我正在嘗試復制一個我能夠遵循并運行教程的模型，但這次使用的是我自己的數據。我能夠將自己的 MRI 圖像轉換為 numpy 數組，其維度與教程數據的數組相同。我嘗試用我自己的數組替換教程中的 numpy 數組，并為正常或異常（大小寫，不是大小寫）編寫我自己的虛構 csv 文件。但是，當我運行它時，我得到：(Pytorch) C:\Users\GlaDOS\PythonProjects\dicomnpy>python train.py  -t acl -p sagittal --epochs=10 --prefix_name hueTraceback (most recent call last):  File "train.py", line 277, in <module>    run(args)  File "train.py", line 214, in run    mrnet, train_loader, epoch, num_epochs, optimizer, writer, current_lr, log_every)  File "train.py", line 34, in train_model    for i, (image, label, weight) in enumerate(train_loader):  File "C:\Users\GlaDOS\anaconda3\envs\Pytorch\lib\site-packages\torch\utils\data\dataloader.py", line 345, in __next__    data = self._next_data()  File "C:\Users\GlaDOS\anaconda3\envs\Pytorch\lib\site-packages\torch\utils\data\dataloader.py", line 385, in _next_data    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration  File "C:\Users\GlaDOS\anaconda3\envs\Pytorch\lib\site-packages\torch\utils\data\_utils\fetch.py", line 44, in fetch    data = [self.dataset[idx] for idx in possibly_batched_index]  File "C:\Users\GlaDOS\anaconda3\envs\Pytorch\lib\site-packages\torch\utils\data\_utils\fetch.py", line 44, in <listcomp>    data = [self.dataset[idx] for idx in possibly_batched_index]  File "C:\Users\GlaDOS\PythonProjects\dicomnpy\dataloader.py", line 56, in __getitem__    array = self.transform(array)  File "c:\users\glados\src\torchsample\torchsample\transforms\tensor_transforms.py", line 32, in __call__    inputs = transform(*inputs)  File "C:\Users\GlaDOS\anaconda3\envs\Pytorch\lib\site-packages\torchvision\transforms\transforms.py", line 313, in __call__    return self.lambd(img)  File "train.py", line 167, in <lambda>    transforms.Lambda(lambda x: torch.Tensor(x)),現在我想知道這個錯誤是否意味著我沒有以某種方式將我的 MRI 轉換為“正確的”numpy 數組類型？如果是這樣，我該如何將它們更改為正確的類型？