Memory Corruption Error: "Process finished with exit code -1073741819 (0xC0000005)" #799
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bug
Bugs and behaviour differing from documentation
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Hey, First, thanks for your patience and the effort you put into debugging this — I know memory errors can be particularly frustrating. I'd hoped to get to this bug sooner because I'm pretty sure I understand the cause. It's due to a change in the Matt |
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that sounds really good, which branch is it and how do I have to install spacy/thinc such that I can test your change? |
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It's up on the master branch of thinc now. If you do you'll get a file in the |
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thank you very much for the little helper script unfortunately the further the build output might be of some use: any help is appreciated |
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Hm! Not sure why that test fails, but it shouldn't affect the memory error — could you go on and try the rest? |
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Not related to this issue (sorry), but using |
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Perfect, I'm glad it worked! |
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Dear spacy-team, this might be related to #786
I tried to train a entity recognizer using spacy's entity recognizer class following this example script
https://github.com/explosion/spaCy/blob/master/examples/training/train_ner.py
However, in my adapted version which runs on a bigger set of example data python breaks frequently with the exit code -1073741819 (0xC0000005) which some research suggest to stand for memory corruption. I think the error occurs in the update function of the entity recognizer https://github.com/explosion/spaCy/blob/master/examples/training/train_ner.py#L32
This bug is extremely difficult to track down. I spend 4 days trying to reduce my case into a minimal working example, however it doesn't seem to work deterministically. I rather have the impression that certain things make it more likely that the bug occurs. I try to list all things which seems to have an influence on this:
nlp = spacy.load('de', parser=False, entity=False, add_vectors=False)ornlp = spacy.load('de')for creatingEntityRecognizer(nlp.vocab, entity_types=entity_types). The keyword arguments seem to be crucial. It is impressively more likely that my code breaks if I skip them.I cannot be certain about all these points, because there was no deterministic pattern at all to be find (at least I couldn't find it yet), and because I had not enough time to do some large statistics on the crash counts.
Still, I hope you might be able to find this weird bug.
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