void Sequential<InputDataType, OutputDataType, CustomLayers...>::Forward(
arma::Mat<eT>&& input, arma::Mat<eT>&& output)
{
boost::apply_visitor(ForwardVisitor(std::move(input), std::move(
boost::apply_visitor(outputParameterVisitor, network.front()))),
network.front());
if (!reset)
{
if (boost::apply_visitor(outputWidthVisitor, network.front()) != 0)
{
width = boost::apply_visitor(outputWidthVisitor, network.front());
}
if (boost::apply_visitor(outputHeightVisitor, network.front()) != 0)
{
height = boost::apply_visitor(outputHeightVisitor, network.front());
}
}
for (size_t i = 1; i < network.size(); ++i)
{
if (!reset)
{
// Set the input width.
boost::apply_visitor(SetInputWidthVisitor(width), network[i]);
// Set the input height.
boost::apply_visitor(SetInputHeightVisitor(height), network[i]);
}
boost::apply_visitor(ForwardVisitor(std::move(boost::apply_visitor(
outputParameterVisitor, network[i - 1])), std::move(
boost::apply_visitor(outputParameterVisitor, network[i]))),
network[i]);
if (!reset)
{
// Get the output width.
if (boost::apply_visitor(outputWidthVisitor, network[i]) != 0)
{
width = boost::apply_visitor(outputWidthVisitor, network[i]);
}
// Get the output height.
if (boost::apply_visitor(outputHeightVisitor, network[i]) != 0)
{
height = boost::apply_visitor(outputHeightVisitor, network[i]);
}
}
}
if (!reset)
{
reset = true;
}
output = boost::apply_visitor(outputParameterVisitor, network.back());
}
void RecurrentAttention<InputDataType, OutputDataType>::Forward(
arma::Mat<eT>&& input, arma::Mat<eT>&& output)
{
// Initialize the action input.
if (initialInput.is_empty())
{
initialInput = arma::zeros(outSize, input.n_cols);
}
// Propagate through the action and recurrent module.
for (forwardStep = 0; forwardStep < rho; ++forwardStep)
{
if (forwardStep == 0)
{
boost::apply_visitor(ForwardVisitor(std::move(initialInput), std::move(
boost::apply_visitor(outputParameterVisitor, actionModule))),
actionModule);
}
else
{
boost::apply_visitor(ForwardVisitor(std::move(boost::apply_visitor(
outputParameterVisitor, rnnModule)), std::move(boost::apply_visitor(
outputParameterVisitor, actionModule))), actionModule);
}
// Initialize the glimpse input.
arma::mat glimpseInput = arma::zeros(input.n_elem, 2);
glimpseInput.col(0) = input;
glimpseInput.submat(0, 1, boost::apply_visitor(outputParameterVisitor,
actionModule).n_elem - 1, 1) = boost::apply_visitor(
outputParameterVisitor, actionModule);
boost::apply_visitor(ForwardVisitor(std::move(glimpseInput),
std::move(boost::apply_visitor(outputParameterVisitor, rnnModule))),
rnnModule);
// Save the output parameter when training the module.
if (!deterministic)
{
for (size_t l = 0; l < network.size(); ++l)
{
boost::apply_visitor(SaveOutputParameterVisitor(
std::move(moduleOutputParameter)), network[l]);
}
}
}
output = boost::apply_visitor(outputParameterVisitor, rnnModule);
forwardStep = 0;
backwardStep = 0;
}
void Recurrent<InputDataType, OutputDataType>::Forward(
arma::Mat<eT>&& input, arma::Mat<eT>&& output)
{
if (forwardStep == 0)
{
boost::apply_visitor(ForwardVisitor(std::move(input), std::move(output)),
initialModule);
}
else
{
boost::apply_visitor(ForwardVisitor(std::move(input), std::move(
boost::apply_visitor(outputParameterVisitor, inputModule))),
inputModule);
boost::apply_visitor(ForwardVisitor(std::move(boost::apply_visitor(
outputParameterVisitor, transferModule)), std::move(
boost::apply_visitor(outputParameterVisitor, feedbackModule))),
feedbackModule);
boost::apply_visitor(ForwardVisitor(std::move(input), std::move(output)),
recurrentModule);
}
output = boost::apply_visitor(outputParameterVisitor, transferModule);
// Save the feedback output parameter when training the module.
if (!deterministic)
{
feedbackOutputParameter.push_back(output);
}
forwardStep++;
if (forwardStep == rho)
{
forwardStep = 0;
backwardStep = 0;
if (!recurrentError.is_empty())
{
recurrentError.zeros();
}
}
}
void Concat<InputDataType, OutputDataType>::Forward(
arma::Mat<eT>&& input, arma::Mat<eT>&& output)
{
size_t outSize = 0;
for (size_t i = 0; i < network.size(); ++i)
{
boost::apply_visitor(ForwardVisitor(std::move(input), std::move(
boost::apply_visitor(outputParameterVisitor, network[i]))),
network[i]);
if (boost::apply_visitor(
outputParameterVisitor, network[i]).n_elem > outSize)
{
outSize = boost::apply_visitor(outputParameterVisitor,
network[i]).n_elem;
}
}
output = arma::zeros(outSize, network.size());
for (size_t i = 0; i < network.size(); ++i)
{
size_t elements = boost::apply_visitor(outputParameterVisitor,
network[i]).n_elem;
if (elements < outSize)
{
output.submat(0, i, elements - 1, i) = arma::vectorise(
boost::apply_visitor(outputParameterVisitor, network[i]));
}
else
{
output.col(i) = arma::vectorise(boost::apply_visitor(
outputParameterVisitor, network[i]));
}
}
}
