Compilation error with cuda

🐛 Describe the bug

When compiling vision with cuda enabled I am getting following error
CMake Error at /usr/local/share/cmake-3.22/Modules/CMakeTestCUDACompiler.cmake:56 (message):
The CUDA compiler
"/usr/bin/nvcc"
is not able to compile a simple test program.

I was able to compile the library after adding following in CMakeLists.txt after if(WITH_CUDA)
set(CMAKE_CUDA_COMPILER "/usr/local/cuda-11.1/bin/nvcc").

Versions

PyTorch version: 1.8.2+cu111
Is debug build: False
CUDA used to build PyTorch: 11.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.4 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: 10.0.0-4ubuntu1
CMake version: version 3.22.5
Libc version: glibc-2.17

Python version: 3.6.13 |Anaconda, Inc.| (default, Jun 4 2021, 14:25:59) [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-5.14.0-1044-oem-x86_64-with-debian-bullseye-sid
Is CUDA available: True
CUDA runtime version: 11.1.74
GPU models and configuration: GPU 0: NVIDIA T600 Laptop GPU
Nvidia driver version: 510.73.05
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.3.2
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.3.2
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.3.2
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.3.2
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.3.2
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.3.2
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.3.2
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn.so.8.1.1
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.1.1
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.1.1
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.1.1
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.1.1
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.1.1
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.1.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.19.5
[pip3] numpy-quaternion==2021.11.4.15.26.3
[pip3] numpy-ros==0.1.3
[pip3] torch==1.8.2+cu111
[pip3] torchaudio==0.8.2
[pip3] torchvision==0.9.2+cu111
[conda] blas 1.0 mkl conda-forge
[conda] cudatoolkit 10.1.243 h6bb024c_0 anaconda
[conda] libblas 3.8.0 14_mkl conda-forge
[conda] libcblas 3.8.0 14_mkl conda-forge
[conda] liblapack 3.8.0 14_mkl conda-forge
[conda] mkl 2019.4 243 anaconda
[conda] mkl-service 2.3.0 py36he904b0f_0 anaconda
[conda] mkl_fft 1.2.0 py36h23d657b_0 anaconda
[conda] mkl_random 1.1.0 py36hd6b4f25_0 anaconda
[conda] numpy 1.19.5 py36hfc0c790_2 conda-forge
[conda] numpy-quaternion 2021.11.4.15.26.3 pypi_0 pypi
[conda] numpy-ros 0.1.3 pypi_0 pypi
[conda] torch 1.8.2+cu111 pypi_0 pypi
[conda] torchaudio 0.8.2 pypi_0 pypi
[conda] torchvision 0.9.2+cu111 pypi_0 pypi

Start in CMakeLists.txt around the if(WITH_CUDA) block and compare its CUDA compiler handling with CMakeTestCUDACompiler.cmake, which reports the failure. Reproduce the CUDA-enabled vision build using the reported Ubuntu, CMake, CUDA, and nvcc versions; done means the build succeeds without manually setting CMAKE_CUDA_COMPILER.