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[BUG] Semi-Supervised UMAP, with euclidean target_metric, reduction errors when input passes a certain size. #2333
Comments
Possibly related to #1604 |
Linking to #2241. Looking into this. |
I am having the same issue. I tried with 0.14 and then with 0.15a nightly. Unfortunately I don't have a way for you to reproduce it on a sample dataset. I just wanted to let you know that it is still happening
Environment location: AWS EC2 g4dn.8xlarge |
This issue has been marked stale due to no recent activity in the past 30d. Please close this issue if no further response or action is needed. Otherwise, please respond with a comment indicating any updates or changes to the original issue and/or confirm this issue still needs to be addressed. This issue will be marked rotten if there is no activity in the next 60d. |
This issue has been marked rotten due to no recent activity in the past 90d. Please close this issue if no further response or action is needed. Otherwise, please respond with a comment indicating any updates or changes to the original issue and/or confirm this issue still needs to be addressed. |
Describe the bug
UMAP errors for supervised reduction with different sized input when using target labels and a
target_metric
ofeuclidean
Steps/Code to reproduce bug
Categorical Metric Working Input
Categorical Output
Euclidean Metric Erroring Input
Output with error
Expected behavior
fit_transform
should not error witheuclidean
target_metric
Environment details (please complete the following information):
NVIDIA-SMI Driver: 440.33.01, CUDA: 10.2 Tesla V100
-c defaults rapids=0.14 python=3.7 cudatoolkit=10.2
Additional context
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