在此代码中,作者定义了2个输入,但是模型只有一个输入提要。应该有一些错误,但是,我可以运行它。我不知道为什么我可以成功运行此代码。
def han():
# refer to 4.2 in the paper whil reading the following code
# Input for one day : max article per day =40, dim_vec=200
input1 = Input(shape=(40, 200), dtype='float32')
# Attention Layer
dense_layer = Dense(200, activation='tanh')(input1)
softmax_layer = Activation('softmax')(dense_layer)
attention_mul = multiply([softmax_layer,input1])
#end attention layer
vec_sum = Lambda(lambda x: K.sum(x, axis=1))(attention_mul)
pre_model1 = Model(input1, vec_sum)
pre_model2 = Model(input1, vec_sum)
# Input of the HAN shape (None,11,40,200)
# 11 = Window size = N in the paper 40 = max articles per day, dim_vec = 200
input2 = Input(shape=(11, 40, 200), dtype='float32')
# TimeDistributed is used to apply a layer to every temporal slice of an input
# So we use it here to apply our attention layer ( pre_model ) to every article in one day
# to focus on the most critical article
pre_gru = TimeDistributed(pre_model1)(input2)
# bidirectional gru
l_gru = Bidirectional(GRU(100, return_sequences=True))(pre_gru)
# We apply attention layer to every day to focus on the most critical day
post_gru = TimeDistributed(pre_model2)(l_gru)
# MLP to perform classification
dense1 = Dense(100, activation='tanh')(post_gru)
dense2 = Dense(3, activation='tanh')(dense1)
final = Activation('softmax')(dense2)
final_model = Model(input2, final)
final_model.summary()
return final_model
答案 0 :(得分:0)
Keras模型可以用作图层。在上面的代码中,input1
用于定义pre_model{1,2}
。然后,名为final_model
的模型将这些模型称为波纹管。
final_model
具有单个输入层。