Could be used CrossChannelNormalization of pylearn as a local response normalization?
Regards. El martes, 22 de noviembre de 2016, 16:15:08 (UTC+1), Beatriz G. escribió: > > Hi. > > I have the same problem. > > Anyone could help me? > > El miércoles, 30 de julio de 2014, 5:44:54 (UTC+2), xu shen escribió: >> >> Does anyone have the normalization code for LeNetPoolLayer? >> >> The convolution layer is defined as follows: >> Class LeNetConvPoolLayer(object): >> >> conv_out=conv.conv2d(input=input, filters=self.W, >> image_shape=image_shape,filter_shape=filter_shape, subsample = subsampe) >> >> norm_out = normalizer(conv_out,k,n,alpha,beta)# I want to do >> normalization here just as Alex Krizhevsky does in DCNN, but I can not find >> proper code to do this in theano. >> >> pooled_out = >> downsample.max_pool_2d(input=norm_out,ds=poolsize,ignore_border=True) >> >> I found out that it's hard to incorporate CrossChannelNormalization in >> pylearn2.expr.normalize for this task... >> can any one share your normalization theano code in CNN or how to use >> CrossChannelNormalizaiton in this code? >> Thanks very much. >> > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
