void
sanguis::server::auras::update_sight::enter(
sanguis::server::entities::with_body &_entity,
sanguis::collision::world::created const _created
)
{
fcppt::optional::maybe_void(
fcppt::cast::dynamic_cross<
sanguis::server::entities::with_id const
>(
_entity
),
[
this,
_created
](
fcppt::reference<
sanguis::server::entities::with_id const
> const _with_id
)
{
add_(
_with_id.get(),
_created
);
}
);
}
/// Adapted from
/// https://github.com/pytorch/pytorch/blob/master/torch/optim/adagrad.py
void Adagrad::step() {
for (auto& pair : model_->parameters()) {
auto& name = pair.first;
auto& grad = pair.second.grad();
auto& p = pair.second.data();
if (!grad.defined())
continue;
auto d_p = torch::autograd::as_variable_ref(grad).data();
if (weight_decay_ > 0) {
d_p.add_(p, weight_decay_);
};
auto& step = step_[name];
step += 1.0;
auto clr = lr_ / (1.0 + (step - 1.0) * lr_decay_);
at::Tensor buf;
if (sum_.find(name) == sum_.end()) {
buf = sum_[name] = at::zeros_like(p);
} else {
buf = sum_[name];
}
buf.addcmul_(d_p, d_p, 1.0);
at::Tensor std = buf.sqrt().add_(1e-10);
p.addcdiv_(d_p, std, -clr);
}
}
int main(){
int num,num1;
char sim;
printf("사칙연산 할 두 수를 적으세요. : ");
scanf("%d %d",&num,&num1);
printf("사칙연산 할 기호를 적어주세요. : ");
scanf(" %c",&sim);
int (*add_)(int,int);
int (*minus_)(int,int);
int (*multi_)(int,int);
double (*avg_)(int,int);
add_ = add;
minus_ = minus;
multi_ = multi;
avg_ = avg;
switch(sim){
case '+' : printf("두 수의 덧셈의 값 : %d\n",add_(num,num1)); break;
case '-' : printf("두 수의 뺄셈의 값 : %d\n",minus_(num,num1)); break;
case '/' : printf("두 수의 나눗셈의 값 : %.2lf",avg_(num,num1)); break;
case '*' : printf("두 수의 곱셈의 값 : %d\n",multi_(num,num1)); break;
default : printf("문자를 잘못입력하셨습니다.\n종료합니다.\n");
}
return 0;
}
void SGD::step() {
for (auto& pair : model_->parameters()) {
auto& name = pair.first;
auto& grad = pair.second.grad();
auto& p = pair.second.data();
if (!grad.defined())
continue;
auto d_p = torch::autograd::as_variable_ref(grad).data();
if (weight_decay_ > 0) {
d_p.add_(p, weight_decay_);
};
if (momentum_ != 0) {
at::Tensor buf;
if (momentum_buffers_.find(name) == momentum_buffers_.end()) {
buf = momentum_buffers_[name] = at::zeros_like(p);
buf.mul_(momentum_).add_(d_p);
} else {
buf = momentum_buffers_[name];
buf.mul_(momentum_).add_(d_p, 1 - dampening_);
}
if (nesterov_) {
d_p = d_p.add(buf, momentum_);
} else {
d_p = buf;
}
}
p.add_(d_p, -lr_);
}
}
TEST_F(LQPUtilsTest, LQPFindModifiedTables) {
// clang-format off
const auto read_only_lqp =
PredicateNode::make(greater_than_(a_a, 5),
ProjectionNode::make(expression_vector(add_(a_a, a_b), a_a),
PredicateNode::make(less_than_(a_b, 4),
SortNode::make(expression_vector(a_b), std::vector<OrderByMode>{OrderByMode::Ascending},
node_a))));
// clang-format on
EXPECT_EQ(lqp_find_modified_tables(read_only_lqp).size(), 0);
// clang-format off
const auto insert_lqp =
InsertNode::make("insert_table_name",
PredicateNode::make(greater_than_(a_a, 5),
node_a));
// clang-format on
const auto insert_tables = lqp_find_modified_tables(insert_lqp);
EXPECT_EQ(insert_tables.size(), 1);
EXPECT_NE(insert_tables.find("insert_table_name"), insert_tables.end());
const auto delete_lqp = DeleteNode::make(node_a);
const auto delete_tables = lqp_find_modified_tables(delete_lqp);
EXPECT_EQ(delete_tables.size(), 1);
EXPECT_NE(delete_tables.find("node_a"), delete_tables.end());
}
TEST_F(JoinNodeTest, IsColumnNullableWithoutOuterJoin) {
// Test that for LQPs without (Left,Right)Outer Joins, lqp_column_is_nullable() is equivalent to
// expression.is_nullable()
// clang-format off
const auto lqp =
JoinNode::make(JoinMode::Inner, equals_(add_(_t_a_a, null_()), _t_b_x),
ProjectionNode::make(expression_vector(_t_a_a, _t_a_b, add_(_t_a_a, null_())),
_mock_node_a),
_mock_node_b);
// clang-format on
EXPECT_FALSE(lqp->is_column_nullable(ColumnID{0}));
EXPECT_FALSE(lqp->is_column_nullable(ColumnID{1}));
EXPECT_TRUE(lqp->is_column_nullable(ColumnID{2}));
EXPECT_FALSE(lqp->is_column_nullable(ColumnID{3}));
EXPECT_FALSE(lqp->is_column_nullable(ColumnID{4}));
}
bool Set::add(int val){
if (size > 0){
for (int i = 0; i < size; i++){
if (values[i] == val){
return 0;
}
if (values[i] > val){
return add_(val, i);
}
}
return add_(val, size);
}
else{
add_(val, 0);
}
}
static inline void mul_(num *a,num *b,num *c){
register int i;
num t;
c->n=1;
c->a[0]=0;
for(i=0;i<b->n;++i){
shift_left(c,1);
mul1_(a,b->a[i],&t);
add_(c,&t,c);
rm0(c);
}
}
TEST_F(JoinNodeTest, IsColumnNullableWithOuterJoin) {
// Test that columns on the "null-supplying" side of an outer join are always nullable.
// Test that is_null_(<nullable>) is never nullable
// clang-format off
const auto lqp_left_join_basic =
JoinNode::make(JoinMode::Left, equals_(_t_a_a, _t_b_x),
_mock_node_a,
_mock_node_b);
// clang-format on
EXPECT_FALSE(lqp_left_join_basic->is_column_nullable(ColumnID{0}));
EXPECT_FALSE(lqp_left_join_basic->is_column_nullable(ColumnID{1}));
EXPECT_FALSE(lqp_left_join_basic->is_column_nullable(ColumnID{2}));
EXPECT_TRUE(lqp_left_join_basic->is_column_nullable(ColumnID{3}));
EXPECT_TRUE(lqp_left_join_basic->is_column_nullable(ColumnID{4}));
// clang-format off
const auto lqp_left_join =
ProjectionNode::make(expression_vector(_t_a_a, _t_b_x, add_(_t_a_a, _t_b_x), add_(_t_a_a, 3), is_null_(add_(_t_a_a, _t_b_x))), // NOLINT
JoinNode::make(JoinMode::Left, equals_(_t_a_a, _t_b_x),
_mock_node_a,
_mock_node_b));
// clang-format on
EXPECT_FALSE(lqp_left_join->is_column_nullable(ColumnID{0}));
EXPECT_TRUE(lqp_left_join->is_column_nullable(ColumnID{1}));
EXPECT_TRUE(lqp_left_join->is_column_nullable(ColumnID{2}));
EXPECT_FALSE(lqp_left_join->is_column_nullable(ColumnID{3}));
EXPECT_FALSE(lqp_left_join->is_column_nullable(ColumnID{4}));
// clang-format off
const auto lqp_right_join =
ProjectionNode::make(expression_vector(_t_a_a, _t_b_x, add_(_t_a_a, _t_b_x), add_(_t_a_a, 3), is_null_(add_(_t_a_a, _t_b_x))), // NOLINT
JoinNode::make(JoinMode::Right, equals_(_t_a_a, _t_b_x),
_mock_node_a,
_mock_node_b));
// clang-format on
EXPECT_TRUE(lqp_right_join->is_column_nullable(ColumnID{0}));
EXPECT_FALSE(lqp_right_join->is_column_nullable(ColumnID{1}));
EXPECT_TRUE(lqp_right_join->is_column_nullable(ColumnID{2}));
EXPECT_TRUE(lqp_right_join->is_column_nullable(ColumnID{3}));
EXPECT_FALSE(lqp_right_join->is_column_nullable(ColumnID{4}));
// clang-format off
const auto lqp_full_join =
ProjectionNode::make(expression_vector(_t_a_a, _t_b_x, add_(_t_a_a, _t_b_x), add_(_t_a_a, 3), is_null_(add_(_t_a_a, _t_b_x))), // NOLINT
JoinNode::make(JoinMode::FullOuter, equals_(_t_a_a, _t_b_x),
_mock_node_a,
_mock_node_b));
// clang-format on
EXPECT_TRUE(lqp_full_join->is_column_nullable(ColumnID{0}));
EXPECT_TRUE(lqp_full_join->is_column_nullable(ColumnID{1}));
EXPECT_TRUE(lqp_full_join->is_column_nullable(ColumnID{2}));
EXPECT_TRUE(lqp_full_join->is_column_nullable(ColumnID{3}));
EXPECT_FALSE(lqp_full_join->is_column_nullable(ColumnID{4}));
}
TEST_F(OperatorsProjectionTest, DontForwardReferencesWithExpression) {
const auto table_scan = create_table_scan(table_wrapper_a, ColumnID{0}, PredicateCondition::LessThan, 100'000);
table_scan->execute();
const auto projection =
std::make_shared<opossum::Projection>(table_scan, expression_vector(a_b, a_a, add_(a_b, a_a)));
projection->execute();
const auto input_chunk = table_wrapper_a->get_output()->get_chunk(ChunkID{0});
const auto output_chunk = projection->get_output()->get_chunk(ChunkID{0});
EXPECT_NE(input_chunk->get_segment(ColumnID{1}), output_chunk->get_segment(ColumnID{0}));
EXPECT_NE(input_chunk->get_segment(ColumnID{0}), output_chunk->get_segment(ColumnID{1}));
}
TEST_F(LQPUtilsTest, LQPSubplanToBooleanExpression_A) {
// clang-format off
const auto lqp =
PredicateNode::make(greater_than_(a_a, 5),
ProjectionNode::make(expression_vector(add_(a_a, a_b), a_a),
PredicateNode::make(less_than_(a_b, 4),
SortNode::make(expression_vector(a_b), std::vector<OrderByMode>{OrderByMode::Ascending}, node_a))));
// clang-format on
const auto actual_expression = lqp_subplan_to_boolean_expression(lqp);
const auto expected_expression = and_(less_than_(a_b, 4), greater_than_(a_a, 5));
EXPECT_EQ(*actual_expression, *expected_expression);
}
static inline sub(num *a,num *b,num *c){
if(a->sbit*b->sbit<0){
add_(a,b,c);
c->sbit=a->sbit;
}else{
int compare=cmp_(a,b);
if(compare>0){
sub_(a,b,c);
}else{
sub_(b,a,c);
}
c->sbit=compare*a->sbit;
}
rm0(c);
}
void Adam::step() {
for (auto& pair : model_->parameters()) {
auto& name = pair.first;
auto& grad = pair.second.grad();
auto& p = pair.second.data();
if (!grad.defined())
continue;
if (step_buffer_.find(name) == step_buffer_.end()) {
step_buffer_[name] = 0;
exp_avg_buffer_[name] = at::zeros_like(p);
exp_avg_sq_buffer_[name] = at::zeros_like(p);
if (amsgrad_) {
max_exp_avg_sq_buffer_[name] = at::zeros_like(p);
};
}
auto& step = step_buffer_[name];
auto& exp_avg = exp_avg_buffer_[name];
auto& exp_avg_sq = exp_avg_sq_buffer_[name];
step += 1;
auto d_p = torch::autograd::as_variable_ref(grad).data();
if (weight_decay_ > 0) {
d_p.add_(p, weight_decay_);
}
exp_avg.mul_(beta1_).add_(d_p, 1 - beta1_);
exp_avg_sq.mul_(beta2_).addcmul_(d_p, d_p, 1 - beta2_);
at::Tensor denom;
if (amsgrad_) {
auto& max_exp_avg_sq = max_exp_avg_sq_buffer_[name];
at::max_out(max_exp_avg_sq, max_exp_avg_sq, exp_avg_sq);
denom = max_exp_avg_sq.sqrt().add_(eps_);
} else {
denom = exp_avg_sq.sqrt().add_(eps_);
};
auto bias_correction1 = 1 - std::pow(beta1_, step);
auto bias_correction2 = 1 - std::pow(beta2_, step);
auto step_size = lr_ * std::sqrt(bias_correction2) / bias_correction1;
p.addcdiv_(exp_avg, denom, -step_size);
}
}
Fx* FxManager::getFx( const tstring& resourceID )
{
Fx* pEffect = find_( resourceID );
if (!pEffect)
{
pEffect = new Fx;
if (pEffect->create( resourceID ))
{
add_( pEffect, resourceID );
}
else
{
delete pEffect;
pEffect = Fx::getNullObject();
}
}
return pEffect;
}
/// Adapted from
/// https://github.com/pytorch/pytorch/blob/master/torch/optim/rmsprop.py
void RMSprop::step() {
for (auto& pair : model_->parameters()) {
auto& name = pair.first;
auto& grad = pair.second.grad();
auto& p = pair.second.data();
if (!grad.defined())
continue;
if (square_avg_buffer_.find(name) == square_avg_buffer_.end()) {
square_avg_buffer_[name] = at::zeros_like(p);
if (momentum_) {
momentum_buffer_[name] = at::zeros_like(p);
};
if (centered_) {
grad_avg_buffer_[name] = at::zeros_like(p);
};
};
auto d_p = torch::autograd::as_variable_ref(grad).data();
if (weight_decay_ > 0) {
d_p.add_(p, weight_decay_);
};
auto& square_avg = square_avg_buffer_[name];
square_avg.mul_(alpha_).addcmul_(d_p, d_p, 1.0 - alpha_);
at::Tensor avg;
if (centered_) {
auto& grad_avg = grad_avg_buffer_[name];
grad_avg.mul_(alpha_).add_(d_p, 1.0 - alpha_);
avg = square_avg.addcmul(grad_avg, grad_avg, -1.0).sqrt().add_(eps_);
} else {
avg = square_avg.sqrt().add_(eps_);
};
if (momentum_ > 0) {
auto& buf = momentum_buffer_[name];
buf.mul_(momentum_).addcdiv_(d_p, avg);
p.add_(buf, -lr_);
} else {
p.addcdiv_(d_p, avg, -lr_);
};
}
}
// Tokenizes the instruction part of the text command. If it corresponds to one of the supported
// instructions, like "add" or "remove", it searches for the next token (the sample name) in the
// list of samples and sends its buttonID to the relevant instruction function for further processing
void instructionControl(char *string_pointer) {
char *buttonID = NULL;
int instruction_to_execute;
if (!string_pointer) {
return;
}
instruction_to_execute = selectInstruction(string_pointer);
string_pointer = strtok(NULL, " \n");
if (string_pointer != NULL) {
buttonID = findSampleInArray(string_pointer); //
}
switch(instruction_to_execute) {
case ADD: add_(buttonID); break;
case REMOVE: remove_(buttonID); break;
case SET: set_(string_pointer); break;
case STOP: stopAll_(); break;
}
}
void
xml_compiler::filter_vector::traverse(const extracted_ptree& pt)
{
for (auto& it : pt) {
/* */ if (it.get_tag_name() == "not") {
add_(BRIDGE_FILTERTYPE_APPLICATION_NOT, "ApplicationType::", it.get_data());
} else if (it.get_tag_name() == "only") {
add_(BRIDGE_FILTERTYPE_APPLICATION_ONLY, "ApplicationType::", it.get_data());
} else if (it.get_tag_name() == "device_not") {
add_(BRIDGE_FILTERTYPE_DEVICE_NOT, "", it.get_data());
} else if (it.get_tag_name() == "device_only") {
add_(BRIDGE_FILTERTYPE_DEVICE_ONLY, "", it.get_data());
} else if (it.get_tag_name() == "config_not") {
add_(BRIDGE_FILTERTYPE_CONFIG_NOT, "ConfigIndex::", it.get_data());
} else if (it.get_tag_name() == "config_only") {
add_(BRIDGE_FILTERTYPE_CONFIG_ONLY, "ConfigIndex::", it.get_data());
} else if (it.get_tag_name() == "modifier_not") {
add_(BRIDGE_FILTERTYPE_MODIFIER_NOT, "", it.get_data());
} else if (it.get_tag_name() == "modifier_only") {
add_(BRIDGE_FILTERTYPE_MODIFIER_ONLY, "", it.get_data());
} else if (it.get_tag_name() == "inputmode_not") {
add_(BRIDGE_FILTERTYPE_INPUTMODE_NOT, "InputMode::", it.get_data());
} else if (it.get_tag_name() == "inputmode_only") {
add_(BRIDGE_FILTERTYPE_INPUTMODE_ONLY, "InputMode::", it.get_data());
} else if (it.get_tag_name() == "inputmodedetail_not") {
add_(BRIDGE_FILTERTYPE_INPUTMODEDETAIL_NOT, "InputModeDetail::", it.get_data());
} else if (it.get_tag_name() == "inputmodedetail_only") {
add_(BRIDGE_FILTERTYPE_INPUTMODEDETAIL_ONLY, "InputModeDetail::", it.get_data());
}
}
}
TEST_F(OperatorsProjectionTest, ForwardsIfPossibleDataTableAndExpression) {
const auto projection =
std::make_shared<opossum::Projection>(table_wrapper_a, expression_vector(a_b, a_a, add_(a_b, a_a)));
projection->execute();
const auto input_chunk = table_wrapper_a->get_output()->get_chunk(ChunkID{0});
const auto output_chunk = projection->get_output()->get_chunk(ChunkID{0});
EXPECT_EQ(input_chunk->get_segment(ColumnID{1}), output_chunk->get_segment(ColumnID{0}));
EXPECT_EQ(input_chunk->get_segment(ColumnID{0}), output_chunk->get_segment(ColumnID{1}));
}
TEST_F(OperatorsProjectionTest, ExecutedOnAllChunks) {
const auto projection = std::make_shared<opossum::Projection>(table_wrapper_a, expression_vector(add_(a_a, a_b)));
projection->execute();
EXPECT_TABLE_EQ_UNORDERED(projection->get_output(),
load_table("resources/test_data/tbl/projection/int_float_add.tbl"));
}
static inline karatsuba(num *a,num *b,num *c){
/*
* a=[hi1:lo1]
* b=[h2:lo2]
* a=hi1*B^m2+lo1
* b=hi2*B^m2+lo2
* a*b=(hi1*hi2)B^(2*m2)+ (l1h2+l2h1) B^m2+lo1*lo2
*/
if(a->n<2){
mul1_(b,a->a[0],c);
return;
}
if(b->n<2){
mul1_(a,b->a[0],c);
return;
}
/* printf("%d %d\n",a->n,b->n);
printNum(a);
printNum(b);
printf("case #3\n");*/
int m=max2(a->n,b->n);
int m2=m/2;
//printf("m2=%d\n",m2);
num hi1,lo1,hi2,lo2,z0,z1,z2,t1,t2,lh1,lh2;
split_at(a,m2,&hi1,&lo1);
split_at(b,m2,&hi2,&lo2);
/*puts("--- hi1 ---");
printNum(&hi1);
puts("--- lo1 ---");
printNum(&lo1);
puts("--- hi2 ---");
printNum(&hi2);
puts("--- lo2 ---");
printNum(&lo2);
*/
add_(&lo1,&hi1,&lh1);
add_(&lo2,&hi2,&lh2);
karatsuba(&lh1,&lh2,&z1);
karatsuba(&lo1,&lo2,&z0);
karatsuba(&hi1,&hi2,&z2);
/*puts(" z0 z1 z2 ");
printNum(&z0);
printNum(&z1);
printNum(&z2);
*/
add_(&z0,&z2,&t1); //t1=z0+z2
sub_(&z1,&t1,&t2);//t2=z1-t1
//puts("t2= ");
//printNum(&t2);
shift_left(&z2,2*m2);//z2*B^2*m2
shift_left(&t2,m2); //t2*B^m2
//printNum(&z2);
//printNum(&t2);
//printNum(&z0);
add_(&z0,&z2,c);
//printNum(c);
add_(c,&t2,c);
rm0(c);
//printNum(c);
}
int main()
{
add_(2,3);
F77_FUNC(add)(2,3);
return 0;
}
void xml_compiler::filter_vector::traverse(const extracted_ptree& pt) {
for (const auto& it : pt) {
/* */ if (it.get_tag_name() == "not") {
add_(BRIDGE_FILTERTYPE_APPLICATION_NOT, "ApplicationType::", it.get_data());
} else if (it.get_tag_name() == "only") {
add_(BRIDGE_FILTERTYPE_APPLICATION_ONLY, "ApplicationType::", it.get_data());
} else if (it.get_tag_name() == "windowname_not") {
add_(BRIDGE_FILTERTYPE_WINDOWNAME_NOT, "WindowName::", it.get_data());
} else if (it.get_tag_name() == "windowname_only") {
add_(BRIDGE_FILTERTYPE_WINDOWNAME_ONLY, "WindowName::", it.get_data());
} else if (it.get_tag_name() == "uielementrole_not") {
add_(BRIDGE_FILTERTYPE_UIELEMENTROLE_NOT, "UIElementRole::", it.get_data());
} else if (it.get_tag_name() == "uielementrole_only") {
add_(BRIDGE_FILTERTYPE_UIELEMENTROLE_ONLY, "UIElementRole::", it.get_data());
} else if (it.get_tag_name() == "config_not") {
add_(BRIDGE_FILTERTYPE_CONFIG_NOT, "ConfigIndex::", it.get_data());
} else if (it.get_tag_name() == "config_only") {
add_(BRIDGE_FILTERTYPE_CONFIG_ONLY, "ConfigIndex::", it.get_data());
} else if (it.get_tag_name() == "device_not") {
add_(BRIDGE_FILTERTYPE_DEVICE_NOT, "", it.get_data());
} else if (it.get_tag_name() == "device_only") {
add_(BRIDGE_FILTERTYPE_DEVICE_ONLY, "", it.get_data());
} else if (it.get_tag_name() == "elapsedtimesincelastpressed_greaterthan") {
add_(BRIDGE_FILTERTYPE_ELAPSEDTIMESINCELASTPRESSED_GREATERTHAN, "", it.get_data());
} else if (it.get_tag_name() == "elapsedtimesincelastpressed_lessthan") {
add_(BRIDGE_FILTERTYPE_ELAPSEDTIMESINCELASTPRESSED_LESSTHAN, "", it.get_data());
} else if (it.get_tag_name() == "modifier_not") {
add_(BRIDGE_FILTERTYPE_MODIFIER_NOT, "", it.get_data());
} else if (it.get_tag_name() == "modifier_only") {
add_(BRIDGE_FILTERTYPE_MODIFIER_ONLY, "", it.get_data());
} else if (it.get_tag_name() == "modifierlocked_not") {
add_(BRIDGE_FILTERTYPE_MODIFIER_LOCKED_NOT, "", it.get_data());
} else if (it.get_tag_name() == "modifierlocked_only") {
add_(BRIDGE_FILTERTYPE_MODIFIER_LOCKED_ONLY, "", it.get_data());
} else if (it.get_tag_name() == "modifierstuck_not") {
add_(BRIDGE_FILTERTYPE_MODIFIER_STUCK_NOT, "", it.get_data());
} else if (it.get_tag_name() == "modifierstuck_only") {
add_(BRIDGE_FILTERTYPE_MODIFIER_STUCK_ONLY, "", it.get_data());
} else if (it.get_tag_name() == "inputsource_not" ||
it.get_tag_name() == "inputmode_not" ||
it.get_tag_name() == "inputsourcedetail_not" ||
it.get_tag_name() == "inputmodedetail_not") {
// We allow "inputmode_*", "inputmodedetail_*", "inputsourcedetail_*" for compatibility.
add_(BRIDGE_FILTERTYPE_INPUTSOURCE_NOT, "InputSource::", it.get_data());
} else if (it.get_tag_name() == "inputsource_only" ||
it.get_tag_name() == "inputmode_only" ||
it.get_tag_name() == "inputsourcedetail_only" ||
it.get_tag_name() == "inputmodedetail_only") {
// We allow "inputmode_*", "inputmodedetail_*", "inputsourcedetail_*" for compatibility.
add_(BRIDGE_FILTERTYPE_INPUTSOURCE_ONLY, "InputSource::", it.get_data());
} else if (it.get_tag_name() == "lastpressedphysicalkey_not") {
add_(BRIDGE_FILTERTYPE_LASTPRESSEDPHYSICALKEY_NOT, "", it.get_data());
} else if (it.get_tag_name() == "lastpressedphysicalkey_only") {
add_(BRIDGE_FILTERTYPE_LASTPRESSEDPHYSICALKEY_ONLY, "", it.get_data());
} else if (it.get_tag_name() == "pressingphysicalkeys_greaterthan") {
add_(BRIDGE_FILTERTYPE_PRESSINGPHYSICALKEYS_GREATERTHAN, "Count::RawValue::", it.get_data());
} else if (it.get_tag_name() == "pressingphysicalkeys_lessthan") {
add_(BRIDGE_FILTERTYPE_PRESSINGPHYSICALKEYS_LESSTHAN, "Count::RawValue::", it.get_data());
}
}
}
