void update_delta(const Expression& gradient, int index) {
if (index >= _delta.size() || index >= _first_moment.size() || index >= _second_moment.size() || index >= _current_iteration.size()) {
_delta.resize(index + 1);
_first_moment.resize(index + 1);
_second_moment.resize(index + 1);
_current_iteration.resize(index + 1);
}
if (!_delta[index] || !_first_moment[index] || !_second_moment[index]) {
_delta[index] = boost::make_shared<vector_t>(zeros<value_t>(gradient.count()));
_first_moment[index] = boost::make_shared<vector_t>(zeros<value_t>(gradient.count()));
_second_moment[index] = boost::make_shared<vector_t>(zeros<value_t>(gradient.count()));
_current_iteration[index] = 0;
}
++_current_iteration[index];
// Perform adadelta updates
*_first_moment[index] = get_beta1() * reshape(gradient, _delta[index]->size()) + (1.0 - get_beta1()) * *_first_moment[index];
*_second_moment[index] = get_beta2() * reshape(gradient, _delta[index]->size()) * reshape(gradient, _delta[index]->size()) + (1.0 - get_beta2()) * *_second_moment[index];
*_delta[index] = -get_alpha() * *_first_moment[index] / (value_t(1) - ::pow(value_t(1) - get_beta1(), _current_iteration[index])) /
(sqrt(*_second_moment[index] / (value_t(1) - ::pow(value_t(1) - get_beta2(), _current_iteration[index]))) + get_epsilon());
}
void update_delta(const Expression& gradient, int index) {
if (index >= _delta.size() || index >= _d2.size() || index >= _delta2.size()) {
_delta.resize(index + 1);
_delta2.resize(index + 1);
_d2.resize(index + 1);
}
if (!_delta[index] || !_delta2[index] || !_d2[index]) {
_delta[index] = boost::make_shared<vector_t>(zeros<value_t>(gradient.count()));
_delta2[index] = boost::make_shared<vector_t>(zeros<value_t>(gradient.count()));
_d2[index] = boost::make_shared<vector_t>(zeros<value_t>(gradient.count()));
}
// Perform adadelta updates
*_d2[index] = get_decay_rate() * *_d2[index] + (1.0 - get_decay_rate()) * reshape(gradient, _d2[index]->size()) * reshape(gradient, _d2[index]->size());
*_delta[index] = -sqrt(*_delta2[index] + get_epsilon()) / sqrt(*_d2[index] + get_epsilon()) * reshape(gradient, _d2[index]->size());
*_delta2[index] = get_decay_rate() * *_delta2[index] + (1.0 - get_decay_rate()) * *_delta[index] * *_delta[index];
}
void update_delta(const Expression& gradient, int index) {
if (index >= _deltas.size()) {
_deltas.resize(index + 1);
}
if (!_deltas[index]) {
_deltas[index] = boost::make_shared<vector_t>(zeros<value_t>(gradient.count()));
}
}
void update_delta(const Expression& gradient, int index) {
if (index >= _delta.size()) {
_delta.resize(index + 1);
}
if (!_delta[index]) {
_delta[index] = boost::make_shared<vector_t>(zeros<value_t>(gradient.count()));
}
// Block-wise normalize the gradient
vector_t norm_grad = reshape(gradient, _delta[index]->size()) / (sqrt(dot(reshape(gradient, _delta[index]->size()), reshape(gradient, _delta[index]->size()))) + get_epsilon());
// Calculate running averages
mg = get_decay_rate() * mg + (1.0 - get_decay_rate()) * norm_grad;
gamma_nume_sqr = gamma_nume_sqr * (1 - 1 / taus_x_t) + (norm_grad - old_grad) * (old_grad - mg) * (norm_grad - old_grad) * (old_grad - mg) / taus_x_t;
gamma_deno_sqr = gamma_dneo_sqr * (1 - 1 / taus_x_t) + (mg - norm_grad) * (old_grad - mg) * (mg - norm_grad) * (old_grad - mg) / taus_x_t;
_gamma = sqrt(_gamma_nume) / (sqrt(_gamma_deno_sqr) + get_epsilon());
// Update delta with momentum and epsilon parameter
*_delta[index] = _gamma * mg;
}
int Olap::count(Query* query,WrapDataSource* dataExtractor)//remove 2nd para later
{
//DataExtraction dataExtractor;
//bitstring bitstring1,bitstring2;BitStreamInfo*
//bitstring result;
BitStreamInfo* bitstring1;
BitStreamInfo* bitstring2;
BitStreamInfo* result;
Expression* postfixExpression = query->getPostfixExpression();
stack<Symbol*> operandStack;
for (int i=0;i<postfixExpression->count();i++)
{
Symbol* inputSymbol = postfixExpression->getSymbolAt(i);
if(inputSymbol->getType()==TYPEOPERAND||inputSymbol->getType()==TYPENOT)
{
operandStack.push(inputSymbol);
}
else
{
if (!operandStack.empty())
{
Operand* operand2 = dynamic_cast<Operand*>(operandStack.top());
operandStack.pop();
bitstring2 = dataExtractor->getBitString(operand2->getAttributeIndex(),operand2->getbitStringIndex());
if (!operandStack.empty())
{
Symbol* possibleNot = operandStack.top();
if (possibleNot->getType()==TYPENOT)
{
operandStack.pop();
bitstring2=~(*bitstring2);
}
}
if (!operandStack.empty())
{
Operand* operand1 = dynamic_cast<Operand*>(operandStack.top());
operandStack.pop();
bitstring1 = dataExtractor->getBitString(operand1->getAttributeIndex(),operand1->getbitStringIndex());
if (!operandStack.empty())
{
Symbol* possibleNot = operandStack.top();
if (possibleNot->getType()==TYPENOT)
{
operandStack.pop();
bitstring1=~(*bitstring1);
}
}
}
}
if (inputSymbol->getType()==TYPEAND)
{
result=(*bitstring1)&(*bitstring2);
}
else if (inputSymbol->getType()==TYPEOR)
{
result=(*bitstring1)|(*bitstring2);
}
}
}
while(!operandStack.empty())
{
Operand* operand = dynamic_cast<Operand*>(operandStack.top());
operandStack.pop();
result = dataExtractor->getBitString(operand->getAttributeIndex(),operand->getbitStringIndex());
if (!operandStack.empty())
{
Symbol* possibleNot = operandStack.top();
if (possibleNot->getType()==TYPENOT)
{
operandStack.pop();
result=~(*result);
}
}
}
return result->count();
}
void update_delta(const Expression& gradient, int index) {
if (index >= _delta.size() || index >= _old_grad.size() || index >= _g.size() || index >= _g2.size() ||
index >= _h.size() || index >= _h2.size() || index >= _tau.size() || index >= _current_iteration.size())
{
_delta.resize(index + 1);
_old_grad.resize(index + 1);
_g.resize(index + 1);
_g2.resize(index + 1);
_h.resize(index + 1);
_h2.resize(index + 1);
_tau.resize(index + 1);
_current_iteration.resize(index + 1);
}
if (!_delta[index] || !_old_grad[index] || !_g[index] || !_g2[index] || !_h[index] || !_h2[index] || !_tau[index]) {
_delta[index] = boost::make_shared<vector_t>(zeros<value_t>(gradient.count()));
_old_grad[index] = boost::make_shared<vector_t>(zeros<value_t>(gradient.count()));
_g[index] = boost::make_shared<vector_t>(zeros<value_t>(gradient.count()));
_g2[index] = boost::make_shared<vector_t>(zeros<value_t>(gradient.count()));
_h[index] = boost::make_shared<vector_t>(zeros<value_t>(gradient.count()));
_h2[index] = boost::make_shared<vector_t>(zeros<value_t>(gradient.count()));
_tau[index] = boost::make_shared<vector_t>(ones<value_t>(gradient.count()));
_current_iteration[index] = 0;
}
++_current_iteration[index];
// Detect outlier
// if (abs(reshape(gradient, _delta[index]->size()) - *_g[index]) > 2 * sqrt(*_g2[index] - *_g[index] * *_g[index]) ||
// abs(abs((reshape(gradient, _delta[index]->size()) - *_old_grad[index]) / (*_delta[index] + get_epsilon())) - *_h[index]) > 2 * sqrt(*_h2[index] - *_h[index] * *_h[index]))
// {
// *_tau[index] = *_tau[index] + 1.0;
// }
*_tau[index] = *_tau[index] + abs(reshape(gradient, _delta[index]->size()) - *_g[index]) > 2 * sqrt(*_g2[index] - *_g[index] * *_g[index]);
// Update moving averages
*_g[index] = (1.0 - 1.0 / *_tau[index]) * *_g[index] + 1.0 / *_tau[index] * reshape(gradient, _delta[index]->size());
*_g2[index] = (1.0 - 1.0 / *_tau[index]) * *_g2[index] + 1.0 / *_tau[index] * reshape(gradient, _delta[index]->size()) * reshape(gradient, _delta[index]->size());
if (_current_iteration[index] > 1) {
// Calculate h and do h updates
// diag(H) = abs((reshape(gradient, _delta[index]->size()) - *_old_grad[index]) / (*_delta[index] + get_epsilon()));
*_h[index] = (1.0 - 1.0 / *_tau[index]) * *_h[index] + 1.0 / *_tau[index] * abs((reshape(gradient, _delta[index]->size()) - *_old_grad[index]) / (*_delta[index] + get_epsilon()));
*_h2[index] = (1.0 - 1.0 / *_tau[index]) * *_h[index] + 1.0 / *_tau[index] * ((reshape(gradient, _delta[index]->size()) - *_old_grad[index]) / (*_delta[index] + get_epsilon())) * ((reshape(gradient, _delta[index]->size()) - *_old_grad[index]) / (*_delta[index] + get_epsilon()));
// Initialization phase -> multiply with C where C = D/10
if (_current_iteration[index] == 2) {
*_g2[index] = *_g2[index] * get_c();
*_h[index] = *_h[index] * get_c();
*_h2[index] = *_h2[index] * get_c();
}
*_delta[index] = -*_h[index] * *_g[index] * *_g[index] / (*_h2[index] * *_g2[index] + get_epsilon()) * reshape(gradient, _delta[index]->size());
} else {
*_delta[index] = get_epsilon() * *_g[index];
}
*_tau[index] = (1.0 - *_g[index] * *_g[index] / (*_g2[index] + get_epsilon())) * *_tau[index] + 1;
*_old_grad[index] = reshape(gradient, _delta[index]->size());
}
