lstm_bilstm.py 文件源码

def create_BiLSTM(wordvecs, lstm_dim=300, output_dim=2, dropout=.5,
                weights=None, train=True):
    model = Sequential()
    if weights != None:
        model.add(Embedding(len(wordvecs)+1,
            len(wordvecs['the']),
            weights=[weights],
                    trainable=train))
    else:
        model.add(Embedding(len(wordvecs)+1,
            len(wordvecs['the']),
                    trainable=train))
    model.add(Dropout(dropout))
    model.add(Bidirectional(LSTM(lstm_dim)))
    model.add(Dropout(dropout))
    model.add(Dense(output_dim, activation='softmax'))
    if output_dim == 2:
        model.compile('adam', 'binary_crossentropy',
                  metrics=['accuracy'])
    else:
        model.compile('adam', 'categorical_crossentropy',
                  metrics=['accuracy'])
    return model