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How to train XNMT with datasets that do not fit in RAM? #585

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rrmariani opened this issue Jan 7, 2020 · 1 comment

rrmariani commented Jan 7, 2020 •

edited

I have source and target files that are 15GB each and the system crashes after allocating all the 32GB RAM I have and the 2GB of swap disk.

I am now trying with 15 pairs of 1GB files...

Is there a way to tell XNMT how to train on very large files?

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rrmariani commented Jan 21, 2020

I found an answer to my problem in the doc...

"sample_train_sents – If given, load a random subset of training sentences before each epoch. Useful when training data does not fit in memory."

I guess we need to read a large corpus by consecutive chunks as well, to make sure we cover the entire data set.

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