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- #!/bin/bash
- set -ex
-
- PYTHON_VERSION=${PYTHON_VERSION:-3.7.5}
- MINDSPORE_VERSION=${MINDSPORE_VERSION:-1.5.0}
- CUDA_VERSION=${CUDA_VERSION:-8.0.5.39-1+cuda11.1}
- DISTRIBUTED=${DISTRIBUTED:-false}
- CUDA_VERSION=${CUDA_VERSION:-11.1.1-1}
- CUDA_INSTALL_PATH=${CUDA_INSTALL_PATH:-cuda-11.1}
- LIBNCCL2_VERSION=${LIBNCCL2_VERSION:-2.7.8-1+cuda11.1}
- ARCH=$(uname -m)
-
- declare -A version_map=()
- version_map["3.7.5"]="${MINDSPORE_VERSION}-cp37-cp37m"
- version_map["3.9.0"]="${MINDSPORE_VERSION}-cp39-cp39m"
-
- #use huaweicloud mirror in China
- sudo sed -i "s@http://.*archive.ubuntu.com@http://repo.huaweicloud.com@g" /etc/apt/sources.list
- sudo sed -i "s@http://.*security.ubuntu.com@http://repo.huaweicloud.com@g" /etc/apt/sources.list
- sudo apt-get update
-
- # install python 3.7 and make it default
- sudo apt-get install gcc-7 libgmp-dev curl python3.7 openssl ubuntu-drivers-common openssl software-properties-common -y
- sudo update-alternatives --install /usr/bin/python python /usr/bin/python3.7 100
-
- cd /tmp
- curl -O https://bootstrap.pypa.io/get-pip.py
- sudo python get-pip.py
-
- # add pip mirror
- mkdir -p ~/.pip
- cat > ~/.pip/pip.conf <<END
- [global]
- index-url = https://repo.huaweicloud.com/repository/pypi/simple
- trusted-host = repo.huaweicloud.com
- timeout = 120
- END
-
- # install nvidia driver if not presented
- # root@ecs-gpu-testing:~# ubuntu-drivers devices
- # == /sys/devices/pci0000:20/0000:20:00.0/0000:21:01.0 ==
- # modalias : pci:v000010DEd00001EB8sv000010DEsd000012A2bc03sc02i00
- # vendor : NVIDIA Corporation
- # driver : nvidia-driver-418 - third-party non-free
- # driver : nvidia-driver-450 - third-party non-free
- # driver : nvidia-driver-460 - third-party non-free
- # driver : nvidia-driver-450-server - distro non-free
- # driver : nvidia-driver-460-server - distro non-free
- # driver : nvidia-driver-440 - third-party non-free
- # driver : nvidia-driver-418-server - distro non-free
- # driver : nvidia-driver-465 - third-party non-free
- # driver : nvidia-driver-470 - third-party non-free recommended #pick the latest one
- # driver : nvidia-driver-410 - third-party non-free
- # driver : nvidia-driver-470-server - distro non-free
- # driver : nvidia-driver-455 - third-party non-free
- # driver : xserver-xorg-video-nouveau - distro free builtin
- # sudo apt-get install nvidia-driver-470 -y
- # nvidia-smi # run this to check the driver is working
- #root@ecs-testing:~# nvidia-smi
- #Thu Dec 30 21:06:13 2021
- #+-----------------------------------------------------------------------------+
- #| NVIDIA-SMI 460.73.01 Driver Version: 460.73.01 CUDA Version: 11.2 |
- #|-------------------------------+----------------------+----------------------+
- #| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
- #| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
- #| | | MIG M. |
- #|===============================+======================+======================|
- #| 0 Tesla T4 Off | 00000000:21:01.0 Off | 0 |
- #| N/A 61C P0 29W / 70W | 0MiB / 15109MiB | 0% Default |
- #| | | N/A |
- #+-------------------------------+----------------------+----------------------+
- #
- #+-----------------------------------------------------------------------------+
- #| Processes: |
- #| GPU GI CI PID Type Process name GPU Memory |
- #| ID ID Usage |
- #|=============================================================================|
- #| No running processes found |
- #+-----------------------------------------------------------------------------+
-
- # install cuda/cudnn/nccl2 with apt-get
- # another option is to use linux.run https://developer.download.nvidia.com/compute/cuda/11.1.0/local_installers/cuda_11.1.0_455.23.05_linux.run
- sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
- sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/ /"
- sudo add-apt-repository "deb https://developer.download.nvidia.cn/compute/machine-learning/repos/ubuntu1804/x86_64/ /"
- sudo apt-get update
- sudo apt-get -y install cuda=${CUDA_VERSION}
-
- # add cuda to path
- cat >> ~/.bash_profile <<END
- export PATH=/usr/local/cuda/bin:\$PATH
- export LD_LIBRARY_PATH=\$LD_LIBRARY_PATH:/usr/local/cuda/lib64
- END
- source ~/.bash_profile
- echo "cuda install success."
-
- sudo apt-get install -y libcudnn8=${CUDA_VERSION} libcudnn8-dev=${CUDA_VERSION} libnccl2=${LIBNCCL2_VERSION} libnccl-dev=${LIBNCCL2_VERSION}
-
- # optional (tensort for serving, openmpi for distributed training)
- # uncomment this to compile openmpi
- # cd /tmp
- # curl -O https://download.open-mpi.org/release/open-mpi/v4.0/openmpi-4.0.3.tar.gz
- # tar xvzf openmpi-4.0.3.tar.gz
- # cd openmpi-4.0.3
- # ./configure --prefix=/usr/local/openmpi
- # make
- # sudo make install
- # echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/openmpi/lib' >> ~/.bash_profile
- # echo 'export PATH=$PATH:/usr/local/openmpi/bin' >> ~/.bash_profile
- # source ~/.bash_profile
- # reference this to install tensorrt https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html#downloading
-
- echo "install mindspore gpu ${MINDSPORE_VERSION}"
- pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/${MINDSPORE_VERSION}/MindSpore/gpu/${ARCH}/${CUDA_INSTALL_PATH}/mindspore_gpu-${version_map["$PYTHON_VERSION"]}-linux_${ARCH}.whl --trusted-host ms-release.obs.cn-north-4.myhuaweicloud.com -i https://pypi.tuna.tsinghua.edu.cn/simple
-
-
- # check if it is the right mindspore version
- python -c "import mindspore;mindspore.run_check()"
-
- # check if it can be run with GPU
-
- cat > example.py <<END
- import numpy as np
- from mindspore import Tensor
- import mindspore.ops as ops
- import mindspore.context as context
-
- context.set_context(device_target="GPU")
- x = Tensor(np.ones([1,3,3,4]).astype(np.float32))
- y = Tensor(np.ones([1,3,3,4]).astype(np.float32))
- print(ops.add(x, y))
- END
-
- python example.py
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