Hi 7VoltCrayon,
Thanks for pointing to this grouped convolution. I am not sure if I
understood the slide 100%, but to me it sounds similar to caffe's "group
by" (https://github.com/BVLC/caffe/issues/778), is that true? If not, can
you help me spot the differences?

Thanks a lot.

On Thu, Aug 25, 2016 at 3:29 AM, 7VoltCrayon <[email protected]> wrote:

> Thank you for the reply. I see that in TensorFlow, this is implemented at
> the CUDA level
> <https://github.com/tensorflow/tensorflow/blob/d42facc3cc9611f0c9722c81551a7404a0bd3f6b/tensorflow/core/kernels/depthwise_conv_op_gpu.cu.cc>
>  (linked),
> if implementing this in Theano, would it be possible to get a fast
> implementation using pre-existing Theano ops? Or is this something that
> needs to be done at a C++ / CUDA level?
>
> On Wednesday, 24 August 2016 13:48:59 UTC-7, nouiz wrote:
>>
>> no, but if someone is interrested, it can be done in Theano too.
>>
>> Fred
>>
>> On Wed, Aug 24, 2016 at 4:09 PM, 7VoltCrayon <[email protected]> wrote:
>>
>>> Does theano have the equivalent of TensorFlow's separable_conv2d function?
>>> Where it implements a separable factorized convolution as described in
>>> these slides:  http://vincent.vanhoucke.com/
>>> publications/vanhoucke-iclr14.pdf?attredirects=0
>>>
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