Java Code Examples for org.deeplearning4j.models.embeddings.wordvectors.WordVectors#wordsNearest()
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org.deeplearning4j.models.embeddings.wordvectors.WordVectors#wordsNearest() .
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Example 1
Source File: Word2VecTests.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Test public void testLoadingWordVectors() throws Exception { String backend = Nd4j.getExecutioner().getEnvironmentInformation().getProperty("backend"); if(!isIntegrationTests() && "CUDA".equalsIgnoreCase(backend)) { skipUnlessIntegrationTests(); //AB 2020/02/06 Skip CUDA except for integration tests due to very slow test speed - > 5 minutes on Titan X } File modelFile = new File(pathToWriteto); if (!modelFile.exists()) { testRunWord2Vec(); } WordVectors wordVectors = WordVectorSerializer.loadTxtVectors(modelFile); Collection<String> lst = wordVectors.wordsNearest("day", 10); System.out.println(Arrays.toString(lst.toArray())); }
Example 2
Source File: WordVectorSerializerTest.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Test @Ignore public void testLoaderTextSmall() throws Exception { INDArray vec = Nd4j.create(new double[] {0.002001, 0.002210, -0.001915, -0.001639, 0.000683, 0.001511, 0.000470, 0.000106, -0.001802, 0.001109, -0.002178, 0.000625, -0.000376, -0.000479, -0.001658, -0.000941, 0.001290, 0.001513, 0.001485, 0.000799, 0.000772, -0.001901, -0.002048, 0.002485, 0.001901, 0.001545, -0.000302, 0.002008, -0.000247, 0.000367, -0.000075, -0.001492, 0.000656, -0.000669, -0.001913, 0.002377, 0.002190, -0.000548, -0.000113, 0.000255, -0.001819, -0.002004, 0.002277, 0.000032, -0.001291, -0.001521, -0.001538, 0.000848, 0.000101, 0.000666, -0.002107, -0.001904, -0.000065, 0.000572, 0.001275, -0.001585, 0.002040, 0.000463, 0.000560, -0.000304, 0.001493, -0.001144, -0.001049, 0.001079, -0.000377, 0.000515, 0.000902, -0.002044, -0.000992, 0.001457, 0.002116, 0.001966, -0.001523, -0.001054, -0.000455, 0.001001, -0.001894, 0.001499, 0.001394, -0.000799, -0.000776, -0.001119, 0.002114, 0.001956, -0.000590, 0.002107, 0.002410, 0.000908, 0.002491, -0.001556, -0.000766, -0.001054, -0.001454, 0.001407, 0.000790, 0.000212, -0.001097, 0.000762, 0.001530, 0.000097, 0.001140, -0.002476, 0.002157, 0.000240, -0.000916, -0.001042, -0.000374, -0.001468, -0.002185, -0.001419, 0.002139, -0.000885, -0.001340, 0.001159, -0.000852, 0.002378, -0.000802, -0.002294, 0.001358, -0.000037, -0.001744, 0.000488, 0.000721, -0.000241, 0.000912, -0.001979, 0.000441, 0.000908, -0.001505, 0.000071, -0.000030, -0.001200, -0.001416, -0.002347, 0.000011, 0.000076, 0.000005, -0.001967, -0.002481, -0.002373, -0.002163, -0.000274, 0.000696, 0.000592, -0.001591, 0.002499, -0.001006, -0.000637, -0.000702, 0.002366, -0.001882, 0.000581, -0.000668, 0.001594, 0.000020, 0.002135, -0.001410, -0.001303, -0.002096, -0.001833, -0.001600, -0.001557, 0.001222, -0.000933, 0.001340, 0.001845, 0.000678, 0.001475, 0.001238, 0.001170, -0.001775, -0.001717, -0.001828, -0.000066, 0.002065, -0.001368, -0.001530, -0.002098, 0.001653, -0.002089, -0.000290, 0.001089, -0.002309, -0.002239, 0.000721, 0.001762, 0.002132, 0.001073, 0.001581, -0.001564, -0.001820, 0.001987, -0.001382, 0.000877, 0.000287, 0.000895, -0.000591, 0.000099, -0.000843, -0.000563}); String w1 = "database"; String w2 = "DBMS"; WordVectors vecModel = WordVectorSerializer.readWord2VecModel(new ClassPathResource("word2vec/googleload/sample_vec.txt").getFile()); WordVectors vectorsBinary = WordVectorSerializer.readWord2VecModel(new ClassPathResource("word2vec/googleload/sample_vec.bin").getFile()); INDArray textWeights = vecModel.lookupTable().getWeights(); INDArray binaryWeights = vectorsBinary.lookupTable().getWeights(); Collection<String> nearest = vecModel.wordsNearest("database", 10); Collection<String> nearestBinary = vectorsBinary.wordsNearest("database", 10); System.out.println(nearestBinary); assertEquals(vecModel.similarity("DBMS", "DBMS's"), vectorsBinary.similarity("DBMS", "DBMS's"), 1e-1); }
Example 3
Source File: Word2VecTest.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Test @Ignore public void testPortugeseW2V() throws Exception { WordVectors word2Vec = WordVectorSerializer.loadTxtVectors(new File("/ext/Temp/para.txt")); word2Vec.setModelUtils(new FlatModelUtils()); Collection<String> portu = word2Vec.wordsNearest("carro", 10); printWords("carro", portu, word2Vec); portu = word2Vec.wordsNearest("davi", 10); printWords("davi", portu, word2Vec); }