The full error will tell you which op don't have a grad impolemented for
that case.

I think I responded to that elsewhere. Don't duplicate question, we have
limited time to help.

On Wed, Jul 20, 2016 at 5:56 PM, Aditya Gudimella <
[email protected]> wrote:

> I have defined a theano function which given a matrix(named array) and a
> list of integers (named split_cts), splits the array into rows such that
> number of rows in i th split = split_cts[i] and returns the sum of each
> split joined together as a tensor. However when I try to differentiate it,
> it gives me a gradient error. Specifically, the error says:
> NotImplementedError: Grad is not implemented for inputs withnumber of
> dimension other than 1.
>
> The function is as follows:
>
> def split_sum(array, split_cts):
>     '''
>     Given an array like and an array of counts, it returns an array where
> each element is the sum of count number of indices in array
>     That is retval[i] = sum(array[counts.cumsum()[i-1]:counts.cumsum()[i]])
>     '''
>     sep = cumsum(split_cts) - 1
>     return diff(T.concatenate((T.zeros((array.shape[1], ))[None,:], cumsum
> (array, axis=0)[sep]), axis=0), axis=0)
>
> How do I make it differentiable? Any help would be appreciated.
>
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