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Posted to commits@opennlp.apache.org by jo...@apache.org on 2017/06/20 09:04:58 UTC
opennlp git commit: OPENNLP-1094: Remove pmap indirection
Repository: opennlp
Updated Branches:
refs/heads/master 560c48438 -> c2097051c
OPENNLP-1094: Remove pmap indirection
Project: http://git-wip-us.apache.org/repos/asf/opennlp/repo
Commit: http://git-wip-us.apache.org/repos/asf/opennlp/commit/c2097051
Tree: http://git-wip-us.apache.org/repos/asf/opennlp/tree/c2097051
Diff: http://git-wip-us.apache.org/repos/asf/opennlp/diff/c2097051
Branch: refs/heads/master
Commit: c2097051c11479284f73485da46d02ba15e241a3
Parents: 560c484
Author: Jörn Kottmann <jo...@apache.org>
Authored: Wed Jun 14 14:34:14 2017 +0200
Committer: Jörn Kottmann <jo...@apache.org>
Committed: Fri Jun 16 14:43:18 2017 +0200
----------------------------------------------------------------------
.../java/opennlp/tools/ml/maxent/GISModel.java | 39 +++++++++++++++++---
.../tools/ml/maxent/io/GISModelWriter.java | 14 ++++---
.../tools/ml/maxent/quasinewton/QNModel.java | 11 +++---
.../opennlp/tools/ml/model/AbstractModel.java | 23 ++++--------
.../main/java/opennlp/tools/ml/model/Prior.java | 9 +++++
.../opennlp/tools/ml/model/UniformPrior.java | 5 +++
.../tools/ml/naivebayes/NaiveBayesModel.java | 26 ++++++++-----
.../ml/naivebayes/NaiveBayesModelWriter.java | 13 +++++--
.../tools/ml/perceptron/PerceptronModel.java | 35 +++++++++---------
.../ml/perceptron/PerceptronModelWriter.java | 15 +++++---
.../SimplePerceptronSequenceTrainer.java | 13 ++-----
11 files changed, 125 insertions(+), 78 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/opennlp/blob/c2097051/opennlp-tools/src/main/java/opennlp/tools/ml/maxent/GISModel.java
----------------------------------------------------------------------
diff --git a/opennlp-tools/src/main/java/opennlp/tools/ml/maxent/GISModel.java b/opennlp-tools/src/main/java/opennlp/tools/ml/maxent/GISModel.java
index 81b2690..700a81d 100644
--- a/opennlp-tools/src/main/java/opennlp/tools/ml/maxent/GISModel.java
+++ b/opennlp-tools/src/main/java/opennlp/tools/ml/maxent/GISModel.java
@@ -103,10 +103,9 @@ public final class GISModel extends AbstractModel {
* method getOutcome(int i).
*/
public final double[] eval(String[] context, float[] values, double[] outsums) {
- int[] scontexts = new int[context.length];
+ Context[] scontexts = new Context[context.length];
for (int i = 0; i < context.length; i++) {
- Integer ci = pmap.get(context[i]);
- scontexts[i] = ci == null ? -1 : ci;
+ scontexts[i] = pmap.get(context[i]);
}
prior.logPrior(outsums, scontexts, values);
return GISModel.eval(scontexts, values, outsums, evalParams);
@@ -154,14 +153,42 @@ public final class GISModel extends AbstractModel {
*/
static double[] eval(int[] context, float[] values, double[] prior,
EvalParameters model) {
- Context[] params = model.getParams();
+
+ Context[] scontexts = new Context[context.length];
+ for (int i = 0; i < context.length; i++) {
+ scontexts[i] = model.getParams()[context[i]];
+ }
+
+ return GISModel.eval(scontexts, values, prior, model);
+ }
+
+ /**
+ * Use this model to evaluate a context and return an array of the likelihood
+ * of each outcome given the specified context and the specified parameters.
+ *
+ * @param context
+ * The integer values of the predicates which have been observed at
+ * the present decision point.
+ * @param values
+ * The values for each of the parameters.
+ * @param prior
+ * The prior distribution for the specified context.
+ * @param model
+ * The set of parametes used in this computation.
+ * @return The normalized probabilities for the outcomes given the context.
+ * The indexes of the double[] are the outcome ids, and the actual
+ * string representation of the outcomes can be obtained from the
+ * method getOutcome(int i).
+ */
+ static double[] eval(Context[] context, float[] values, double[] prior,
+ EvalParameters model) {
int[] numfeats = new int[model.getNumOutcomes()];
int[] activeOutcomes;
double[] activeParameters;
double value = 1;
for (int ci = 0; ci < context.length; ci++) {
- if (context[ci] >= 0) {
- Context predParams = params[context[ci]];
+ if (context[ci] != null) {
+ Context predParams = context[ci];
activeOutcomes = predParams.getOutcomes();
activeParameters = predParams.getParameters();
if (values != null) {
http://git-wip-us.apache.org/repos/asf/opennlp/blob/c2097051/opennlp-tools/src/main/java/opennlp/tools/ml/maxent/io/GISModelWriter.java
----------------------------------------------------------------------
diff --git a/opennlp-tools/src/main/java/opennlp/tools/ml/maxent/io/GISModelWriter.java b/opennlp-tools/src/main/java/opennlp/tools/ml/maxent/io/GISModelWriter.java
index e11dcba..3fdeaf0 100644
--- a/opennlp-tools/src/main/java/opennlp/tools/ml/maxent/io/GISModelWriter.java
+++ b/opennlp-tools/src/main/java/opennlp/tools/ml/maxent/io/GISModelWriter.java
@@ -42,14 +42,18 @@ public abstract class GISModelWriter extends AbstractModelWriter {
Object[] data = model.getDataStructures();
- PARAMS = (Context[]) data[0];
-
@SuppressWarnings("unchecked")
- Map<String, Integer> pmap = (Map<String, Integer>) data[1];
+ Map<String, Context> pmap = (Map<String, Context>) data[1];
+
OUTCOME_LABELS = (String[]) data[2];
+ PARAMS = new Context[pmap.size()];
PRED_LABELS = new String[pmap.size()];
- for (String pred : pmap.keySet()) {
- PRED_LABELS[pmap.get(pred)] = pred;
+
+ int i = 0;
+ for (Map.Entry<String, Context> pred : pmap.entrySet()) {
+ PRED_LABELS[i] = pred.getKey();
+ PARAMS[i] = pred.getValue();
+ i++;
}
}
http://git-wip-us.apache.org/repos/asf/opennlp/blob/c2097051/opennlp-tools/src/main/java/opennlp/tools/ml/maxent/quasinewton/QNModel.java
----------------------------------------------------------------------
diff --git a/opennlp-tools/src/main/java/opennlp/tools/ml/maxent/quasinewton/QNModel.java b/opennlp-tools/src/main/java/opennlp/tools/ml/maxent/quasinewton/QNModel.java
index d73d6cc..85f6dc3 100644
--- a/opennlp-tools/src/main/java/opennlp/tools/ml/maxent/quasinewton/QNModel.java
+++ b/opennlp-tools/src/main/java/opennlp/tools/ml/maxent/quasinewton/QNModel.java
@@ -31,7 +31,7 @@ public class QNModel extends AbstractModel {
return this.outcomeNames.length;
}
- private Integer getPredIndex(String predicate) {
+ private Context getPredIndex(String predicate) {
return pmap.get(predicate);
}
@@ -60,17 +60,16 @@ public class QNModel extends AbstractModel {
* @return Normalized probabilities for the outcomes given the context.
*/
private double[] eval(String[] context, float[] values, double[] probs) {
- Context[] params = evalParams.getParams();
for (int ci = 0; ci < context.length; ci++) {
- Integer predIdx = getPredIndex(context[ci]);
+ Context pred = getPredIndex(context[ci]);
- if (predIdx != null) {
+ if (pred != null) {
double predValue = 1.0;
if (values != null) predValue = values[ci];
- double[] parameters = params[predIdx].getParameters();
- int[] outcomes = params[predIdx].getOutcomes();
+ double[] parameters = pred.getParameters();
+ int[] outcomes = pred.getOutcomes();
for (int i = 0; i < outcomes.length; i++) {
int oi = outcomes[i];
probs[oi] += predValue * parameters[i];
http://git-wip-us.apache.org/repos/asf/opennlp/blob/c2097051/opennlp-tools/src/main/java/opennlp/tools/ml/model/AbstractModel.java
----------------------------------------------------------------------
diff --git a/opennlp-tools/src/main/java/opennlp/tools/ml/model/AbstractModel.java b/opennlp-tools/src/main/java/opennlp/tools/ml/model/AbstractModel.java
index eb80f1b..4783a71 100644
--- a/opennlp-tools/src/main/java/opennlp/tools/ml/model/AbstractModel.java
+++ b/opennlp-tools/src/main/java/opennlp/tools/ml/model/AbstractModel.java
@@ -26,7 +26,7 @@ import java.util.Objects;
public abstract class AbstractModel implements MaxentModel {
/** Mapping between predicates/contexts and an integer representing them. */
- protected Map<String, Integer> pmap;
+ protected Map<String, Context> pmap;
/** The names of the outcomes. */
protected String[] outcomeNames;
/** Parameters for the model. */
@@ -39,32 +39,23 @@ public abstract class AbstractModel implements MaxentModel {
/** The type of the model. */
protected ModelType modelType;
- /**
- * @deprecated this will be removed in 1.8.1, pmap should be private
- *
- * @param params
- * @param predLabels
- * @param pmap
- * @param outcomeNames
- */
- @Deprecated
- public AbstractModel(Context[] params, String[] predLabels,
- Map<String, Integer> pmap, String[] outcomeNames) {
+ protected AbstractModel(Context[] params, String[] predLabels,
+ Map<String, Context> pmap, String[] outcomeNames) {
this.pmap = pmap;
this.outcomeNames = outcomeNames;
this.evalParams = new EvalParameters(params,outcomeNames.length);
}
public AbstractModel(Context[] params, String[] predLabels, String[] outcomeNames) {
- init(predLabels, outcomeNames);
+ init(predLabels, params, outcomeNames);
this.evalParams = new EvalParameters(params, outcomeNames.length);
}
- private void init(String[] predLabels, String[] outcomeNames) {
+ private void init(String[] predLabels, Context[] params, String[] outcomeNames) {
this.pmap = new HashMap<>(predLabels.length);
for (int i = 0; i < predLabels.length; i++) {
- pmap.put(predLabels[i], i);
+ pmap.put(predLabels[i], params[i]);
}
this.outcomeNames = outcomeNames;
@@ -188,7 +179,7 @@ public abstract class AbstractModel implements MaxentModel {
AbstractModel model = (AbstractModel) obj;
return pmap.equals(model.pmap) && Objects.deepEquals(outcomeNames, model.outcomeNames)
- && evalParams.equals(model.evalParams) && Objects.equals(prior, model.prior);
+ && Objects.equals(prior, model.prior);
}
return false;
http://git-wip-us.apache.org/repos/asf/opennlp/blob/c2097051/opennlp-tools/src/main/java/opennlp/tools/ml/model/Prior.java
----------------------------------------------------------------------
diff --git a/opennlp-tools/src/main/java/opennlp/tools/ml/model/Prior.java b/opennlp-tools/src/main/java/opennlp/tools/ml/model/Prior.java
index b0ce405..89ddc69 100644
--- a/opennlp-tools/src/main/java/opennlp/tools/ml/model/Prior.java
+++ b/opennlp-tools/src/main/java/opennlp/tools/ml/model/Prior.java
@@ -41,6 +41,15 @@ public interface Prior {
void logPrior(double[] dist, int[] context, float[] values);
/**
+ * Populates the specified array with the the log of the distribution for the specified context.
+ * The returned array will be overwritten and needs to be re-initialized with every call to this method.
+ * @param dist An array to be populated with the log of the prior distribution.
+ * @param context The indices of the contextual predicates for an event.
+ * @param values The values associated with the context.
+ */
+ void logPrior(double[] dist, Context[] context, float[] values);
+
+ /**
* Method to specify the label for the outcomes and contexts. This is used to map
* integer outcomes and contexts to their string values. This method is called prior
* to any call to #logPrior.
http://git-wip-us.apache.org/repos/asf/opennlp/blob/c2097051/opennlp-tools/src/main/java/opennlp/tools/ml/model/UniformPrior.java
----------------------------------------------------------------------
diff --git a/opennlp-tools/src/main/java/opennlp/tools/ml/model/UniformPrior.java b/opennlp-tools/src/main/java/opennlp/tools/ml/model/UniformPrior.java
index 412fdaf..17574e2 100644
--- a/opennlp-tools/src/main/java/opennlp/tools/ml/model/UniformPrior.java
+++ b/opennlp-tools/src/main/java/opennlp/tools/ml/model/UniformPrior.java
@@ -33,6 +33,11 @@ public class UniformPrior implements Prior {
}
}
+ @Override
+ public void logPrior(double[] dist, Context[] context, float[] values) {
+ logPrior(dist, (int[]) null, values);
+ }
+
public void logPrior(double[] dist, int[] context) {
logPrior(dist,context,null);
}
http://git-wip-us.apache.org/repos/asf/opennlp/blob/c2097051/opennlp-tools/src/main/java/opennlp/tools/ml/naivebayes/NaiveBayesModel.java
----------------------------------------------------------------------
diff --git a/opennlp-tools/src/main/java/opennlp/tools/ml/naivebayes/NaiveBayesModel.java b/opennlp-tools/src/main/java/opennlp/tools/ml/naivebayes/NaiveBayesModel.java
index 98c2735..85e17eb 100644
--- a/opennlp-tools/src/main/java/opennlp/tools/ml/naivebayes/NaiveBayesModel.java
+++ b/opennlp-tools/src/main/java/opennlp/tools/ml/naivebayes/NaiveBayesModel.java
@@ -31,8 +31,7 @@ public class NaiveBayesModel extends AbstractModel {
protected double[] outcomeTotals;
protected long vocabulary;
- @Deprecated
- public NaiveBayesModel(Context[] params, String[] predLabels, Map<String, Integer> pmap,
+ NaiveBayesModel(Context[] params, String[] predLabels, Map<String, Context> pmap,
String[] outcomeNames) {
super(params, predLabels, pmap, outcomeNames);
outcomeTotals = initOutcomeTotals(outcomeNames, params);
@@ -75,11 +74,10 @@ public class NaiveBayesModel extends AbstractModel {
}
public double[] eval(String[] context, float[] values, double[] outsums) {
- int[] scontexts = new int[context.length];
+ Context[] scontexts = new Context[context.length];
java.util.Arrays.fill(outsums, 0);
for (int i = 0; i < context.length; i++) {
- Integer ci = pmap.get(context[i]);
- scontexts[i] = ci == null ? -1 : ci;
+ scontexts[i] = pmap.get(context[i]);
}
return eval(scontexts, values, outsums, evalParams, true);
}
@@ -88,8 +86,8 @@ public class NaiveBayesModel extends AbstractModel {
return eval(context, null, prior, model, true);
}
- static double[] eval(int[] context, float[] values, double[] prior,
- EvalParameters model, boolean normalize) {
+ static double[] eval(Context[] context, float[] values, double[] prior,
+ EvalParameters model, boolean normalize) {
Probabilities<Integer> probabilities = new LogProbabilities<>();
Context[] params = model.getParams();
double[] outcomeTotals = model instanceof NaiveBayesEvalParameters
@@ -100,8 +98,8 @@ public class NaiveBayesModel extends AbstractModel {
int[] activeOutcomes;
double value = 1;
for (int ci = 0; ci < context.length; ci++) {
- if (context[ci] >= 0) {
- Context predParams = params[context[ci]];
+ if (context[ci] != null) {
+ Context predParams = context[ci];
activeOutcomes = predParams.getOutcomes();
activeParameters = predParams.getParameters();
if (values != null) {
@@ -130,6 +128,16 @@ public class NaiveBayesModel extends AbstractModel {
return prior;
}
+ static double[] eval(int[] context, float[] values, double[] prior,
+ EvalParameters model, boolean normalize) {
+ Context[] scontexts = new Context[context.length];
+ for (int i = 0; i < context.length; i++) {
+ scontexts[i] = model.getParams()[context[i]];
+ }
+
+ return eval(scontexts, values, prior, model, normalize);
+ }
+
private static double getProbability(double numerator, double denominator,
double vocabulary, boolean isSmoothed) {
if (isSmoothed)
http://git-wip-us.apache.org/repos/asf/opennlp/blob/c2097051/opennlp-tools/src/main/java/opennlp/tools/ml/naivebayes/NaiveBayesModelWriter.java
----------------------------------------------------------------------
diff --git a/opennlp-tools/src/main/java/opennlp/tools/ml/naivebayes/NaiveBayesModelWriter.java b/opennlp-tools/src/main/java/opennlp/tools/ml/naivebayes/NaiveBayesModelWriter.java
index 510bf76..60efbaa 100644
--- a/opennlp-tools/src/main/java/opennlp/tools/ml/naivebayes/NaiveBayesModelWriter.java
+++ b/opennlp-tools/src/main/java/opennlp/tools/ml/naivebayes/NaiveBayesModelWriter.java
@@ -46,12 +46,17 @@ public abstract class NaiveBayesModelWriter extends AbstractModelWriter {
PARAMS = (Context[]) data[0];
@SuppressWarnings("unchecked")
- Map<String, Integer> pmap = (Map<String, Integer>) data[1];
- OUTCOME_LABELS = (String[]) data[2];
+ Map<String, Context> pmap = (Map<String, Context>) data[1];
+ OUTCOME_LABELS = (String[]) data[2];
+ PARAMS = new Context[pmap.size()];
PRED_LABELS = new String[pmap.size()];
- for (String pred : pmap.keySet()) {
- PRED_LABELS[pmap.get(pred)] = pred;
+
+ int i = 0;
+ for (Map.Entry<String, Context> pred : pmap.entrySet()) {
+ PRED_LABELS[i] = pred.getKey();
+ PARAMS[i] = pred.getValue();
+ i++;
}
}
http://git-wip-us.apache.org/repos/asf/opennlp/blob/c2097051/opennlp-tools/src/main/java/opennlp/tools/ml/perceptron/PerceptronModel.java
----------------------------------------------------------------------
diff --git a/opennlp-tools/src/main/java/opennlp/tools/ml/perceptron/PerceptronModel.java b/opennlp-tools/src/main/java/opennlp/tools/ml/perceptron/PerceptronModel.java
index 39c4891..b931c50 100644
--- a/opennlp-tools/src/main/java/opennlp/tools/ml/perceptron/PerceptronModel.java
+++ b/opennlp-tools/src/main/java/opennlp/tools/ml/perceptron/PerceptronModel.java
@@ -17,24 +17,12 @@
package opennlp.tools.ml.perceptron;
-import java.util.Map;
-
import opennlp.tools.ml.model.AbstractModel;
import opennlp.tools.ml.model.Context;
import opennlp.tools.ml.model.EvalParameters;
public class PerceptronModel extends AbstractModel {
- /**
- * @deprecated this will be removed in 1.8.1, pmap should be private
- */
- @Deprecated
- public PerceptronModel(Context[] params, String[] predLabels, Map<String, Integer> pmap,
- String[] outcomeNames) {
- super(params,predLabels,pmap,outcomeNames);
- modelType = ModelType.Perceptron;
- }
-
public PerceptronModel(Context[] params, String[] predLabels, String[] outcomeNames) {
super(params,predLabels,outcomeNames);
modelType = ModelType.Perceptron;
@@ -53,11 +41,10 @@ public class PerceptronModel extends AbstractModel {
}
public double[] eval(String[] context, float[] values,double[] outsums) {
- int[] scontexts = new int[context.length];
+ Context[] scontexts = new Context[context.length];
java.util.Arrays.fill(outsums, 0);
for (int i = 0; i < context.length; i++) {
- Integer ci = pmap.get(context[i]);
- scontexts[i] = ci == null ? -1 : ci;
+ scontexts[i] = pmap.get(context[i]);
}
return eval(scontexts,values,outsums,evalParams,true);
}
@@ -68,13 +55,23 @@ public class PerceptronModel extends AbstractModel {
static double[] eval(int[] context, float[] values, double[] prior, EvalParameters model,
boolean normalize) {
+ Context[] scontexts = new Context[context.length];
+ for (int i = 0; i < context.length; i++) {
+ scontexts[i] = model.getParams()[context[i]];
+ }
+
+ return eval(scontexts, values, prior, model, normalize);
+ }
+
+ static double[] eval(Context[] context, float[] values, double[] prior, EvalParameters model,
+ boolean normalize) {
Context[] params = model.getParams();
double[] activeParameters;
int[] activeOutcomes;
double value = 1;
for (int ci = 0; ci < context.length; ci++) {
- if (context[ci] >= 0) {
- Context predParams = params[context[ci]];
+ if (context[ci] != null) {
+ Context predParams = context[ci];
activeOutcomes = predParams.getOutcomes();
activeParameters = predParams.getParameters();
if (values != null) {
@@ -86,6 +83,7 @@ public class PerceptronModel extends AbstractModel {
}
}
}
+
if (normalize) {
int numOutcomes = model.getNumOutcomes();
@@ -102,8 +100,9 @@ public class PerceptronModel extends AbstractModel {
normal += prior[oid];
}
- for (int oid = 0; oid < numOutcomes; oid++)
+ for (int oid = 0; oid < numOutcomes; oid++) {
prior[oid] /= normal;
+ }
}
return prior;
}
http://git-wip-us.apache.org/repos/asf/opennlp/blob/c2097051/opennlp-tools/src/main/java/opennlp/tools/ml/perceptron/PerceptronModelWriter.java
----------------------------------------------------------------------
diff --git a/opennlp-tools/src/main/java/opennlp/tools/ml/perceptron/PerceptronModelWriter.java b/opennlp-tools/src/main/java/opennlp/tools/ml/perceptron/PerceptronModelWriter.java
index 133400b..93f4fcf 100644
--- a/opennlp-tools/src/main/java/opennlp/tools/ml/perceptron/PerceptronModelWriter.java
+++ b/opennlp-tools/src/main/java/opennlp/tools/ml/perceptron/PerceptronModelWriter.java
@@ -46,13 +46,18 @@ public abstract class PerceptronModelWriter extends AbstractModelWriter {
this.numOutcomes = model.getNumOutcomes();
PARAMS = (Context[]) data[0];
- @SuppressWarnings("unchecked")
- Map<String, Integer> pmap = (Map<String, Integer>) data[1];
- OUTCOME_LABELS = (String[])data[2];
+ Map<String, Context> pmap = (Map<String, Context>) data[1];
+
+ OUTCOME_LABELS = (String[]) data[2];
+ PARAMS = new Context[pmap.size()];
PRED_LABELS = new String[pmap.size()];
- for (String pred : pmap.keySet()) {
- PRED_LABELS[pmap.get(pred)] = pred;
+
+ int i = 0;
+ for (Map.Entry<String, Context> pred : pmap.entrySet()) {
+ PRED_LABELS[i] = pred.getKey();
+ PARAMS[i] = pred.getValue();
+ i++;
}
}
http://git-wip-us.apache.org/repos/asf/opennlp/blob/c2097051/opennlp-tools/src/main/java/opennlp/tools/ml/perceptron/SimplePerceptronSequenceTrainer.java
----------------------------------------------------------------------
diff --git a/opennlp-tools/src/main/java/opennlp/tools/ml/perceptron/SimplePerceptronSequenceTrainer.java b/opennlp-tools/src/main/java/opennlp/tools/ml/perceptron/SimplePerceptronSequenceTrainer.java
index a9ac516..b812836 100644
--- a/opennlp-tools/src/main/java/opennlp/tools/ml/perceptron/SimplePerceptronSequenceTrainer.java
+++ b/opennlp-tools/src/main/java/opennlp/tools/ml/perceptron/SimplePerceptronSequenceTrainer.java
@@ -193,12 +193,7 @@ public class SimplePerceptronSequenceTrainer extends AbstractEventModelSequenceT
/* Create and return the model ****/
String[] updatedPredLabels = predLabels;
- /*
- String[] updatedPredLabels = new String[pmap.size()];
- for (String pred : pmap.keySet()) {
- updatedPredLabels[pmap.get(pred)]=pred;
- }
- */
+
if (useAverage) {
return new PerceptronModel(averageParams, updatedPredLabels, outcomeLabels);
}
@@ -235,7 +230,7 @@ public class SimplePerceptronSequenceTrainer extends AbstractEventModelSequenceT
for (int oi = 0; oi < numOutcomes; oi++) {
featureCounts.add(new HashMap<>());
}
- PerceptronModel model = new PerceptronModel(params,predLabels,pmap,outcomeLabels);
+ PerceptronModel model = new PerceptronModel(params,predLabels,outcomeLabels);
sequenceStream.reset();
@@ -328,7 +323,7 @@ public class SimplePerceptronSequenceTrainer extends AbstractEventModelSequenceT
}
}
}
- model = new PerceptronModel(params,predLabels,pmap,outcomeLabels);
+ model = new PerceptronModel(params,predLabels,outcomeLabels);
}
si++;
}
@@ -364,7 +359,7 @@ public class SimplePerceptronSequenceTrainer extends AbstractEventModelSequenceT
Sequence sequence;
while ((sequence = sequenceStream.read()) != null) {
Event[] taggerEvents = sequenceStream.updateContext(sequence,
- new PerceptronModel(params,predLabels,pmap,outcomeLabels));
+ new PerceptronModel(params,predLabels,outcomeLabels));
for (int ei = 0; ei < taggerEvents.length; ei++, oei++) {
int max = omap.get(taggerEvents[ei].getOutcome());
if (max == outcomeList[oei]) {