pytorch/ignite

Are there any ways to filter out or ignore a batch in engine?

Open

#996 ouverte le 30 avr. 2020

Voir sur GitHub
 (7 commentaires) (1 réaction) (0 assignés)Python (602 forks)batch import
enhancementhelp wanted

Métriques du dépôt

Stars
 (4 313 stars)
Métriques de merge PR
 (Merge moyen 18j 23h) (19 PRs mergées en 30 j)

Description

❓ Questions/Help/Support

I'm really new to the ML area and I'm trying to train a network with a dataset that when sampling batches, it can create batches with really large sizes (the sampling method is just torch's weightedSampling). Though the batch size is fixed the data size in the batch will be really large sometimes. It seems pretty complicated to define a customized sampler, and the way I originally did was just ignore that batch when the data size in the batch is too large. Now, I'm trying to use ignite as the framework to train the network, I don't know how to do this. I think it might relate to event_filter? But it seems to be triggered by event, so are there any ways to pass in a batch instead?

Thanks so much for your time!

Guide contributeur