public NetProcess(INeuralNetworkImage image)
{
if (image == null)
{
throw new ArgumentNullException(nameof(image));
}
history = NetProcessHistory.Restore(image);
}
public static NetProcessHistory Restore(INeuralNetworkImage stable_image)
{
var history = new NetProcessHistory();
if (stable_image != null)
{
history.StableNetImage = new NetProcessImage(stable_image, -1);
}
return(history);
}
public static NetProcessHistory Restore(INeuralNetworkImage stable_image, double[] chain)
{
var history = new NetProcessHistory();
if (stable_image != null)
{
if (chain == null || chain.Length < 1)
{
throw new ArgumentNullException(nameof(chain));
}
history.StableNetImage = new NetProcessImage(stable_image, chain[0]);
foreach (var accuracy in chain)
{
history.accuracy_chain.AddLast(accuracy);
}
}
return(history);
}
public NetProcess(NetProcessInfo state)
{
if (state == null)
{
throw new ArgumentNullException(nameof(state));
}
history = NetProcessHistory.Restore(state.stable_image, state.accuracy_chain_history);
if (state.running_image is NeuralNetworkImage image)
{
RunningChistaNet = new ChistaNet(image);
}
else if (state.running_image is NeuralNetworkLineImage line_image)
{
RunningChistaNet = new ChistaNetLine(line_image);
}
else if (state.stable_image == null)
{
throw new ArgumentException(nameof(state),
"The state must have stable-image or running-image");
}
else
{
return;
}
record_count = state.running_record_count;
total_accruacy = state.running_total_accruacy;
if (record_count > 0)
{
RunningAccuracy = total_accruacy / record_count;
}
}
public NetProcess(IChistaNet chista_net)
{
RunningChistaNet = chista_net ?? throw new ArgumentNullException(nameof(chista_net));
history = new NetProcessHistory();
}
