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#!/bin/bash
set -ex
TRT_VER="10.13.3.9"
# Align with the pre-installed cuDNN / cuBLAS / NCCL versions from
# https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel-25-10.html#rel-25-10
CUDA_VER="13.0" # 13.0.2
# Keep the installation for cuDNN if users want to install PyTorch with source codes.
# PyTorch 2.x can compile with cuDNN v9.
CUDNN_VER="9.14.0.64-1"
NCCL_VER="2.27.7-1+cuda13.0"
CUBLAS_VER="13.1.0.3-1"
# Align with the pre-installed CUDA / NVCC / NVRTC versions from
# https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html
NVRTC_VER="13.0.88-1"
CUDA_RUNTIME="13.0.96-1"
CUDA_DRIVER_VERSION="580.95.05-1.el8"
for i in "$@"; do
case $i in
--TRT_VER=?*) TRT_VER="${i#*=}";;
--CUDA_VER=?*) CUDA_VER="${i#*=}";;
--CUDNN_VER=?*) CUDNN_VER="${i#*=}";;
--NCCL_VER=?*) NCCL_VER="${i#*=}";;
--CUBLAS_VER=?*) CUBLAS_VER="${i#*=}";;
*) ;;
esac
shift
done
NVCC_VERSION_OUTPUT=$(nvcc --version)
if [[ $(echo $NVCC_VERSION_OUTPUT | grep -oP "\d+\.\d+" | head -n 1) != ${CUDA_VER} ]]; then
echo "The version of pre-installed CUDA is not equal to ${CUDA_VER}."
fi
install_ubuntu_requirements() {
apt-get update && apt-get install -y --no-install-recommends gnupg2 curl ca-certificates
ARCH=$(uname -m)
if [ "$ARCH" = "amd64" ];then ARCH="x86_64";fi
if [ "$ARCH" = "aarch64" ];then ARCH="sbsa";fi
curl -fsSLO https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/${ARCH}/cuda-keyring_1.1-1_all.deb
dpkg -i cuda-keyring_1.1-1_all.deb
rm cuda-keyring_1.1-1_all.deb
apt-get update
if [[ $(apt list --installed | grep libcudnn9) ]]; then
apt-get remove --purge -y libcudnn9*
fi
if [[ $(apt list --installed | grep libnccl) ]]; then
apt-get remove --purge -y --allow-change-held-packages libnccl*
fi
if [[ $(apt list --installed | grep libcublas) ]]; then
apt-get remove --purge -y --allow-change-held-packages libcublas*
fi
if [[ $(apt list --installed | grep cuda-nvrtc-dev) ]]; then
apt-get remove --purge -y --allow-change-held-packages cuda-nvrtc-dev*
fi
CUBLAS_CUDA_VERSION=$(echo $CUDA_VER | sed 's/\./-/g')
NVRTC_CUDA_VERSION=$(echo $CUDA_VER | sed 's/\./-/g')
apt-get install -y --no-install-recommends \
libcudnn9-cuda-13=${CUDNN_VER} \
libcudnn9-dev-cuda-13=${CUDNN_VER} \
libcudnn9-headers-cuda-13=${CUDNN_VER} \
libnccl2=${NCCL_VER} \
libnccl-dev=${NCCL_VER} \
libcublas-${CUBLAS_CUDA_VERSION}=${CUBLAS_VER} \
libcublas-dev-${CUBLAS_CUDA_VERSION}=${CUBLAS_VER} \
cuda-nvrtc-dev-${NVRTC_CUDA_VERSION}=${NVRTC_VER}
apt-get clean
rm -rf /var/lib/apt/lists/*
}
install_rockylinux_requirements() {
CUBLAS_CUDA_VERSION=$(echo $CUDA_VER | sed 's/\./-/g')
ARCH=$(uname -m)
if [ "$ARCH" = "x86_64" ];then ARCH1="x86_64" && ARCH2="x64" && ARCH3=$ARCH1;fi
if [ "$ARCH" = "aarch64" ];then ARCH1="aarch64" && ARCH2="aarch64sbsa" && ARCH3="sbsa";fi
# Download and install packages
for pkg in \
"libnccl-${NCCL_VER}.${ARCH1}" \
"libnccl-devel-${NCCL_VER}.${ARCH1}" \
"cuda-compat-${CUBLAS_CUDA_VERSION}-${CUDA_DRIVER_VERSION}.${ARCH1}" \
"cuda-toolkit-${CUBLAS_CUDA_VERSION}-config-common-${CUDA_RUNTIME}.noarch" \
"cuda-toolkit-13-config-common-${CUDA_RUNTIME}.noarch" \
"cuda-toolkit-config-common-${CUDA_RUNTIME}.noarch" \
"libcublas-${CUBLAS_CUDA_VERSION}-${CUBLAS_VER}.${ARCH1}" \
"libcublas-devel-${CUBLAS_CUDA_VERSION}-${CUBLAS_VER}.${ARCH1}"; do
wget --retry-connrefused --timeout=180 --tries=10 --continue "https://developer.download.nvidia.com/compute/cuda/repos/rhel8/${ARCH3}/${pkg}.rpm"
done
# Remove old packages
dnf remove -y "libnccl*"
# Install new packages
dnf -y install \
libnccl-${NCCL_VER}.${ARCH1}.rpm \
libnccl-devel-${NCCL_VER}.${ARCH1}.rpm \
cuda-compat-${CUBLAS_CUDA_VERSION}-${CUDA_DRIVER_VERSION}.${ARCH1}.rpm \
cuda-toolkit-${CUBLAS_CUDA_VERSION}-config-common-${CUDA_RUNTIME}.noarch.rpm \
cuda-toolkit-13-config-common-${CUDA_RUNTIME}.noarch.rpm \
cuda-toolkit-config-common-${CUDA_RUNTIME}.noarch.rpm \
libcublas-${CUBLAS_CUDA_VERSION}-${CUBLAS_VER}.${ARCH1}.rpm \
libcublas-devel-${CUBLAS_CUDA_VERSION}-${CUBLAS_VER}.${ARCH1}.rpm
# Clean up
rm -f *.rpm
dnf clean all
nvcc --version
}
install_tensorrt() {
PY_VERSION=$(python3 -c 'import sys; print(".".join(map(str, sys.version_info[0:2])))')
PARSED_PY_VERSION=$(echo "${PY_VERSION//./}")
TRT_CUDA_VERSION=${CUDA_VER}
TRT_VER_SHORT=$(echo $TRT_VER | cut -d. -f1-3)
if [ -z "$RELEASE_URL_TRT" ];then
ARCH=${TRT_TARGETARCH}
if [ -z "$ARCH" ];then ARCH=$(uname -m);fi
if [ "$ARCH" = "arm64" ];then ARCH="aarch64";fi
if [ "$ARCH" = "amd64" ];then ARCH="x86_64";fi
RELEASE_URL_TRT="https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/${TRT_VER_SHORT}/tars/TensorRT-${TRT_VER}.Linux.${ARCH}-gnu.cuda-${TRT_CUDA_VERSION}.tar.gz"
fi
wget --retry-connrefused --timeout=180 --tries=10 --continue ${RELEASE_URL_TRT} -O /tmp/TensorRT.tar
tar -xf /tmp/TensorRT.tar -C /usr/local/
mv /usr/local/TensorRT-${TRT_VER} /usr/local/tensorrt
pip3 install --no-cache-dir /usr/local/tensorrt/python/tensorrt-*-cp${PARSED_PY_VERSION}-*.whl
rm -rf /tmp/TensorRT.tar
echo 'export LD_LIBRARY_PATH=/usr/local/tensorrt/lib:$LD_LIBRARY_PATH' >> "${ENV}"
rm -f /usr/local/tensorrt/lib/libnvinfer_vc_plugin_static.a \
/usr/local/tensorrt/lib/libnvinfer_plugin_static.a \
/usr/local/tensorrt/lib/libnvinfer_static.a \
/usr/local/tensorrt/lib/libnvinfer_dispatch_static.a \
/usr/local/tensorrt/lib/libnvinfer_lean_static.a \
/usr/local/tensorrt/lib/libnvonnxparser_static.a \
/usr/local/tensorrt/lib/libnvinfer_builder_resource_win.so.10.10.0
}
# Install base packages depending on the base OS
ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
case "$ID" in
ubuntu)
install_ubuntu_requirements
install_tensorrt
;;
rocky)
install_rockylinux_requirements
install_tensorrt
;;
*)
echo "Unable to determine OS..."
exit 1
;;
esac