public void augment(int[] instanceLengths, String trainfile, File train_forest, int numParts)
throws IOException {
// System.out.print("About to train. ");
// System.out.print("Num Feats: " + pipe.dataAlphabet.size());
int i, j;
int[] ignore = new int[instanceLengths.length];
// String trainpartfile;
// createPartitions(instanceLengths, trainfile, numParts);
// for(i = 0; i < numParts; i++)
// {
// trainpartfile = trainfile + "." + i;
// }
int numInstances = instanceLengths.length;
int numInstancesPerPart = numInstances / numParts; // The last partition becomes bigger
pipe.initOutputFile(options.outfile); // Initialize the output file once
for (j = 0; j < numParts; j++) {
System.out.println("Training classifier for partition " + j);
// Make partition
for (i = 0; i < numInstances; i++) {
if (i >= j * numInstancesPerPart && i < (j + 1) * numInstancesPerPart)
ignore[i] = 1; // Mark to ignore this instance in training
else ignore[i] = 0;
}
// Train on one split
params = new Parameters(pipe.dataAlphabet.size());
train(instanceLengths, ignore, trainfile, train_forest);
// Test on the other split
System.out.println("Making predictions for partition " + j);
for (i = 0; i < numInstances; i++) ignore[i] = 1 - ignore[i]; // Toggle ignore
outputParses(ignore);
}
pipe.close(); // Close the output file once
}
//////////////////////////////////////////////////////
// Get Best Parses ///////////////////////////////////
//////////////////////////////////////////////////////
public void outputParses() throws IOException {
String tFile = options.testfile;
String file = options.outfile;
long start = System.currentTimeMillis();
pipe.initInputFile(tFile);
pipe.initOutputFile(file);
System.out.print("Processing Sentence: ");
DependencyInstance instance = pipe.nextInstance();
int cnt = 0;
while (instance != null) {
cnt++;
System.out.print(cnt + " ");
String[] forms = instance.forms;
int length = forms.length;
FeatureVector[][][] fvs = new FeatureVector[forms.length][forms.length][2];
double[][][] probs = new double[forms.length][forms.length][2];
FeatureVector[][][][] nt_fvs = new FeatureVector[forms.length][pipe.types.length][2][2];
double[][][][] nt_probs = new double[forms.length][pipe.types.length][2][2];
FeatureVector[][][] fvs_trips = new FeatureVector[length][length][length];
double[][][] probs_trips = new double[length][length][length];
FeatureVector[][][] fvs_sibs = new FeatureVector[length][length][2];
double[][][] probs_sibs = new double[length][length][2];
if (options.secondOrder)
((DependencyPipe2O) pipe)
.fillFeatureVectors(
instance,
fvs,
probs,
fvs_trips,
probs_trips,
fvs_sibs,
probs_sibs,
nt_fvs,
nt_probs,
params);
else pipe.fillFeatureVectors(instance, fvs, probs, nt_fvs, nt_probs, params);
int K = options.testK;
Object[][] d = null;
if (options.decodeType.equals("proj")) {
if (options.secondOrder)
d =
((DependencyDecoder2O) decoder)
.decodeProjective(
instance,
fvs,
probs,
fvs_trips,
probs_trips,
fvs_sibs,
probs_sibs,
nt_fvs,
nt_probs,
K);
else d = decoder.decodeProjective(instance, fvs, probs, nt_fvs, nt_probs, K);
}
if (options.decodeType.equals("non-proj")) {
if (options.secondOrder)
d =
((DependencyDecoder2O) decoder)
.decodeNonProjective(
instance,
fvs,
probs,
fvs_trips,
probs_trips,
fvs_sibs,
probs_sibs,
nt_fvs,
nt_probs,
K);
else d = decoder.decodeNonProjective(instance, fvs, probs, nt_fvs, nt_probs, K);
}
String[] res = ((String) d[0][1]).split(" ");
String[] pos = instance.cpostags;
String[] formsNoRoot = new String[forms.length - 1];
String[] posNoRoot = new String[formsNoRoot.length];
String[] labels = new String[formsNoRoot.length];
int[] heads = new int[formsNoRoot.length];
Arrays.toString(forms);
Arrays.toString(res);
for (int j = 0; j < formsNoRoot.length; j++) {
formsNoRoot[j] = forms[j + 1];
posNoRoot[j] = pos[j + 1];
String[] trip = res[j].split("[\\|:]");
labels[j] = pipe.types[Integer.parseInt(trip[2])];
heads[j] = Integer.parseInt(trip[0]);
}
pipe.outputInstance(new DependencyInstance(formsNoRoot, posNoRoot, labels, heads));
// String line1 = ""; String line2 = ""; String line3 = ""; String line4 = "";
// for(int j = 1; j < pos.length; j++) {
// String[] trip = res[j-1].split("[\\|:]");
// line1+= sent[j] + "\t"; line2 += pos[j] + "\t";
// line4 += trip[0] + "\t"; line3 += pipe.types[Integer.parseInt(trip[2])] + "\t";
// }
// pred.write(line1.trim() + "\n" + line2.trim() + "\n"
// + (pipe.labeled ? line3.trim() + "\n" : "")
// + line4.trim() + "\n\n");
instance = pipe.nextInstance();
}
pipe.close();
long end = System.currentTimeMillis();
System.out.println("Took: " + (end - start));
}
//////////////////////////////////////////////////////
// Get Best Parses ///////////////////////////////////
//////////////////////////////////////////////////////
public void outputParses(int[] ignore) throws IOException {
String tFile = options.testfile;
String file = options.outfile;
long start = System.currentTimeMillis();
pipe.initInputFile(tFile);
// if (ignore == null) // afm 03-07-2008 --- If this is called for each partition, must have
// initialized output file before
if (!options.train
|| !options
.stackedLevel0) // afm 03-07-2008 --- If this is called for each partition, must have
// initialized output file before
pipe.initOutputFile(file);
System.out.print("Processing Sentence: ");
DependencyInstance instance = pipe.nextInstance();
int cnt = 0;
int i = 0;
LabelClassifier oc = new LabelClassifier(options);
while (instance != null) {
cnt++;
System.out.print(cnt + " ");
String[] forms = instance.forms;
int length = forms.length;
// afm 03-07-08 --- If this instance is to be ignored, just go for the next one
if (ignore != null && ignore[i] != 0) {
instance = pipe.nextInstance();
i++;
continue;
}
FeatureVector[][][] fvs = new FeatureVector[forms.length][forms.length][2];
double[][][] probs = new double[forms.length][forms.length][2];
FeatureVector[][][][] nt_fvs = new FeatureVector[forms.length][pipe.types.length][2][2];
double[][][][] nt_probs = new double[forms.length][pipe.types.length][2][2];
FeatureVector[][][] fvs_trips = new FeatureVector[length][length][length];
double[][][] probs_trips = new double[length][length][length];
FeatureVector[][][] fvs_sibs = new FeatureVector[length][length][2];
double[][][] probs_sibs = new double[length][length][2];
if (options.secondOrder)
((DependencyPipe2O) pipe)
.fillFeatureVectors(
instance,
fvs,
probs,
fvs_trips,
probs_trips,
fvs_sibs,
probs_sibs,
nt_fvs,
nt_probs,
params);
else pipe.fillFeatureVectors(instance, fvs, probs, nt_fvs, nt_probs, params);
int K = options.testK;
Object[][] d = null;
if (options.decodeType.equals("proj")) {
if (options.secondOrder)
d =
((DependencyDecoder2O) decoder)
.decodeProjective(
instance,
fvs,
probs,
fvs_trips,
probs_trips,
fvs_sibs,
probs_sibs,
nt_fvs,
nt_probs,
K);
else d = decoder.decodeProjective(instance, fvs, probs, nt_fvs, nt_probs, K);
}
if (options.decodeType.equals("non-proj")) {
if (options.secondOrder) {
d =
((DependencyDecoder2O) decoder)
.decodeNonProjective(
instance,
fvs,
probs,
fvs_trips,
probs_trips,
fvs_sibs,
probs_sibs,
nt_fvs,
nt_probs,
K);
} else d = decoder.decodeNonProjective(instance, fvs, probs, nt_fvs, nt_probs, K);
}
String[] res = ((String) d[0][1]).split(" ");
String[] pos = instance.cpostags;
String[] formsNoRoot = new String[forms.length - 1];
String[] posNoRoot = new String[formsNoRoot.length];
String[] labels = new String[formsNoRoot.length];
int[] heads = new int[formsNoRoot.length];
Arrays.toString(forms);
Arrays.toString(res);
for (int j = 0; j < formsNoRoot.length; j++) {
formsNoRoot[j] = forms[j + 1];
posNoRoot[j] = pos[j + 1];
String[] trip = res[j].split("[\\|:]");
labels[j] = pipe.types[Integer.parseInt(trip[2])];
heads[j] = Integer.parseInt(trip[0]);
}
// afm 06-04-08
if (options.separateLab) {
/*
* ask whether instance contains level0 information
*/
/*
* Note, forms and pos have the root. labels and heads do not
*/
if (options.stackedLevel1)
labels =
oc.outputLabels(
classifier,
instance.forms,
instance.postags,
labels,
heads,
instance.deprels_pred,
instance.heads_pred,
instance);
else
labels =
oc.outputLabels(
classifier,
instance.forms,
instance.postags,
labels,
heads,
null,
null,
instance);
}
// afm 03-07-08
// if (ignore == null)
if (options.stackedLevel0 == false)
pipe.outputInstance(new DependencyInstance(formsNoRoot, posNoRoot, labels, heads));
else {
int[] headsNoRoot = new int[instance.heads.length - 1];
String[] labelsNoRoot = new String[instance.heads.length - 1];
for (int j = 0; j < headsNoRoot.length; j++) {
headsNoRoot[j] = instance.heads[j + 1];
labelsNoRoot[j] = instance.deprels[j + 1];
}
DependencyInstance out_inst =
new DependencyInstance(formsNoRoot, posNoRoot, labelsNoRoot, headsNoRoot);
out_inst.stacked = true;
out_inst.heads_pred = heads;
out_inst.deprels_pred = labels;
pipe.outputInstance(out_inst);
}
// String line1 = ""; String line2 = ""; String line3 = ""; String line4 = "";
// for(int j = 1; j < pos.length; j++) {
// String[] trip = res[j-1].split("[\\|:]");
// line1+= sent[j] + "\t"; line2 += pos[j] + "\t";
// line4 += trip[0] + "\t"; line3 += pipe.types[Integer.parseInt(trip[2])] + "\t";
// }
// pred.write(line1.trim() + "\n" + line2.trim() + "\n"
// + (pipe.labeled ? line3.trim() + "\n" : "")
// + line4.trim() + "\n\n");
instance = pipe.nextInstance();
i++;
}
// if (ignore == null) // afm 03-07-2008 --- If this is called for each partition (ignore !=
// null), must close pipe outside the loop
if (!options.train
|| !options
.stackedLevel0) // afm 03-07-2008 --- If this is called for each partition (ignore !=
// null), must close pipe outside the loop
pipe.close();
long end = System.currentTimeMillis();
System.out.println("Took: " + (end - start));
}
/**
* Get the parses.
*
* @param allInstances a list to which all parse results are written. Can be {@code null}.
* @param writeOutput write output to file and log some messages to screen.
*/
protected void outputParses(List<DependencyInstance> allInstances, boolean writeOutput)
throws IOException {
String tFile = options.testfile;
String file = null;
if (writeOutput) {
file = options.outfile;
}
ConfidenceEstimator confEstimator = null;
if (options.confidenceEstimator != null) {
confEstimator = ConfidenceEstimator.resolveByName(options.confidenceEstimator, this);
System.out.println("Applying confidence estimation: " + options.confidenceEstimator);
}
long start = System.currentTimeMillis();
pipe.initInputFile(tFile);
if (writeOutput) {
pipe.initOutputFile(file);
}
if (writeOutput) {
System.out.print("Processing Sentence: ");
}
DependencyInstance instance = pipe.nextInstance();
int cnt = 0;
while (instance != null) {
cnt++;
if (writeOutput) {
System.out.print(cnt + " ");
}
String[] forms = instance.forms;
String[] formsNoRoot = new String[forms.length - 1];
String[] posNoRoot = new String[formsNoRoot.length];
String[] cposNoRoot = new String[formsNoRoot.length];
String[] labels = new String[formsNoRoot.length];
int[] heads = new int[formsNoRoot.length];
decode(
instance,
options.testK,
params,
formsNoRoot,
cposNoRoot,
posNoRoot,
labels,
heads,
confEstimator,
writeOutput);
/*
DependencyInstance parsedInstance;
if (confEstimator != null) {
double[] confidenceScores = confEstimator.estimateConfidence(instance);
parsedInstance = new DependencyInstance(formsNoRoot, posNoRoot, labels, heads,
confidenceScores);
} else {
parsedInstance = new DependencyInstance(formsNoRoot, posNoRoot, labels, heads);
}
if (writeOutput) {
pipe.outputInstance(parsedInstance);
}
if (allInstances != null) {
allInstances.add(parsedInstance);
}
*/
// String line1 = ""; String line2 = ""; String line3 = ""; String line4 = "";
// for(int j = 1; j < pos.length; j++) {
// String[] trip = res[j-1].split("[\\|:]");
// line1+= sent[j] + "\t"; line2 += pos[j] + "\t";
// line4 += trip[0] + "\t"; line3 += pipe.types[Integer.parseInt(trip[2])] + "\t";
// }
// pred.write(line1.trim() + "\n" + line2.trim() + "\n"
// + (pipe.labeled ? line3.trim() + "\n" : "")
// + line4.trim() + "\n\n");
instance = pipe.nextInstance();
}
pipe.close();
if (writeOutput) {
long end = System.currentTimeMillis();
System.out.println("Took: " + (end - start));
}
}
