ARG REGISTRY=quay.io
ARG OWNER=jupyter
ARG LABEL=notebook
ARG VERSION
ARG BASE_CONTAINER=$REGISTRY/$OWNER/$LABEL:$VERSION
FROM $BASE_CONTAINER
ARG HTTP_PROXY
ARG HTTPS_PROXY
ENV http_proxy=${HTTP_PROXY}
ENV https_proxy=${HTTPS_PROXY}
ARG DEBIAN_FRONTEND="noninteractive"
ENV DEBIAN_FRONTEND=${DEBIAN_FRONTEND}
ARG ROOT_PASSWD="root"
ENV ROOT_PASSWD=${ROOT_PASSWD}
WORKDIR /root
SHELL ["/bin/bash", "-c"]

# https://network.nvidia.com/products/infiniband-drivers/linux/mlnx_ofed/
ENV MLNX_OFED_VERSION=23.10-3.2.2.0 
ENV STAGE_DIR=/tmp
RUN <<EOT
#!/bin/bash
# install Mellanox OFED prepare
apt-get update
apt install -y libnvidia-compute-535
apt-get install -y pciutils tk kmod libusb-1.0-0 tcl chrpath libpci3 bison lsof graphviz ethtool swig udev libltdl-dev libelf1 libmnl0 debhelper flex libfuse2
# install Mellanox OFED
mkdir -p ${STAGE_DIR}
wget http://www.mellanox.com/downloads/ofed/MLNX_OFED-${MLNX_OFED_VERSION}/MLNX_OFED_LINUX-${MLNX_OFED_VERSION}-ubuntu22.04-x86_64.tgz -O ${STAGE_DIR}/MLNX_OFED_LINUX-${MLNX_OFED_VERSION}-ubuntu22.04-x86_64.tgz
tar xzf ${STAGE_DIR}/MLNX_OFED_LINUX-${MLNX_OFED_VERSION}-ubuntu22.04-x86_64.tgz -C ${STAGE_DIR}
cd ${STAGE_DIR}/MLNX_OFED_LINUX-${MLNX_OFED_VERSION}-ubuntu22.04-x86_64
./mlnxofedinstall --user-space-only --without-fw-update --all -q > ${STAGE_DIR}/mlnxofedinstall.log 2>&1
cd ${STAGE_DIR} 
rm -rf ${STAGE_DIR}/MLNX_OFED_LINUX-${MLNX_OFED_VERSION}-ubuntu22.04-x86_64*
EOT

ARG NV_PEER_MEM_VERSION="1.2"
ENV NV_PEER_MEM_VERSION=${NV_PEER_MEM_VERSION}
ENV NV_PEER_MEM_TAG=${NV_PEER_MEM_VERSION}-0
RUN <<EOT
#!/bin/bash
# install nv_peer_mem
mkdir -p ${STAGE_DIR}
git clone https://github.com/Mellanox/nv_peer_memory.git --branch ${NV_PEER_MEM_TAG} ${STAGE_DIR}/nv_peer_memory
cd ${STAGE_DIR}/nv_peer_memory
./build_module.sh
cd ${STAGE_DIR}
tar xzf ${STAGE_DIR}/nvidia-peer-memory_${NV_PEER_MEM_VERSION}.orig.tar.gz
cd ${STAGE_DIR}/nvidia-peer-memory-${NV_PEER_MEM_VERSION}
apt-get update
apt --fix-broken install -y
apt-get install -y dkms
dpkg-buildpackage -us -uc
dpkg -i ${STAGE_DIR}/nvidia-peer-memory_${NV_PEER_MEM_TAG}_all.deb
EOT

# base tools
ENV SSH_PORT=2222
RUN <<EOT
#!/bin/bash
apt-get update
apt-get install -y libgl1-mesa-glx bash-completion wget curl htop jq vim bash libaio-dev build-essential openssh-server openssh-client python3 python3-pip python3-venv bzip2
apt-get install -y --no-install-recommends software-properties-common build-essential autotools-dev nfs-common pdsh cmake g++ gcc curl wget vim tmux emacs less unzip htop iftop iotop ca-certificates openssh-client openssh-server rsync iputils-ping net-tools sudo llvm-dev re2c
add-apt-repository ppa:git-core/ppa -y
apt-get install -y git libnuma-dev wget
pip install pipx
pipx install nvitop
pipx ensurepath 
. ~/.bashrc
# Configure SSH for password and public key authentication
cp /etc/ssh/sshd_config /etc/ssh/sshd_config.bak
sed -i 's/#PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config
sed -i 's/#PasswordAuthentication yes/PasswordAuthentication yes/' /etc/ssh/sshd_config
sed -i 's/#PubkeyAuthentication yes/PubkeyAuthentication yes/' /etc/ssh/sshd_config
sed -i 's/^\(\s*\)GSSAPIAuthentication yes/\1GSSAPIAuthentication no/' /etc/ssh/ssh_config
sed -i "s/^#Port 22/Port ${SSH_PORT}/" /etc/ssh/sshd_config
ssh-keygen -t rsa -b 4096 -f /root/.ssh/id_rsa -q -N ""
cat /root/.ssh/id_rsa.pub >> /root/.ssh/authorized_keys
cat /root/.ssh/id_rsa.pub >> /root/.ssh/authorized_keys2
chmod 600 /root/.ssh/authorized_keys
chmod 600 /root/.ssh/authorized_keys2
mkdir /var/run/sshd
echo "root:${ROOT_PASSWD}" | chpasswd
mkdir -p ~/.pip
# install miniconda
wget -qO- https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh
bash /tmp/miniconda.sh -b -p /opt/conda 
rm /tmp/miniconda.sh 
ln -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh
echo "source /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc 
. /opt/conda/etc/profile.d/conda.sh 
conda init bash
conda config --set show_channel_urls true
# 配置 .condarc 文件
cat <<EOF > ~/.condarc
channels:
  - conda-forge
  - bioconda
  - pytorch
  - pytorch-nightly
  - nvidia
  - defaults
show_channel_urls: true
EOF
# install pixi
curl -fsSL https://pixi.sh/install.sh | bash
EOT

RUN <<EOT
#!/bin/bash
pip install -v -U git+https://github.com/facebookresearch/xformers.git@main#egg=xformers
EOT

RUN <<EOT
#!/bin/bash
pip install git+https://github.com/huggingface/transformers
python -c "from transformers import pipeline; print(pipeline('sentiment-analysis')('I love you'))"
EOT

RUN <<EOT
#!/bin/bash
git clone https://github.com/microsoft/DeepSpeed-Kernels.git ${STAGE_DIR}/DeepSpeed-Kernels
cd ${STAGE_DIR}/DeepSpeed-Kernels
python -m pip install -v .
EOT

RUN <<EOT
#!/bin/bash
git clone https://github.com/oneapi-src/oneCCL.git ${STAGE_DIR}/oneCCL
cd ${STAGE_DIR}/oneCCL
git checkout . 
git checkout master
mkdir build
cd build 
cmake .. -DCMAKE_INSTALL_PREFIX=/usr/local
make -j"$(nproc)" install
EOT

ARG DEEPSPEED_VERSION="v0.14.3"
ENV DEEPSPEED_VERSION=${DEEPSPEED_VERSION}
ARG DEEPSPEED_INSTALL_FLAGS="--allow_sudo --pip_sudo --verbose"
ENV DEEPSPEED_INSTALL_FLAGS=${DEEPSPEED_INSTALL_FLAGS}
ARG DS_BUILD_SPARSE_ATTN=0
ENV DS_BUILD_SPARSE_ATTN=${DS_BUILD_SPARSE_ATTN}
ARG DS_BUILD_FUSED_ADAM=1
ENV DS_BUILD_FUSED_ADAM=${DS_BUILD_FUSED_ADAM}
ARG DS_BUILD_CPU_ADAM=1
ENV DS_BUILD_CPU_ADAM=${DS_BUILD_CPU_ADAM}
ARG DS_BUILD_OPS=1
ENV DS_BUILD_OPS=${DS_BUILD_OPS}
ARG HOSTFILE_CONTENT=""
ENV HOSTFILE_CONTENT=${HOSTFILE_CONTENT}
ENV CUTLASS_PATH="/opt/pytorch/pytorch/third_party/cutlass"
ENV CUDA_HOME="/usr/local/cuda"
ENV LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
ENV PATH=${CUDA_HOME}/bin:${PATH}
RUN <<EOT
#!/bin/bash
git clone https://github.com/microsoft/DeepSpeed.git ${STAGE_DIR}/DeepSpeed
cd ${STAGE_DIR}/DeepSpeed
git checkout ${DEEPSPEED_VERSION}
./install.sh ${DEEPSPEED_INSTALL_FLAGS}
ds_report
EOT

RUN <<EOT
#!/bin/bash
python -m pip install --upgrade pip
python -m pip install peft tiktoken seaborn blobfile open_clip_torch zstandard mpi4py
# optimum 手动解决依赖
python -m pip install black~=23.1 ruff==0.1.5 diffusers>=0.17.0
python -m pip install --no-deps git+https://github.com/huggingface/optimum.git#egg=optimum[diffusers,quality]
python -m pip install evaluate datasets
EOT

RUN <<EOT
#!/bin/bash
# 项目目录中的定义通常会覆盖用户家目录中的定义
# 配置 .deepspeed_env 文件
cat <<EOF > ~/.deepspeed_env
TORCH_USE_CUDA_DSA=1
DEEPSPEED_VERBOSE=1
DEEPSPEED_LOG_LEVEL=DEBUG
CUTLASS_PATH=${CUTLASS_PATH}
TORCH_CUDA_ARCH_LIST=${TORCH_CUDA_ARCH_LIST}
CUDA_HOME=${CUDA_HOME}
LD_LIBRARY_PATH=${LD_LIBRARY_PATH}
EOF
unset https_proxy http_proxy
EOT

CMD ["/usr/sbin/sshd", "-D"]