Thanks for your swift reply. I check the environment for A6000 using https://raw.githubusercontent.com/pytorch/pytorch/master/torch/ utils/collect_env.py.
Collecting environment information...
PyTorch version: 1.10.0.dev20210831
Is debug build: False
CUDA used to build PyTorch: 11.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 16.04.6 LTS (x86_64)
GCC version: (Ubuntu 5.4.0-6ubuntu1~16.04.12) 5.4.0 20160609
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.23

Python version: 3.8.11 (default, Aug  3 2021, 15:09:35)  [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-4.4.0-142-generic-x86_64-with-glibc2.17
Is CUDA available: True
CUDA runtime version: Could not collect
GPU models and configuration:
GPU 0: NVIDIA RTX A6000
GPU 1: NVIDIA RTX A6000
GPU 2: NVIDIA RTX A6000
GPU 3: NVIDIA RTX A6000

Nvidia driver version: 465.19.01
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.20.3
[pip3] torch==1.10.0.dev20210831
[pip3] torchaudio==0.10.0.dev20210831
[pip3] torchvision==0.11.0.dev20210831
[conda] blas                      1.0                         mkl
[conda] cudatoolkit               11.1.74              h6bb024c_0    nvidia
[conda] mkl                       2021.3.0           h06a4308_520
[conda] mkl-service               2.4.0            py38h7f8727e_0
[conda] mkl_fft                   1.3.0            py38h42c9631_2
[conda] mkl_random                1.2.2            py38h51133e4_0
[conda] numpy                     1.20.3           py38hf144106_0
[conda] numpy-base                1.20.3           py38h74d4b33_0
[conda] pytorch                   1.10.0.dev20210831 py3.8_cuda11.1_cudnn8.0.5_0    pytorch-nightly
[conda] torchaudio                0.10.0.dev20210831            py38    pytorch-nightly
[conda] torchvision               0.11.0.dev20210831      py38_cu111    pytorch-nightly

However, regarding other GPUs, such as TITAN RTX. The 1.6.0 PyTorch environment is shown below
Collecting environment information...
PyTorch version: 1.6.0
Is debug build: False
CUDA used to build PyTorch: 10.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 16.04.6 LTS (x86_64)
GCC version: (Ubuntu 5.4.0-6ubuntu1~16.04.12) 5.4.0 20160609
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.23

Python version: 3.8.3 (default, Jul  2 2020, 16:21:59)  [GCC 7.3.0] (64-bit runtime)
Python platform: Linux-4.4.0-142-generic-x86_64-with-glibc2.10
Is CUDA available: True
CUDA runtime version: 10.1.243
GPU models and configuration:
GPU 0: TITAN RTX
GPU 1: TITAN RTX
GPU 2: TITAN RTX
GPU 3: TITAN RTX

Nvidia driver version: 440.31
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] efficientnet-pytorch==0.7.1
[pip3] numpy==1.20.1
[pip3] numpydoc==1.1.0
[pip3] torch==1.6.0
[pip3] torchaudio==0.6.0
[pip3] torchvision==0.7.0
[conda] blas                      1.0                         mkl
[conda] cudatoolkit               10.1.243             h6bb024c_0
[conda] efficientnet-pytorch      0.7.1                    pypi_0    pypi
[conda] mkl                       2020.1                      217
[conda] mkl-service               2.3.0            py38he904b0f_0
[conda] mkl_fft                   1.1.0            py38h23d657b_0
[conda] mkl_random                1.1.1            py38h0573a6f_0
[conda] numpy                     1.18.5                   pypi_0    pypi
[conda] numpy-base                1.18.5           py38hde5b4d6_0
[conda] numpydoc                  1.1.0                      py_0
[conda] pytorch                   1.6.0           py3.8_cuda10.1.243_cudnn7.6.3_0    pytorch
[conda] torchaudio                0.6.0                    pypi_0    pypi
[conda] torchvision               0.7.0                py38_cu101    pytorch

Are the above information helps you to identify what happened?