[SciPy-Dev] scipy improve performance by parallelizing

[Frédéric Bastien]

On Mon, Jul 14, 2014 at 10:53 AM, Sai Rajeshwar <rajsai24 at gmail.com> wrote:

> hi frederic,
>
> thanks, actually im trying to implement a 3d-convolutional neural network
> as you can see in the snippet..  so you mean to say
>
> 1)instead of using scipy.signal.convolve  i should import theano and use
> signal.conv2d
> <http://deeplearning.net/software/theano/library/tensor/signal/conv.html#theano.tensor.signal.conv.conv2d>
> ,  if so signal.conv2d is right or any other function according to my
> need..
>

We have some special conv3d for neural network:
http://deeplearning.net/software/theano/library/tensor/nnet/conv.html.
Maybe the suite better what you want. But to be useful, you will need
medium/big convolution, not tini video.


>
> 2)also any hints on speeding up numpy.sum in
>
>    pooled[0][i][j][k][l]=math.
>
> tanh((numpy.sum(conv_out[0][i][j][k*3][l*3:(l+1)*3])+numpy.sum(conv_out[0][i][j][k*3+1][l*3:(l+1)*3])+numpy.sum(conv_out[0][i][j][k*3+2][l*3:(l+1)*3]))/9.0+b[i][j])
>

Someone else reply with some information to do less indexing and do the sum
on bigger chunk of data each time. This could speed up your stuff.


> thanks a lot..   also i have seen your name some where in pylearn2.. are
> ua pylearn developer too.
>

Yes and no. I'm in the same lab as the main Pylearn2 dev and I do some
small contribution from time to time(stuff mostly related to optimizaiton
or Theano). But I wouldn't call me a pylearn2 core dev.

Fred
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scipy-dev/attachments/20140714/681a15de/attachment.html>