CUDA support doesnot work about dct-net

[onefish51]

there is something wrong !
you said :

pip install --upgrade tensorflow-gpu==1.15

and the tensorflow official documentation shown :

so cuda is 10.0, and cudnn is 7.4

then

pip install "modelscope[cv]==1.3.2" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html

install log shown

CuDNN8.5.0 is required install

and then

Loaded runtime CuDNN library: 8.5.0 but source was compiled with: 7.6.4.  CuDNN library major and minor version needs to match or have higher minor version in case of CuDNN 7.0 or later version. If using a binary install, upgrade your CuDNN library.  If building from sources, make sure the library loaded at runtime is compatible with the version specified during compile configuration.

so I failed !

I tested tensorflow-gpu

python 
Python 3.7.16 (default, Jan 17 2023, 22:20:44) 
[GCC 11.2.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> tf.test.is_gpu_available()
...
True

[menyifang]

it supports both GPU and CPU. Please ensure tensorflow-gpu compatible with cuda version.

[h3clikejava]

I tested on:
ubuntu 18.04
python 3.7
CUDA 10/10.1/11.2
cudnn 7.4/7.6.0/7.6.1
tensorflow-gup 1.14/1.15
torch 1.7.1+cu101
numpy1.18.5

I always get black result like this:

I have been trying to set up this training environment for three days, but ultimately failed.
The documentation for this project is really terrible, and I don't know if it's because of changes in the company's business, but the development members have stopped maintaining it.
The documentation has inconsistencies in various places regarding the runtime environment.
If there is anyone kind enough who has been able to train successfully, please provide your environment and training scripts. Thank you.