class_ids = dit_pipeline.get_label_ids(words)
output = dit_pipeline(class_labels=class_ids, generator=generator, output_type="np")

fake_images = output.images
fake_images = torch.tensor(fake_images)
fake_images = fake_images.permute(0, 3, 1, 2)
print(fake_images.shape)
# torch.Size([10, 3, 256, 256])
```  
Now, we can compute the FID using[`torchmetrics`](https://torchmetrics.readthedocs.io/).  
```python
from torchmetrics.image.fid import FrechetInceptionDistance