Using Pytorch model trained on RTX2080 on RTX3060
I try to run my PyTorch model (trained on a Nvidia RTX2080) on the newer Nvidia RTX3060 with CUDA support. It is possible to load the model and to execute it. If I run it on the CPU with the --no_cuda flag it runs smootly and gives back the correct predictions, but if I want to run it with CUDA, it only returns wrong predictions which make no sense.
Does the different GPU-architecture of the cards affect the prediction?

Ok it seemed that the problem was the different floating point of the two architectures. The flag torch.backends.cuda.matmul.allow_tf32 = false needs to be set, to provide a stable execution of the model of a different architecture.
