a look at the DDPMScheduler and use the add_noise method to add some random noise to the sample_image from before:   Copied >>> import torch
>>> from PIL import Image
>>> from diffusers import DDPMScheduler

>>> noise_scheduler = DDPMScheduler(num_train_timesteps=1000)
>>> noise = torch.randn(sample_image.shape)
>>> timesteps = torch.LongTensor([50])
>>> noisy_image = noise_scheduler.add_noise(sample_image, noise, timesteps)

>>> Image.fromarra