Hello everyone I have been trying to do a 1d convolution in theano for problem i am doing in Pymc3, which is built on top of theano.
I have used the theano.tensor.signal.conv.conv2d function to do the convolution between the data and the function i have, but from what i understand from the docs <http://deeplearning.net/software/theano/library/tensor/signal/conv.html?highlight=border_mode#theano.tensor.signal.conv.conv2d> and this conversation <https://github.com/Theano/Theano/issues/2118> that there is no border_mode='same' in theano like with numpy and scipy, which makes the output dimensions the same as the input. My idea was to make a function which could take the output of the border_mode='full' convolution and take the middle of the array and take half the length of the data array in each direction from the middle of the output and create a new array. This new array i could then in the sampler. i came up with the following that takes into account even and odd array sizes: *def findMiddle(input_list):* * if len(input_list) % 2 != 0:* * return (int((len(input_list))/2)-1)* * else:* * return (int((len(input_list)/2)-1)-1,int((len(input_list))/2)-1)* *# 1 is subtracted from both because python indicies start at 0 * *def Middlearray(input_list, data):* * mid = findMiddle(input_list)* * if isinstance(mid, int) == False:#if there is two mid values* * li = input_list* * limid=li[int(mid[0]-(len(data)/2)):mid[0]]* * limid2 = li[mid[1]:int(mid[1]+(len(data)/2))]* * convsame=np.hstack((limid,limid2))* * else:#if there is one mid value * * li = input_list * * convsame = li[int(mid-(len(data)/2)):int(mid+(len(data)/2))]* * if len(convsame) == len(data):* * return convsame* * else:* * return -inf* My problem i need some way to obtain the output from the convolution not just as an object but an array for this to work. Is it possible to extract the values of the convolution output so i can obtain the border_mode='same' result? i also noticed that theano.tensor .nnet.conv2d has border_mode='half' which is similar to what i need. Is the syntax transferable between the two functions? currently i write my convolution as * convol=theano.tensor.signal.conv.conv2d(muJ[None,:],transfer[None,:],(1,100),(1,100),border_mode='full')* Where muJ is my data and transfer is my function/filter, both have a length of 100. -- --- 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 theano-users+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/theano-users/e17b3977-46d1-45e1-854d-adff91c2f00f%40googlegroups.com.
