The code is given below. How can the  variable computed in the previous epoch be used for
computing the loss function in the next epoch?
for epoch in range((args.start_epoch+1), args.epochs):
for input, target in train_loader:
target = target.cuda()
input=input.cuda()
input_var = torch.autograd.Variable(input)
target_var = torch.autograd.Variable(target)
outputs, feature = model(input_var)
if epoch>0:
l= criterion.forward(feature,target_var, Fea)
Fea=function(model,train_loader)