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nvidia--tensorrt/docker/rockylinux8.Dockerfile
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chore: import upstream snapshot with attribution
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Docker

#
# SPDX-FileCopyrightText: Copyright (c) 1993-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
ARG CUDA_VERSION=13.3.0
FROM nvidia/cuda:${CUDA_VERSION}-devel-rockylinux8
LABEL maintainer="NVIDIA CORPORATION"
ENV TRT_VERSION 11.1.0.106
SHELL ["/bin/bash", "-c"]
# Setup user account
ARG uid=1000
ARG gid=1000
RUN groupadd -r -f -g ${gid} trtuser && useradd -o -r -l -u ${uid} -g ${gid} -ms /bin/bash trtuser
RUN usermod -aG wheel trtuser
RUN echo 'trtuser:nvidia' | chpasswd
RUN mkdir -p /workspace && chown trtuser /workspace
# Install requried packages
RUN dnf -y groupinstall "Development Tools"
RUN dnf -y install \
openssl-devel \
bzip2-devel \
libffi-devel \
wget \
perl-core \
git \
pkg-config \
unzip \
sudo \
libnccl \
libnccl-devel \
openmpi \
openmpi-devel \
zstd \
epel-release
RUN dnf -y install ccache
# Install python3
RUN dnf install -y python38 python38-devel &&\
cd /usr/bin && ln -s /usr/bin/pip3.8 pip;
# Install TensorRT
RUN if [ "${CUDA_VERSION:0:2}" = "13" ]; then \
wget https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/11.1.0/tars/TensorRT-Enterprise-11.1.0.106-Linux-x86_64-cuda-13.3-Release-external.tar.zst \
&& tar --use-compress-program=unzstd -xf TensorRT-Enterprise-11.1.0.106-Linux-x86_64-cuda-13.3-Release-external.tar.zst \
&& cp -a TensorRT-11.1.0.106/lib/*.so* /usr/lib64 \
&& pip install TensorRT-11.1.0.106/python/tensorrt-11.1.0.106-cp38-none-linux_x86_64.whl ;\
elif [ "${CUDA_VERSION:0:2}" = "12" ]; then \
wget https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/11.1.0/tars/TensorRT-Enterprise-11.1.0.106-Linux-x86_64-cuda-12.9-Release-external.tar.zst \
&& tar --use-compress-program=unzstd -xf TensorRT-Enterprise-11.1.0.106-Linux-x86_64-cuda-12.9-Release-external.tar.zst \
&& cp -a TensorRT-11.1.0.106/lib/*.so* /usr/lib64 \
&& pip install TensorRT-11.1.0.106/python/tensorrt-11.1.0.106-cp38-none-linux_x86_64.whl ;\
else \
echo "Invalid CUDA_VERSION"; \
exit 1; \
fi
# Install PyPI packages
RUN pip install --upgrade pip
RUN pip install setuptools>=41.0.0
RUN pip install numpy
RUN pip install jupyter jupyterlab
# Install Cmake
RUN cd /tmp && \
wget https://github.com/Kitware/CMake/releases/download/v3.31.11/cmake-3.31.11-Linux-x86_64.sh && \
chmod +x cmake-3.31.11-Linux-x86_64.sh && \
./cmake-3.31.11-Linux-x86_64.sh --prefix=/usr/local --exclude-subdir --skip-license && \
rm ./cmake-3.31.11-Linux-x86_64.sh
# Install gtest
RUN cd /tmp && \
git clone https://github.com/google/googletest.git -b v1.14.0 && \
cd googletest && \
mkdir build && cd build && \
cmake .. && \
make -j4 && \
make install && \
rm -rf /tmp/googletest
# Download NGC client
RUN cd /usr/local/bin && wget https://ngc.nvidia.com/downloads/ngccli_cat_linux.zip && unzip ngccli_cat_linux.zip && chmod u+x ngc-cli/ngc && rm ngccli_cat_linux.zip ngc-cli.md5 && echo "no-apikey\nascii\n" | ngc-cli/ngc config set
RUN ln -s /usr/bin/python3 /usr/bin/python
# Set environment and working directory
ENV TRT_LIBPATH /usr/lib64
ENV TRT_OSSPATH /workspace/TensorRT
ENV PATH="/workspace/TensorRT/build/out:${PATH}:/usr/local/bin/ngc-cli"
ENV LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:${TRT_OSSPATH}/build/out:${TRT_LIBPATH}"
WORKDIR /workspace
USER trtuser
RUN ["/bin/bash"]