File size: 4,430 Bytes
dfbcd52 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 | # 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"
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