System information:
PyTorch version: 1.5.1
CUDA used to build PyTorch: 9.2
OS: Ubuntu 18.04.5 LTS (x86_64)
GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Clang version: Could not collect
CMake version: version 3.10.2
Libc version: glibc-2.27
Python version: 3.8.10 (default, Jun  4 2021, 15:09:15)  [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-5.4.0-77-generic-x86_64-with-glibc2.17
Is CUDA available: True
CUDA runtime version: Could not collect
GPU models and configuration: GPU 0: GeForce RTX 3070 Laptop GPU
Nvidia driver version: 460.80
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Versions of relevant libraries:
[pip3] numpy==1.20.2
[pip3] pytorch3d==0.4.0
[pip3] torch==1.5.1
[pip3] torchvision==0.6.0a0+35d732a
[conda] blas                      1.0                         mkl
[conda] cudatoolkit               9.2                           0
[conda] mkl                       2021.2.0           h06a4308_296
[conda] mkl-service               2.3.0            py38h27cfd23_1
[conda] mkl_fft                   1.3.0            py38h42c9631_2
[conda] mkl_random                1.2.1            py38ha9443f7_2
[conda] numpy                     1.20.2           py38h2d18471_0
[conda] numpy-base                1.20.2           py38hfae3a4d_0
[conda] pytorch                   1.5.1           py3.8_cuda9.2.148_cudnn7.6.3_0    pytorch
[conda] pytorch3d                 0.4.0           py38_cu92_pyt151    pytorch3d
[conda] torchvision               0.6.1                 py38_cu92    pytorch
When I run the following code, it simply gets stuck in the fourth statement.
import torch
device = torch.device("cpu" if False else "cuda")
a = torch.randn(10,10)
a = a.to(device)

The same code works properly if I use pytorch 1.7.1, cuda 11.0.