Mini-batch train about causaldiscoverytoolbox

[Diviyan-Kalainathan]

Hi, You're right, some of the algorithms have this functionality, others haven't. I should look into this. Best, Diviyan

…

On Fri, Aug 3, 2018, 00:28 thongnnguyen ***@***.***> wrote: Hi, I would like suggest to implement mini-batch training. Specifically, I tried to run FSGNN on my data and got the following error not enough memory: you tried to allocate 160465GB. Buy new RAM! at /opt/conda/conda-bld/pytorch_1524584710464/work/aten/src/TH/THGeneral.c:218 I looked into the code but unfortunately I'm not familiar with GAN to modify the code. — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <https://github.com/Diviyan-Kalainathan/CausalDiscoveryToolbox/issues/9>, or mute the thread <https://github.com/notifications/unsubscribe-auth/ATuWdD1TTPtrFfA1czHtjmO9tZxdmmMSks5uM0vtgaJpZM4Vs1PE> .

[Diviyan-Kalainathan]

I'm sorry that it took so long, but it should be done. It revealed itself to be trickier than expected. Now instead of feeding raw data as a numpy array or Tensor, you can feed torch.utils.data.Dataset types, with a custom loading function of elements that you write accordingly to your data.

[Diviyan-Kalainathan]

I will be closing this issue, as it should be solved. Don't hesitate to reopen it if the bug still persists in the latest version.
Best,
Diviyan