NishantShri4 commented on code in PR #758:
URL: https://github.com/apache/opennlp/pull/758#discussion_r2012761368
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opennlp-tools/src/main/java/opennlp/tools/monitoring/ConsoleTrainingProgressMonitor.java:
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@@ -0,0 +1,51 @@
+package opennlp.tools.monitoring;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.util.LinkedList;
+import java.util.List;
+import java.util.Objects;
+
+import static
opennlp.tools.monitoring.StopCriteria.TRAINING_FINISHED_DEFAULT_MSG;
+
+/**
+ * Publishes ML model's Training progress to console.
+ */
+public class ConsoleTrainingProgressMonitor implements TrainingProgressMonitor
{
+
+ private static final Logger logger =
LoggerFactory.getLogger(ConsoleTrainingProgressMonitor.class);
+
+ /**
+ * Keeps a track whether training was already finished because StopCriteria
was met.
+ */
+ volatile boolean isTrainingFinished;
+
+ private final List<String> progress = new LinkedList<>();
Review Comment:
Good point! Should we think about following?
1. Add an extractAndClear() method on TPM interface , which when invoked
empties the underlying data-structure and returns the logged progress. The
caller then decides what to do with the returned results?
2. finishedIteration() issues a warning when number of items logged reach a
configured threshold e.g. 50k progress events logged.
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