diffusers

1096f88e - sampling bug fix in diffusers tutorial "basic_training.md" (#8223)

sampling bug fix in diffusers tutorial "basic_training.md" (#8223) sampling bug fix in basic_training.md In the diffusers basic training tutorial, setting the manual seed argument (generator=torch.manual_seed(config.seed)) in the pipeline call inside evaluate() function rewinds the dataloader shuffling, leading to overfitting due to the model seeing same sequence of training examples after every evaluation call. Using generator=torch.Generator(device='cpu').manual_seed(config.seed) avoids this.