如何用2D输出训练网络? (蟒蛇，凯拉斯) [英] How to train network with 2D output? (python,Keras)

问题描述

我想训练一个回归网络，其输出是两个坐标(x1，y1)和(x2，y2). 我的问题是:如果我想训练网络，我的输出应该分开吗? 我的意思是我的输出应该像这样:

I want to train a regression network which its outputs are two coordinates (x1,y1) and (x2,y2). my question is: if I want to train network should my output be separated? I mean should my output like this:

 [x1,y1,x2,y2] 

或者有没有办法像这样堆叠它们:

or is there a way to stack them like:

[(x1,y1),(x2,y2)]

预先感谢

推荐答案

RepeatVector用于此目的(请参见

The RepeatVector is there for this purpose (see Keras documentation).

您希望输出形状为(2, 2)，或者是两个坐标且每个都有两个条目的数组.

You want your output shape to be (2, 2), or an array of two coordinates with two entries each.

num_outputs = 2
num_elements = 2

添加用于处理网络输入的图层后，添加RepeatVector.这样就可以获取数据数组作为输出.最后一层需要输出num_elements，例如:

After you have added layers for processing input to your network, add a RepeatVector. This will make it possible to get an array of data as output. Your final layer needs to output num_elements so for example:

model.add(RepeatVector(num_outputs))
# Optional layers can be inserted here
model.add(Dense(num_elements))

简而言之，重复矢量将复制要发送到其他节点的上一层的内容，每个路径将输出一个num_elements数组，从而为您提供所需的输出形状.请注意，您的训练数据(标签)也必须由形状(2, 2)数组组成.

In a nutshell, repeat vectors copy the content of the previous layer to be sent to further nodes, and each path will output an array of num_elements, giving you the desired output shape. Note that your training data (labels) has to consist of shape (2, 2) arrays also.

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