pytorch 加载mnist数据集报错not gzip file

import torchvision
import torchvision.transforms as transforms
from torch.utils.data import DataLoader

train_data = torchvision.datasets.MNIST(
    root=‘./mnist/‘,
    train=True,                                     # this is training data
    transform=torchvision.transforms.ToTensor(),    # Converts a PIL.Image or numpy.ndarray to
                                                    # torch.FloatTensor of shape (C x H x W) and normalize in the range [0.0, 1.0]
    download=True,
)
test_data = torchvision.datasets.MNIST(
    root=‘./mnist/‘,
    train=False,                                     # this is training data
    transform=torchvision.transforms.ToTensor(),    # Converts a PIL.Image or numpy.ndarray to
                                                    # torch.FloatTensor of shape (C x H x W) and normalize in the range [0.0, 1.0]
    download=True,
)

train_data_loader = DataLoader(train_data, shuffle=True, batch_size = 100)
test_data_loader = DataLoader(test_data,shuffle=True, batch_size=100)