[WIP] Fix backward incompatibility due to random_state

gensim/models/ldamodel.py

@@ -1023,9 +1023,9 @@ def save(self, fname, ignore=['state', 'dispatcher'], separately=None, *args, **
         separately_explicit = ['expElogbeta', 'sstats']
         # Also add 'alpha' and 'eta' to separately list if they are set 'auto' or some
         # array manually.
-        if (isinstance(self.alpha, six.string_types) and self.alpha == 'auto') or len(self.alpha.shape) != 1:
+        if (isinstance(self.alpha, six.string_types) and self.alpha == 'auto') or (isinstance(self.alpha, np.ndarray) and len(self.alpha.shape) != 1):
             separately_explicit.append('alpha')
-        if (isinstance(self.eta, six.string_types) and self.eta == 'auto') or len(self.eta.shape) != 1:
+        if (isinstance(self.eta, six.string_types) and self.eta == 'auto') or (isinstance(self.eta, np.ndarray) and len(self.eta.shape) != 1):
             separately_explicit.append('eta')
         # Merge separately_explicit with separately.
         if separately:
@@ -1049,6 +1049,9 @@ def load(cls, fname, *args, **kwargs):
         """
         kwargs['mmap'] = kwargs.get('mmap', None)
         result = super(LdaModel, cls).load(fname, *args, **kwargs)
+        if not hasattr(result, 'random_state'):
+            result.random_state = utils.get_random_state(None)
+            logging.warning("random_state not set so using default value")
         state_fname = utils.smart_extension(fname, '.state')
         try:
             result.state = super(LdaModel, cls).load(state_fname, *args, **kwargs)
@@ -1060,7 +1063,5 @@ def load(cls, fname, *args, **kwargs):
                 result.id2word = utils.unpickle(id2word_fname)
             except Exception as e:
                 logging.warning("failed to load id2word dictionary from %s: %s", id2word_fname, e)
-        else:
-            result.id2word = None
         return result
 # endclass LdaModel

gensim/test/test_ldamodel.py

@@ -46,7 +46,7 @@
 
 def testfile(test_fname=''):
     # temporary data will be stored to this file
-    fname = 'gensim_models_' + test_fname + '.tst' 
+    fname = 'gensim_models_' + test_fname + '.tst'
     return os.path.join(tempfile.gettempdir(), fname)
 
 
@@ -247,9 +247,9 @@ def testGetDocumentTopics(self):
 
         #Test case to use the get_document_topic function for the corpus
         all_topics = model.get_document_topics(self.corpus, per_word_topics=True)
-        
+
         self.assertEqual(model.state.numdocs, len(corpus))
-        
+
         for topic in all_topics:
             self.assertTrue(isinstance(topic, tuple))
             for k, v in topic[0]: # list of doc_topics
@@ -269,9 +269,9 @@ def testGetDocumentTopics(self):
         word_phi_count_na = 0
 
         all_topics = model.get_document_topics(self.corpus, minimum_probability=0.8, minimum_phi_value=1.0, per_word_topics=True)
-        
+
         self.assertEqual(model.state.numdocs, len(corpus))
-        
+
         for topic in all_topics:
             self.assertTrue(isinstance(topic, tuple))
             for k, v in topic[0]: # list of doc_topics
@@ -470,6 +470,31 @@ def testLargeMmapCompressed(self):
         # test loading the large model arrays with mmap
         self.assertRaises(IOError, self.class_.load, fname, mmap='r')
 
+    def testRandomStateBackwardCompatibility(self):
+        # load a model saved using a pre-0.13.2 version of Gensim
+        pre_0_13_2_fname = datapath('pre_0_13_2_model')
+        model_pre_0_13_2 = self.class_.load(pre_0_13_2_fname)
+
+        # set `num_topics` less than `model_pre_0_13_2.num_topics` so that `model_pre_0_13_2.random_state` is used
+        model_topics = model_pre_0_13_2.print_topics(num_topics=2, num_words=3)
+
+        for i in model_topics:
+            self.assertTrue(isinstance(i[0], int))
+            self.assertTrue(isinstance(i[1], six.string_types))
+
+        # save back the loaded model using a post-0.13.2 version of Gensim
+        post_0_13_2_fname = datapath('post_0_13_2_model')
+        model_pre_0_13_2.save(post_0_13_2_fname)
+
+        # load a model saved using a post-0.13.2 version of Gensim
+        model_post_0_13_2 = self.class_.load(post_0_13_2_fname)
+        model_topics_new = model_post_0_13_2.print_topics(num_topics=2, num_words=3)
+
+        for i in model_topics_new:
+            self.assertTrue(isinstance(i[0], int))
+            self.assertTrue(isinstance(i[1], six.string_types))
+
+
 #endclass TestLdaModel