# vllm: x86_64=0.20.2, aarch64=0.20.2

ARG CUDA_VERSION=13.0.2
FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu24.04

ARG CUDA_VERSION
ARG PYTHON_VERSION=3.12
ARG TORCH_VERSION=2.11.0
ARG TORCH_VISION_VERSION=0.26.0
ARG TORCH_AUDIO_VERSION=2.11.0
ARG TRANSFORMERS_VERSION=5.3.0
ARG VLLM_VERSION=0.23.0
ARG TRL_VERSION=0.27.0
ARG TRANSFORMER_ENGINE_VERSION=v2.15
ARG FLASH_ATTENTION_VERSION=2.8.3
ARG NSIGHT_VERSION=2025.6.1
ARG MCORE_VERSION=core_v0.18.0
ARG VERL_VERSION=v0.7.1
ARG DEBIAN_FRONTEND=noninteractive
ARG PIP_NO_CACHE_DIR=1
ARG APT_MIRROR=""
# PEP 668: Ubuntu 24.04 blocks system-wide pip installs; override for Docker
ENV PIP_BREAK_SYSTEM_PACKAGES=1

RUN if [ -n "${APT_MIRROR}" ]; then \
    sed -i "s@http://.*archive.ubuntu.com@${APT_MIRROR}@g" /etc/apt/sources.list.d/ubuntu.sources; \
    fi

RUN apt-get update && apt-get install -y \
    git \
    wget \
    curl \
    cmake \
    build-essential \
    libibverbs-dev \
    libnuma-dev \
    librdmacm-dev \
    numactl \
    software-properties-common \
    vim \
    python${PYTHON_VERSION} \
    python${PYTHON_VERSION}-dev \
    && rm -rf /var/lib/apt/lists/*

RUN wget https://bootstrap.pypa.io/get-pip.py && \
    python${PYTHON_VERSION} get-pip.py && \
    rm get-pip.py

RUN ln -sf /usr/bin/python${PYTHON_VERSION} /usr/bin/python3 && \
    ln -sf /usr/bin/python${PYTHON_VERSION} /usr/bin/python

RUN pip install torch==${TORCH_VERSION} torchvision==${TORCH_VISION_VERSION} torchaudio==${TORCH_AUDIO_VERSION} --index-url https://download.pytorch.org/whl/cu130

RUN pip install pybind11 wheel

# =========================
# Install cuDNN (network repo)
# =========================
RUN ARCH=$(if [ "$(uname -m)" = "aarch64" ]; then echo "sbsa"; else echo "x86_64"; fi) && \
    CUDA_VERSION_MAJOR=$(echo ${CUDA_VERSION} | cut -d '.' -f 1) && \
    wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/${ARCH}/cuda-keyring_1.1-1_all.deb && \
    sed -i '/developer\.download\.nvidia\.com\/compute\/cuda\/repos/d' /etc/apt/sources.list.d/* && \
    dpkg -i cuda-keyring_1.1-1_all.deb && \
    apt-get update && \
    apt-get -y --allow-downgrades --allow-change-held-packages install \
    cudnn9-cuda-${CUDA_VERSION_MAJOR} \
    libcudnn9-cuda-${CUDA_VERSION_MAJOR} \
    libcudnn9-dev-cuda-${CUDA_VERSION_MAJOR} \
    libcudnn9-headers-cuda-${CUDA_VERSION_MAJOR} && \
    rm -f cuda-keyring_1.1-1_all.deb && \
    rm -rf /var/lib/apt/lists/*

RUN pip install nvidia-mathdx ninja

RUN MAX_JOBS=256 pip install -v --disable-pip-version-check --no-build-isolation \
    --config-settings "--build-option=--cpp_ext" \
    --config-settings "--build-option=--cuda_ext" \
    git+https://github.com/NVIDIA/apex.git

RUN export NVTE_FRAMEWORK=pytorch && \
    MAX_JOBS=256 NVTE_BUILD_THREADS_PER_JOB=4 \
    pip3 install --resume-retries 999 --no-build-isolation git+https://github.com/NVIDIA/TransformerEngine.git@${TRANSFORMER_ENGINE_VERSION}

    RUN pip install codetiming mathruler pylatexenc cachetools pytest-asyncio

RUN export FLASH_ATTENTION_FORCE_BUILD="TRUE" && MAX_JOBS=32 pip install --no-build-isolation flash_attn==${FLASH_ATTENTION_VERSION}

RUN NSIGHT_VERSION=2025.6.1_2025.6.1.190-1_$(if [ "$(uname -m)" = "aarch64" ]; then echo "arm64"; else echo "amd64"; fi) && \
    wget https://developer.nvidia.com/downloads/assets/tools/secure/nsight-systems/2025_6/nsight-systems-${NSIGHT_VERSION}.deb && \
    apt-get update && apt-get install -y libxcb-cursor0 && \
    apt-get install -y ./nsight-systems-${NSIGHT_VERSION}.deb && \
    rm -rf /usr/local/cuda/bin/nsys && \
    ln -s /opt/nvidia/nsight-systems/2025.6.1/nsys  /usr/local/cuda/bin/nsys && \
    rm -rf /usr/local/cuda/bin/nsys-ui && \
    ln -s /opt/nvidia/nsight-systems/2025.6.1/nsys-ui /usr/local/cuda/bin/nsys-ui && \
    rm nsight-systems-${NSIGHT_VERSION}.deb && \
    rm -rf /var/lib/apt/lists/*

# =========================
# Install DeepEP
# =========================
RUN cd /home && mkdir -p dpsk_a2a && cd dpsk_a2a && \
    git clone -b v2.5.1 https://github.com/NVIDIA/gdrcopy.git && \
    cd gdrcopy && \
    make prefix=/usr/local lib_install && \
    cd .. && rm -rf gdrcopy && \
    git clone -b hybrid-ep https://github.com/deepseek-ai/DeepEP.git && \
    export NVSHMEM_DIR=/usr/local/lib/python3.12/dist-packages/nvidia/nvshmem && \
    export LD_LIBRARY_PATH="${NVSHMEM_DIR}/lib:$LD_LIBRARY_PATH" && \
    export PATH="${NVSHMEM_DIR}/bin:$PATH" && \
    cd ${NVSHMEM_DIR}/lib && \
    ln -sf libnvshmem_host.so.3 libnvshmem_host.so && \
    cd /home/dpsk_a2a/DeepEP && \
    git checkout 3f601f7ac1c062c46502646ff04c535013bfca00 && \
    CUDA_TARGET=$(uname -m | sed 's/aarch64/sbsa-linux/;s/x86_64/x86_64-linux/') && \
    export CPATH=/usr/local/cuda/targets/${CUDA_TARGET}/include/cccl:$CPATH && \
    TORCH_CUDA_ARCH_LIST="9.0;10.0" python setup.py install

# Debian python3-jwt has no pip RECORD; vllm cannot uninstall it when upgrading PyJWT.
RUN apt-get update && \
    apt-get remove -y --purge python3-jwt 2>/dev/null || true && \
    rm -rf /var/lib/apt/lists/* && \
    pip install --ignore-installed PyJWT

# Apply two unmerged vLLM fixes required by verl weight-sync flows by patching in each
# PR's cumulative diff (GitHub ".diff") with `git apply --3way`, rather than cherry-picking
# commits or ranges. These PR branches are periodically rebased and even contain
# "Merge branch 'main'" commits, so a "v${VLLM_VERSION}_fix..pr" range replays hundreds of
# unrelated main commits and aborts on an empty/merge commit. The net diff carries only the
# PR's own changes, so it stays small and stable regardless of how the branch is rebased.
#   #44483: illegal memory access during a partial wake_up (sleep mode).
#   #45589: FlashInfer-TRTLLM MoE load OOM.
RUN git clone https://github.com/vllm-project/vllm.git && cd vllm && \
    git checkout v${VLLM_VERSION} && \
    curl -fsSL https://github.com/vllm-project/vllm/pull/44483.diff -o /tmp/vllm-pr-44483.diff && \
    git apply --3way --whitespace=nowarn /tmp/vllm-pr-44483.diff && \
    curl -fsSL https://github.com/vllm-project/vllm/pull/45589.diff -o /tmp/vllm-pr-45589.diff && \
    git apply --3way --whitespace=nowarn /tmp/vllm-pr-45589.diff && \
    MAX_JOBS=256 pip install -e .

RUN pip3 install --no-deps trl==${TRL_VERSION}

RUN pip3 install nvtx matplotlib liger_kernel

RUN pip install transformers==${TRANSFORMERS_VERSION}

RUN pip install -U git+https://github.com/ISEEKYAN/mbridge.git@main

RUN pip install --no-deps megatron-bridge==0.5.0

RUN pip install --no-deps git+https://github.com/NVIDIA/Megatron-LM.git@${MCORE_VERSION}

RUN pip install torchcodec --index-url=https://download.pytorch.org/whl/cu130

RUN apt-get update && \
    apt-get install -y ffmpeg && \
    ffmpeg -decoders | grep -i nvidia && \
    rm -rf /var/lib/apt/lists/*

RUN pip install qwen-vl-utils==0.0.14

RUN pip install git+https://github.com/verl-project/verl.git@${VERL_VERSION} && pip uninstall -y verl

RUN CUDA_VERSION_MAJOR=$(echo ${CUDA_VERSION} | cut -d '.' -f 1) && \
    CUDNN_PKG=libcudnn9-cuda-${CUDA_VERSION_MAJOR} && \
    CUDNN_VERSION=$(dpkg-query -W -f='${Version}' "${CUDNN_PKG}" 2>/dev/null | sed 's/-[0-9]*$//') && \
    if [ -z "${CUDNN_VERSION}" ]; then \
        CUDNN_HDR=$(find /usr/include -name cudnn_version.h | head -1) && \
        CUDNN_VERSION=$(grep -E '^#define CUDNN_(MAJOR|MINOR|PATCHLEVEL) ' "${CUDNN_HDR}" | awk '{print $3}' | paste -sd. -); \
    fi && \
    pip install "nvidia-cudnn-cu${CUDA_VERSION_MAJOR}>=${CUDNN_VERSION}"

# Override NCCL to >= 2.29.7 for ncclCommSuspend / ncclCommResume
# (RFC: https://github.com/verl-project/verl/issues/6266).
# TODO(xiefan46): remove once torch pin bumps to >= 2.12.0.
RUN pip install --no-deps --upgrade "nvidia-nccl-cu13>=2.29.7,<3.0"