models.py 文件源码

def c2r(dic_len,input_length,output_length,emb_dim=128,hidden=512,nb_filter=64,deepth=(1,1),stride=3):
    model = Sequential()
    model.add(Embedding(input_dim=dic_len, output_dim=emb_dim, input_length=input_length))
    for l in range(deepth[0]):
        model.add(Conv1D(nb_filter,3,activation='relu'))
    model.add(GlobalMaxPooling1D())
    model.add(Dropout(0.5))
    model.add(RepeatVector(output_length))
    for l in range(deepth[0]):
        model.add(LSTM(hidden, return_sequences=True))
    model.add(TimeDistributed(Dense(units=dic_len, activation='softmax')))
    model.compile(optimizer='rmsprop',loss='categorical_crossentropy',metrics=['acc'])
    return model