What is the % of sparcity? On the GPU if it isn't high, it won't speed up
the computation to do sparse computation.

We have some block sparse operation in that module, maybe it can help you:

http://deeplearning.net/software/theano/library/tensor/nnet/blocksparse.html?highlight=block%20sparse#module-tensor.nnet.blocksparse

On Tue, Aug 16, 2016 at 11:31 AM, Peter O'Connor <[email protected]
> wrote:

> I'm looking for an efficient way to do convolution when the input
> images/feature maps are sparse.
>
> So you'd have a sparse input (n_samples, n_features_in, n_rows, n_cols), a
> dense kernel (n_features_out, n_features_in, n_kernel_rows, n_kernel_cols),
> and produce either a sparse or dense output of shape (n_samples,
> n_features_out, n_rows +n_kernel_rows-1, n_cols+n_kernel_cols-1).
>
> I've seen theano's sparse sandbox
> <http://deeplearning.net/software/theano/library/sparse/sandbox.html>,
> but it's not obvious from here that it would support this kind of operation
> (it seems to be more about implementing dense convolutions as sparse matrix
> multiplications).  Does anybody know of existing code that deals with this
> situation?
>
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