/// <summary>
/// Remove an additional dataset that was created.
/// </summary>
/// <param name="child">The additional dataset to remove.</param>
public void RemoveAdditional(BufferedNeuralDataSet child)
{
lock (this)
{
this.additional.Remove(child);
}
}
/// <summary>
/// Open an additional training set.
/// </summary>
/// <returns>An additional training set.</returns>
public IEngineIndexableSet OpenAdditional()
{
BufferedNeuralDataSet result = new BufferedNeuralDataSet(this.file);
result.owner = this;
this.additional.Add(result);
return(result);
}
/// <summary>
/// Convert a CSV file to a binary training file.
/// </summary>
/// <param name="csvFile">The CSV file.</param>
/// <param name="binFile">The binary file.</param>
/// <param name="inputCount">The number of input values.</param>
/// <param name="outputCount">The number of output values.</param>
/// <param name="headers">True, if there are headers on the3 CSV.</param>
public static void ConvertCSV2Binary(String csvFile,
String binFile, int inputCount, int outputCount,
bool headers)
{
File.Delete(binFile);
CSVNeuralDataSet csv = new CSVNeuralDataSet(csvFile.ToString(),
inputCount, outputCount, false);
BufferedNeuralDataSet buffer = new BufferedNeuralDataSet(binFile);
buffer.BeginLoad(50, 6);
foreach (INeuralDataPair pair in csv)
{
buffer.Add(pair);
}
buffer.EndLoad();
}
/// <summary>
/// Close the dataset.
/// </summary>
public void Close()
{
Object[] obj = this.additional.ToArray();
for (int i = 0; i < obj.Length; i++)
{
BufferedNeuralDataSet set = (BufferedNeuralDataSet)obj[i];
set.Close();
}
this.additional.Clear();
if (this.owner != null)
{
this.owner.RemoveAdditional(this);
}
this.egb.Close();
this.egb = null;
}
/// <summary>
/// Evaluate disk.
/// </summary>
private void EvalBinary()
{
String file = "temp.egb";
BasicNeuralDataSet training = RandomTrainingFactory.Generate(
1000, 10000, 10, 10, -1, 1);
// create the binary file
File.Delete(file);
BufferedNeuralDataSet training2 = new BufferedNeuralDataSet(file);
training2.Load(training);
long stop = (10 * Evaluate.MILIS);
int record = 0;
INeuralDataPair pair = BasicNeuralDataPair.CreatePair(10, 10);
Stopwatch watch = new Stopwatch();
watch.Start();
int iterations = 0;
while (watch.ElapsedMilliseconds < stop)
{
iterations++;
training2.GetRecord(record++, pair);
if (record >= training2.Count)
record = 0;
}
training2.Close();
iterations /= 100000;
this.report.Report(EncogBenchmark.STEPS, EncogBenchmark.STEP4,
"Disk(binary) dataset, result: "
+ Format.FormatInteger(iterations));
File.Delete(file);
this.binaryScore = iterations;
}
/// <summary>
/// Remove an additional dataset that was created.
/// </summary>
/// <param name="child">The additional dataset to remove.</param>
public void RemoveAdditional(BufferedNeuralDataSet child)
{
lock (this)
{
this.additional.Remove(child);
}
}
/// <summary>
/// Open an additional training set.
/// </summary>
/// <returns>An additional training set.</returns>
public IEngineIndexableSet OpenAdditional()
{
BufferedNeuralDataSet result = new BufferedNeuralDataSet(this.file);
result.owner = this;
this.additional.Add(result);
return result;
}
/// <summary>
/// Construct the buffered enumerator. This is where the file is actually
/// opened.
/// </summary>
/// <param name="owner">The object that created this enumeration.</param>
public BufferedNeuralDataSetEnumerator(BufferedNeuralDataSet owner)
{
this.data = owner;
this.current = 0;
}