自定义数据集不接受 PyTorch 中的参数

我正在尝试使用此数据集在 PyTorch 中创建自定义数据集。它的形状为 (X, 785)，X 是样本数，每行包含索引 0 和 784 像素值处的标签。这是我的代码：

from torch.utils.data import Dataset
def SignMNISTDataset(Dataset):

  def __init__(self, csv_file_path, mode='Train'):
    self.labels = []
    self.pixels = []
    self.mode = mode

    data = pd.read_csv(csv_file_path).values
    if self.mode == 'Train':
      self.labels = data[:,0].tolist()
      print("Training labels acquired")

    for idx in range(len(self.labels)):
      self.pixels.append(data[idx][1:].tolist())

  def __len__(self):
    return len(self.labels)

  def __getitem__(self, idx):
    pixels = self.pixels[idx]
    if self.mode == 'Train':
      labels = self.labels[idx]
      content = {"pixels":pixels, "label":labels}
    else:
      content = {"pixels":pixels}
    return content

training_data = SignMNISTDataset('sign_mnist_train/sign_mnist_train.csv', 'Train')

在运行时，我收到以下错误：

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-46-0173199f8794> in <module>()
     27     return content
     28 
---> 29 training_data = SignMNISTDataset('sign_mnist_train/sign_mnist_train.csv', 'Train')
     30 from torch.utils.data import DataLoader
     31 

TypeError: SignMNISTDataset() takes 1 positional argument but 2 were given

这究竟是从哪里来的？在对象创建过程中，模式参数是否以某种方式不被读取？我的最终目标是按照本教程创建一个用于对符号字符进行分类的神经网络。

我尝试mode在对象创建期间明确提及关键字。这就是我得到的 -

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-48-fd796c48dc67> in <module>()
     27     return content
     28 
---> 29 training_data = SignMNISTDataset('sign_mnist_train/sign_mnist_train.csv', mode='Train')

TypeError: SignMNISTDataset() got an unexpected keyword argument 'mode'