规范代码，删除不必要的注释

PyTorch/Compute-Vision/Accuracy_Validation/ResNet50/main_acc.py

@@ -209,22 +209,6 @@ def main_worker(gpu, ngpus_per_node, args):
             model = torch.nn.DataParallel(model).cuda()
 
     # optionally resume from a checkpoint
-#    if args.resume:
-#        if os.path.isfile(args.resume):
-#            print("=> loading checkpoint '{}'".format(args.resume))
-#            checkpoint = torch.load(args.resume)
-#            args.start_epoch = checkpoint['epoch']
-#            best_acc1 = checkpoint['best_acc1']
-#            if args.gpu is not None:
-#                # best_acc1 may be from a checkpoint from a different GPU
-#                best_acc1 = best_acc1.to(args.gpu)
-#            model.load_state_dict(checkpoint['state_dict'])
-#            optimizer.load_state_dict(checkpoint['optimizer'])
-#            print("=> loaded checkpoint '{}' (epoch {})"
-#                  .format(args.resume, checkpoint['epoch']))
-#        else:
-#            print("=> no checkpoint found at '{}'".format(args.resume))
-
     if args.resume:
         if os.path.isfile(args.resume):
             print("=> loading checkpoint '{}'".format(args.resume))
@@ -421,15 +405,6 @@ def validate(val_loader, model, criterion, args):
 
     return top1.avg
 
-
-#def save_checkpoint(state, epoch, is_best, rank, filename='/public/home/aiss/419_rocm2.x_DL/examples_dl/aiss_test/base_acc/HK/HK3/test_resume/checkpoint.pth.tar'):
-#    filename='/public/home/aiss/419_rocm2.x_DL/examples_dl/aiss_test/base_acc/HK/HK3/test_resume'+str(rank)+'/checkpoint_'+str(epoch)+'.pth.tar'
-#    torch.save(state, filename)
-#    if is_best:
-#        #shutil.copyfile(filename, '/public/home/aiss/419_rocm2.x_DL/examples_dl/aiss_test/base_acc/HK/HK3/test_resume/model_best.pth.tar')
-#        best_dir='/public/home/aiss/419_rocm2.x_DL/examples_dl/aiss_test/base_acc/HK/HK3/test_resume'+str(rank)+'/model_best.pth.tar'
-#        shutil.copyfile(filename, best_dir)
-
 def save_checkpoint(state, epoch, is_best, rank, filename):
     rank_path = filename + '/' + str(rank)
     if not os.path.isdir(rank_path):
@@ -437,7 +412,6 @@ def save_checkpoint(state, epoch, is_best, rank, filename):
     filename = rank_path+'/checkpoint_'+str(epoch)+'.pth.tar'
     torch.save(state, filename)
     if is_best:
-        #shutil.copyfile(filename, '/public/home/aiss/419_rocm2.x_DL/examples_dl/aiss_test/base_acc/HK/HK3/test_resume/model_best.pth.tar')
         best_dir=rank_path+'/model_best.pth.tar'
         shutil.copyfile(filename, best_dir)