto op1 = model->addOperand(&type0);
auto op2 = model->addOperand(&type0);
auto act = model->addOperand(&type1);
auto op3 = model->addOperand(&type2);
// Phase 2, operations
static int32_t act_init[] = {0};
model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
model->addOperation(ANEURALNETWORKS_MUL, {op1, op2, act}, {op3});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op1, op2},
{op3});
assert(model->isValid());
}
bool is_ignored_dynamic_output_shape(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
} // namespace generated_tests::mul