/// <summary>
/// Train the model with training dataset, for certain number of iterations and using batch size
/// </summary>
/// <param name="x"></param>
/// <param name="y"></param>
/// <param name="numIterations"></param>
/// <param name="batchSize"></param>
public void Train(NDArray x, NDArray y, int numIterations, int batchSize)
{
//Initialise bacch loss and metric list for temporary holding of result
List <double> batchLoss = new List <double>();
List <double> batchMetrics = new List <double>();
//Loop through till the end of specified iterations
for (int i = 1; i <= numIterations; i++)
{
//Initialize local variables
int currentIndex = 0;
batchLoss.Clear();
batchMetrics.Clear();
//Loop untill the data is exhauted for every batch selected
while (x.Next(currentIndex, batchSize))
{
//Get the batch data based on the specified batch size
var xtrain = x.Slice(currentIndex, batchSize);
var ytrain = y.Slice(currentIndex, batchSize);
//Run forward for all the layers to predict the value for the training set
var ypred = Forward(xtrain);
//Find the loss/cost value for the prediction wrt expected result
var costVal = Cost.Forward(ypred, ytrain);
batchLoss.AddRange(costVal.Data);
//Find the metric value for the prediction wrt expected result
if (Metric != null)
{
var metric = Metric.Calculate(ypred, ytrain);
batchMetrics.AddRange(metric.Data);
}
//Get the gradient of the cost function which is the passed to the layers during back-propagation
var grad = Cost.Backward(ypred, ytrain);
//Run back-propagation accross all the layers
Backward(grad);
//Now time to update the neural network weights using the specified optimizer function
foreach (var layer in Layers)
{
Optimizer.Update(i, layer);
}
currentIndex = currentIndex + batchSize;;
}
//Collect the result and fire the event
double batchLossAvg = Math.Round(batchLoss.Average(), 2);
double batchMetricAvg = Metric != null?Math.Round(batchMetrics.Average(), 2) : 0;
TrainingLoss.Add(batchLossAvg);
if (batchMetrics.Count > 0)
{
TrainingMetrics.Add(batchMetricAvg);
}
EpochEndEventArgs eventArgs = new EpochEndEventArgs(i, batchLossAvg, batchMetricAvg);
BatchEnd?.Invoke(i, eventArgs);
}
}
public ActionResult Summary()
{
var metrics = Metric.Calculate();
return(View(metrics));
}