datasets

main_custom.py

@@ -24,9 +24,7 @@ def train(model, data_train, epoch, optimizer, criterion_rt, criterion_intensity
     for param in model.parameters():
         param.requires_grad = True
     if forward == 'both':
-        i=0
         for seq, charge, rt, intensity in data_train:
-            i+=seq.shape[0]
             rt, intensity = rt.float(), intensity.float()
             if torch.cuda.is_available():
                 seq, charge, rt, intensity = seq.cuda(), charge.cuda(), rt.cuda(), intensity.cuda()
@@ -43,7 +41,6 @@ def train(model, data_train, epoch, optimizer, criterion_rt, criterion_intensity
             optimizer.zero_grad()
             loss.backward()
             optimizer.step()
-            print(i,'/',len(data_train.dataset))
 
         if wandb is not None:
             wdb.log({"train rt loss": losses_rt / len(data_train), "train int loss": losses_int / len(data_train),