public void Train(NeuralNetworkTrainArgs trainArgs)
{
TrainArgs = trainArgs;
for (int epoch = 0; epoch < trainArgs.trainEpoches; ++epoch)
{
trainArgs.onOnceEpoch?.Invoke(epoch);
for (int i = 0; i < trainArgs.trainingData.Length; ++i)
{
TrainOnce(trainArgs.trainingData[i], trainArgs.trainingLabels[i], trainArgs.learningRate);
}
}
trainArgs.onOnceEpoch?.Invoke(trainArgs.trainEpoches);
trainArgs.onFinish?.Invoke();
}
public void CheckGradient(NeuralNetworkTrainArgs trainArgs)
{
TrainArgs = trainArgs;
var input = trainArgs.trainingData[0];
var label = trainArgs.trainingLabels[0];
var predict = Forward(input);
var delta = predict - label;
var temp = delta;
for (int i = _layers.Count - 1; i >= 0; --i)
{
var layer = _layers[i];
temp = layer.CheckGradient(temp);
}
}
