real_images = torch.cat([preprocess_image(image) for image in real_images])
print(real_images.shape)
# torch.Size([10, 3, 256, 256])
```  
We now load the[`DiTPipeline`](https://huggingface.co/docs/diffusers/api/pipelines/dit) to generate images conditioned on the above-mentioned classes.  
```python
from diffusers import DiTPipeline, DPMSolverMultistepScheduler