将cuML安装到Colab或Kaggle笔记本中

Question

我想使用这个!pip install cuml安装一个cuml包。虽然，这以前是有效的。但是，它现在不工作，并给出以下输出:

Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/
Collecting cuml
Downloading cuml-0.6.1.post1.tar.gz (1.1 kB)
Preparing metadata (setup.py) ... done
Building wheels for collected packages: cuml
error: subprocess-exited-with-error

× python setup.py bdist_wheel did not run successfully.
│ exit code: 1
╰─> See above for output.

note: This error originates from a subprocess, and is likely not a problem with pip.
Building wheel for cuml (setup.py) ... error
ERROR: Failed building wheel for cuml
Running setup.py clean for cuml
Failed to build cuml
Installing collected packages: cuml
error: subprocess-exited-with-error

× Running setup.py install for cuml did not run successfully.
│ exit code: 1
╰─> See above for output.

note: This error originates from a subprocess, and is likely not a problem with pip.
Running setup.py install for cuml ... error
error: legacy-install-failure
× Encountered error while trying to install package.
╰─> cuml
note: This is an issue with the package mentioned above, not pip.
hint: See above for output from the failure.

我使用这些命令来安装包，但是当我导入包时，我得到以下错误:

命令

!pip install cupy-cuda11x
!pip install cuml-cu11 --extra-index-url=https://pypi.ngc.nvidia.com

<<p>输出/strong>

/usr/local/lib/python3.8/site-packages/cudf/utils/gpu_utils.py:148: UserWarning: No NVIDIA GPU detected
warnings.warn("No NVIDIA GPU detected")
---------------------------------------------------------------------------
CUDARuntimeError                          Traceback (most recent call last)
<ipython-input-1-95aa20f405cb> in <module>
11 from sklearn import preprocessing, metrics
12 from sklearn.model_selection import train_test_split, GridSearchCV
---> 13 from cuml.svm import SVR
14 
15 #from hummingbird.ml import convert,load
10 frames
kernel_shap.pyx in init cuml.explainer.kernel_shap()
elastic_net.pyx in init cuml.linear_model.elastic_net()
qn.pyx in init cuml.solvers.qn()
hinge_loss.pyx in init cuml.metrics.hinge_loss()
cuda.pyx in cuml.common.cuda.has_cuda_gpu()
/usr/local/lib/python3.8/site-packages/rmm/_cuda/gpu.py in getDeviceCount()
99     status, count = cudart.cudaGetDeviceCount()
100     if status != cudart.cudaError_t.cudaSuccess:
--> 101         raise CUDARuntimeError(status)
102     return count
103 
CUDARuntimeError: cudaErrorNoDevice: no CUDA-capable device is detected

我得到这些结果是因为我认为我没有激活Colab上的GPU。

Answer 1

要在Colab上pip安装RAPIDS cuML，请确保使用GPU运行时，然后使用这里提到的pip install命令。您错过了--extra-index-url选项。

您将无法在Kaggle上pip安装cuML，因为pip包需要Python 3.8或3.9，但Kaggle与Python 3.7绑定(在撰写本文时)。

Answer 2

最近(5月23日)的Kaggle图像附带cuml预装.

python --version
pip show cuml

Python 3.10.10
Name: cuml
Version: 23.4.1
Summary: cuML - RAPIDS ML Algorithms
Home-page: 
Author: NVIDIA Corporation
Author-email: 
License: Apache 2.0
Location: /opt/conda/lib/python3.10/site-packages
Requires: cudf, cupy-cuda11x, dask, dask-cuda, dask-cudf, distributed, joblib, numba, raft-dask, scipy, seaborn, treelite, treelite_runtime
Required-by: