PyTorch -当通过ImageFolder加载数据时，如何使用k-折交叉验证？

import torch
import torchvision.transforms as transforms
from torchvision.datasets import ImageFolder
from sklearn.model_selection import KFold

transform = transforms.Compose([
    transforms.Resize((224, 224)),  # 调整图像大小
    transforms.ToTensor(),  # 转换为张量
    transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])  # 归一化
])

dataset = ImageFolder(root='path_to_dataset', transform=transform)

k = 5  # 假设使用5折交叉验证

kf = KFold(n_splits=k, shuffle=True)

for train_index, val_index in kf.split(dataset):
    train_data = torch.utils.data.Subset(dataset, train_index)
    val_data = torch.utils.data.Subset(dataset, val_index)
    
    # 在这里进行模型训练和验证
    # 可以使用train_data作为训练集，val_data作为验证集