Added table executor

run

@@ -650,6 +650,7 @@ addMode('tables', 'QA on HTML tables', lambda { |e| l(
     'alter-ex' => l('edu.stanford.nlp.sempre.tables.alter.AlteredTablesExecutor', let(:parser, 'serialized')),
     'filter' => 'edu.stanford.nlp.sempre.tables.serialize.DumpFilterer',
     'column' => 'edu.stanford.nlp.sempre.tables.test.TableColumnAnalyzer',
+    'execute' => 'edu.stanford.nlp.sempre.tables.test.BatchTableExecutor',
   }),
   # Fig parameters
   selo(:cldir, 'execDir', '_OUTPATH_', '.'),
@@ -674,6 +675,7 @@ addMode('tables', 'QA on HTML tables', lambda { |e| l(
   }),
   # Parser
   letDefault(:parser, 'floatsize'),
+  o('beamSize', 100),
   o('useSizeInsteadOfDepth'),
   sel(:parser, {
     'floatsize' => l(
@@ -702,7 +704,6 @@ addMode('tables', 'QA on HTML tables', lambda { |e| l(
     'cprune' => l(
       o('Builder.parser', 'cprune.CPruneFloatingParser'),
       o('FloatingParser.maxDepth', 15),
-      o('beamSize', 100),
       o('maxNumNeighbors', 40),
       o('maxPredictedPatterns', 1000),
     nil),

src/edu/stanford/nlp/sempre/Learner.java

@@ -312,6 +312,7 @@ public class Learner {
     // evaluation.add(LexiconFn.lexEval);
     evaluation.logStats(prefix);
     evaluation.putOutput(prefix);
+    evaluation.putOutput(prefix.replaceAll("iter=", "").replace('.', '_'));
   }
 
   private void printLearnerEventsIter(Example ex, int iter, String group) {

src/edu/stanford/nlp/sempre/tables/test/BatchTableExecutor.java

@@ -0,0 +1,136 @@
+package edu.stanford.nlp.sempre.tables.test;
+
+import java.io.*;
+import java.util.*;
+
+import edu.stanford.nlp.sempre.*;
+import edu.stanford.nlp.sempre.tables.TableKnowledgeGraph;
+import edu.stanford.nlp.sempre.tables.TableValueEvaluator;
+import edu.stanford.nlp.sempre.tables.lambdadcs.LambdaDCSExecutor;
+import fig.basic.*;
+import fig.exec.Execution;
+
+/**
+ * Execute the specified logical forms on the specified WikiTableQuestions context.
+ *
+ * @author ppasupat
+ */
+public class BatchTableExecutor implements Runnable {
+  public static class Options {
+    @Option(gloss = "TSV file containing table contexts and logical forms")
+    public String batchInput;
+    @Option(gloss = "Datasets for mapping example IDs to contexts")
+    public List<String> batchDatasets = Arrays.asList("lib/data/tables/data/training.examples");
+  }
+  public static Options opts = new Options();
+
+  public static void main(String[] args) {
+    Execution.run(args, "BatchTableExecutorMain", new BatchTableExecutor(), Master.getOptionsParser());
+  }
+
+  @Override
+  public void run() {
+    if (opts.batchInput == null || opts.batchInput.isEmpty()) {
+      LogInfo.logs("*******************************************************************************");
+      LogInfo.logs("USAGE: ./run @mode=tables @class=execute -batchInput <filename>");
+      LogInfo.logs("");
+      LogInfo.logs("Input file format: Each line has something like");
+      LogInfo.logs("  nt-218    [tab]   (count (fb:type.object.type fb:type.row))");
+      LogInfo.logs("or");
+      LogInfo.logs("  csv/204-csv/23.csv    [tab]   (count (fb:type.object.type fb:type.row))");
+      LogInfo.logs("");
+      LogInfo.logs("Results will also be printed to state/execs/___.exec/denotations.tsv");
+      LogInfo.logs("Output format:");
+      LogInfo.logs("  nt-218    [tab]   (count (fb:type.object.type fb:type.row))   [tab]   (list (number 10))   [tab]   false");
+      LogInfo.logs("where the last column indicates whether the answer is consistent with the target answer");
+      LogInfo.logs("(only available when the first column is nt-___)");
+      LogInfo.logs("*******************************************************************************");
+      System.exit(1);
+    }
+    LambdaDCSExecutor executor = new LambdaDCSExecutor();
+    ValueEvaluator evaluator = new TableValueEvaluator();
+    try {
+      BufferedReader reader = IOUtils.openIn(opts.batchInput);
+      PrintWriter output = IOUtils.openOut(Execution.getFile("denotations.tsv"));
+      String line;
+      while ((line = reader.readLine()) != null) {
+        String[] tokens = line.split("\t");
+        String answer;
+        try {
+          Formula formula = Formula.fromString(tokens[1]);
+          if (tokens[0].startsWith("csv")) {
+            TableKnowledgeGraph graph = TableKnowledgeGraph.fromFilename(tokens[0]);
+            ContextValue context = new ContextValue(graph);
+            Value denotation = executor.execute(formula, context).value;
+            if (denotation instanceof ListValue)
+              denotation = addOriginalStrings((ListValue) denotation, graph);
+            answer = denotation.toString();
+          } else {
+            Example ex = exIdToExample(tokens[0]);
+            Value denotation = executor.execute(formula, ex.context).value;
+            if (denotation instanceof ListValue)
+              denotation = addOriginalStrings((ListValue) denotation, (TableKnowledgeGraph) ex.context.graph);
+            answer = denotation.toString();
+            boolean correct = evaluator.getCompatibility(ex.targetValue, denotation) == 1.;
+            answer = denotation.toString() + "\t" + correct;
+          }
+        } catch (Exception e) {
+          answer = "ERROR: " + e;
+        }
+        System.out.printf("%s\t%s\t%s\n", tokens[0], tokens[1], answer);
+        output.printf("%s\t%s\t%s\n", tokens[0], tokens[1], answer);
+      }
+      reader.close();
+      output.close();
+    } catch (IOException e) {
+      throw new RuntimeException(e);
+    }
+  }
+
+  private Map<String, Object> exIdToExampleMap;
+
+  private Example exIdToExample(String exId) {
+    if (exIdToExampleMap == null) {
+      exIdToExampleMap = new HashMap<>();
+      try {
+        for (String filename : opts.batchDatasets) {
+          BufferedReader reader = IOUtils.openIn(filename);
+          String line;
+          while ((line = reader.readLine()) != null) {
+            LispTree tree = LispTree.proto.parseFromString(line);
+            if (!"id".equals(tree.child(1).child(0).value))
+              throw new RuntimeException("Malformed example: " + line);
+            exIdToExampleMap.put(tree.child(1).child(1).value, tree);
+          }
+        }
+      } catch (IOException e) {
+        throw new RuntimeException(e);
+      }
+    }
+    Object obj = exIdToExampleMap.get(exId);
+    if (obj == null) return null;
+    Example ex;
+    if (obj instanceof LispTree) {
+      ex = Example.fromLispTree((LispTree) obj, exId);
+      ex.preprocess();
+      exIdToExampleMap.put(exId, ex);
+    } else {
+      ex = (Example) obj;
+    }
+    return ex;
+  }
+
+  ListValue addOriginalStrings(ListValue answers, TableKnowledgeGraph graph) {
+    List<Value> values = new ArrayList<>();
+    for (Value value : answers.values) {
+      if (value instanceof NameValue) {
+        NameValue name = (NameValue) value;
+        if (name.description == null)
+          value = new NameValue(name.id, graph.getOriginalString(((NameValue) value).id));
+      }
+      values.add(value);
+    }
+    return new ListValue(values);
+  }
+
+}