参考：https://github.com/BVLC/caffe/issues/684

1. Add a class declaration for your layer to the appropriate one of common_layers.hpp,data_layers.hpp, loss_layers.hpp, neuron_layers.hpp, or vision_layers.hpp. Include an inline implementation of type and the *Blobs() methods to specify blob number requirements. Omit the*_gpu declarations if you'll only be implementing CPU code.

2. Implement your layer in layers/your_layer.cpp.

   • SetUp for initialization: reading parameters, allocating buffers, etc.

   • Forward_cpu for the function your layer computes

   • Backward_cpu for its gradient

3. (Optional) Implement the GPU versions Forward_gpu and Backward_gpu in layers/your_layer.cu.

4. Add your layer to proto/caffe.proto, updating the next available ID. Also declare parameters, if needed, in this file.

5. Make your layer createable by adding it to layer_factory.cpp.

6. Write tests in test/test_your_layer.cpp. Use test/test_gradient_check_util.hpp to check that your Forward and Backward implementations are in numerical agreement.

以上是github上某大神的解答，步骤很清晰，具体说一下，比如现在要添加一个vision layer，名字叫Aaa_Layer：

1、属于哪个类型的layer，就打开哪个hpp文件，这里就打开vision_layers.hpp，然后自己添加该layer的定义，或者直接复制Convolution_Layer的相关代码来修改类名和构造函数名都改为Aaa_Layer，如果不用GPU，将*_gpu的声明都去掉。

2、实现自己的layer，编写Aaa_Layer.cpp，加入到src/caffe/layers，主要实现Setup、Forward_cpu、Backward_cpu。

3、如果需要GPU实现，那么在Aaa_Layer.cu中实现Forward_gpu和Backward_gpu。

4、修改src/caffe/proto/caffe.proto，好到LayerType，添加Aaa，并更新ID，如果Layer有参数，添加AaaParameter类。

5、在src/caffe/layer_factory.cpp中添加响应代码。

6、在src/caffe/test中写一个test_Aaa_layer.cpp，用include/caffe/test/test_gradient_check_util.hpp来检查前向后向传播是否正确。