bert_intent_prediction_prediction.py

class Prediction():
    def __init__(self):
        self.model = model_obj.model
        
    def predict_validation(self):
        valid_sentences = load_data_obj.validation_data_frame["query"].tolist()
        valid_labels = load_data_obj.validation_data_frame["category"].tolist()

        preprocess_bert_data_obj = PreprocessingBertData()
        val_x = preprocess_bert_data_obj.prepare_data_x(valid_sentences)
        prediction_labels = list(self.model.predict(val_x).argmax(axis=-1))
        return valid_labels,prediction_labels
        
    
    def predict(self,query):
        query_seq = bert_model_obj.get_input_array([query])
        pred = self.model.predict(query_seq)
        pred = np.argmax(pred)
        result = load_data_obj.cat_to_intent[pred]
        return result
pred_obj = Prediction()
querylist = [['I want to see Medal for the General', 'SearchScreeningEvent', 1],
       ['Book a reservation for 5 people at the top-rated brasserie restaurant',
        'BookRestaurant', 5],
       ['Can I put this tune onto my sin estres playlist?',
        'AddToPlaylist', 6],
       ['add the artist Pete Murray to my relaxing playlist',
        'AddToPlaylist', 6],
       ['Book me a reservation for a party of 3 at a pub in Northern Mariana Islands',
        'BookRestaurant', 5]]
for query in querylist:
    result = pred_obj.predict(query[0])
    print("Predicted Intent: "+str(result)+"\tActual Intent: "+(load_data_obj.cat_to_intent[query[2]])+"\tQuery: "+str(query[0]))