Yes, this is what I am doing
# x.shape
torch.Size([100, 3, 40, 40])

#y values
tensor([ 1, 30, 63, 70, 37, 29, 40, 40, 16, 15,  3, 31, 34, 42, 96, 71, 53, 25,
        61, 64,  5, 34, 68, 23, 21, 32, 98, 86, 41, 15, 82, 77, 44, 79, 42, 28,
         9, 86, 17, 42, 98, 25, 66, 28, 15, 56, 45, 13, 86, 70, 37, 94, 68, 65,
         2, 90, 24, 11, 14, 18, 29, 46, 44,  7, 12, 31, 51, 80, 56, 35, 79, 92,
        89, 25, 17, 80, 90, 83, 19, 44, 17, 57, 98, 29, 20, 21, 29, 46, 82, 51,
        35, 51,  2, 27, 70, 17,  6, 35, 23, 48], device='cuda:0')
#y shape
torch.Size([100])

#y_pred
torch.Size([100, 100])

I am comparing with the same code but regular CIFAR100 dataset (not custom) and I get the same sizes
(well in this case the batch size is 800)
torch.Size([800, 3, 40, 40])
torch.Size([800])
torch.Size([800, 100])


I am sure I am running the latest file, but I don’t know is not working on ignite…