RNN<LayerTypes, OutputLayerType, InitializationRuleType, PerformanceFunction
>::RNN(LayerType &&network,
OutputType &&outputLayer,
const arma::mat& predictors,
const arma::mat& responses,
InitializationRuleType initializeRule,
PerformanceFunction performanceFunction) :
network(std::forward<LayerType>(network)),
outputLayer(std::forward<OutputType>(outputLayer)),
performanceFunc(std::move(performanceFunction)),
inputSize(0),
outputSize(0)
{
static_assert(std::is_same<typename std::decay<LayerType>::type,
LayerTypes>::value,
"The type of network must be LayerTypes.");
static_assert(std::is_same<typename std::decay<OutputType>::type,
OutputLayerType>::value,
"The type of outputLayer must be OutputLayerType.");
initializeRule.Initialize(parameter, NetworkSize(this->network), 1);
NetworkWeights(parameter, this->network);
Train(predictors, responses);
}
FFN<LayerTypes, OutputLayerType, InitializationRuleType, PerformanceFunction
>::FFN(LayerType &&network,
OutputType &&outputLayer,
const arma::mat& predictors,
const arma::mat& responses,
OptimizerType<NetworkType>& optimizer,
InitializationRuleType initializeRule,
PerformanceFunction performanceFunction) :
network(std::forward<LayerType>(network)),
outputLayer(std::forward<OutputType>(outputLayer)),
performanceFunc(std::move(performanceFunction)),
predictors(predictors),
responses(responses),
numFunctions(predictors.n_cols)
{
static_assert(std::is_same<typename std::decay<LayerType>::type,
LayerTypes>::value,
"The type of network must be LayerTypes.");
static_assert(std::is_same<typename std::decay<OutputType>::type,
OutputLayerType>::value,
"The type of outputLayer must be OutputLayerType.");
initializeRule.Initialize(parameter, NetworkSize(this->network), 1);
NetworkWeights(parameter, this->network);
// Train the model.
Timer::Start("ffn_optimization");
const double out = optimizer.Optimize(parameter);
Timer::Stop("ffn_optimization");
Log::Info << "FFN::FFN(): final objective of trained model is " << out
<< "." << std::endl;
}
typename std::enable_if<
HasWeightsCheck<T, arma::mat&(T::*)()>::value, size_t>::type
LayerWeights(InitializationRuleType& initializeRule,
T& layer,
arma::mat& weights,
size_t offset,
arma::mat& /* output */)
{
layer.Weights() = arma::mat(weights.memptr() + offset,
layer.Weights().n_rows, layer.Weights().n_cols, false, false);
initializeRule.Initialize(layer.Weights(), layer.Weights().n_rows,
layer.Weights().n_cols);
return layer.Weights().n_elem;
}
FFN<LayerTypes, OutputLayerType, InitializationRuleType, PerformanceFunction
>::FFN(LayerType &&network,
OutputType &&outputLayer,
InitializationRuleType initializeRule,
PerformanceFunction performanceFunction) :
network(std::forward<LayerType>(network)),
outputLayer(std::forward<OutputType>(outputLayer)),
performanceFunc(std::move(performanceFunction))
{
static_assert(std::is_same<typename std::decay<LayerType>::type,
LayerTypes>::value,
"The type of network must be LayerTypes.");
static_assert(std::is_same<typename std::decay<OutputType>::type,
OutputLayerType>::value,
"The type of outputLayer must be OutputLayerType.");
initializeRule.Initialize(parameter, NetworkSize(this->network), 1);
NetworkWeights(parameter, this->network);
}
