# syntax=docker/dockerfile:1

# NOTE: Building this image require's docker version >= 23.0.
#
# For reference:
# - https://docs.docker.com/build/dockerfile/frontend/#stable-channel
ARG CUDA_VERSION=12.1.0
FROM nvidia/cuda:${CUDA_VERSION}-cudnn8-devel-ubuntu22.04
ARG HTTP_PROXY
ARG HTTPS_PROXY
ENV http_proxy=${HTTP_PROXY}
ENV https_proxy=${HTTPS_PROXY}
ARG DEBIAN_FRONTEND="noninteractive"
ENV DEBIAN_FRONTEND=${DEBIAN_FRONTEND}
ENV MAMBA_ROOT_PREFIX=~/micromamba
ARG ROOT_PASSWD="root"
ENV ROOT_PASSWD=${ROOT_PASSWD}
WORKDIR /root
SHELL ["/bin/bash", "-c"]
COPY id_rsa.pub /root/.ssh/id_rsa.pub

# base tools
RUN apt-get update && \
    apt-get install -y rdma-core ibverbs-utils perftest libibverbs-dev infiniband-diags && \
    apt-get install -y wget curl htop jq vim bash libaio-dev build-essential openssh-server python3 python3-pip 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 && \
    wget -O - https://apt.kitware.com/keys/kitware-archive-latest.asc | sudo apt-key add - && \
    sudo apt-add-repository "deb https://apt.kitware.com/ubuntu/ $(lsb_release -cs) main" && \
    sudo apt-get update && \
    sudo apt-get install -y cmake && \
    sed -i 's/#PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config && \
    sed -i 's/#PasswordAuthentication yes/PasswordAuthentication yes/' /etc/ssh/sshd_config && \
    sed -i 's/PubkeyAuthentication no/PubkeyAuthentication yes/' /etc/ssh/sshd_config && \
    sed -i 's/^#Port 22/Port 22/' /etc/ssh/sshd_config && \
    mkdir /var/run/sshd && \
    echo "root:${ROOT_PASSWD}" | chpasswd && \
    mkdir -p ~/.pip && \
    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 && \
    conda init bash && \
    ln -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh && \
    echo ". /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc && \
    cat <<EOF > ~/.condarc
channels:
  - conda-forge
  - bioconda
  - pytorch
  - pytorch-nightly
  - nvidia
  - defaults
show_channel_urls: true
EOF

# reference: https://github.com/huggingface/transformers/blob/main/docker/transformers-pytorch-deepspeed-latest-gpu/Dockerfile
# PyTorch
ARG CONDA_ENV_NAME="deepspeed"
ENV CONDA_ENV_NAME=${CONDA_ENV_NAME}
ARG PYTHON_VERSION=3.10
ENV PYTHON_VERSION=${PYTHON_VERSION}
ENV PATH=/opt/conda/envs/${CONDA_ENV_NAME}/bin:/usr/bin:/opt/conda/bin:$PATH
ENV DEEPSPEED_PYTHON="/opt/conda/envs/${CONDA_ENV_NAME}/bin/python3"
ENV REF='main'
ENV STAGE_DIR=/tmp
ENV OPENMPI_BASEVERSION=4.1
ENV OPENMPI_VERSION=${OPENMPI_BASEVERSION}.6
ARG CUDA='cu121'
ENV CUDA=${CUDA}
ARG PYTORCH_VERSION=2.3.1
ENV PYTORCH_VERSION=${PYTORCH_VERSION}
ARG TORCHVISION_VERSION=0.18.1
ENV TORCHVISION_VERSION=${TORCHVISION_VERSION}
ARG TORCHAUDIO_VERSION=2.3.1
ENV TORCHAUDIO_VERSION=${TORCHAUDIO_VERSION}
ARG PYTORCH_CUDA_VERSION=12.1
ENV PYTORCH_CUDA_VERSION=${PYTORCH_CUDA_VERSION}
ARG SETUPTOOLS_VERSION=69.5.1
ENV SETUPTOOLS_VERSION=${SETUPTOOLS_VERSION}
ARG USE_CUDA=1
ENV USE_CUDA=${USE_CUDA}
ARG USE_ROCM=0
ENV USE_ROCM=${USE_ROCM}
ARG USE_XPU=0
ENV USE_XPU=${USE_XPU}
ARG _GLIBCXX_USE_CXX11_ABI=1
ENV _GLIBCXX_USE_CXX11_ABI=${_GLIBCXX_USE_CXX11_ABI}
RUN source /opt/conda/etc/profile.d/conda.sh && \
    conda create -n ${CONDA_ENV_NAME} python=${PYTHON_VERSION} -c conda-forge -y && \
    echo "conda activate ${CONDA_ENV_NAME}" >> ~/.bashrc && \
    which python > ~/python_path.txt && \
    conda activate ${CONDA_ENV_NAME} && \
    git clone https://github.com/ninja-build/ninja.git ${STAGE_DIR}/ninja && \
    cd ${STAGE_DIR}/ninja && \
    git clone https://github.com/google/googletest.git && \
    python ./configure.py --bootstrap && \
    conda run -n ${CONDA_ENV_NAME} bash -c "CXXFLAGS='-pthread' LDFLAGS='-pthread' python ./configure.py --bootstrap --gtest-source-dir=$(pwd)/googletest" && \
    ./ninja all && \
    ./ninja_test && \
    python3 -m pip install --no-cache-dir --upgrade pip && \
    python3 -m pip install open_clip_torch nvidia-ml-py3 opencv-contrib-python && \
    conda clean -afy && \
    git clone https://github.com/huggingface/transformers && cd transformers && git checkout $REF && cd .. && \
    python -m pip install setuptools==${SETUPTOOLS_VERSION} && \
    python3 -m pip install --no-cache-dir ./transformers[deepspeed-testing] && \
    python3 -m pip uninstall -y torch torchvision torchaudio && \
    python3 -m pip install torch==${PYTORCH_VERSION}+${CUDA} torchvision==${TORCHVISION_VERSION}+${CUDA} torchaudio==${TORCHAUDIO_VERSION} xformers --extra-index-url https://download.pytorch.org/whl/${CUDA} && \
    python3 -m pip install --no-cache-dir git+https://github.com/huggingface/accelerate@main#egg=accelerate && \
    python3 -m pip uninstall -y transformer-engine && \
    python3 -m pip uninstall -y torch-tensorrt && \
    python3 -m pip uninstall -y apex

# install apex
RUN source /opt/conda/etc/profile.d/conda.sh && \
    conda activate ${CONDA_ENV_NAME} && \
    git clone https://github.com/NVIDIA/apex ${STAGE_DIR}/apex && \
    cd apex && \
    MAX_JOBS=1 python3 -m pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" ./ && \
    python -c "import apex.amp; print('Apex is installed and the amp module is available.')" && \
    cd .. && \
    rm -rf ${STAGE_DIR}/apex

ENV MLNX_OFED_VERSION=5.8-4.1.5.0
RUN source /opt/conda/etc/profile.d/conda.sh && \
    conda activate ${CONDA_ENV_NAME} && \
    mkdir -p ${STAGE_DIR} && \
    wget -q -O - http://www.mellanox.com/downloads/ofed/MLNX_OFED-${MLNX_OFED_VERSION}/MLNX_OFED_LINUX-${MLNX_OFED_VERSION}-ubuntu22.04-x86_64.tgz | tar xzf - && \
    cd MLNX_OFED_LINUX-${MLNX_OFED_VERSION}-ubuntu22.04-x86_64 && \
    ./mlnxofedinstall --user-space-only --without-fw-update --all -q && \
    cd ${STAGE_DIR} && \
    rm -rf ${STAGE_DIR}/MLNX_OFED_LINUX-${MLNX_OFED_VERSION}-ubuntu22.04-x86_64*

ENV NV_PEER_MEM_VERSION=1.2
ENV NV_PEER_MEM_TAG=${NV_PEER_MEM_VERSION}-0
RUN source /opt/conda/etc/profile.d/conda.sh && \
    conda activate ${CONDA_ENV_NAME} && \
    rm -rf ${STAGE_DIR} && \
    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

# install mpi
ENV PATH=/usr/local/mpi/bin:${PATH} 
ENV LD_LIBRARY_PATH=/usr/local/lib:/usr/local/mpi/lib:/usr/local/mpi/lib64:${LD_LIBRARY_PATH}
RUN source /opt/conda/etc/profile.d/conda.sh && \
    conda activate ${CONDA_ENV_NAME} && \
    rm -rf ${STAGE_DIR} && \
    mkdir -p ${STAGE_DIR} && \
    cd ${STAGE_DIR} && \
    wget -q -O - https://download.open-mpi.org/release/open-mpi/v${OPENMPI_BASEVERSION}/openmpi-${OPENMPI_VERSION}.tar.gz | tar xzf - && \
    cd openmpi-${OPENMPI_VERSION} && \
    ./configure --prefix=/usr/local/openmpi-${OPENMPI_VERSION} && \
    make -j"$(nproc)" install && \
    ln -s /usr/local/openmpi-${OPENMPI_VERSION} /usr/local/mpi && \
    test -f /usr/local/mpi/bin/mpic++ && \
    cd ${STAGE_DIR} && \
    rm -r ${STAGE_DIR}/openmpi-${OPENMPI_VERSION} && \
    mv /usr/local/mpi/bin/mpirun /usr/local/mpi/bin/mpirun.real && \
    echo '#!/bin/bash' > /usr/local/mpi/bin/mpirun && \
    echo 'mpirun.real --allow-run-as-root --prefix /usr/local/mpi "$@"' >> /usr/local/mpi/bin/mpirun && \
    chmod a+x /usr/local/mpi/bin/mpirun

# SSH daemon port inside container cannot conflict with host OS port
# ENV SSH_PORT=2222
# RUN source /opt/conda/etc/profile.d/conda.sh && \
#     conda activate ${CONDA_ENV_NAME} && \
#     cat /etc/ssh/sshd_config > ${STAGE_DIR}/sshd_config && \
#     sed "0,/^Port 22/s//Port ${SSH_PORT}/" ${STAGE_DIR}/sshd_config > /etc/ssh/sshd_config

RUN source /opt/conda/etc/profile.d/conda.sh && \
    conda activate ${CONDA_ENV_NAME} && \
    useradd --create-home --uid 1000 --shell /bin/bash deepspeed && \
    usermod -aG sudo deepspeed && \
    echo "deepspeed ALL=(ALL) NOPASSWD: ALL" >> /etc/sudoers

# install cutlass https://github.com/NVIDIA/cutlass
# H100: architecture is Hopper (cutlass need add : cmake .. -DCUTLASS_NVCC_ARCHS="90a" )
# A100: architecture is Ampere 
# V100: architecture is Volta 
# T4: architecture is Turing 
# ENV CUDACXX=${CUDA_INSTALL_PATH}/bin/nvcc
# 70：适用于 NVIDIA Volta 架构（如 Tesla V100）。
# 75：适用于 NVIDIA Turing 架构（如 Tesla T4）。
# 80：适用于 NVIDIA Ampere 架构（如 A100）。
# 90a：适用于 NVIDIA Hopper 架构（如 H100）。
# 89:GeForce RTX 4090 
ARG DCUTLASS_NVCC_ARCHS="80;89;90a"
ENV DCUTLASS_NVCC_ARCHS=${DCUTLASS_NVCC_ARCHS}
RUN source /opt/conda/etc/profile.d/conda.sh && \
    conda activate ${CONDA_ENV_NAME} && \
    git clone https://github.com/NVIDIA/cutlass /opt/cutlass && \
    cd /opt/cutlass && \
    git checkout . && \
    git checkout master && \
    mkdir build && \
    cd build && \
    cmake .. -DCUTLASS_NVCC_ARCHS=${DCUTLASS_NVCC_ARCHS} -DCUTLASS_ENABLE_TESTS=OFF -DCUTLASS_UNITY_BUILD_ENABLED=ON && \
    make -j"$(nproc)" install && \
    cd ..

# Some Packages from https://github.com/microsoft/DeepSpeed/blob/master/docker/Dockerfile
# RUN source /opt/conda/etc/profile.d/conda.sh && \
#     conda activate ${CONDA_ENV_NAME} && \
#     apt-get update && \
#     apt-get install -y --no-install-recommends libsndfile-dev libcupti-dev libjpeg-dev libpng-dev screen libaio-dev && \
#     python -m pip install pipdeptree psutil yappi cffi ipdb pandas matplotlib py3nvml pyarrow graphviz astor boto3 tqdm sentencepiece msgpack requests pandas sphinx sphinx_rtd_theme scipy numpy scikit-learn nvidia-ml-py3 mpi4py

# install deepspeed step 1
RUN source /opt/conda/etc/profile.d/conda.sh && \
    conda activate ${CONDA_ENV_NAME} && \
    /opt/conda/envs/${CONDA_ENV_NAME}/bin/python -m pip install setuptools==${SETUPTOOLS_VERSION} && \
    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

# install deepspeed step 2
ARG CUDA_ARCH_LIST="80;86;89;90"
ENV CUDA_ARCH_LIST=${CUDA_ARCH_LIST}
RUN source /opt/conda/etc/profile.d/conda.sh && \
    conda activate ${CONDA_ENV_NAME} && \
    git clone https://github.com/microsoft/DeepSpeed-Kernels.git ${STAGE_DIR}/DeepSpeed-Kernels && \
    cd ${STAGE_DIR}/DeepSpeed-Kernels && \
    CUDA_ARCH_LIST=${CUDA_ARCH_LIST} python -m pip install -v .

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=${HOSTFILE_CONTENT}
ENV CUTLASS_PATH='/opt/cutlass'
ENV CUDA_HOME='/usr/local/cuda'
ENV LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
ENV PATH=${CUDA_HOME}/bin:${PATH}

# install deepspeed step 3
RUN source /opt/conda/etc/profile.d/conda.sh && \
    conda activate ${CONDA_ENV_NAME} && \
    git clone https://github.com/microsoft/DeepSpeed.git ${STAGE_DIR}/DeepSpeed && \
    cd ${STAGE_DIR}/DeepSpeed && \
    git checkout ${DEEPSPEED_VERSION} && \
    sed 's/pip install/python -m pip install/' install.sh > install_modified.sh && \
    chmod +x ./install_modified.sh && \
    if [ -n "${HOSTFILE_CONTENT}" ]; then \
        echo "${HOSTFILE_CONTENT}" > /tmp/hostfile && \
        INSTALL_CMD="./install_modified.sh ${DEEPSPEED_INSTALL_FLAGS} --hostfile /tmp/hostfile"; \
    else \
        INSTALL_CMD="./install_modified.sh ${DEEPSPEED_INSTALL_FLAGS}"; \
    fi && \
    eval $INSTALL_CMD && \
    cat <<EOF > ~/compile_deepspeed_ops.py
import deepspeed

def compile_ops():
    builders = [
        deepspeed.ops.op_builder.AsyncIOBuilder,
        deepspeed.ops.op_builder.FusedAdamBuilder,
        deepspeed.ops.op_builder.CPUAdamBuilder,
        deepspeed.ops.op_builder.CPUAdagradBuilder,
        deepspeed.ops.op_builder.CPULionBuilder,
        deepspeed.ops.op_builder.EvoformerAttnBuilder,
        deepspeed.ops.op_builder.FPQuantizerBuilder,
        deepspeed.ops.op_builder.FusedLambBuilder,
        deepspeed.ops.op_builder.FusedLionBuilder,
        deepspeed.ops.op_builder.QuantizerBuilder,
        deepspeed.ops.op_builder.RaggedOpsBuilder,
        deepspeed.ops.op_builder.RandomLTDBuilder,
        deepspeed.ops.op_builder.SparseAttnBuilder,
        deepspeed.ops.op_builder.SpatialInferenceBuilder,
        deepspeed.ops.op_builder.TransformerBuilder,
        deepspeed.ops.op_builder.StochasticTransformerBuilder,
    ]
    
    for builder in builders:
        print(f"Compiling {builder.__name__}")
        builder().load()

if __name__ == "__main__":
    compile_ops()
EOF && \
    python compile_deepspeed_ops.py && \
    ds_report

# install transformers and flash-attn
RUN source /opt/conda/etc/profile.d/conda.sh && \
    conda activate ${CONDA_ENV_NAME} && \
    git clone https://github.com/huggingface/transformers ${STAGE_DIR}/transformers && \
    cd ${STAGE_DIR}/transformers && \
    python3 ./setup.py develop && \
    python3 -m pip install -U --no-cache-dir "pydantic<2" && \
    pip install flash-attn --no-build-isolation -i https://pypi.org/simple/ --trusted-host pypi.org

# other packages
ENV TORCH_CUDA_ARCH_LIST="80;86;89;90"
RUN source /opt/conda/etc/profile.d/conda.sh && \
    conda activate ${CONDA_ENV_NAME} && \
    pip3 install optimum && \
    pip3 install peft tiktoken tqdm matplotlib seaborn numpy pandas scikit-learn diffusers huggingface_hub spacy blobfile pycocotools open_clip_torch zstandard -i https://pypi.org/simple/ --trusted-host pypi.org

ARG DEEPSPEED_TRAIN='/data/train_data'
ENV DEEPSPEED_TRAIN=DEEPSPEED_TRAIN
ARG DEEPSPEED_VALIDATION='/data/validation_data'
ENV DEEPSPEED_VALIDATION=DEEPSPEED_VALIDATION
ARG NCCL_SOCKET_IFNAME='eth0'

CMD ["/usr/sbin/sshd", "-D"]
# CMD ["/bin/bash", "-c", "/usr/sbin/sshd -D & while true; do sleep 1000; done"]