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// Generated file (from: l2_pool_float_large.mod.py). Do not edit
void CreateModel(Model *model) {
OperandType type1(Type::INT32, {});
OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 1, 3});
OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 3});
// Phase 1, operands
auto op1 = model->addOperand(&type0);
auto filter_width = model->addOperand(&type1);
auto filter_height = model->addOperand(&type1);
auto stride_width = model->addOperand(&type1);
auto stride_height = model->addOperand(&type1);
auto pad0 = model->addOperand(&type1);
auto act = model->addOperand(&type1);
auto op3 = model->addOperand(&type2);
// Phase 2, operations
static int32_t filter_width_init[] = {2};
model->setOperandValue(filter_width, filter_width_init, sizeof(int32_t) * 1);
static int32_t filter_height_init[] = {2};
model->setOperandValue(filter_height, filter_height_init, sizeof(int32_t) * 1);
static int32_t stride_width_init[] = {1};
model->setOperandValue(stride_width, stride_width_init, sizeof(int32_t) * 1);
static int32_t stride_height_init[] = {1};
model->setOperandValue(stride_height, stride_height_init, sizeof(int32_t) * 1);
static int32_t pad0_init[] = {0};
model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
static int32_t act_init[] = {0};
model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
model->addOperation(ANEURALNETWORKS_L2_POOL_2D, {op1, pad0, pad0, pad0, pad0, stride_width, stride_height, filter_width, filter_height, act}, {op3});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op1},
{op3});
assert(model->isValid());
}
bool is_ignored(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
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