美购精排模型

mlp/train.py

@@ -149,14 +149,18 @@ def train(emb_columns, number_columns, oneHot_columns, inputs, train_dataset):
 
     # train the model
     print("train start...")
-    model.fit(train_dataset, epochs=3)
+    model.fit(train_dataset, epochs=20)
     print("train end...")
     print("train save...")
 
     model.save(model_file, include_optimizer=False, save_format='tf')
+    return model
 
 
 def evaluate(model,test_dataset):
+    if not model:
+        print("加载模型中")
+        model = tf.keras.models.load_model(model_file)
     # evaluate the model
     timestmp1 = int(round(time.time()))
     print("evaluate:")
@@ -216,14 +220,14 @@ if __name__ == '__main__':
 
     print("train start...")
     timestmp3 = int(round(time.time()))
-    model = train(emb_columns,number_columns,oneHot_columns,inputs,train_data)
+    # model = train(emb_columns,number_columns,oneHot_columns,inputs,train_data)
     timestmp4 = int(round(time.time()))
     print("train end...耗时h:{}".format((timestmp4 - timestmp3)/60/60))
 
-    evaluate(model,test_data)
+    evaluate(None,test_data)
 
 
-    predict(model_file,df_test)
+    predict(model_file,test_data)
 
     pass