Keras中的多个输出

Question

给定一个预测变量向量时，我有一个问题要处理两个输出。假设预测变量矢量看起来像x1, y1, att1, att2, ..., attn，它x1, y1是坐标，并且att's是附加到出现x1, y1坐标的其他属性。基于这个预测变量集，我想进行预测x2, y2。这是一个时间序列问题，我正在尝试使用多元回归解决。我的问题是如何设置keras，这可以在最后一层为我提供2个输出。

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=...)