public TrainingParameters()
        {
            InitializeComponent();

            Data = new TrainingRate();
            DataContext = Data;
        }
Esempio n. 2
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		public void PrepareTrainingData(TrainingRate learningParameters, int epoch, ref int index, ref bool stop)
		{
			if (learningParameters.Distorted)
			{
				if (((epoch-1) % learningParameters.SameDistortionsForNEpochs) == 0)
				{
					bool parameterChanged = false;

					if (SeverityFactor != learningParameters.SeverityFactor)
					{
						SeverityFactor = learningParameters.SeverityFactor;
						parameterChanged = true;
					}

					if (MaxScaling != learningParameters.MaxScaling)
					{
						MaxScaling = learningParameters.MaxScaling;
						parameterChanged = true;
					}

					if (MaxRotation != learningParameters.MaxRotation)
					{
						MaxRotation = learningParameters.MaxRotation;
						parameterChanged = true;
					}

					if (ElasticSigma != learningParameters.ElasticSigma)
					{
						ElasticSigma = learningParameters.ElasticSigma;
						parameterChanged = true;
					}

					if (ElasticScaling != learningParameters.ElasticScaling)
					{
						ElasticScaling = learningParameters.ElasticScaling;
						parameterChanged = true;
					}
					
					if (parameterChanged)
						CalculateGaussianKernel();

					PreparedTrainingPatterns = new DoubleImageData[TrainingPatternsCount];
					for (index = 0; index < TrainingPatternsCount; index++)
					{
						if (stop)
							break;

						PreparedTrainingPatterns[index] =  new DoubleImageData(TrainingPatterns[index].Label, GetDistortedPattern(index, true));
					}
				}
			}
			else
			{
				PreparedTrainingPatterns = TrainingPatterns;
			}
		}
Esempio n. 3
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        public void AddGlobalTrainingRate(TrainingRate rate, Boolean clear = true)
        {
            if (TrainingRates == null)
                 TrainingRates = new List<TrainingRate>();

            if ((TrainingRates != null) && (clear))
                TrainingRates.Clear();

            if (rate.DecayFactor == 1D)
            {
                TrainingRates.Add(rate);

                int numEpochs = 0;
                foreach (TrainingRate aRate in TrainingRates)
                {
                    numEpochs += aRate.Epochs;
                }
            }
            else
            {
                // Decaying Training Rate
                if (rate.Epochs < rate.DecayAfterEpochs)
                    rate.DecayAfterEpochs = rate.Epochs;

                int totIteration = rate.Epochs / rate.DecayAfterEpochs;
                double newRating = rate.Rate;

                for (int i = 0; i < totIteration; i++)
                {
                    TrainingRates.Add(new TrainingRate(newRating, rate.DecayAfterEpochs, rate.MinimumRate, rate.DecayFactor, rate.DecayAfterEpochs, rate.WeightSaveTreshold, rate.Distorted, rate.SameDistortionsForNEpochs, rate.SeverityFactor, rate.MaxScaling, rate.MaxRotation, rate.ElasticSigma, rate.ElasticScaling));
                    if (newRating * rate.DecayFactor > rate.MinimumRate)
                        newRating *= rate.DecayFactor;
                    else
                        newRating = rate.MinimumRate;
                }

                if ((totIteration * rate.DecayAfterEpochs) < rate.Epochs)
                {
                    TrainingRates.Add(new TrainingRate(newRating, rate.Epochs - (totIteration * rate.DecayAfterEpochs), rate.MinimumRate, rate.DecayFactor, rate.DecayAfterEpochs, rate.WeightSaveTreshold, rate.Distorted, rate.SameDistortionsForNEpochs, rate.SeverityFactor, rate.MaxScaling, rate.MaxRotation, rate.ElasticSigma, rate.ElasticScaling));
                }
            }
        }
 public TrainingParametersEditor()
 {
     Data = new TrainingRate(true);
     InitializeComponent();
 }
Esempio n. 5
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        private void TestingTask()
        {
            avgMSE = 0;
            misrecognitions = 0;
            curIndex = 0;

            testingPageViewModel.CurrentState = TestingStates.PreparingData;

            TrainingRate rate = new TrainingRate(testingPageViewModel.UseDistortions);
            if (testingPageViewModel.UseDistortions)
            {
                rate.SeverityFactor = testingPageViewModel.SeverityFactor;
                rate.MaxScaling = testingPageViewModel.MaxScaling;
                rate.MaxRotation = testingPageViewModel.MaxRotation;
                rate.ElasticScaling = testingPageViewModel.ElasticScaling;
                rate.ElasticSigma = testingPageViewModel.ElasticSigma;
            }

            pageViewModel.DataProvider.PrepareTrainingData(rate, 1, ref curIndex, ref testingStopped);

            testingPageViewModel.CurrentState = TestingStates.Testing;
            TestPattern(ref curIndex, ref testingStopped);

            testingPageViewModel.CurrentState = TestingStates.Idle;

            while (testingPageViewModel.CurrentState == TestingStates.Idle)
            {
                Thread.SpinWait(1);
                if (testingStopped)
                    break;
            }

            testingStopped = true;
        }