Why i'm getting the message "UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors."?
I'm building my own dataset:
class MyDataset(Dataset):
    def __init__(self, folders):                
        self.folders         = folders                
        
        
    def __len__(self):            
        return len(self.folders)
        
    
    def __getitem__(self, item):
                         
        pos_file_list =  glob(self.folders[item] + &quot;/*&quot;)            
        positive_img  = pos_file_list[1]
                
        positive_img   = mpimg.imread(positive_img)                
        positive_img   = np.transpose(positive_img,     (2,0,1))                    

        # positive_img have the type: &lt;class 'numpy.ndarray'&gt;, shape: (3, 128, 128)        
        return positive_img

And I'm using it with:
batch_size =  128      
train_ds   = MyDataset(train_folder_list)


oTrainDL   = DataLoader(train_ds, batch_size=batch_size, shuffle=True, num_workers=2)        


for i, imgs in enumerate(oTrainDL):                       
    break

I'm getting the following warrning:
UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at  ../torch/csrc/utils/tensor_numpy.cpp:189.)
  return default_collate([torch.as_tensor(b) for b in batch])

Why I'm getting warrning messaage ? How can I fix it ?

change from return positive_img to:
return torch.tensor(positive_img)

