Esempio n. 1
0
        private SimpleMatrix ConcatenateContextWords(SimpleMatrix childVec, IntPair span, IList <string> words)
        {
            // TODO: factor out getting the words
            SimpleMatrix left  = (span.GetSource() < 0) ? dvModel.GetStartWordVector() : dvModel.GetWordVector(words[span.GetSource()]);
            SimpleMatrix right = (span.GetTarget() >= words.Count) ? dvModel.GetEndWordVector() : dvModel.GetWordVector(words[span.GetTarget()]);

            return(NeuralUtils.Concatenate(childVec, left, right));
        }
        public virtual void Evaluate(Tree guess, Tree gold, PrintWriter pw, double weight)
        {
            IList <ILabel> words = guess.Yield();
            int            pos   = 0;

            foreach (ILabel word in words)
            {
                ++pos;
                SimpleMatrix wv = model.GetWordVector(word.Value());
                // would be faster but more implementation-specific if we
                // removed wv.equals
                if (wv == unk || wv.Equals(unk))
                {
                    pw.Printf("  Unknown word in position %d: %s%n", pos, word.Value());
                    unkWords.Add(word.Value());
                }
            }
        }
        /// <exception cref="System.IO.IOException"/>
        public static void Main(string[] args)
        {
            string         modelPath          = null;
            string         outputPath         = null;
            string         inputPath          = null;
            string         testTreebankPath   = null;
            IFileFilter    testTreebankFilter = null;
            IList <string> unusedArgs         = Generics.NewArrayList();

            for (int argIndex = 0; argIndex < args.Length;)
            {
                if (Sharpen.Runtime.EqualsIgnoreCase(args[argIndex], "-model"))
                {
                    modelPath = args[argIndex + 1];
                    argIndex += 2;
                }
                else
                {
                    if (Sharpen.Runtime.EqualsIgnoreCase(args[argIndex], "-output"))
                    {
                        outputPath = args[argIndex + 1];
                        argIndex  += 2;
                    }
                    else
                    {
                        if (Sharpen.Runtime.EqualsIgnoreCase(args[argIndex], "-input"))
                        {
                            inputPath = args[argIndex + 1];
                            argIndex += 2;
                        }
                        else
                        {
                            if (Sharpen.Runtime.EqualsIgnoreCase(args[argIndex], "-testTreebank"))
                            {
                                Pair <string, IFileFilter> treebankDescription = ArgUtils.GetTreebankDescription(args, argIndex, "-testTreebank");
                                argIndex           = argIndex + ArgUtils.NumSubArgs(args, argIndex) + 1;
                                testTreebankPath   = treebankDescription.First();
                                testTreebankFilter = treebankDescription.Second();
                            }
                            else
                            {
                                unusedArgs.Add(args[argIndex++]);
                            }
                        }
                    }
                }
            }
            string[]          newArgs = Sharpen.Collections.ToArray(unusedArgs, new string[unusedArgs.Count]);
            LexicalizedParser parser  = ((LexicalizedParser)LexicalizedParser.LoadModel(modelPath, newArgs));
            DVModel           model   = DVParser.GetModelFromLexicalizedParser(parser);
            File outputFile           = new File(outputPath);

            FileSystem.CheckNotExistsOrFail(outputFile);
            FileSystem.MkdirOrFail(outputFile);
            int count = 0;

            if (inputPath != null)
            {
                Reader input = new BufferedReader(new FileReader(inputPath));
                DocumentPreprocessor processor = new DocumentPreprocessor(input);
                foreach (IList <IHasWord> sentence in processor)
                {
                    count++;
                    // index from 1
                    IParserQuery pq = parser.ParserQuery();
                    if (!(pq is RerankingParserQuery))
                    {
                        throw new ArgumentException("Expected a RerankingParserQuery");
                    }
                    RerankingParserQuery rpq = (RerankingParserQuery)pq;
                    if (!rpq.Parse(sentence))
                    {
                        throw new Exception("Unparsable sentence: " + sentence);
                    }
                    IRerankerQuery reranker = rpq.RerankerQuery();
                    if (!(reranker is DVModelReranker.Query))
                    {
                        throw new ArgumentException("Expected a DVModelReranker");
                    }
                    DeepTree deepTree = ((DVModelReranker.Query)reranker).GetDeepTrees()[0];
                    IdentityHashMap <Tree, SimpleMatrix> vectors = deepTree.GetVectors();
                    foreach (KeyValuePair <Tree, SimpleMatrix> entry in vectors)
                    {
                        log.Info(entry.Key + "   " + entry.Value);
                    }
                    FileWriter     fout = new FileWriter(outputPath + File.separator + "sentence" + count + ".txt");
                    BufferedWriter bout = new BufferedWriter(fout);
                    bout.Write(SentenceUtils.ListToString(sentence));
                    bout.NewLine();
                    bout.Write(deepTree.GetTree().ToString());
                    bout.NewLine();
                    foreach (IHasWord word in sentence)
                    {
                        OutputMatrix(bout, model.GetWordVector(word.Word()));
                    }
                    Tree rootTree = FindRootTree(vectors);
                    OutputTreeMatrices(bout, rootTree, vectors);
                    bout.Flush();
                    fout.Close();
                }
            }
        }