renaming to DCA

shrdlurn/README.md

@@ -1,15 +1,28 @@
+# Readme
 
-## Basics
+## Running an experiment
 
 1) Start the server
-    ./interactive/run @mode=voxlurn -Server.port 8410
-    ./interactive/run @mode=voxlurn -Server.port 8410
-2) Blast the server with simulator on previous logs, under sandbox mode, to get the server into state
-3) Collect and append to more logs
-4) For any particular experiment, save the previous log
+    ./interactive/run @mode=voxelurn -Server.port 8410
+2) last the server with previous logs to get the server into state
+    ./interactive/run @mode=simulator @server=local @sandbox=none @task=freebig
+2) Run analysis script to get results
+    ./interactive/run @mode=analyze -execNumber 1
+0) (Optional) clean up
     ./interactive/run @mode=backup # save previous data logs
     ./interactive/run @mode=trash # deletes previous data logs
 
 ## Tests
-    ./shrdlurn/run @mode=test
-    ./shrdlurn/run @mode=test @class=ActionExecutorTest -verbose 5
+
+There are many units for interactive learning
+    ./interactive/run @mode=test
+    ./interactive/run @mode=test @class=DACExecutorTest -verbose 5
+
+## Running the server for voxelurn
+
+1) Start the sempre server
+    ./interactive/run @mode=voxelurn -Server.port 8410
+1) Start the client server
+    ./interactive/run @mode=community
+2) (optionallly) Blast the server with previous logs to get the server into state
+    ./interactive/run @mode=simulator @server=local @sandbox=none @task=freebig

shrdlurn/analyze_definitions.ipynb

@@ -16,12 +16,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 61,
    "metadata": {
     "collapsed": false,
     "scrolled": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "682\n",
+      "log.file\tstate/execs/682.exec/log\n",
+      "Simulator.reqParams\tgrammar=1&cite=1&learn=1&logging=0\n",
+      "Simulator.logFiles\t./shrdlurn/queries/freebuildbig-0206.def.json.gz\n",
+      "2495 lines in plotInfo\n",
+      "[u'java.util.concurrent.TimeoutException', u'java.util.concurrent.TimeoutException', u'java.util.concurrent.TimeoutException', u'java.util.concurrent.TimeoutException', u'java.util.concurrent.TimeoutException']\n",
+      "errors:69, stats.uncaught_error:5\n",
+      "{u'stats.head_len': 14, u'remote': u'188.0.26.146', u'format': u'lisp2json', u'stats.num_body': 7, u'stats.json_len': 979, u'q': u'(:def_iso \"add red ring 5\" \"[[\\\\\"repeat 2 [select left]\\\\\",\\\\\"(:loop (number 2) (: select (call adj left)))\\\\\"],[\\\\\"repeat 2 [select front]\\\\\",\\\\\"(:loop (number 2) (: select (call adj front)))\\\\\"],[\\\\\"repeat 5 [add red; select right]; select left\\\\\",\\\\\"(:s (:loop (number 5) (:s (: add red here) (: select (call adj right)))) (: select (call adj left)))\\\\\"],[\\\\\"select back; repeat 4 [add red; select back]; select left; select front\\\\\",\\\\\"(:s (:s (:s (: select (call adj back)) (:loop (number 4) (:s (: add red here) (: select (call adj back))))) (: select (call adj left))) (: select (call adj front)))\\\\\"],[\\\\\"repeat 4 [add red; select left]; select right\\\\\",\\\\\"(:s (:loop (number 4) (:s (: add red here) (: select (call adj left)))) (: select (call adj right)))\\\\\"],[\\\\\"select front; repeat 3 [add red; select front]\\\\\",\\\\\"(:s (: select (call adj front)) (:loop (number 3) (:s (: add red here) (: select (call adj front)))))\\\\\"],[\\\\\"repeat 2 [select back; select right]\\\\\",\\\\\"(:loop (number 2) (:s (: select (call adj back)) (: select (call adj right))))\\\\\"]]\")', u'sessionId': u'MT_AIWEXPJAU66D9', u'queryCount': 1, u'stats.num_rules': 2, u'stats.num_failed': 0, u'time': u'2017-02-03T03:26:45.640', u'stats.time': 0.177893299, u'stats.type': u'def'}\n",
+      "{'total_rules': 2880, 'total_failed': 819, 'total_def_queries': 2421, 'total_body': 15577}\n",
+      "failpercent: 0.0526\n"
+     ]
+    }
+   ],
    "source": [
     "import csv\n",
     "import numpy as np\n",

shrdlurn/run

@@ -153,12 +153,12 @@ addMode('voxelurn', 'interactive semantic parsing in a VoxelWorld', lambda { |e|
   #figOpts,
   o('interactiveLearning', true),
 
-  o('Executor', 'interactive.DASExecutor'),
-  o('LanguageAnalyzer', 'interactive.DASLanguageAnalyzer'),
-  o('DASExecutor.convertNumberValues', true),
-  o('DASExecutor.printStackTrace', true),
+  o('Executor', 'interactive.DCAExecutor'),
+  o('LanguageAnalyzer', 'interactive.DCALanguageAnalyzer'),
+  o('DCAExecutor.convertNumberValues', true),
+  o('DCAExecutor.printStackTrace', true),
   o('VoxelWorld.maxBlocks', 100000),
-  selo(0, 'DASExecutor.worldType', 'VoxelWorld', 'CalendarWorld', 'Otherworld'),
+  selo(0, 'DCAExecutor.worldType', 'VoxelWorld', 'CalendarWorld', 'Otherworld'),
   selo(0, 'Grammar.inPaths', './shrdlurn/voxelurn.grammar', './shrdlurn/calendar.grammar'),
 
   o('Params.initWeightsRandomly', false),
@@ -170,13 +170,13 @@ addMode('voxelurn', 'interactive semantic parsing in a VoxelWorld', lambda { |e|
   o('Parser.pruneErrorValues', true),
   o('Parser', 'BeamFloatingParser'),
   o('Parser.callSetEvaluation', false),
-  o('Parser.beamSize', 100),
+  o('Parser.beamSize', 25),
   o('ParserState.customExpectedCounts', 'None'),
 
   selo(0, 'BeamFloatingParser.floatStrategy', 'Never', 'NoParse', 'Always'),
   o('BeamFloatingParser.trackedCats', 'Number', 'Numbers', 'Color',  'Direction', 'Set', 'Sets', 'Action', 'Actions'),
 
-  o('BeamFloatingParser.maxNewTreesPerSpan', 1000),
+  o('BeamFloatingParser.maxNewTreesPerSpan', 100),
 
   o('Params.l1Reg', 'nonlazy'),
   o('Params.l1RegCoeff', 0.0001),
@@ -185,7 +185,7 @@ addMode('voxelurn', 'interactive semantic parsing in a VoxelWorld', lambda { |e|
   o('Params.adaptiveStepSize', true),
   #o('Params.stepSizeReduction', 0.25),
 
-  o('FeatureExtractor.featureComputers', 'interactive.DASFeatureComputer'),
+  o('FeatureExtractor.featureComputers', 'interactive.DCAFeatureComputer'),
   o('FeatureExtractor.featureDomains', ':rule', ':span', ':stats', ':scope', ':social', ':window'),
   # o('FeatureExtractor.featureDomains', ':rule'),
 

src/edu/stanford/nlp/sempre/interactive/DCAExecutor.java

@@ -23,7 +23,7 @@ import fig.basic.Option;
  * supports ActionFormula here, and does conversions of singleton sets
  * @author Sida Wang
  */
-public class DASExecutor extends Executor {
+public class DCAExecutor extends Executor {
   public static class Options {
     @Option(gloss = "Whether to convert NumberValue to int/double") public boolean convertNumberValues = true;
     @Option(gloss = "Whether to convert name values to string literal") public boolean convertNameValues = true;

src/edu/stanford/nlp/sempre/interactive/DCAFeatureComputer.java

@@ -15,7 +15,7 @@ import edu.stanford.nlp.sempre.*;
  * - control what categories to abstract out
  * - efficiency improvement, right now use all members of the cross product
  */
-public class DASFeatureComputer implements FeatureComputer {
+public class DCAFeatureComputer implements FeatureComputer {
   public static class Options {
     @Option(gloss = "Verbosity")
     public int verbose = 0;

src/edu/stanford/nlp/sempre/interactive/DCALanguageAnalyzer.java

@@ -10,7 +10,7 @@ import edu.stanford.nlp.sempre.LanguageInfo;
  *
  * @author sidaw
  */
-public class DASLanguageAnalyzer extends LanguageAnalyzer {
+public class DCALanguageAnalyzer extends LanguageAnalyzer {
   // Stanford tokenizer doesn't break hyphens.
   // Replace hypens with spaces for utterances like
   // "Spanish-speaking countries" but not for "2012-03-28".

src/edu/stanford/nlp/sempre/interactive/Definition.java

@@ -0,0 +1,9 @@
+package edu.stanford.nlp.sempre.interactive;
+import java.util.List;
+
+import edu.stanford.nlp.sempre.*;
+
+public class Definition {
+  public Definition(Example head, List<Derivation> chartList, List<Example> body) {
+  }
+}

src/edu/stanford/nlp/sempre/interactive/test/DASExecutorTest.java

@@ -13,7 +13,7 @@ import edu.stanford.nlp.sempre.Formulas;
 import edu.stanford.nlp.sempre.Json;
 import edu.stanford.nlp.sempre.NaiveKnowledgeGraph;
 import edu.stanford.nlp.sempre.StringValue;
-import edu.stanford.nlp.sempre.interactive.DASExecutor;
+import edu.stanford.nlp.sempre.interactive.DCAExecutor;
 import edu.stanford.nlp.sempre.interactive.Item;
 import edu.stanford.nlp.sempre.interactive.World;
 import edu.stanford.nlp.sempre.interactive.voxelurn.Color;
@@ -27,9 +27,9 @@ import fig.basic.LogInfo;
  */
 
 public class DASExecutorTest {
-  DASExecutor executor = new DASExecutor();
+  DCAExecutor executor = new DCAExecutor();
 
-  protected static void runFormula(DASExecutor executor, String formula, ContextValue context, Predicate<World> checker) {
+  protected static void runFormula(DCAExecutor executor, String formula, ContextValue context, Predicate<World> checker) {
     LogInfo.begin_track("formula: %s", formula);
     executor.opts.worldType = "VoxelWorld";
     Executor.Response response = executor.execute(Formulas.fromLispTree(LispTree.proto.parseFromString(formula)), context);

src/edu/stanford/nlp/sempre/interactive/test/FloatingParsingTest.java

@@ -8,7 +8,7 @@ import java.util.function.Predicate;
 import fig.basic.*;
 import edu.stanford.nlp.sempre.*;
 import edu.stanford.nlp.sempre.Parser.Spec;
-import edu.stanford.nlp.sempre.interactive.DASExecutor;
+import edu.stanford.nlp.sempre.interactive.DCAExecutor;
 
 import org.testng.Assert;
 import org.testng.annotations.Test;
@@ -50,15 +50,15 @@ public class FloatingParsingTest {
 
   private static Spec defaultSpec() {
     FloatingParser.opts.defaultIsFloating = true;
-    DASExecutor.opts.convertNumberValues  = true;
-    DASExecutor.opts.printStackTrace = true;
-    DASExecutor.opts.worldType = "VoxelWorld";
+    DCAExecutor.opts.convertNumberValues  = true;
+    DCAExecutor.opts.printStackTrace = true;
+    DCAExecutor.opts.worldType = "VoxelWorld";
     Grammar.opts.inPaths = Lists.newArrayList("./shrdlurn/voxelurn.grammar");
     Grammar.opts.useApplyFn = "interactive.ApplyFn";
     Grammar.opts.binarizeRules = false;
 
-    DASExecutor executor = new DASExecutor();
-    DASExecutor.opts.worldType = "BlocksWorld";
+    DCAExecutor executor = new DCAExecutor();
+    DCAExecutor.opts.worldType = "BlocksWorld";
     FeatureExtractor extractor = new FeatureExtractor(executor);
     FeatureExtractor.opts.featureDomains.add("rule");
     ValueEvaluator valueEvaluator = new ExactValueEvaluator();

src/edu/stanford/nlp/sempre/interactive/test/GrammarInducerTest.java

@@ -29,7 +29,7 @@ import edu.stanford.nlp.sempre.ParserState;
 import edu.stanford.nlp.sempre.Rule;
 import edu.stanford.nlp.sempre.Session;
 import edu.stanford.nlp.sempre.ValueEvaluator;
-import edu.stanford.nlp.sempre.interactive.DASExecutor;
+import edu.stanford.nlp.sempre.interactive.DCAExecutor;
 import edu.stanford.nlp.sempre.interactive.DefinitionAligner;
 import edu.stanford.nlp.sempre.interactive.GrammarInducer;
 import edu.stanford.nlp.sempre.interactive.ILUtils;
@@ -45,9 +45,9 @@ public class GrammarInducerTest {
 
   private static Spec defaultSpec() {
     FloatingParser.opts.defaultIsFloating = true;
-    DASExecutor.opts.convertNumberValues  = true;
-    DASExecutor.opts.printStackTrace = true;
-    DASExecutor.opts.worldType = "VoxelWorld";
+    DCAExecutor.opts.convertNumberValues  = true;
+    DCAExecutor.opts.printStackTrace = true;
+    DCAExecutor.opts.worldType = "VoxelWorld";
 
     Derivation.opts.showTypes = false;
     Derivation.opts.showRules = false;
@@ -66,7 +66,7 @@ public class GrammarInducerTest {
     GrammarInducer.opts.verbose = 2;
     InteractiveMaster.opts.useAligner = true;
 
-    DASExecutor executor = new DASExecutor();
+    DCAExecutor executor = new DCAExecutor();
 
     FeatureExtractor extractor = new FeatureExtractor(executor);