mindspore/scripts/install/ubuntu-gpu-pip.sh

#!/bin/bash
# Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================

# Prepare and Install mindspore gpu by pip on Ubuntu 18.04.
#
# This file will:
#   - change deb source to huaweicloud mirror
#   - install mindspore dependencies via apt like gcc, libgmp
#   - install python3 & pip3 via apt and set it to default
#   - install CUDA by run file and cudnn via apt.
#   - install mindspore-cpu within new installed python by pip
#   - compile and install Open MPI if OPENMPI is set to on.
#
# Augments:
#   - PYTHON_VERSION: python version to install. [3.7(default), 3.8, 3.9]
#   - MINDSPORE_VERSION: mindspore version to install, >=1.6.0, required
#   - CUDA_VERSION: CUDA version to install. [10.1, 11.1 11.6(default)]
#   - OPENMPI: whether to install optional package Open MPI for distributed training. [on, off(default)]
#
# Usage:
#   Run script like `MINDSPORE_VERSION=1.7.0 bash -i ./ubuntu-gpu-pip.sh`.
#   To set augments, run it as `MINDSPORE_VERSION=1.6.0 CUDA_VERSION=10.1 OPENMPI=on bash -i ./ubuntu-gpu-pip.sh`.

set -e

PYTHON_VERSION=${PYTHON_VERSION:-3.7}
MINDSPORE_VERSION=${MINDSPORE_VERSION:EMPTY}
CUDA_VERSION=${CUDA_VERSION:-11.6}
OPENMPI=${OPENMPI:-off}
release_info=$(lsb_release -a | grep Release)
UBUNTU_VERSION=${release_info//[!0-9]/}

[[ "$UBUNTU_VERSION" == "2004" &&  "$CUDA_VERSION" == "10.1" ]] && echo "CUDA 10.1 is not supported on Ubuntu 20.04" && exit 1

version_less() {
    test "$(echo "$@" | tr ' ' '\n' | sort -rV | head -n 1)" != "$1";
}

if [ $MINDSPORE_VERSION == "EMPTY" ] || version_less "${MINDSPORE_VERSION}" "1.6.0"; then
    echo "MINDSPORE_VERSION should be >=1.6.0, please check available versions at https://www.mindspore.cn/versions."
    exit 1
fi

available_py_version=(3.7 3.8 3.9)
if [[ " ${available_py_version[*]} " != *" $PYTHON_VERSION "* ]]; then
    echo "PYTHON_VERSION is '$PYTHON_VERSION', but available versions are [${available_py_version[*]}]."
    exit 1
fi

if [[ "$PYTHON_VERSION" == "3.8" && ${MINDSPORE_VERSION:0:3} == "1.6" ]]; then
    echo "PYTHON_VERSION==3.8 is not compatible with MINDSPORE_VERSION==1.6.x, please use PYTHON_VERSION==3.7 or 3.9 for MINDSPORE_VERSION==1.6.x."
    exit 1
fi

available_cuda_version=(10.1 11.1 11.6)
if [[ " ${available_cuda_version[*]} " != *" $CUDA_VERSION "* ]]; then
    echo "CUDA_VERSION is '$CUDA_VERSION', but available versions are [${available_cuda_version[*]}]."
    exit 1
fi
declare -A minimum_driver_version_map=()
minimum_driver_version_map["10.1"]="418.39"
minimum_driver_version_map["11.1"]="450.80.02"
minimum_driver_version_map["11.6"]="510.39.01"
driver_version=$(nvidia-smi --query-gpu=driver_version --format=csv,noheader --id=0)
if [[ $driver_version < ${minimum_driver_version_map[$CUDA_VERSION]} ]]; then
    echo "CUDA $CUDA_VERSION minimum required driver version is ${minimum_driver_version_map[$CUDA_VERSION]}, \
        but current nvidia driver version is $driver_version, please upgrade your driver manually."
    exit 1
fi
cuda_name="cuda-$CUDA_VERSION"

declare -A version_map=()
version_map["3.7"]="${MINDSPORE_VERSION/-/}-cp37-cp37m"
version_map["3.8"]="${MINDSPORE_VERSION/-/}-cp38-cp38"
version_map["3.9"]="${MINDSPORE_VERSION/-/}-cp39-cp39"

# add value to environment variable if value is not in it
add_env() {
    local name=$1
    if [[ ":${!name}:" != *":$2:"* ]]; then
        echo -e "export $1=$2:\$$1" >> ~/.bashrc
    fi
}

# 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

sudo apt-get install curl make gcc-7 libgmp-dev -y

# python
sudo add-apt-repository -y ppa:deadsnakes/ppa
sudo apt-get install python$PYTHON_VERSION python$PYTHON_VERSION-distutils python3-pip -y
sudo update-alternatives --install /usr/bin/python python /usr/bin/python$PYTHON_VERSION 100
# pip
python -m pip install -U pip -i https://pypi.tuna.tsinghua.edu.cn/simple
echo -e "alias pip='python -m pip'" >> ~/.bashrc
python -m pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple

# install cuda/cudnn
echo "installing CUDA and cuDNN"
cd /tmp
declare -A cuda_url_map=()
cuda_url_map["10.1"]=https://developer.download.nvidia.cn/compute/cuda/10.1/Prod/local_installers/cuda_10.1.243_418.87.00_linux.run
cuda_url_map["11.1"]=https://developer.download.nvidia.cn/compute/cuda/11.1.1/local_installers/cuda_11.1.1_455.32.00_linux.run
cuda_url_map["11.6"]=https://developer.download.nvidia.cn/compute/cuda/11.6.0/local_installers/cuda_11.6.0_510.39.01_linux.run
cuda_url=${cuda_url_map[$CUDA_VERSION]}
wget $cuda_url
sudo sh ${cuda_url##*/} --silent --toolkit
cd -
sudo apt-key adv --fetch-keys https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/7fa2af80.pub
sudo add-apt-repository "deb https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/ /"
sudo add-apt-repository "deb https://developer.download.nvidia.cn/compute/machine-learning/repos/ubuntu${UBUNTU_VERSION}/x86_64/ /"
sudo apt-get update
declare -A cudnn_name_map=()
cudnn_name_map["10.1"]="libcudnn7=7.6.5.32-1+cuda10.1 libcudnn7-dev=7.6.5.32-1+cuda10.1"
cudnn_name_map["11.1"]="libcudnn8=8.0.5.39-1+cuda11.1 libcudnn8-dev=8.0.5.39-1+cuda11.1"
cudnn_name_map["11.6"]="libcudnn8=8.5.0.96-1+cuda11.6 libcudnn8-dev=8.5.0.96-1+cuda11.6"
sudo apt-get install --no-install-recommends ${cudnn_name_map[$CUDA_VERSION]} -y

# add cuda to path
set +e && source ~/.bashrc
set -e
add_env PATH /usr/local/cuda/bin
add_env LD_LIBRARY_PATH /usr/local/cuda/lib64
add_env LD_LIBRARY_PATH /usr/lib/x86_64-linux-gnu
set +e && source ~/.bashrc
set -e

# optional openmpi for distributed training
if [[ X"$OPENMPI" == "Xon" ]]; then
    echo "installing openmpi"
    cd /tmp
    curl -O https://download.open-mpi.org/release/open-mpi/v4.0/openmpi-4.0.3.tar.gz
    tar xzf openmpi-4.0.3.tar.gz
    cd openmpi-4.0.3
    ./configure --prefix=/usr/local/openmpi-4.0.3
    make
    sudo make install
    add_env PATH /usr/local/openmpi-4.0.3/bin
    add_env LD_LIBRARY_PATH /usr/local/openmpi-4.0.3/lib
fi

arch=`uname -m`
python -m pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/${MINDSPORE_VERSION}/MindSpore/gpu/${arch}/${cuda_name}/mindspore_gpu-${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 mindspore installation
python -c "import mindspore;mindspore.run_check()"

# check if it can be run with GPU
cd /tmp
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
cd -