训练ucf101时__getitem__函数得返回值跟dataloader的返回值不一致

[dengfenglai321]

hi， 我训练ucf101时发现： 训练ucf101时getitem函数得返回值跟dataloader的返回值不一致

1. 打印getitem函数的返回值如下： ` def getitem(self, index): record = self.video_list[index]

   check this is a legit video folder

   if self.image_tmpl == 'flow_{}_{:05d}.jpg':
       file_name = self.image_tmpl.format('x', 1)
       full_path = os.path.join(self.root_path, record.path, file_name)
   elif self.image_tmpl == '{:06d}-{}_{:05d}.jpg':
       file_name = self.image_tmpl.format(int(record.path), 'x', 1)
       full_path = os.path.join(self.root_path, '{:06d}'.format(int(record.path)), file_name)
   else:
       file_name = self.image_tmpl.format(1)
       full_path = os.path.join(self.root_path, record.path, file_name)
   
   while not os.path.exists(full_path):
       print('################## Not Found:', os.path.join(self.root_path, record.path, file_name))
       index = np.random.randint(len(self.video_list))
       record = self.video_list[index]
       if self.image_tmpl == 'flow_{}_{:05d}.jpg':
           file_name = self.image_tmpl.format('x', 1)
           full_path = os.path.join(self.root_path, record.path, file_name)
       elif self.image_tmpl == '{:06d}-{}_{:05d}.jpg':
           file_name = self.image_tmpl.format(int(record.path), 'x', 1)
           full_path = os.path.join(self.root_path, '{:06d}'.format(int(record.path)), file_name)
       else:
           file_name = self.image_tmpl.format(1)
           full_path = os.path.join(self.root_path, record.path, file_name)
   
   if not self.test_mode:
       segment_indices = self._sample_indices(record) if self.random_shift else self._get_val_indices(record)
   else:
       segment_indices = self._get_test_indices(record)
   # print('record : {}'.format(record))
   print('segment_indices : {}'.format(segment_indices))
   data, label = self.get(record, segment_indices)
   print('data : {}'.format(data.size()))
   print('label : {}'.format(label)) 
   return self.get(record, segment_indices)`

2. 打印dataloader返回值如下：

` for i, (input, target) in enumerate(train_loader):

measure data loading time

    data_time.update(time.time() - end)
    target = target.cuda()
    input_var = torch.autograd.Variable(input)
    target_var = torch.autograd.Variable(target)
    print('\n')
    print('input_var : {}'.format(input_var.size()))
    print('target_var : {}'.format(target_var))`

3. 实际结果如下 我检查了很多次， 发现两者的返回都是对不上的，请问可能时什么原因呢