They use different implementation. Make sure Theano use a parallel blas
library. The new conv2d use it for part of the parallelism.

Le 25 août 2016 21:53, <[email protected]> a écrit :

> Hi everyone,
>
> I've recently come across some weird behaviour regarding the new
> theano.tensor.nnet.conv2d
> and the old
> theano.tensor.nnet.conv.conv2d
> convolution functions.
>
> I have 2 different models one uses the old the other the new conv2d method.
> The difference between the two is that the the model that uses the new
> conv2d methods has more layers than the other one, plus that I've
> explicitly defined padding and stride.
>
> Other than that everything else is the same. Number of data, training
> algorithm, batchSize .... etc. pretty much the same.
>
> Once I execute them, the smaller model with the old conv2d method utilizes
> all the cores in my system ;) great.
> The bigger model with the new conv2d method doesn't, which is strange
> because in this case the bigger the model the more resources would need.
>
> Are there any differences in the way the two conv2d methods utilize openmp?
>
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