Thanks a lot for sharing the video! :)

On Thu, Aug 25, 2016 at 10:18 PM, 7VoltCrayon <[email protected]> wrote:

> Yes, the slides are a bit difficult to understand on their own, I haven't
> looked at what Caffe is doing with group yet, from the discussion it looks
> like something similar but I could be wrong (and they don't mention the 1 x
> 1 convolutions to mix the resulting feature maps). Until I take a closer
> look at it, this lecture by the author has a ~5 minute section where he
> explains the separable convolution slides succinctly: https://youtu.be/
> VhLe-u0M1a8?t=1087
>
> On Wednesday, 24 August 2016 20:45:22 UTC-7, Arjun Jain wrote:
>>
>> 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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