Java Code Examples for org.deeplearning4j.text.tokenization.tokenizerfactory.TokenizerFactory#create()
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org.deeplearning4j.text.tokenization.tokenizerfactory.TokenizerFactory#create() .
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Example 1
Source File: JapaneseTokenizerTest.java From deeplearning4j with Apache License 2.0 | 6 votes |
@Test public void testGetTokens() throws Exception { TokenizerFactory tf = new JapaneseTokenizerFactory(); Tokenizer tokenizer = tf.create(toTokenize); // Exhaust iterator. assertEquals(expect.length, tokenizer.countTokens()); for (int i = 0; i < tokenizer.countTokens(); ++i) { assertEquals(tokenizer.nextToken(), expect[i]); } // Ensure exhausted. assertEquals(false, tokenizer.hasMoreTokens()); // Count doesn't change. assertEquals(expect.length, tokenizer.countTokens()); // getTokens still returns everything. List<String> tokens = tokenizer.getTokens(); assertEquals(expect.length, tokens.size()); }
Example 2
Source File: Windows.java From deeplearning4j with Apache License 2.0 | 6 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, @NonNull TokenizerFactory tokenizerFactory, int windowSize, WordVectors vectors) { Tokenizer tokenizer = tokenizerFactory.create(words); List<String> list = new ArrayList<>(); while (tokenizer.hasMoreTokens()) { String token = tokenizer.nextToken(); // if we don't have UNK word defined - we have to skip this word if (vectors.getWordVectorMatrix(token) != null) list.add(token); } if (list.isEmpty()) throw new IllegalStateException("No tokens found for windows"); return windows(list, windowSize); }
Example 3
Source File: BertWordPieceTokenizerTests.java From deeplearning4j with Apache License 2.0 | 6 votes |
@Test @Ignore("AB 2019/05/24 - Disabled until dev branch merged - see issue #7657") public void testBertWordPieceTokenizer5() throws Exception { // Longest Token in Vocab is 22 chars long, so make sure splits on the edge are properly handled String toTokenize = "Donaudampfschifffahrts Kapitänsmützeninnenfuttersaum"; TokenizerFactory t = new BertWordPieceTokenizerFactory(pathToVocab, false, false, c); Tokenizer tokenizer = t.create(toTokenize); Tokenizer tokenizer2 = t.create(new ByteArrayInputStream(toTokenize.getBytes())); final List<String> expected = Arrays.asList("Donau", "##dam", "##pf", "##schiff", "##fahrt", "##s", "Kapitän", "##sm", "##ützen", "##innen", "##fu", "##tter", "##sa", "##um"); assertEquals(expected, tokenizer.getTokens()); assertEquals(expected, tokenizer2.getTokens()); String s2 = BertWordPiecePreProcessor.reconstructFromTokens(tokenizer.getTokens()); assertEquals(toTokenize, s2); }
Example 4
Source File: DefaultDocumentIteratorTest.java From deeplearning4j with Apache License 2.0 | 6 votes |
@Test public void testDocumentIterator() throws Exception { ClassPathResource reuters5250 = new ClassPathResource("/reuters/5250"); File f = reuters5250.getFile(); DocumentIterator iter = new FileDocumentIterator(f.getAbsolutePath()); InputStream doc = iter.nextDocument(); TokenizerFactory t = new DefaultTokenizerFactory(); Tokenizer next = t.create(doc); String[] list = "PEARSON CONCENTRATES ON FOUR SECTORS".split(" "); ///PEARSON CONCENTRATES ON FOUR SECTORS int count = 0; while (next.hasMoreTokens() && count < list.length) { String token = next.nextToken(); assertEquals(list[count++], token); } doc.close(); }
Example 5
Source File: DefaulTokenizerTests.java From deeplearning4j with Apache License 2.0 | 6 votes |
@Test public void testDefaultTokenizer1() throws Exception { String toTokenize = "Mary had a little lamb."; TokenizerFactory t = new DefaultTokenizerFactory(); Tokenizer tokenizer = t.create(toTokenize); Tokenizer tokenizer2 = t.create(new ByteArrayInputStream(toTokenize.getBytes())); int position = 1; while (tokenizer2.hasMoreTokens()) { String tok1 = tokenizer.nextToken(); String tok2 = tokenizer2.nextToken(); log.info("Position: [" + position + "], token1: '" + tok1 + "', token 2: '" + tok2 + "'"); position++; assertEquals(tok1, tok2); } ClassPathResource resource = new ClassPathResource("reuters/5250"); String str = FileUtils.readFileToString(resource.getFile()); int stringCount = t.create(str).countTokens(); int stringCount2 = t.create(resource.getInputStream()).countTokens(); assertTrue(Math.abs(stringCount - stringCount2) < 2); }
Example 6
Source File: DefaulTokenizerTests.java From deeplearning4j with Apache License 2.0 | 6 votes |
@Test public void testDefaultTokenizer2() throws Exception { String toTokenize = "Mary had a little lamb."; TokenizerFactory t = new DefaultTokenizerFactory(); Tokenizer tokenizer = t.create(toTokenize); Tokenizer tokenizer2 = t.create(new ByteArrayInputStream(toTokenize.getBytes())); tokenizer2.countTokens(); while (tokenizer.hasMoreTokens()) { String tok1 = tokenizer.nextToken(); String tok2 = tokenizer2.nextToken(); assertEquals(tok1, tok2); } System.out.println("-----------------------------------------------"); ClassPathResource resource = new ClassPathResource("reuters/5250"); String str = FileUtils.readFileToString(resource.getFile()); int stringCount = t.create(str).countTokens(); int stringCount2 = t.create(resource.getInputStream()).countTokens(); log.info("String tok: [" + stringCount + "], Stream tok: [" + stringCount2 + "], Difference: " + Math.abs(stringCount - stringCount2)); assertTrue(Math.abs(stringCount - stringCount2) < 2); }
Example 7
Source File: DefaulTokenizerTests.java From deeplearning4j with Apache License 2.0 | 6 votes |
@Test public void testDefaultStreamTokenizer() throws Exception { String toTokenize = "Mary had a little lamb."; TokenizerFactory t = new DefaultTokenizerFactory(); Tokenizer tokenizer2 = t.create(new ByteArrayInputStream(toTokenize.getBytes())); assertEquals(5, tokenizer2.countTokens()); int cnt = 0; while (tokenizer2.hasMoreTokens()) { String tok1 = tokenizer2.nextToken(); log.info(tok1); cnt++; } assertEquals(5, cnt); }
Example 8
Source File: BertWordPieceTokenizerTests.java From deeplearning4j with Apache License 2.0 | 6 votes |
@Test public void testBertWordPieceTokenizer1() throws Exception { String toTokenize = "I saw a girl with a telescope."; TokenizerFactory t = new BertWordPieceTokenizerFactory(pathToVocab, false, false, c); Tokenizer tokenizer = t.create(toTokenize); Tokenizer tokenizer2 = t.create(new ByteArrayInputStream(toTokenize.getBytes())); int position = 1; while (tokenizer2.hasMoreTokens()) { String tok1 = tokenizer.nextToken(); String tok2 = tokenizer2.nextToken(); log.info("Position: [" + position + "], token1: '" + tok1 + "', token 2: '" + tok2 + "'"); position++; assertEquals(tok1, tok2); String s2 = BertWordPiecePreProcessor.reconstructFromTokens(tokenizer.getTokens()); assertEquals(toTokenize, s2); } }
Example 9
Source File: DefaulTokenizerTests.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Test public void testDefaultTokenizer3() throws Exception { String toTokenize = "Mary had a little lamb."; TokenizerFactory t = new DefaultTokenizerFactory(); Tokenizer tokenizer = t.create(toTokenize); Tokenizer tokenizer2 = t.create(new ByteArrayInputStream(toTokenize.getBytes())); int position = 1; while (tokenizer2.hasMoreTokens()) { String tok1 = tokenizer.nextToken(); String tok2 = tokenizer2.nextToken(); log.info("Position: [" + position + "], token1: '" + tok1 + "', token 2: '" + tok2 + "'"); position++; assertEquals(tok1, tok2); } }
Example 10
Source File: JapaneseTokenizerTest.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Test public void testBaseForm() throws Exception { TokenizerFactory tf = new JapaneseTokenizerFactory(true); Tokenizer tokenizer1 = tf.create(toTokenize); Tokenizer tokenizer2 = tf.create(baseString); assertEquals("黒い", tokenizer1.nextToken()); assertEquals("驚く", tokenizer2.nextToken()); }
Example 11
Source File: JapaneseTokenizerTest.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Test public void testJapaneseTokenizer() throws Exception { TokenizerFactory t = new JapaneseTokenizerFactory(); Tokenizer tokenizer = t.create(toTokenize); assertEquals(expect.length, tokenizer.countTokens()); for (int i = 0; i < tokenizer.countTokens(); ++i) { assertEquals(tokenizer.nextToken(), expect[i]); } }
Example 12
Source File: BertWordPieceTokenizerTests.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Test public void testBertWordPieceTokenizer4() throws Exception { String toTokenize = "I saw a girl with a telescope."; TokenizerFactory t = new BertWordPieceTokenizerFactory(pathToVocab, false, false, c); Tokenizer tokenizer = t.create(toTokenize); Tokenizer tokenizer2 = t.create(new ByteArrayInputStream(toTokenize.getBytes())); final List<String> expected = Arrays.asList("I", "saw", "a", "girl", "with", "a", "tele", "##scope", "."); assertEquals(expected, tokenizer.getTokens()); assertEquals(expected, tokenizer2.getTokens()); String s2 = BertWordPiecePreProcessor.reconstructFromTokens(tokenizer.getTokens()); assertEquals(toTokenize, s2); }
Example 13
Source File: BertWordPieceTokenizerTests.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Test public void testBertWordPieceTokenizer3() throws Exception { String toTokenize = "Donaudampfschifffahrtskapitänsmützeninnenfuttersaum"; TokenizerFactory t = new BertWordPieceTokenizerFactory(pathToVocab, false, false, c); Tokenizer tokenizer = t.create(toTokenize); Tokenizer tokenizer2 = t.create(new ByteArrayInputStream(toTokenize.getBytes())); final List<String> expected = Arrays.asList("Donau", "##dam", "##pf", "##schiff", "##fahrt", "##skap", "##itä", "##ns", "##m", "##ützen", "##innen", "##fu", "##tter", "##sa", "##um"); assertEquals(expected, tokenizer.getTokens()); assertEquals(expected, tokenizer2.getTokens()); String s2 = BertWordPiecePreProcessor.reconstructFromTokens(tokenizer.getTokens()); assertEquals(toTokenize, s2); }
Example 14
Source File: KoreanTokenizerTest.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Test public void testKoreanTokenizer() throws Exception { String toTokenize = "세계 최초의 상용 수준 오픈소스 딥러닝 라이브러리입니다"; TokenizerFactory t = new KoreanTokenizerFactory(); Tokenizer tokenizer = t.create(toTokenize); String[] expect = {"세계", "최초", "의", "상용", "수준", "오픈소스", "딥", "러닝", "라이브러리", "입니", "다"}; assertEquals(expect.length, tokenizer.countTokens()); for (int i = 0; i < tokenizer.countTokens(); ++i) { assertEquals(tokenizer.nextToken(), expect[i]); } }
Example 15
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 16
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 17
Source File: ChineseTokenizerTest.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Test public void testChineseTokenizer() { TokenizerFactory tokenizerFactory = new ChineseTokenizerFactory(); Tokenizer tokenizer = tokenizerFactory.create(toTokenize); assertEquals(expect.length, tokenizer.countTokens()); for (int i = 0; i < tokenizer.countTokens(); ++i) { assertEquals(tokenizer.nextToken(), expect[i]); } }
Example 18
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)) { if (endLabel != null) throw new IllegalStateException( "Tried parsing sentence; found an end label when the begin label has not been cleared"); 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); }