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[python-package] Deploy a Cuda Version to Conda Forge #6657
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Thanks for using LightGBM.
I'm assuming you mean the Python package (because you mentioned As described in https://github.com/microsoft/LightGBM/blob/master/python-package/README.rst#install-from-conda-forge-channel, on Linux systems with CUDA, the following will select a CUDA-enabled build of conda install -c conda-forge 'lightgbm>=4.4.0' The CUDA build isn't supported on Windows or macOS. If this doesn't answer your question, please provide more specifics about what you'd like to do and what "can be difficult" means, and we will try to help. |
I think this does answer my question. I believe the conda build automatically downloading a cuda-enabled build is new to a recent version? The last time I tried this I though the conda build did not come with a cuda-enabled version. Thanks for the answer! |
Hi. I just tried running on an A100. I got the following errors: [LightGBM] [Warning] Using sparse features with CUDA is currently not supported. [LightGBM] [Warning] Defaulting to malloc in CHAllocator!!! [LightGBM] [Fatal] [CUDA] initialization error /home/conda/feedstock_root/build_artifacts/lightgbm_1722621077976/work/src/io/cuda/cuda_column_data.cpp 16 |
You mentioned that you'd previously tried to build LightGBM from source... are you certain you've uninstalled it? pip uninstall lightgbm Can you share the output of the following commands? nvidia-smi
conda info
conda env export
python --version Are you able to provide a minimal, reproducible example that demonstrates this error? For example, is this sufficient to reproduce it? from sklearn.datasets import make_regression
import lightgbm as lgb
X, y = make_regression(n_samples=10_000)
dtrain = lgb.Dataset(X, label=y)
bst = lgb.train(
train_set=dtrain,
params={
"device": "cuda",
"objective": "regression",
"num_leaves": 7
},
num_boost_round=5
) |
Yes, I'm quite confident it's been uninstalled. This was several months ago, and I have since re-installed the conda environment.
Your program did not produce those errors. |
Ah I've figured it out! This is really embarrassing. I use python multiprocessing. When you launch launch lightgbm from a spawned process in python, it crashes cuda. I should have realized this because pytorch causes the same issues |
I have one last question for this thread, the parameter "data_sample_strategy": "goss" crashes the run in cuda mode? Is this known? I get this error: [LightGBM] [Fatal] [CUDA] invalid argument /home/conda/feedstock_root/build_artifacts/lightgbm_1722621077976/work/src/boosting/goss.hpp 63 |
Hi. I’m having a lot of trouble building and deploying a CUDA version of LGBM in my conda environment. When you source everything from conda forge, it can be difficult to try to integrate a pip version of LGBM.
Would it be possible to deploy the CUDA version to conda forge?
Thanks
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