#!/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 environment for mindspore gpu compilation on Ubuntu 18.04.
#
# This file will:
#   - change deb source to huaweicloud mirror
#   - install compile dependencies via apt like cmake, gcc
#   - install python3 & pip3 via apt and set it to default
#   - install CUDA by run file and cudnn via apt.
#   - compile and install Open MPI if OPENMPI is set to on.
#   - install LLVM if LLVM is set to on.
#
# Augments:
#   - PYTHON_VERSION: python version to install. [3.7(default), 3.8, 3.9]
#   - 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)]
#   - LLVM: whether to install optional dependency LLVM for graph kernel fusion. [on, off(default)]
#
# Usage:
#   Run script like `bash -i ./ubuntu-gpu-source.sh`.
#   To set augments, run it as `PYTHON_VERSION=3.9 CUDA_VERSION=10.1 OPENMPI=on bash -i ./ubuntu-gpu-source.sh`.

set -e

PYTHON_VERSION=${PYTHON_VERSION:-3.7}
CUDA_VERSION=${CUDA_VERSION:-11.6}
OPENMPI=${OPENMPI:-off}
LLVM=${LLVM:-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

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
available_cuda_version=(10.1 11.1)
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

# 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

# base packages
sudo apt-get update
sudo apt-get install software-properties-common lsb-release -y
sudo apt-get install curl tcl automake autoconf libtool gcc-7 git libgmp-dev patch libnuma-dev flex -y

# cmake
wget -O - https://apt.kitware.com/keys/kitware-archive-latest.asc 2>/dev/null | sudo apt-key add -
sudo apt-add-repository "deb https://apt.kitware.com/ubuntu/ $(lsb_release -cs) main"
sudo apt-get install cmake -y

# optional dependency LLVM for graph-computation fusion
if [[ X"$LLVM" == "Xon" ]]; then
    wget -O - https://apt.llvm.org/llvm-snapshot.gpg.key | sudo apt-key add -
    sudo add-apt-repository "deb http://apt.llvm.org/bionic/ llvm-toolchain-bionic-12 main"
    sudo apt-get update
    sudo apt-get install llvm-12-dev -y
fi

# optional openmpi for distributed training
if [[ X"$OPENMPI" == "Xon" ]]; then
    echo "installing openmpi"
    origin_wd=$PWD
    cd /tmp
    curl -O https://download.open-mpi.org/release/open-mpi/v4.1/openmpi-4.1.4.tar.gz
    tar xzf openmpi-4.1.4.tar.gz
    cd openmpi-4.1.4
    ./configure --prefix=/usr/local/openmpi-4.1.4
    make
    sudo make install
    add_env PATH /usr/local/openmpi-4.1.4/bin
    add_env LD_LIBRARY_PATH /usr/local/openmpi-4.1.4/lib
    cd $origin_wd
fi

# python
sudo add-apt-repository -y ppa:deadsnakes/ppa
sudo apt-get install python$PYTHON_VERSION python$PYTHON_VERSION-dev 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
cd /tmp
echo "installing CUDA and cuDNN"
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

# wheel
python -m pip install wheel
# python 3.9 needs setuptools>44.0
python -m pip install -U setuptools

echo "The environment is ready to clone and compile mindspore."