You can also create a Dataset class which returns the same image, len of 1000 for 1000 instances and returns the same image in getitem
from torch.utils.data import Dataset
class data(Dataset):
    def __init__(self, image_path, transform=None):
        self.image_path = image_path
        self.transform = transform

    def __len__(self):
        return 1000

    def __getitem__(self, x):
        # open image here as PIL / numpy
        image = #load image here
        label = # if label
        if self.transform is not None:
            image = self.transform(image)

        return image, label

Then pass this dataset to the Dataloader