# HG changeset patch # User Razvan Pascanu # Date 1284423683 14400 # Node ID 5e6d7d9e803ab448c528d782e29fa99bde83e431 # Parent 56c5f0990869abe5cc9684a7a3b5acaab16919d2 a comment on the GPU issue for datasets diff -r 56c5f0990869 -r 5e6d7d9e803a doc/v2_planning/dataset.txt --- a/doc/v2_planning/dataset.txt Mon Sep 13 16:50:24 2010 -0400 +++ b/doc/v2_planning/dataset.txt Mon Sep 13 20:21:23 2010 -0400 @@ -324,3 +324,17 @@ understanding of it, but my feeling is that you need your learner to be written in a specific way to achieve this, in which case it may be up to the learner to take its input data and store it into a shared variable. + +RP comment: Yes, the dataset object alone can not handle this, the issue is somewhere +between the dataset and the learner. Or in other words, everytime you change +the data you need to recompile your theano function. So the learner can not +only get data from the dataset, it needs to get a shared variable. The learner +should also be aware when the dataset is changed, to recompile its internal +functions. I'm not sure which is the best wa to do this. My personal feeling +is that the dataset should be part of the learner. The lerner should provide +a function use_dataset ( or replace_dataset). When this function is called, +all the theano functions in the learner get recompiled based on shared +variables that the dataset object provides. It sort of fits very well in the +framework that I have in mind, which was spattered around in the learner.txt +and some of my previous emails. I think it shares a lot with James concepts, +since it follows quite closely the concepts behind Theano.