8000 Increasing max_phrase_words runs into memory issues · Issue #20 · thunlp/BERT-KPE · GitHub
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Increasing max_phrase_words runs into memory issues #20

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lumalik opened this issue Jul 19, 2022 · 1 comment
Open

Increasing max_phrase_words runs into memory issues #20

lumalik opened this issue Jul 19, 2022 · 1 comment

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@lumalik
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lumalik commented Jul 19, 2022

Hi, first of all, thank you very much for the repository! :)

I want to retrain the model using a larger number of keyphrases and output longer keyphrases in general.

To achieve this I:

  • increase the number of max_phrase_words from 5 to 10 in scripts/config.py
  • increase max_gram from 5 to 10 parameter in my model (in bertkpe/networks/)

However, I see that every number bigger than 5 makes me run out of memory during the step
"start preparing (train) features for bert2joint (bert) ..."
I can also see that if I increase the numbers to 6, I run out of memory at a much later stage in the preparation step than if I increase it to something higher like 10, even though the operation is performed on batches. I suspect that there is a memory leak in one of the data loader functions.
@SunSiShining
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Which dataset are you using? In which line does the OOM you mentioned occur? I may need more information.

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