lstm_intent_network.py 文件源码

def __init__(self, nlp, expressions):
        self.nlp = nlp
        self.all_expressions = expressions
        self.num_features = nlp.vocab.vectors_length
        self.categories = list(set([expression.intent().name for expression in expressions]))

        intents = [expression.intent().name for expression in expressions]
        intents_indices = [self.categories.index(intent) for intent in intents]

        self.x = np.zeros(shape=(len(expressions), DOCUMENT_MAX_NUM_WORDS, self.num_features)).astype('float32')
        self.__init_x(self.x, expressions)

        self.y = np_utils.to_categorical(intents_indices)

        self.model = Sequential()
        self.model.add(Bidirectional(LSTM(int(DOCUMENT_MAX_NUM_WORDS * 1.5)),
                                     input_shape=(DOCUMENT_MAX_NUM_WORDS, self.num_features)))
        self.model.add(Dropout(0.3))
        self.model.add(Dense(len(self.categories), activation='sigmoid'))
        self.model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])