Keras中的多個輸出

Question

我有一個問題，當給定一個預測變量向量時，我會處理預測兩個輸出。 假設預測向量看起來像x1, y1, att1, att2, ..., attn，它表示x1, y1是座標，而att's是附加到x1, y1座標出現處的其他屬性。基於這個預測集，我想預測x2, y2。這是一個時間序列問題，我試圖使用多重回歸來解決。 我的問題是我如何設置keras，它可以在最後一層給我2個輸出。我已經解決了keras中的簡單迴歸問題，代碼在my github中可用。

Answer 1

from keras.models import Model 
from keras.layers import *  

#inp is a "tensor", that can be passed when calling other layers to produce an output 
inp = Input((10,)) #supposing you have ten numeric values as input 


#here, SomeLayer() is defining a layer, 
#and calling it with (inp) produces the output tensor x 
x = SomeLayer(blablabla)(inp) 
x = SomeOtherLayer(blablabla)(x) #here, I just replace x, because this intermediate output is not interesting to keep 


#here, I want to keep the two different outputs for defining the model 
#notice that both left and right are called with the same input x, creating a fork 
out1 = LeftSideLastLayer(balbalba)(x)  
out2 = RightSideLastLayer(banblabala)(x) 


#here, you define which path you will follow in the graph you've drawn with layers 
#notice the two outputs passed in a list, telling the model I want it to have two outputs. 
model = Model(inp, [out1,out2]) 
model.compile(optimizer = ...., loss = ....) #loss can be one for both sides or a list with different loss functions for out1 and out2  

model.fit(inputData,[outputYLeft, outputYRight], epochs=..., batch_size=...)