/// <summary>
/// Determine if the network is valid. If invalid, throw an error.
/// </summary>
///
/// <param name="network">The network to check.</param>
public virtual void Validate(IEngineMachineLearning network)
{
String msg = ((String)IsValid(network));
if (msg != null)
{
throw new ValidateMachineLearningError(msg);
}
}
/// <summary>
/// Determine if the network is valid. If invalid, throw an error.
/// </summary>
///
/// <param name="network">The network to check.</param>
public virtual void Validate(IEngineMachineLearning network)
{
String msg = ((String)IsValid(network));
if (msg != null)
{
throw new ValidateMachineLearningError(msg);
}
}
/// <summary>
/// Determine if the specified neural network can be flat. If it can a null
/// is returned, otherwise, an error is returned to show why the network
/// cannot be flattened.
/// </summary>
/// <param name="eml">The network to check.</param>
/// <returns>Null, if the net can not be flattened, an error message
/// otherwise.</returns>
public override String IsValid(IEngineMachineLearning eml)
{
if (!(eml is BasicNetwork))
{
return "Only a BasicNetwork can be converted to a flat network.";
}
BasicNetwork network = (BasicNetwork)eml;
ILayer inputLayer = network.GetLayer(BasicNetwork.TAG_INPUT);
ILayer outputLayer = network.GetLayer(BasicNetwork.TAG_OUTPUT);
if (inputLayer == null)
{
return "To convert to a flat network, there must be an input layer.";
}
if (outputLayer == null)
{
return "To convert to a flat network, there must be an output layer.";
}
if (!(network.Logic is FeedforwardLogic) ||
(network.Logic is ThermalLogic))
{
return "To convert to flat, must be using FeedforwardLogic or SimpleRecurrentLogic.";
}
foreach (ILayer layer in network.Structure.Layers)
{
if (layer.Next.Count > 2)
{
return "To convert to flat a network must have at most two outbound synapses.";
}
if (layer.GetType() != typeof(ContextLayer)
&& layer.GetType() != typeof(BasicLayer)
&& layer.GetType() != typeof(RadialBasisFunctionLayer))
{
return "To convert to flat a network must have only BasicLayer and ContextLayer layers.";
}
}
foreach (ISynapse synapse in network.Structure.Synapses)
{
if (synapse is NEATSynapse)
{
return "A NEAT synapse cannot be flattened.";
}
}
return null;
}
/// <summary>
/// Determine if the specified neural network can be flat. If it can a null
/// is returned, otherwise, an error is returned to show why the network
/// cannot be flattened.
/// </summary>
/// <param name="eml">The network to check.</param>
/// <returns>Null, if the net can not be flattened, an error message
/// otherwise.</returns>
public override String IsValid(IEngineMachineLearning eml)
{
if (!(eml is BasicNetwork))
{
return("Only a BasicNetwork can be converted to a flat network.");
}
BasicNetwork network = (BasicNetwork)eml;
ILayer inputLayer = network.GetLayer(BasicNetwork.TAG_INPUT);
ILayer outputLayer = network.GetLayer(BasicNetwork.TAG_OUTPUT);
if (inputLayer == null)
{
return("To convert to a flat network, there must be an input layer.");
}
if (outputLayer == null)
{
return("To convert to a flat network, there must be an output layer.");
}
if (!(network.Logic is FeedforwardLogic) ||
(network.Logic is ThermalLogic))
{
return("To convert to flat, must be using FeedforwardLogic or SimpleRecurrentLogic.");
}
foreach (ILayer layer in network.Structure.Layers)
{
if (layer.Next.Count > 2)
{
return("To convert to flat a network must have at most two outbound synapses.");
}
if (layer.GetType() != typeof(ContextLayer) &&
layer.GetType() != typeof(BasicLayer) &&
layer.GetType() != typeof(RadialBasisFunctionLayer))
{
return("To convert to flat a network must have only BasicLayer and ContextLayer layers.");
}
}
foreach (ISynapse synapse in network.Structure.Synapses)
{
if (synapse is NEATSynapse)
{
return("A NEAT synapse cannot be flattened.");
}
}
return(null);
}
/// <summary>
/// Determine if the network is valid for OpenCL.
/// </summary>
///
/// <param name="network">The network to check.</param>
/// <returns>The string indicating the error that prevents OpenCL from usingthe network, or null if the network is fine for OpenCL.</returns>
public override String IsValid(IEngineMachineLearning network)
{
if (!(network is FlatNetwork))
{
return "Only flat networks are valid to be used for OpenCL";
}
FlatNetwork flat = (FlatNetwork)network;
/* foreach */
foreach (IActivationFunction activation in flat.ActivationFunctions)
{
if (activation.GetOpenCLExpression(true) == null)
{
return "Can't use OpenCL if activation function does not have an OpenCL expression.";
}
}
if (flat.HasSameActivationFunction() == null)
{
return "Can't use OpenCL training on a neural network that uses multiple activation functions.";
}
bool hasContext = false;
for (int i = 0; i < flat.LayerCounts.Length; i++)
{
if (flat.ContextTargetOffset[i] != 0)
{
hasContext = true;
}
if (flat.ContextTargetSize[i] != 0)
{
hasContext = true;
}
}
if (hasContext)
{
return "Can't use OpenCL if context neurons are present.";
}
return null;
}
/// <summary>
/// Determine if the network is valid for OpenCL.
/// </summary>
///
/// <param name="network">The network to check.</param>
/// <returns>The string indicating the error that prevents OpenCL from usingthe network, or null if the network is fine for OpenCL.</returns>
public override String IsValid(IEngineMachineLearning network)
{
if (!(network is FlatNetwork))
{
return("Only flat networks are valid to be used for OpenCL");
}
FlatNetwork flat = (FlatNetwork)network;
/* foreach */
foreach (IActivationFunction activation in flat.ActivationFunctions)
{
if (activation.GetOpenCLExpression(true) == null)
{
return("Can't use OpenCL if activation function does not have an OpenCL expression.");
}
}
if (flat.HasSameActivationFunction() == null)
{
return("Can't use OpenCL training on a neural network that uses multiple activation functions.");
}
bool hasContext = false;
for (int i = 0; i < flat.LayerCounts.Length; i++)
{
if (flat.ContextTargetOffset[i] != 0)
{
hasContext = true;
}
if (flat.ContextTargetSize[i] != 0)
{
hasContext = true;
}
}
if (hasContext)
{
return("Can't use OpenCL if context neurons are present.");
}
return(null);
}
/// <summary>
/// from org.encog.engine.validate.ValidateMachineLearning
/// </summary>
///
public abstract System.String IsValid(
IEngineMachineLearning network);
/// <summary>
/// from org.encog.engine.validate.ValidateMachineLearning
/// </summary>
///
public abstract System.String IsValid(
IEngineMachineLearning network);
