load data

word_vector/word_to_vec.py

@@ -32,10 +32,14 @@ def w2v_train(f_name, model_output_name):
 if __name__ == "__main__":
     begin_time = time.time()
 
-    w2v_train("dispose_problem.txt", "w2v_model")
+    model_output_name = "w2v_model"
+    # w2v_train("dispose_problem.txt", model_output_name)
 
-    # input_file = os.path.join(data_dir, "dispose_problem.txt")
-    # for line in open(input_file, "r"):
-    #     print(line)
+    model_path = os.path.join(model_dir, model_output_name)
+
+    w2v_model = word2vec.Word2Vec.load(model_path)
+
+    for i in ["双眼皮", "隆鼻"]:
+        print(w2v_model.wv.most_similar(i))
 
     print("total cost: {:.2f}mins".format((time.time() - begin_time) / 60))