private static GamePlayerBenchmark.SampleState SelectOrCreateChildAtRandom(Random r, GraphicalModel model, int[] variables, int[] variableSizes, IList <GamePlayerBenchmark.SampleState> children, ConcatVector[] humanFeatureVectors)
{
int i = r.NextInt(variables.Length);
int variable = variables[i];
int observation = r.NextInt(variableSizes[i]);
foreach (GamePlayerBenchmark.SampleState s in children)
{
if (s.variable == variable && s.observation == observation)
{
return(s);
}
}
int humanObservationVariable = 0;
foreach (GraphicalModel.Factor f in model.factors)
{
foreach (int j in f.neigborIndices)
{
if (j >= humanObservationVariable)
{
humanObservationVariable = j + 1;
}
}
}
GraphicalModel.Factor f_1 = model.AddFactor(new int[] { variable, humanObservationVariable }, new int[] { variableSizes[i], variableSizes[i] }, null);
model.factors.Remove(f_1);
GamePlayerBenchmark.SampleState newState = new GamePlayerBenchmark.SampleState(f_1, variable, observation);
children.Add(newState);
return(newState);
}
public static void Annotate(GraphicalModel model, IList <string> tags, ConcatVectorNamespace @namespace, IDictionary <string, double[]> embeddings)
{
for (int i = 0; i < model.variableMetaData.Count; i++)
{
IDictionary <string, string> metadata = model.GetVariableMetaDataByReference(i);
string token = metadata["TOKEN"];
string pos = metadata["POS"];
string chunk = metadata["CHUNK"];
IDictionary <string, string> leftMetadata = null;
if (i > 0)
{
leftMetadata = model.GetVariableMetaDataByReference(i - 1);
}
string leftToken = (leftMetadata == null) ? "^" : leftMetadata["TOKEN"];
string leftPos = (leftMetadata == null) ? "^" : leftMetadata["POS"];
string leftChunk = (leftMetadata == null) ? "^" : leftMetadata["CHUNK"];
IDictionary <string, string> rightMetadata = null;
if (i < model.variableMetaData.Count - 1)
{
rightMetadata = model.GetVariableMetaDataByReference(i + 1);
}
string rightToken = (rightMetadata == null) ? "$" : rightMetadata["TOKEN"];
string rightPos = (rightMetadata == null) ? "$" : rightMetadata["POS"];
string rightChunk = (rightMetadata == null) ? "$" : rightMetadata["CHUNK"];
// Add the unary factor
GraphicalModel.Factor f = model.AddFactor(new int[] { i }, new int[] { tags.Count }, null);
// This is the anonymous function that generates a feature vector for each assignment to the unary
// factor
System.Diagnostics.Debug.Assert((f.neigborIndices.Length == 1));
System.Diagnostics.Debug.Assert((f.neigborIndices[0] == i));
// If this is not the last variable, add a binary factor
if (i < model.variableMetaData.Count - 1)
{
GraphicalModel.Factor jf = model.AddFactor(new int[] { i, i + 1 }, new int[] { tags.Count, tags.Count }, null);
// This is the anonymous function that generates a feature vector for every joint assignment to the
// binary factor
System.Diagnostics.Debug.Assert((jf.neigborIndices.Length == 2));
System.Diagnostics.Debug.Assert((jf.neigborIndices[0] == i));
System.Diagnostics.Debug.Assert((jf.neigborIndices[1] == i + 1));
}
}
}
private void RandomlyMutateGraphicalModel(GraphicalModel model, Random r)
{
if (r.NextBoolean() && model.factors.Count > 1)
{
// Remove one factor at random
model.factors.Remove(Sharpen.Collections.ToArray(model.factors, new GraphicalModel.Factor[model.factors.Count])[r.NextInt(model.factors.Count)]);
}
else
{
// Add a simple binary factor, attaching a variable we haven't touched yet, but do observe, to an
// existing variable. This represents the human observation operation in LENSE
int maxVar = 0;
int attachVar = -1;
int attachVarSize = 0;
foreach (GraphicalModel.Factor f in model.factors)
{
for (int j = 0; j < f.neigborIndices.Length; j++)
{
int k = f.neigborIndices[j];
if (k > maxVar)
{
maxVar = k;
}
if (r.NextDouble() > 0.3 || attachVar == -1)
{
attachVar = k;
attachVarSize = f.featuresTable.GetDimensions()[j];
}
}
}
int newVar = maxVar + 1;
int newVarSize = 1 + r.NextInt(2);
if (maxVar >= 8)
{
bool[] seenVariables = new bool[maxVar + 1];
foreach (GraphicalModel.Factor f_1 in model.factors)
{
foreach (int n in f_1.neigborIndices)
{
seenVariables[n] = true;
}
}
for (int j = 0; j < seenVariables.Length; j++)
{
if (!seenVariables[j])
{
newVar = j;
break;
}
}
// This means the model is already too gigantic to be tractable, so we don't add anything here
if (newVar == maxVar + 1)
{
return;
}
}
if (model.GetVariableMetaDataByReference(newVar).Contains(CliqueTree.VariableObservedValue))
{
int assignment = System.Convert.ToInt32(model.GetVariableMetaDataByReference(newVar)[CliqueTree.VariableObservedValue]);
if (assignment >= newVarSize)
{
newVarSize = assignment + 1;
}
}
GraphicalModel.Factor binary = model.AddFactor(new int[] { newVar, attachVar }, new int[] { newVarSize, attachVarSize }, null);
// "Cook" the randomly generated feature vector thunks, so they don't change as we run the system
foreach (int[] assignment_1 in binary.featuresTable)
{
ConcatVector randomlyGenerated = binary.featuresTable.GetAssignmentValue(assignment_1).Get();
binary.featuresTable.SetAssignmentValue(assignment_1, null);
}
}
}