Comments (3)
zeyiwen
commented on May 17, 2024
Thanks for the comments. We currently aim at optimizing our library for GPUs. We will investigate and evaluate this possibility in the future.
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asheetal
commented on May 17, 2024
any plan to support opencl ? nvidia GPUs are kind of hard to get hold these days.
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zeyiwen
commented on May 17, 2024
Hi, @asheetal Yes. I do plan to support OpenCL, but it may take some time to train new students. COVID-19 has a notable impact on my work on this project.
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Related Issues (20)
- any status update on issue #63? HOT 1
- ImportError: cannot import name 'TGBMClassifier' from 'thundergbm' (unknown location)
- FileNotFoundError: Could not find module 'c:\users\donald seger\miniconda3\envs\tensorflow\lib\site-packages\thundergbm-0.3.16-py3.8.egg\thundergbm\thundergbm.dll' (or one of its dependencies). Try using the full path with constructor syntax.
- Can you please answer issue #63?
- the Random Forest classifies everything to be 1 HOT 2
- Can you please answer issue #68?
- Is there a parameter to set "minimum samples per leaf" for Random Forest? HOT 1
- Why did you remove my issue? It is completely legit. HOT 1
- Please why are you removing my issue without any reason? HOT 1
- Debug Assertion Failed
- AttributeError: 'TGBMClassifier' object has no attribute 'save' HOT 1
- issue with saving and reloading model? HOT 2
- Please answer issue #75
- How to visualize the ThunderGBM? HOT 3
- random seed generator HOT 1
- Output of multi:softprob is probably wrong HOT 4
- Problems with random forest classifier when using more and deeper leaners
- Check failed: [max_elem + n_columns*(max_elem + 1) < 0x7fffffff] Max_values is too large to be transformed.请问这个问题怎么解决？ HOT 2
- Can the Negative Weights be Input? HOT 2
- Cuda 12
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