glove2word2vec conversion script refactoring (#1247)

* merge read/write of py2 py3 and add tests

* correct str format

* added non-ascii characters to test_glove.txt

gensim/scripts/glove2word2vec.py

@@ -41,20 +41,12 @@ def glove2word2vec(glove_input_file, word2vec_output_file):
     """Convert `glove_input_file` in GloVe format into `word2vec_output_file in word2vec format."""
     num_lines, num_dims = get_glove_info(glove_input_file)
     logger.info("converting %i vectors from %s to %s", num_lines, glove_input_file, word2vec_output_file)
-    if sys.version_info < (3,):
-        with smart_open(word2vec_output_file, 'wb') as fout:
-            fout.write("%s %s\n" % (num_lines, num_dims))
-            with smart_open(glove_input_file, 'rb') as fin:
-                for line in fin:
-                    fout.write(line)
-        return num_lines, num_dims
-    else:
-        with smart_open(word2vec_output_file, 'w') as fout:
-            fout.write("%s %s\n" % (num_lines, num_dims))
-            with smart_open(glove_input_file, 'r') as fin:
-                for line in fin:
-                    fout.write(line)
-        return num_lines, num_dims
+    with smart_open(word2vec_output_file, 'wb') as fout:
+        fout.write("{0} {1}\n".format(num_lines, num_dims).encode('utf-8'))
+        with smart_open(glove_input_file, 'rb') as fin:
+            for line in fin:
+                fout.write(line)
+    return num_lines, num_dims
 
 
 if __name__ == "__main__":
@@ -80,27 +72,4 @@ def glove2word2vec(glove_input_file, word2vec_output_file):
     # do the actual conversion
     num_lines, num_dims = glove2word2vec(args.input, args.output)
     logger.info('Converted model with %i vectors and %i dimensions', num_lines, num_dims)
-    # test that the converted model loads successfully
-    model = gensim.models.KeyedVectors.load_word2vec_format(args.output, binary=False)
-    logger.info('Model %s successfully loaded', model)
-    try:
-        logger.info('testing the model....')
-        if sys.version_info < (3,):
-            with smart_open(args.output, 'rb') as f:
-                seed_word1, seed_word2 = random.sample([line.split()[0] for line in f], 2)
-        else:
-            with smart_open(args.output, 'r') as f:
-                seed_word1, seed_word2 = random.sample([line.split()[0] for line in f], 2)
-        logger.info('top-10 most similar words to "%s" are: %s', seed_word1, model.most_similar(positive=[seed_word1], topn=10))
-        logger.info('similarity score between %s and %s: %s', seed_word1, seed_word2, model.similarity(seed_word1, seed_word2))
-    except:
-        logger.error('error encountered. checking for model file creation now....')
-        if os.path.isfile(os.path.join(args.output)):
-            logger.info('model file %s was created but could not be loaded.', args.output)
-        else:
-            logger.info('model file %s creation failed. ')
-        logger.info('please check the parameters and input file format.')
-        raise
-
-    logger.info("finished running %s", program)
 

gensim/test/test_data/test_glove.txt

@@ -1,13 +1,13 @@
 the 0.418 0.24968 -0.41242 0.1217 0.34527 -0.044457 -0.49688 -0.17862 -0.00066023 -0.6566 0.27843 -0.14767 -0.55677 0.14658 -0.0095095 0.011658 0.10204 -0.12792 -0.8443 -0.12181 -0.016801 -0.33279 -0.1552 -0.23131 -0.19181 -1.8823 -0.76746 0.099051 -0.42125 -0.19526 4.0071 -0.18594 -0.52287 -0.31681 0.00059213 0.0074449 0.17778 -0.15897 0.012041 -0.054223 -0.29871 -0.15749 -0.34758 -0.045637 -0.44251 0.18785 0.0027849 -0.18411 -0.11514 -0.78581
-, 0.013441 0.23682 -0.16899 0.40951 0.63812 0.47709 -0.42852 -0.55641 -0.364 -0.23938 0.13001 -0.063734 -0.39575 -0.48162 0.23291 0.090201 -0.13324 0.078639 -0.41634 -0.15428 0.10068 0.48891 0.31226 -0.1252 -0.037512 -1.5179 0.12612 -0.02442 -0.042961 -0.28351 3.5416 -0.11956 -0.014533 -0.1499 0.21864 -0.33412 -0.13872 0.31806 0.70358 0.44858 -0.080262 0.63003 0.32111 -0.46765 0.22786 0.36034 -0.37818 -0.56657 0.044691 0.30392
-. 0.15164 0.30177 -0.16763 0.17684 0.31719 0.33973 -0.43478 -0.31086 -0.44999 -0.29486 0.16608 0.11963 -0.41328 -0.42353 0.59868 0.28825 -0.11547 -0.041848 -0.67989 -0.25063 0.18472 0.086876 0.46582 0.015035 0.043474 -1.4671 -0.30384 -0.023441 0.30589 -0.21785 3.746 0.0042284 -0.18436 -0.46209 0.098329 -0.11907 0.23919 0.1161 0.41705 0.056763 -6.3681e-05 0.068987 0.087939 -0.10285 -0.13931 0.22314 -0.080803 -0.35652 0.016413 0.10216
-of 0.70853 0.57088 -0.4716 0.18048 0.54449 0.72603 0.18157 -0.52393 0.10381 -0.17566 0.078852 -0.36216 -0.11829 -0.83336 0.11917 -0.16605 0.061555 -0.012719 -0.56623 0.013616 0.22851 -0.14396 -0.067549 -0.38157 -0.23698 -1.7037 -0.86692 -0.26704 -0.2589 0.1767 3.8676 -0.1613 -0.13273 -0.68881 0.18444 0.0052464 -0.33874 -0.078956 0.24185 0.36576 -0.34727 0.28483 0.075693 -0.062178 -0.38988 0.22902 -0.21617 -0.22562 -0.093918 -0.80375
-to 0.68047 -0.039263 0.30186 -0.17792 0.42962 0.032246 -0.41376 0.13228 -0.29847 -0.085253 0.17118 0.22419 -0.10046 -0.43653 0.33418 0.67846 0.057204 -0.34448 -0.42785 -0.43275 0.55963 0.10032 0.18677 -0.26854 0.037334 -2.0932 0.22171 -0.39868 0.20912 -0.55725 3.8826 0.47466 -0.95658 -0.37788 0.20869 -0.32752 0.12751 0.088359 0.16351 -0.21634 -0.094375 0.018324 0.21048 -0.03088 -0.19722 0.082279 -0.09434 -0.073297 -0.064699 -0.26044
+ö 0.013441 0.23682 -0.16899 0.40951 0.63812 0.47709 -0.42852 -0.55641 -0.364 -0.23938 0.13001 -0.063734 -0.39575 -0.48162 0.23291 0.090201 -0.13324 0.078639 -0.41634 -0.15428 0.10068 0.48891 0.31226 -0.1252 -0.037512 -1.5179 0.12612 -0.02442 -0.042961 -0.28351 3.5416 -0.11956 -0.014533 -0.1499 0.21864 -0.33412 -0.13872 0.31806 0.70358 0.44858 -0.080262 0.63003 0.32111 -0.46765 0.22786 0.36034 -0.37818 -0.56657 0.044691 0.30392
+é 0.15164 0.30177 -0.16763 0.17684 0.31719 0.33973 -0.43478 -0.31086 -0.44999 -0.29486 0.16608 0.11963 -0.41328 -0.42353 0.59868 0.28825 -0.11547 -0.041848 -0.67989 -0.25063 0.18472 0.086876 0.46582 0.015035 0.043474 -1.4671 -0.30384 -0.023441 0.30589 -0.21785 3.746 0.0042284 -0.18436 -0.46209 0.098329 -0.11907 0.23919 0.1161 0.41705 0.056763 -6.3681e-05 0.068987 0.087939 -0.10285 -0.13931 0.22314 -0.080803 -0.35652 0.016413 0.10216
+हु 0.70853 0.57088 -0.4716 0.18048 0.54449 0.72603 0.18157 -0.52393 0.10381 -0.17566 0.078852 -0.36216 -0.11829 -0.83336 0.11917 -0.16605 0.061555 -0.012719 -0.56623 0.013616 0.22851 -0.14396 -0.067549 -0.38157 -0.23698 -1.7037 -0.86692 -0.26704 -0.2589 0.1767 3.8676 -0.1613 -0.13273 -0.68881 0.18444 0.0052464 -0.33874 -0.078956 0.24185 0.36576 -0.34727 0.28483 0.075693 -0.062178 -0.38988 0.22902 -0.21617 -0.22562 -0.093918 -0.80375
+ü 0.68047 -0.039263 0.30186 -0.17792 0.42962 0.032246 -0.41376 0.13228 -0.29847 -0.085253 0.17118 0.22419 -0.10046 -0.43653 0.33418 0.67846 0.057204 -0.34448 -0.42785 -0.43275 0.55963 0.10032 0.18677 -0.26854 0.037334 -2.0932 0.22171 -0.39868 0.20912 -0.55725 3.8826 0.47466 -0.95658 -0.37788 0.20869 -0.32752 0.12751 0.088359 0.16351 -0.21634 -0.094375 0.018324 0.21048 -0.03088 -0.19722 0.082279 -0.09434 -0.073297 -0.064699 -0.26044
 and 0.26818 0.14346 -0.27877 0.016257 0.11384 0.69923 -0.51332 -0.47368 -0.33075 -0.13834 0.2702 0.30938 -0.45012 -0.4127 -0.09932 0.038085 0.029749 0.10076 -0.25058 -0.51818 0.34558 0.44922 0.48791 -0.080866 -0.10121 -1.3777 -0.10866 -0.23201 0.012839 -0.46508 3.8463 0.31362 0.13643 -0.52244 0.3302 0.33707 -0.35601 0.32431 0.12041 0.3512 -0.069043 0.36885 0.25168 -0.24517 0.25381 0.1367 -0.31178 -0.6321 -0.25028 -0.38097
-in 0.33042 0.24995 -0.60874 0.10923 0.036372 0.151 -0.55083 -0.074239 -0.092307 -0.32821 0.09598 -0.82269 -0.36717 -0.67009 0.42909 0.016496 -0.23573 0.12864 -1.0953 0.43334 0.57067 -0.1036 0.20422 0.078308 -0.42795 -1.7984 -0.27865 0.11954 -0.12689 0.031744 3.8631 -0.17786 -0.082434 -0.62698 0.26497 -0.057185 -0.073521 0.46103 0.30862 0.12498 -0.48609 -0.0080272 0.031184 -0.36576 -0.42699 0.42164 -0.11666 -0.50703 -0.027273 -0.53285
+हि 0.33042 0.24995 -0.60874 0.10923 0.036372 0.151 -0.55083 -0.074239 -0.092307 -0.32821 0.09598 -0.82269 -0.36717 -0.67009 0.42909 0.016496 -0.23573 0.12864 -1.0953 0.43334 0.57067 -0.1036 0.20422 0.078308 -0.42795 -1.7984 -0.27865 0.11954 -0.12689 0.031744 3.8631 -0.17786 -0.082434 -0.62698 0.26497 -0.057185 -0.073521 0.46103 0.30862 0.12498 -0.48609 -0.0080272 0.031184 -0.36576 -0.42699 0.42164 -0.11666 -0.50703 -0.027273 -0.53285
 a 0.21705 0.46515 -0.46757 0.10082 1.0135 0.74845 -0.53104 -0.26256 0.16812 0.13182 -0.24909 -0.44185 -0.21739 0.51004 0.13448 -0.43141 -0.03123 0.20674 -0.78138 -0.20148 -0.097401 0.16088 -0.61836 -0.18504 -0.12461 -2.2526 -0.22321 0.5043 0.32257 0.15313 3.9636 -0.71365 -0.67012 0.28388 0.21738 0.14433 0.25926 0.23434 0.4274 -0.44451 0.13813 0.36973 -0.64289 0.024142 -0.039315 -0.26037 0.12017 -0.043782 0.41013 0.1796
-" 0.25769 0.45629 -0.76974 -0.37679 0.59272 -0.063527 0.20545 -0.57385 -0.29009 -0.13662 0.32728 1.4719 -0.73681 -0.12036 0.71354 -0.46098 0.65248 0.48887 -0.51558 0.039951 -0.34307 -0.014087 0.86488 0.3546 0.7999 -1.4995 -1.8153 0.41128 0.23921 -0.43139 3.6623 -0.79834 -0.54538 0.16943 -0.82017 -0.3461 0.69495 -1.2256 -0.17992 -0.057474 0.030498 -0.39543 -0.38515 -1.0002 0.087599 -0.31009 -0.34677 -0.31438 0.75004 0.97065
-'s 0.23727 0.40478 -0.20547 0.58805 0.65533 0.32867 -0.81964 -0.23236 0.27428 0.24265 0.054992 0.16296 -1.2555 -0.086437 0.44536 0.096561 -0.16519 0.058378 -0.38598 0.086977 0.0033869 0.55095 -0.77697 -0.62096 0.092948 -2.5685 -0.67739 0.10151 -0.48643 -0.057805 3.1859 -0.017554 -0.16138 0.055486 -0.25885 -0.33938 -0.19928 0.26049 0.10478 -0.55934 -0.12342 0.65961 -0.51802 -0.82995 -0.082739 0.28155 -0.423 -0.27378 -0.007901 -0.030231
+या 0.25769 0.45629 -0.76974 -0.37679 0.59272 -0.063527 0.20545 -0.57385 -0.29009 -0.13662 0.32728 1.4719 -0.73681 -0.12036 0.71354 -0.46098 0.65248 0.48887 -0.51558 0.039951 -0.34307 -0.014087 0.86488 0.3546 0.7999 -1.4995 -1.8153 0.41128 0.23921 -0.43139 3.6623 -0.79834 -0.54538 0.16943 -0.82017 -0.3461 0.69495 -1.2256 -0.17992 -0.057474 0.030498 -0.39543 -0.38515 -1.0002 0.087599 -0.31009 -0.34677 -0.31438 0.75004 0.97065
+of 0.23727 0.40478 -0.20547 0.58805 0.65533 0.32867 -0.81964 -0.23236 0.27428 0.24265 0.054992 0.16296 -1.2555 -0.086437 0.44536 0.096561 -0.16519 0.058378 -0.38598 0.086977 0.0033869 0.55095 -0.77697 -0.62096 0.092948 -2.5685 -0.67739 0.10151 -0.48643 -0.057805 3.1859 -0.017554 -0.16138 0.055486 -0.25885 -0.33938 -0.19928 0.26049 0.10478 -0.55934 -0.12342 0.65961 -0.51802 -0.82995 -0.082739 0.28155 -0.423 -0.27378 -0.007901 -0.030231
 for 0.15272 0.36181 -0.22168 0.066051 0.13029 0.37075 -0.75874 -0.44722 0.22563 0.10208 0.054225 0.13494 -0.43052 -0.2134 0.56139 -0.21445 0.077974 0.10137 -0.51306 -0.40295 0.40639 0.23309 0.20696 -0.12668 -0.50634 -1.7131 0.077183 -0.39138 -0.10594 -0.23743 3.9552 0.66596 -0.61841 -0.3268 0.37021 0.25764 0.38977 0.27121 0.043024 -0.34322 0.020339 0.2142 0.044097 0.14003 -0.20079 0.074794 -0.36076 0.43382 -0.084617 0.1214
 - -0.16768 1.2151 0.49515 0.26836 -0.4585 -0.23311 -0.52822 -1.3557 0.16098 0.37691 -0.92702 -0.43904 -1.0634 1.028 0.0053943 0.04153 -0.018638 -0.55451 0.026166 0.28066 -0.66245 0.23435 0.2451 0.025668 -1.0869 -2.844 -0.51272 0.27286 0.0071502 0.033984 3.9084 0.52766 -0.66899 1.8238 0.43436 -0.30084 -0.26996 0.4394 0.69956 0.14885 0.029453 1.4888 0.52361 0.099354 1.2515 0.099381 -0.079261 -0.30862 0.30893 0.11023
 that 0.88387 -0.14199 0.13566 0.098682 0.51218 0.49138 -0.47155 -0.30742 0.01963 0.12686 0.073524 0.35836 -0.60874 -0.18676 0.78935 0.54534 0.1106 -0.2923 0.059041 -0.69551 -0.18804 0.19455 0.32269 -0.49981 0.306 -2.3902 -0.60749 0.37107 0.078912 -0.23896 3.839 -0.20355 -0.35613 -0.69185 -0.17497 -0.35323 0.10598 -0.039303 0.015701 0.038279 -0.35283 0.44882 -0.16534 0.31579 0.14963 -0.071277 -0.53506 0.52711 -0.20148 0.0095952

gensim/test/test_glove2word2vec.py

@@ -6,22 +6,42 @@
 
 """Test for gensim.scripts.glove2word2vec.py."""
 
+import logging
+import unittest
+import os
+import sys
+import tempfile
+
+import numpy
+import gensim
+
+from gensim.utils import check_output
+
+module_path = os.path.dirname(__file__) # needed because sample data files are located in the same folder
+datapath = lambda fname: os.path.join(module_path, 'test_data', fname)
+
+def testfile():
+    # temporary model will be stored to this file
+    return os.path.join(tempfile.gettempdir(), 'glove2word2vec.test')
+
+class TestGlove2Word2Vec(unittest.TestCase):
+    def setUp(self):
+        self.datapath = datapath('test_glove.txt')
+        self.output_file = testfile()
+
+    def testConversion(self):
+        output = check_output(args=['python', '-m', 'gensim.scripts.glove2word2vec', '--input', self.datapath, '--output', self.output_file])    
+        # test that the converted model loads successfully
+        try:
+            self.test_model = gensim.models.KeyedVectors.load_word2vec_format(self.output_file)
+            self.assertTrue(numpy.allclose(self.test_model.n_similarity(['the', 'and'], ['and', 'the']), 1.0))
+        except:
+            if os.path.isfile(os.path.join(self.output_file)):
+                self.fail('model file %s was created but could not be loaded.' % self.output_file)
+            else:
+                self.fail('model file %s creation failed, check the parameters and input file format.' % self.output_file)
+
+if __name__ == '__main__':
+    logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.DEBUG)
+    unittest.main()
 
-# import unittest
-# import os
-# import sys
-# import gensim
-# from gensim.utils import check_output
-
-# class TestGlove2Word2Vec(unittest.TestCase):
-#     def setUp(self):
-#         self.module_path = os.path.dirname(gensim.__file__)
-#         self.datapath = os.path.join(self.module_path, 'test', 'test_data', 'test_glove.txt')  # Sample data files are located in the same folder
-#         self.output_file = 'sample_word2vec_out.txt'
-
-#     def testConversion(self):
-#         output = check_output(['python', '-m', 'gensim.scripts.glove2word2vec', '-i', self.datapath, '-o', self.output_file])
-#         if sys.version_info < (3,):
-#             self.assertEqual(output, '')
-#         else:
-#             self.assertEqual(output, b'')