# sgl0512

FROM lmsysorg/sglang:v0.5.12

ARG CUDA_VERSION=13.0.2
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

# =========================
# 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/*

ARG PIP_NO_CACHE_DIR=1

RUN pip install pybind11 nvidia-mathdx

RUN MAX_JOBS=128 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=128 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 --upgrade transformers tokenizers

RUN pip install codetiming mathruler pylatexenc cachetools pytest-asyncio

RUN if [ "$(uname -m)" = "aarch64" ]; then \
        pip show "flash-attn-4"; \
    else \
        pip uninstall -y "flash-attn-4"; \
    fi

RUN pip install --no-build-isolation flash_attn==2.8.3

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

# sglang image has already installed DeepEP

RUN pip3 install --no-deps trl==0.27.0

RUN pip3 install nvtx matplotlib liger_kernel

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

RUN pip install qwen-vl-utils==0.0.14

RUN if [ "$(uname -m)" = "aarch64" ]; then \
        pip show "sglang-kernel"; \
    else \
        wget https://github.com/sgl-project/whl/releases/download/v0.4.2.post2/sglang_kernel-0.4.2.post2+cu130-cp310-abi3-manylinux2014_x86_64.whl#sha256=4e7ce619274234d182b20da883fcf1d20e7e55cbea90d62244e2b6a3d6c0fc85 && \
        pip install sglang_kernel-0.4.2.post2+cu130-cp310-abi3-manylinux2014_x86_64.whl --force-reinstall; \
    fi

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 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"