/// <summary>
/// Loads weight matrices of a matrix using hte passed in record URL
/// </summary>
/// <param name="RecordName"></param>
/// <param name="InputDimensions"></param>
/// <param name="HiddenLayerDimensions"></param>
/// <param name="OutputDimensions"></param>
private void LoadNNState(string RecordName, int InputDimensions, int HiddenLayerDimensions, int OutputDimensions)
{
Heuristics.Utilities.Matrices.Matrix W = new Heuristics.Utilities.Matrices.Matrix(HiddenLayerDimensions, OutputDimensions);
Heuristics.Utilities.Matrices.Matrix V = new Heuristics.Utilities.Matrices.Matrix(InputDimensions, HiddenLayerDimensions);
Heuristics.Utilities.Matrices.Matrix U = new Heuristics.Utilities.Matrices.Matrix(HiddenLayerDimensions, HiddenLayerDimensions);
string Content = File.ReadAllText(SavedStatesDirectory + RecordName);
try
{
foreach (string line in Content.Split('\n'))
{
List <string> chars = line.Split('_').ToList();
try
{
string Matrix = chars[0];
int i = Convert.ToInt32(chars[1]);
int j = Convert.ToInt32(chars[2]);
double Value = Convert.ToDouble(chars[3]);
switch (Matrix)
{
case "W":
W.SetValue(i, j, Value);
break;
case "U":
U.SetValue(i, j, Value);
break;
case "V":
V.SetValue(i, j, Value);
break;
default:
throw new Exception();
}
}
catch
{
}
}
}
catch (Exception e)
{
MessageBox.Show("There was an error loading the file!\n" + e.Message);
}
rnn = new RecurrentNeuralNetwork(InputDimensions, HiddenLayerDimensions, OutputDimensions, U, V, W);
}
/// <summary>
/// Trains the RNN
/// </summary>
private void Train()
{
if (IORecords == null || !IORecords.Any())
{
return;
}
if (rnn == null)
{
rnn = new RecurrentNeuralNetwork(NumberOfRecordsToKeep, 100, 5);
}
IORecords = SplitIORecords(IORecords, PercentTrainingData * .01);
int AmountPerBatch = (int)(IORecords.Count * (PercentTrainingData * .01) / NumberOfBatches);// / NumberOfBatches);
int CurrentCounter = 0;
int TotalTrainingData = NumberOfBatches * AmountPerBatch;
while (CurrentCounter < TotalTrainingData)
{
List <Heuristics.Utilities.Matrices.Matrix> Inputs = new List <Heuristics.Utilities.Matrices.Matrix>();
List <Heuristics.Utilities.Matrices.Matrix> Outputs = new List <Heuristics.Utilities.Matrices.Matrix>();
for (int sample = 0; sample < AmountPerBatch; sample++)
{
SentenceIORecord temp = IORecords[sample + CurrentCounter];
Heuristics.Utilities.Matrices.Matrix Input = new Heuristics.Utilities.Matrices.Matrix(temp.Inputs.Count, NumberOfRecordsToKeep);
Heuristics.Utilities.Matrices.Matrix Output = new Heuristics.Utilities.Matrices.Matrix(temp.Inputs.Count, 5);
for (int i = 0; i < Input.Height; i++)
{
int Value = temp.Inputs[i];
for (int j = 0; j < Input.Width; j++)
{
if (j == Value)
{
Input.SetValue(i, j, 1);
}
else
{
Input.SetValue(i, j, 0);
}
}
Value = temp.Output;
for (int j = 0; j < Output.Width; j++)
{
if (j == Value)
{
Output.SetValue(i, j, 1);
}
else
{
Output.SetValue(i, j, 0);
}
}
}
Inputs.Add(Input);
Outputs.Add(Output);
}
rnn.Train(Inputs, Outputs, .001, NumberOfEpochs, 0);
CurrentCounter += AmountPerBatch;
}
SaveNNStates();
}