Yes, both are under version 11.

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In fact all my neural network is under CUDA, so normally under GPU, but when I run my code, I see that the execution time is really slow and in the task manager the percentage of GPU usage is at ~1-4%, while this morning with the same code without changing anything, my GPU is used at 100%, because with CUDA we can not limit the use of the GPU to a certain percentage.
And more concretely, I have the “impression” that my code uses CUDA/GPU well, but it runs in slow motion, I just did a test with :
torch.device(“cpu”)
And it goes at the same speed as :
torch.device(“cuda”)
except that the CPU version, we can see in the task manager that it uses 40% of the processor while with CUDA, there is no use of the CPU almost and the GPU too, I wonder if it is a problem of memory allocated to the GPU, which is very low, but I do not know how to set it, otherwise I have already emptied several times also the cache of cuda.
Also this problem appeared just after I tried to display on my jupyter notebook, a very large list that made my jupyter notebook crash. I don’t know if there is a problem related to this. But I also reinstalled all python and all libraries.