Java Code Examples for org.datavec.nlp.tokenization.tokenizerfactory.TokenizerFactory#create()
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org.datavec.nlp.tokenization.tokenizerfactory.TokenizerFactory#create() .
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Example 1
Source File: Windows.java From DataVec with Apache License 2.0 | 5 votes |
/** * Constructs a list of window of size windowSize. * Note that padding for each window is created as well. * @param words the words to tokenize and construct windows from * @param tokenizerFactory tokenizer factory to use * @param windowSize the window size to generate * @return the list of windows for the tokenized string */ public static List<Window> windows(InputStream words, TokenizerFactory tokenizerFactory, int windowSize) { Tokenizer tokenizer = tokenizerFactory.create(words); List<String> list = new ArrayList<>(); while (tokenizer.hasMoreTokens()) list.add(tokenizer.nextToken()); if (list.isEmpty()) throw new IllegalStateException("No tokens found for windows"); return windows(list, windowSize); }
Example 2
Source File: Windows.java From DataVec with Apache License 2.0 | 5 votes |
/** * Constructs a list of window of size windowSize. * Note that padding for each window is created as well. * @param words the words to tokenize and construct windows from * @param tokenizerFactory tokenizer factory to use * @param windowSize the window size to generate * @return the list of windows for the tokenized string */ public static List<Window> windows(String words, TokenizerFactory tokenizerFactory, int windowSize) { Tokenizer tokenizer = tokenizerFactory.create(words); List<String> list = new ArrayList<>(); while (tokenizer.hasMoreTokens()) list.add(tokenizer.nextToken()); if (list.isEmpty()) throw new IllegalStateException("No tokens found for windows"); return windows(list, windowSize); }
Example 3
Source File: Windows.java From DataVec with Apache License 2.0 | 5 votes |
/** * Constructs a list of window of size windowSize. * Note that padding for each window is created as well. * @param words the words to tokenize and construct windows from * @param tokenizerFactory tokenizer factory to use * @return the list of windows for the tokenized string */ public static List<Window> windows(String words, TokenizerFactory tokenizerFactory) { Tokenizer tokenizer = tokenizerFactory.create(words); List<String> list = new ArrayList<>(); while (tokenizer.hasMoreTokens()) list.add(tokenizer.nextToken()); return windows(list, 5); }
Example 4
Source File: Windows.java From deeplearning4j with Apache License 2.0 | 5 votes |
/** * Constructs a list of window of size windowSize. * Note that padding for each window is created as well. * @param words the words to tokenize and construct windows from * @param tokenizerFactory tokenizer factory to use * @param windowSize the window size to generate * @return the list of windows for the tokenized string */ public static List<Window> windows(InputStream words, TokenizerFactory tokenizerFactory, int windowSize) { Tokenizer tokenizer = tokenizerFactory.create(words); List<String> list = new ArrayList<>(); while (tokenizer.hasMoreTokens()) list.add(tokenizer.nextToken()); if (list.isEmpty()) throw new IllegalStateException("No tokens found for windows"); return windows(list, windowSize); }
Example 5
Source File: Windows.java From deeplearning4j with Apache License 2.0 | 5 votes |
/** * Constructs a list of window of size windowSize. * Note that padding for each window is created as well. * @param words the words to tokenize and construct windows from * @param tokenizerFactory tokenizer factory to use * @param windowSize the window size to generate * @return the list of windows for the tokenized string */ public static List<Window> windows(String words, TokenizerFactory tokenizerFactory, int windowSize) { Tokenizer tokenizer = tokenizerFactory.create(words); List<String> list = new ArrayList<>(); while (tokenizer.hasMoreTokens()) list.add(tokenizer.nextToken()); if (list.isEmpty()) throw new IllegalStateException("No tokens found for windows"); return windows(list, windowSize); }
Example 6
Source File: Windows.java From deeplearning4j with Apache License 2.0 | 5 votes |
/** * Constructs a list of window of size windowSize. * Note that padding for each window is created as well. * @param words the words to tokenize and construct windows from * @param tokenizerFactory tokenizer factory to use * @return the list of windows for the tokenized string */ public static List<Window> windows(String words, TokenizerFactory tokenizerFactory) { Tokenizer tokenizer = tokenizerFactory.create(words); List<String> list = new ArrayList<>(); while (tokenizer.hasMoreTokens()) list.add(tokenizer.nextToken()); return windows(list, 5); }
Example 7
Source File: ContextLabelRetriever.java From deeplearning4j with Apache License 2.0 | 4 votes |
/** * Returns a stripped sentence with the indices of words * with certain kinds of labels. * * @param sentence the sentence to process * @return a pair of a post processed sentence * with labels stripped and the spans of * the labels */ public static Pair<String, MultiDimensionalMap<Integer, Integer, String>> stringWithLabels(String sentence, TokenizerFactory tokenizerFactory) { MultiDimensionalMap<Integer, Integer, String> map = MultiDimensionalMap.newHashBackedMap(); Tokenizer t = tokenizerFactory.create(sentence); List<String> currTokens = new ArrayList<>(); String currLabel = null; String endLabel = null; List<Pair<String, List<String>>> tokensWithSameLabel = new ArrayList<>(); while (t.hasMoreTokens()) { String token = t.nextToken(); if (token.matches(BEGIN_LABEL)) { currLabel = token; //no labels; add these as NONE and begin the new label if (!currTokens.isEmpty()) { tokensWithSameLabel.add(new Pair<>("NONE", (List<String>) new ArrayList<>(currTokens))); currTokens.clear(); } } else if (token.matches(END_LABEL)) { if (currLabel == null) throw new IllegalStateException("Found an ending label with no matching begin label"); endLabel = token; } else currTokens.add(token); if (currLabel != null && endLabel != null) { currLabel = currLabel.replaceAll("[<>/]", ""); endLabel = endLabel.replaceAll("[<>/]", ""); Preconditions.checkState(!currLabel.isEmpty(), "Current label is empty!"); Preconditions.checkState(!endLabel.isEmpty(), "End label is empty!"); Preconditions.checkState(currLabel.equals(endLabel), "Current label begin and end did not match for the parse. Was: %s ending with %s", currLabel, endLabel); tokensWithSameLabel.add(new Pair<>(currLabel, (List<String>) new ArrayList<>(currTokens))); currTokens.clear(); //clear out the tokens currLabel = null; endLabel = null; } } //no labels; add these as NONE and begin the new label if (!currTokens.isEmpty()) { tokensWithSameLabel.add(new Pair<>("none", (List<String>) new ArrayList<>(currTokens))); currTokens.clear(); } //now join the output StringBuilder strippedSentence = new StringBuilder(); for (Pair<String, List<String>> tokensWithLabel : tokensWithSameLabel) { String joinedSentence = StringUtils.join(tokensWithLabel.getSecond(), " "); //spaces between separate parts of the sentence if (!(strippedSentence.length() < 1)) strippedSentence.append(" "); strippedSentence.append(joinedSentence); int begin = strippedSentence.toString().indexOf(joinedSentence); int end = begin + joinedSentence.length(); map.put(begin, end, tokensWithLabel.getFirst()); } return new Pair<>(strippedSentence.toString(), map); }