TensorRT-LLMs/docker/common/install_tensorrt.sh

#!/bin/bash

set -ex

TRT_VER="10.9.0.34"
# Align with the pre-installed cuDNN / cuBLAS / NCCL versions from
# https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel-25-03.html#rel-25-03
CUDA_VER="12.8" # 12.8.1
# Keep the installation for cuDNN if users want to install PyTorch with source codes.
# PyTorch 2.x can compile with cuDNN v9.
CUDNN_VER="9.8.0.87-1"
NCCL_VER="2.25.1-1+cuda12.8"
CUBLAS_VER="12.8.4.1-1"
# Align with the pre-installed CUDA / NVCC / NVRTC versions from
# https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html
NVRTC_VER="12.8.93-1"
CUDA_RUNTIME="12.8.90-1"
CUDA_DRIVER_VERSION="570.124.06-1.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 [ "$ARCH" = "aarch64" ];then ARCH="sbsa";fi
    # TODO: Replace with ubuntu2404 rather than using ubuntu2204.
    curl -fsSLO https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/${ARCH}/cuda-keyring_1.1-1_all.deb
    dpkg -i cuda-keyring_1.1-1_all.deb

    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 $CUDA_VER | sed 's/\./-/g')
    apt-get install -y --no-install-recommends libcudnn9-cuda-12=${CUDNN_VER} libcudnn9-dev-cuda-12=${CUDNN_VER}
    apt-get install -y --no-install-recommends libnccl2=${NCCL_VER} libnccl-dev=${NCCL_VER}
    apt-get install -y --no-install-recommends libcublas-${CUBLAS_CUDA_VERSION}=${CUBLAS_VER} libcublas-dev-${CUBLAS_CUDA_VERSION}=${CUBLAS_VER}
    # NVRTC static library doesn't exist in NGC PyTorch container.
    NVRTC_CUDA_VERSION=$(echo $CUDA_VER | sed 's/\./-/g')
    apt-get install -y --no-install-recommends cuda-nvrtc-dev-${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

    wget -q "https://developer.download.nvidia.cn/compute/cuda/repos/rhel8/${ARCH3}/libnccl-${NCCL_VER}.${ARCH1}.rpm"
    dnf remove -y "libnccl*"
    dnf -y install libnccl-${NCCL_VER}.${ARCH1}.rpm
    wget -q "https://developer.download.nvidia.cn/compute/cuda/repos/rhel8/${ARCH3}/libnccl-devel-${NCCL_VER}.${ARCH1}.rpm"
    dnf -y install libnccl-devel-${NCCL_VER}.${ARCH1}.rpm
    wget -q "https://developer.download.nvidia.cn/compute/cuda/repos/rhel8/${ARCH3}/cuda-compat-${CUBLAS_CUDA_VERSION}-${CUDA_DRIVER_VERSION}.${ARCH1}.rpm"
    dnf remove -y "cuda-compat*"
    dnf -y install cuda-compat-${CUBLAS_CUDA_VERSION}-${CUDA_DRIVER_VERSION}.${ARCH1}.rpm
    wget -q "https://developer.download.nvidia.cn/compute/cuda/repos/rhel8/${ARCH3}/cuda-toolkit-12-8-config-common-${CUDA_RUNTIME}.noarch.rpm"
    wget -q "https://developer.download.nvidia.cn/compute/cuda/repos/rhel8/${ARCH3}/cuda-toolkit-12-config-common-${CUDA_RUNTIME}.noarch.rpm"
    wget -q "https://developer.download.nvidia.cn/compute/cuda/repos/rhel8/${ARCH3}/cuda-toolkit-config-common-${CUDA_RUNTIME}.noarch.rpm"
    dnf remove -y "cuda-toolkit*"
    dnf -y install cuda-toolkit-12-8-config-common-${CUDA_RUNTIME}.noarch.rpm
    dnf -y install cuda-toolkit-12-config-common-${CUDA_RUNTIME}.noarch.rpm
    dnf -y install cuda-toolkit-config-common-${CUDA_RUNTIME}.noarch.rpm
    wget -q "https://developer.download.nvidia.cn/compute/cuda/repos/rhel8/${ARCH3}/libcublas-${CUBLAS_CUDA_VERSION}-${CUBLAS_VER}.${ARCH1}.rpm"
    dnf remove -y "libcublas*"
    dnf -y install libcublas-${CUBLAS_CUDA_VERSION}-${CUBLAS_VER}.${ARCH1}.rpm
    wget -q "https://developer.download.nvidia.cn/compute/cuda/repos/rhel8/${ARCH3}/libcublas-devel-${CUBLAS_CUDA_VERSION}-${CUBLAS_VER}.${ARCH1}.rpm"
    dnf -y install libcublas-devel-${CUBLAS_CUDA_VERSION}-${CUBLAS_VER}.${ARCH1}.rpm
    dnf makecache --refresh
    dnf -y install \
      epel-release \
      # libnccl-${NCCL_VER} \
      # libnccl-devel-${NCCL_VER} \
      # libcublas-${CUBLAS_CUDA_VERSION}-${CUBLAS_VER} \
      # libcublas-devel-${CUBLAS_CUDA_VERSION}-${CUBLAS_VER} \
      # cuda-compat-${CUBLAS_CUDA_VERSION}-${CUDA_DRIVER_VERSION}
    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="12.8"

    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/10.9.0/tars/TensorRT-${TRT_VER}.Linux.${ARCH}-gnu.cuda-${TRT_CUDA_VERSION}.tar.gz"
    fi
    wget --no-verbose ${RELEASE_URL_TRT} -O /tmp/TensorRT.tar
    tar -xf /tmp/TensorRT.tar -C /usr/local/
    mv /usr/local/TensorRT-${TRT_VER} /usr/local/tensorrt
    pip3 install /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}"
}

# 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