Beispiel #1
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 def setUp(self):
     self.corpus = mmcorpus.MmCorpus(datapath('testcorpus.mm'))
     # Choose doc to be normalized. [3] chosen to demonstrate different results for l1 and l2 norm.
     # doc is [(1, 1.0), (5, 2.0), (8, 1.0)]
     self.doc = list(self.corpus)[3]
     self.model_l1 = normmodel.NormModel(self.corpus, norm='l1')
     self.model_l2 = normmodel.NormModel(self.corpus, norm='l2')
Beispiel #2
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 def testPersistenceCompressed(self):
     fname = testfile() + '.gz'
     model = normmodel.NormModel(self.corpus)
     model.save(fname)
     model2 = normmodel.NormModel.load(fname, mmap=None)
     self.assertTrue(model.norms == model2.norms)
     tstvec = []
     self.assertTrue(np.allclose(model.normalize(tstvec), model2.normalize(tstvec)))  # try projecting an empty vector
 def testPersistence(self):
     fname = get_tmpfile('gensim_models.tst')
     model = normmodel.NormModel(self.corpus)
     model.save(fname)
     model2 = normmodel.NormModel.load(fname)
     self.assertTrue(model.norms == model2.norms)
     tstvec = []
     # try projecting an empty vector
     self.assertTrue(np.allclose(model.normalize(tstvec), model2.normalize(tstvec)))
Beispiel #4
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 def testPersistence(self):
     fname = testfile()
     model = normmodel.NormModel(self.corpus)
     model.save(fname)
     model2 = normmodel.NormModel.load(fname)
     self.assertTrue(model.norms == model2.norms)
     tstvec = []
     self.assertTrue(
         numpy.allclose(
             model.normalize(tstvec),
             model2.normalize(tstvec)))  # try projecting an empty vector