You will need just a simple laptop (windows, linux or mac), as the training is going to be done online. #make -j4 2.5 Install python package #cd. We will use PIP to install PyTorch in Mac OS. ![]() ![]() DUSE_CUDA=ON -DUSE_NCCL=ON -DNCCL_ROOT=/path/to/nccl2(in my environment, it is /opt/anaconda3/envs/dlipy2/lib) #export CXX=/opt/anaconda3/envs/dlipy2/bin/x86_64-conda_cos6-linux-gnu-g++ #export CC=/opt/anaconda3/envs/dlipy2/bin/x86_64-conda_cos6-linux-gnu-gcc Install XGBoost 2.1 Download the XGBoost #git clone -recursive Ģ.2 Install the build-essential #yum groupinstall "Development Tools"Ģ.3 Initial the environment setting: #. 1.1 Download the cmake binary package: 1.2 Uncompress the package to /usr/local 1.3 Update-alternatives -install /usr/bin/cmake cmake /usr/local/bin/cmake 1 2. You may use the Conda packaging manager to install XGBoost: conda install -c conda-forge py-xgboost Conda should be able to detect the existence of a GPU on your machine and install the correct variant of XGBoost. xgboost-1.5.2-p圓-none-winamd64.whl (106.6 MB view hashes ) Uploaded p圓. xgboost-1.5.2.tar.gz (730.1 kB view hashes ) Uploaded source. ![]() The higher version cmake has some problems with it, but you can install it with binary package. If youre not sure which to choose, learn more about installing packages.
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