Docker can not be built due to latest NVIDIA key rotation

If you do not know the root cause of the problem, please post according to this template:

## Instructions To Reproduce the Issue:
```
cd docker/
# Build:
docker build --build-arg USER_ID=$UID -t detectron2:v0 .
```
```
W: GPG error: https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 InRelease: The following signatures couldn't be verified because the public key is not available: NO_PUBKEY A4B469963BF863CC
E: The repository 'https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 InRelease' is not signed.
```
## Expected behavior:

Docker should build successfully, however docker build fails due to the key rotation by NVIDIA as described in

https://forums.developer.nvidia.com/t/notice-cuda-linux-repository-key-rotation/212771

Docker can be built successfully if the following two lines are added in the Dockerfile after the the FROM command.

```
FROM nvidia/cuda:11.1.1-cudnn8-devel-ubuntu18.04
# use an older system (18.04) to avoid opencv incompatibility (issue#3524)

ENV DEBIAN_FRONTEND noninteractive
RUN apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
```

## Environment:

```
sys.platform linux
Python 3.6.9 (default, Mar 15 2022, 13:55:28) [GCC 8.4.0]
numpy 1.19.5
detectron2 0.6 @/workspaces/detectron2/detectron2
detectron2._C not built correctly: No module named 'detectron2._C'
Compiler ($CXX) c++ (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
CUDA compiler Build cuda_11.1.TC455_06.29190527_0
DETECTRON2_ENV_MODULE
PyTorch 1.10.0+cu111 @/home/appuser/.local/lib/python3.6/site-packages/torch
PyTorch debug build False
GPU available Yes
GPU 0 NVIDIA RTX A4000 (arch=8.6)
Driver version 510.60.02
CUDA_HOME /usr/local/cuda
TORCH_CUDA_ARCH_LIST Kepler;Kepler+Tesla;Maxwell;Maxwell+Tegra;Pascal;Volta;Turing;Ampere
Pillow 8.4.0
torchvision 0.11.1+cu111 @/home/appuser/.local/lib/python3.6/site-packages/torchvision
torchvision arch flags 3.5, 5.0, 6.0, 7.0, 7.5, 8.0, 8.6
fvcore 0.1.5
iopath 0.1.9
cv2 3.2.0
---------------------- --------------------------------------------------------------------------
PyTorch built with:
- GCC 7.3
- C++ Version: 201402
- Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v2.2.3 (Git Hash 7336ca9f055cf1bfa13efb658fe15dc9b41f0740)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- LAPACK is enabled (usually provided by MKL)
- NNPACK is enabled
- CPU capability usage: AVX2
- CUDA Runtime 11.1
- NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86
- CuDNN 8.0.5
- Magma 2.5.2
- Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.10.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON,
```

The issue identifies the Dockerfile under docker/ and provides the docker build command to reproduce the failure. Start by running that build and compare its result with the reported NVIDIA GPG error; done means the image builds successfully without the repository signature failure.

Written by the indexing model from the issue text.