/// <summary>
/// Called on each testing iteration of the sequence model.
/// </summary>
/// <param name="sender">Specifies the event sender.</param>
/// <param name="e">Specifies the event args.</param>
private void m_mycaffe_OnTestingIteration(object sender, TestingIterationArgs <float> e)
{
float fAccuracy = m_rgAccuracyTraining.Average();
m_plotsSequenceAccuracyTrain.Add(m_nTotalSequences, fAccuracy * 100);
if (m_plotsSequenceAccuracyTrain.Count > 100)
{
m_plotsSequenceAccuracyTrain.RemoveAt(0);
}
m_rgAccuracyTesting.Add((float)e.Accuracy);
m_rgAccuracyTesting.RemoveAt(0);
fAccuracy = m_rgAccuracyTesting.Average();
m_plotsSequenceAccuracyTest.Add(m_nTotalSequences, fAccuracy * 100);
if (m_plotsSequenceAccuracyTest.Count > 100)
{
m_plotsSequenceAccuracyTest.RemoveAt(0);
}
PlotCollectionSet set = new PlotCollectionSet();
set.Add(m_plotsSequenceAccuracyTrain);
set.Add(m_plotsSequenceAccuracyTest);
Image img = SimpleGraphingControl.QuickRender(set, pbImageAccuracy.Width, pbImageAccuracy.Height, false, null, null, false, m_rgZeroLine);
m_bw.ReportProgress(1, new Tuple <Image, int>(img, 1));
}
public PlotCollectionSet GetLastData(int nLookahead = 0, bool bRemove = false)
{
if (m_data.Count == 0)
{
return(null);
}
if (nLookahead > 0 && bRemove)
{
throw new Exception("Removing data is not supported when retrieving data with a lookahead.");
}
PlotCollectionSet lastData = new PlotCollectionSet();
List <PlotCollection> rgPlots = new List <PlotCollection>();
for (int i = 0; i < m_data.Count; i++)
{
PlotCollectionSet dataFrame = m_data[i];
if (dataFrame.Count == 0)
{
return(null);
}
PlotCollection plots = new PlotCollection("Frame " + i.ToString());
for (int j = 0; j < dataFrame.Count; j++)
{
PlotCollection framePlots = dataFrame[j];
if (framePlots.Count == 0)
{
return(null);
}
Plot last = framePlots[framePlots.Count - (1 + nLookahead)];
if (last.Name == null)
{
last.Name = framePlots.Name;
}
plots.Add(last);
if (bRemove)
{
framePlots.RemoveAt(framePlots.Count - 1);
}
}
lastData.Add(plots);
}
if (bRemove)
{
m_output = m_surface.BuildGraph(m_config, m_data);
SimpleGraphingControl_Resize(this, EventArgs.Empty);
ScrollToEnd(false);
}
return(lastData);
}
public void AddData(PlotCollectionSet data, bool bMaintainCount, bool bRender = false)
{
if (data.Count != m_data.Count)
{
throw new Exception("The number of plot collections must match the number of plot sets used by the graph.");
}
List <string> rgUpdated = new List <string>();
for (int i = 0; i < data.Count; i++)
{
PlotCollectionSet dataFrame = m_data[i];
if (rgUpdated.Contains(dataFrame[0].Name))
{
continue;
}
PlotCollection dataToAdd = data[i];
if (dataFrame.Count != dataToAdd.Count)
{
throw new Exception("The number of data items to add must match the number of plot collections in the frame!");
}
for (int j = 0; j < dataFrame.Count; j++)
{
PlotCollection dataFrameItems = dataFrame[j];
Plot plot = dataToAdd[j];
dataFrameItems.Add(plot);
if (bMaintainCount)
{
dataFrameItems.RemoveAt(0);
}
}
rgUpdated.Add(dataFrame[0].Name);
}
m_output = m_surface.BuildGraph(m_config, m_data);
SimpleGraphingControl_Resize(this, EventArgs.Empty);
ScrollToEnd(bRender);
}
/// <summary>
/// Called on each training iteration of the sequence model used to encode each detected hand written character
/// and then decode the encoding into the proper section of the Sin curve.
/// </summary>
/// <param name="sender">Specifies the event sender.</param>
/// <param name="e">Specifies the event args.</param>
private void m_mycaffe_OnTrainingIteration(object sender, TrainingIterationArgs <float> e)
{
if (m_sw.Elapsed.TotalMilliseconds > 1000)
{
m_log.Progress = e.Iteration / (double)m_model.Iterations;
m_log.WriteLine("Seq2Seq Epoch " + m_nTotalEpochs.ToString() + " Sequence " + m_nTotalSequences.ToString() + " Iteration " + e.Iteration.ToString() + " of " + m_model.Iterations.ToString() + ", loss = " + e.SmoothedLoss.ToString(), true);
m_sw.Restart();
m_fTotalCost += (float)e.SmoothedLoss;
m_nTotalIter1++;
float fLoss = m_fTotalCost / m_nTotalIter1;
m_plotsSequenceLoss.Add(m_nTotalSequences, fLoss);
if (m_plotsSequenceLoss.Count > 2000)
{
m_plotsSequenceLoss.RemoveAt(0);
}
Image img = SimpleGraphingControl.QuickRender(m_plotsSequenceLoss, pbImageLoss.Width, pbImageLoss.Height, false, null, null, true, m_rgZeroLine);
m_bw.ReportProgress(1, new Tuple <Image, int>(img, 0));
}
}
