| # 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: |
|
|
|
|
