Nils

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Training many models with gpu_hist in Optuna yields ‘parallel_for failed: out of memory’

Any update on this issue?

Training many models with gpu_hist in Optuna yields ‘parallel_for failed: out of memory’

This is my code, which stops after 28 rounds with the errors stated above. ``` import numpy as np import pandas as pd from sklearn.utils import resample from xgboost import...

Training many models with gpu_hist in Optuna yields ‘parallel_for failed: out of memory’

Hm.. Never saw that before. I will check and let you know.

Training many models with gpu_hist in Optuna yields ‘parallel_for failed: out of memory’

So, the code above is working for me - until the stated error. Anyway, I switched to the learning API and tested everything without Optuna and with a much simpler...

Training many models with gpu_hist in Optuna yields ‘parallel_for failed: out of memory’

Do you think it could be hardware related?

[ENH] Using custom distance measure with `TimeSeriesKMeans` (`distance_matrix_fast` of `dtaidistance`)

No stress! I’m glad to see that something has come out of a small idea and that work is being done on it. I hope it can be useful for...

[ENH] Using custom distance measure with `TimeSeriesKMeans` (`distance_matrix_fast` of `dtaidistance`)

Yes they match my use case 👍