Open navotoz opened 2 years ago
I confirm: when running on CPU there is an increasing memory consumption. @navotoz , could you, please, tell me whether you have been able to solve this issue?
Hi @navotoz , I confirm this issue also appears in Python 3.7, trankit 1.1.1, torch 1.8.1+cu101
Hi @Dielianss @olegpolivin Thanks for the comments. We maneged to mitigate this issue by running inference in a docker and restarting it every predefined interval. This is not a real solution to this issue, but at least we can work with the model.
Hello,
I've initiated the model like so:
nlp = Pipeline('english', gpu=False, cache_dir='./cache')
Than call it by using:with torch.no_grad(): for idx in range(10000): nlp.lemmatize('Hello World', is_sent=True)
. When running the code, the RAM memory slowly fills.I attached a graph of the memory filling up.![image](https://user-images.githubusercontent.com/38127869/171159052-e677add0-287f-4f3d-948b-3aa4bdf2a715.png)
I'm using python3.7, trankit=1.1.0, torch=1.7.1.
Thank you!