PyTorch 中的 KMNIST

from torchvision.datasets import kmnisttrain_data = kmnist(    root="data")train_data = kmnist(    root="data",    train=true,    transform=none,    target_transform=none,    download=false)test_data = kmnist(    root="data",    train=false)len(train_data), len(test_data)# (60000, 10000)train_data# dataset kmnist#     number of datapoints: 60000#     root location: data#     split: traintrain_data.root# 'data'train_data.train# trueprint(train_data.transform)# noneprint(train_data.target_transform)# nonetrain_data.download# <bound method mnist.download of dataset kmnist#     number of datapoints: 60000#     root location: data#     split: train>train_data[0]# (<pil.image.image image mode=l size=28x28>, 8)train_data[1]# (<pil.image.image image mode=l size=28x28>, 7)train_data[2]# (<pil.image.image image mode=l size=28x28>, 0)train_data[3]# (<pil.image.image image mode=l size=28x28>, 1)train_data[4]# (<pil.image.image image mode=l size=28x28>, 4)train_data.classes# ['o', 'ki', 'su', 'tsu', 'na', 'ha', 'ma', 'ya', 're', 'wo']

from torchvision.datasets import KMNISTtrain_data = KMNIST(    root="data",    train=True)test_data = KMNIST(    root="data",    train=False)import matplotlib.pyplot as pltdef show_images(data):    plt.figure(figsize=(12, 2))    col = 5    for i, (image, label) in enumerate(data, 1):        plt.subplot(1, col, i)        plt.title(label)        plt.imshow(image)        if i == col:            break    plt.show()show_images(data=train_data)show_images(data=test_data)