# Diffusers Tools

This is a collection of scripts that can be useful for various tasks related to the [diffusers library](https://github.com/huggingface/diffusers)

## Test against original checkpoints

**It's very important to have visually the exact same results as the original code bases.!**

E.g. to make use `diffusers` is identical to the original [CompVis codebase](https://github.com/CompVis/stable-diffusion), you can run the following script in the original CompVis codebase:

1. Download the original [SD-1-4 checkpoint](https://huggingface.co/CompVis/stable-diffusion-v1-4) and put it in the correct folder following the instructions on: https://github.com/CompVis/stable-diffusion

2. Run the following command
```
python scripts/txt2img.py --prompt "a photograph of an astronaut riding a horse" --seed 0 --n_samples 1 --n_rows 1 --n_iter 1
```

and compare this to the same command in diffusers:

```python
from diffusers import DiffusionPipeline, StableDiffusionPipeline, DDIMScheduler
import torch

#  python scripts/txt2img.py --prompt "a photograph of an astronaut riding a horse" --seed 0 --n_samples 1 --n_rows 1 --n_iter 1
seed = 0

prompt = "a photograph of an astronaut riding a horse"
pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", torch_dtype=torch.float16)

pipe = pipe.to("cuda")
pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
torch.manual_seed(0)
image = pipe(prompt, num_inference_steps=50).images[0]

image.save("/home/patrick_huggingface_co/images/aa_comp.png")
```

Both commands should give the following image on a V100: