I have created a dataset class and dataloader for one of my datasets:
class Visual_DataSet(Dataset):
    def __init__(self, csv_path, root_dir):
        
        self.to_tensor = transforms.ToTensor()
        self.data_info = pd.read_csv(csv_path)
        self.root_dir = root_dir
        self.image_arr = np.asarray(self.data_info.iloc[:, 0])
        self.label_arr = np.asarray(self.data_info.iloc[:, 2])
        self.data_len = len(self.data_info.index)

    def __getitem__(self, index):
        single_image_name = self.image_arr[index]
        img_as_img = Image.open(self.root_dir+single_image_name)
        img_as_tensor = self.to_tensor(img_as_img)
        single_image_label = self.label_arr[index]
        return (img_as_tensor, single_image_label)

    def __len__(self):
        return self.data_len

if __name__ == "__main__":
    vs_trainset =  \
        DataSet(csv_path = 'images/visible/train_batch/trainset_batch.csv',
               root_dir = 'images/visible/train_batch/')
    vs_testset = \
        DataSet(csv_path = 'images/visible/test_batch/trainset_batch.csv',
               root_dir = 'images/visible/test_batch/')

trainloader = torch.utils.data.DataLoader(dataset=fused_data,
                                                batch_size=4,
                                                shuffle=True)
testloader = torch.utils.data.DataLoader(dataset=fused_data,
                                                batch_size=4,
                                                shuffle=False)

I want to add another dataset (i am trying to fuse the datasets). So I have created another class for my other dataset in the same manner as the first previous one. Is there any way that I have put the two datasets together in a single dataloader? Thanks in advance.