Hi all.
I'm trying SdA implementation from http://deeplearning.net/tutorial/SdA.html
Execution of the code test takes 1146 minutes with my MacBook Pro 7,1 
(Intel Core 2 duo), more longer than time reported by the tutorial.

Suppose I use a grid search of 1000 elements equally distributed on 
parameters. So, time for completion is very high.

An idea is use only model which test parameters during model selection, but 
its not a good idea, because we know that its very aleatory and its 
strictly depends only on initialization of weights and bias.

Is there a fashion, a way to reduce time completion of the pretraining and 
finetuning? Or is there a way to improve model selection?

Thank you

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