bilstm_crf.py

class BiLSTM_CRF(BiLSTM):
    def __init__(self, vocab_size, max_words, num_tags, embedding_size, model_file_path):
        super(BiLSTM_CRF, self).__init__(vocab_size, max_words, num_tags, embedding_size, model_file_path)
        
    def build_model(self):
        print "Building model..."
        input = Input(shape=(self.max_words,))
        embed = Embedding(input_dim=self.vocab_size + 1, output_dim=self.embedding_size, input_length=self.max_words, mask_zero=True)(input)
        bilstm = Bidirectional(LSTM(units=50, return_sequences=True, recurrent_dropout=0.1))(embed)
        dense = TimeDistributed(Dense(50, activation="relu"))(bilstm)
        crf = CRF(self.num_tags)
        out = crf(dense)

        self.model = Model(input, out)
        self.model.compile(optimizer="adam", loss=crf.loss_function, metrics=[crf.accuracy])