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A suggestion by @jni. The google colab installation is tricky and on Windows it doesn't install. Thus, we might want to elaborate a bit one this.
Hints:
# intall miniconda !wget -c https://repo.continuum.io/miniconda/Miniconda3-4.5.4-Linux-x86_64.sh !chmod +x Miniconda3-4.5.4-Linux-x86_64.sh !bash ./Miniconda3-4.5.4-Linux-x86_64.sh -b -f -p /usr/local # install RAPIDS packages !conda install -q -y --prefix /usr/local -c conda-forge \ -c rapidsai-nightly/label/cuda10.0 -c nvidia/label/cuda10.0 \ cudf cuml # set environment vars import sys, os, shutil sys.path.append('/usr/local/lib/python3.6/site-packages/') os.environ['NUMBAPRO_NVVM'] = '/usr/local/cuda/nvvm/lib64/libnvvm.so' os.environ['NUMBAPRO_LIBDEVICE'] = '/usr/local/cuda/nvvm/libdevice/' # copy .so files to current working dir for fn in ['libcudf.so', 'librmm.so']: shutil.copy('/usr/local/lib/'+fn, os.getcwd())
Source: https://colab.research.google.com/github/ritchieng/deep-learning-wizard/blob/master/docs/machine_learning/gpu/rapids_cudf.ipynb#scrollTo=qZyMvAQp6iwB
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A suggestion by @jni.
The google colab installation is tricky and on Windows it doesn't install. Thus, we might want to elaborate a bit one this.
Hints:
Source: https://colab.research.google.com/github/ritchieng/deep-learning-wizard/blob/master/docs/machine_learning/gpu/rapids_cudf.ipynb#scrollTo=qZyMvAQp6iwB
The text was updated successfully, but these errors were encountered: