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# 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:
.png)
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