我想用这个!pip install cuml
安装cuml软件包。虽然以前可以用。但是现在不行了,输出如下:
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软件包,但当我导入软件包时,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
- 产出**
/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。
1条答案
按热度按时间kmbjn2e31#
要在Colab上pip安装急流cuML,请确保您使用的是GPU运行时,然后使用此处注明的pip安装命令。您缺少
--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绑定到Python 3.7(在撰写本文时)。