比如我要定义一个Highway network层（关于highway network的知识在网上有很多）

1）首先需要继承lasagne的基础层：

可以看到，自定义的层是继承了lasagne.layers.Layer.

2）然后定义Highway network所需要更新的参数值：

    def __init__(self, incoming, h_w=lasagne.init.Normal(), h_b=lasagne.init.Normal(), t_w=lasagne.init.Normal(), t_b=lasagne.init.Normal(), **kwargs):super(HighwayNetwork2D,self).__init__(incoming, **kwargs)num_filters = self.input_shape[1]cnn_size = self.input_shape[2]self.h_w = self.add_param(h_w, (num_filters,cnn_size), name='h_w')self.h_b=self.add_param(h_b, (cnn_size,), name='h_b')self.t_w=self.add_param(t_w, (num_filters,cnn_size), name='t_w')self.t_b=self.add_param(t_b, (cnn_size,), name='t_b')

3）定义实际的操作，在get_output_for()这个函数中进行

    def get_output_for(self, input, **kwargs):
#        #batch_size
#        batch_size=T.arange(input.shape[0])#H(x)=tanh(W*x+b)h_x=T.tanh(self.h_w*input+self.h_b)#t=sigmoid(W*x+b)t=T.nnet.sigmoid(self.t_w*input+self.t_b)#z=t*H(x)+(1-t)*xz=t*h_x+(1-t)*inputreturn z

4）最后定义输出时候的shape

    def get_output_shape_for(self, input_shape):return (input_shape[0], input_shape[1], input_shape[2])

最后整一个自定义层的代码如下：

class HighwayNetwork2D(lasagne.layers.Layer):"""Highway network  and use it has 3D1.z=t*H(x)+(1-t)*x2.H(x)=tanh(W*x+b)3.t=sigmoid(W*x+b)"""def __init__(self, incoming, h_w=lasagne.init.Normal(), h_b=lasagne.init.Normal(), t_w=lasagne.init.Normal(), t_b=lasagne.init.Normal(), **kwargs):super(HighwayNetwork2D,self).__init__(incoming, **kwargs)num_filters = self.input_shape[1]cnn_size = self.input_shape[2]self.h_w = self.add_param(h_w, (num_filters,cnn_size), name='h_w')self.h_b=self.add_param(h_b, (cnn_size,), name='h_b')self.t_w=self.add_param(t_w, (num_filters,cnn_size), name='t_w')self.t_b=self.add_param(t_b, (cnn_size,), name='t_b')def get_output_for(self, input, **kwargs):
#        #batch_size
#        batch_size=T.arange(input.shape[0])#H(x)=tanh(W*x+b)h_x=T.tanh(self.h_w*input+self.h_b)#t=sigmoid(W*x+b)t=T.nnet.sigmoid(self.t_w*input+self.t_b)#z=t*H(x)+(1-t)*xz=t*h_x+(1-t)*inputreturn zdef get_output_shape_for(self, input_shape):return (input_shape[0], input_shape[1], input_shape[2])