2021-09-16:17:22:35,504 INFO [iwn.py:43] Loading bengali language synsets... 2021-09-16:17:22:49,208 WARNING [utils.py:429] using automatically assigned random_state=3179480306 2021-09-16:17:22:49,361 INFO [splitting.py:60] done splitting triples to groups of sizes [267018, 38830, 38831] /srv/home/bhattacharyya/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/weight_boosting.py:29: DeprecationWarning: numpy.core.umath_tests is an internal NumPy module and should not be imported. It will be removed in a future NumPy release. from numpy.core.umath_tests import inner1d /srv/home/bhattacharyya/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/gradient_boosting.py:34: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations from ._gradient_boosting import predict_stages /srv/home/bhattacharyya/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/gradient_boosting.py:34: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations from ._gradient_boosting import predict_stages [I 2021-09-16 17:22:53,483] A new study created in memory with name: no-name-8e955b25-a1f3-4a57-b42e-1f7594053d64 2021-09-16:17:22:53,565 INFO [hpo.py:622] Using model: 2021-09-16:17:22:53,565 INFO [hpo.py:626] Using loss: 2021-09-16:17:22:53,565 INFO [hpo.py:637] Using regularizer: 2021-09-16:17:22:53,566 INFO [hpo.py:641] Using optimizer: 2021-09-16:17:22:53,566 INFO [hpo.py:645] Using training loop: 2021-09-16:17:22:53,566 INFO [hpo.py:651] Using negative sampler: 2021-09-16:17:22:53,566 INFO [hpo.py:662] Using evaluator: 2021-09-16:17:22:53,566 INFO [hpo.py:666] Attempting to maximize adjusted_arithmetic_mean_rank_index 2021-09-16:17:22:53,566 INFO [hpo.py:668] Filter validation triples when testing: True /srv/home/bhattacharyya/anaconda3/lib/python3.7/site-packages/optuna/distributions.py:563: UserWarning: The distribution is specified by [32, 4000] and step=100, but the range is not divisible by `step`. It will be replaced by [32, 3932]. low=low, old_high=old_high, high=high, step=step 2021-09-16:17:22:53,584 WARNING [api.py:823] No random seed is specified. Setting to 1437431581. Training epochs on cuda: 0%| | 0/10 [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [00:35<00:00, 6.81s/epoch, loss=0.000503, prev_loss=0.000503] Training epochs on cuda: 100%|██████████| 10/10 [00:35<00:00, 3.58s/epoch, loss=0.000503, prev_loss=0.000503] 2021-09-16:17:23:43,771 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpicvbza94' 2021-09-16:17:23:43,840 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpicvbza94' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. 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