@@ -101,14 +101,14 @@ def fit(self, G):
101101 # Adjacency matrix
102102 walks_t = time .time ()
103103 if self .verbose :
104- print ("Making walks..." , end = " " )
104+ print ("Making walks..." , end = " " , flush = True )
105105 self .walks = G .random_walks (walklen = self .walklen ,
106106 epochs = self .epochs ,
107107 return_weight = self .return_weight ,
108108 neighbor_weight = self .neighbor_weight )
109109 if self .verbose :
110110 print (f"Done, T={ time .time () - walks_t :.2f} " )
111- print ("Mapping Walk Names..." , end = " " )
111+ print ("Mapping Walk Names..." , end = " " , flush = True )
112112 map_t = time .time ()
113113 self .walks = pd .DataFrame (self .walks )
114114 # Map nodeId -> node name
@@ -120,7 +120,7 @@ def fit(self, G):
120120 self .walks = [list (x ) for x in self .walks .itertuples (False , None )]
121121 if self .verbose :
122122 print (f"Done, T={ time .time () - map_t :.2f} " )
123- print ("Training W2V..." , end = " " )
123+ print ("Training W2V..." , end = " " , flush = True )
124124 if gensim .models .word2vec .FAST_VERSION < 1 :
125125 print ("WARNING: gensim word2vec version is unoptimized"
126126 "Try version 3.6 if on windows, versions 3.7 "
@@ -179,4 +179,4 @@ def load_vectors(self, out_file):
179179 """
180180 Load embeddings from gensim.models.KeyedVectors format
181181 """
182- self .model = gensim .wv .load_word2vec_format (out_file )
182+ self .model = gensim .wv .load_word2vec_format (out_file )
0 commit comments