Improve the precision of our integration tests

[patrickvonplaten]

We currently have a rather low precision when testing our pipeline due to due reasons.

1. • Our reference is an image and not a numpy array. This means that when we created our reference image we lost float precision which is unnecessary
2. • We only test for .max() < 1e-2 . IMO we should test for .max() < 1e-4 with the numpy arrays. In my experiements across multiple devices I have not seen differences bigger than .max() < 1e-4 when using full precision.

IMO this could have also prevented: #902

[Lewington-pitsos]

I'm going to start work on this right now

[Lewington-pitsos]

@patrickvonplaten after some research I think I understand the issue.

The images are currently stored in a low-precision format (e.g. png) which prevents us from testing with any greater precision than 1e-2. Even if we convert the image into a numpy array this will not help since the image itself is missing precision.

What we need to do is store a numpy representation of the image, say somewhere inside https://huggingface.co/datasets which we can then download and use for comparison.

The way we could do this is by generating the test output, saving that output as a numpy image and uploading it.

This is what I plan to do tomorrow.

This stack overflow thread was very helpful in understanding the issue.

[patrickvonplaten]

Hey @Lewington-pitsos,

That's a very good observation - we came to the same conclusion here: #937 :-)
Do you have an account on the Hugging Face Hub? Would you like to upload the numpy images to a dataset on the Hub maybe? :-) This would be super useful!

[Lewington-pitsos]

Hey, yes I am currently working on this in fact!

[Lewington-pitsos]

@patrickvonplaten I made a PR adding the files: https://huggingface.co/datasets/hf-internal-testing/diffusers-images/discussions/2

[patrickvonplaten]

Thanks a mille @Lewington-pitsos for making this very important improvement-of-life PR! Leaving this issue open as we still need to apply the same changes to:

• https://github.com/huggingface/diffusers/blob/main/tests/pipelines/stable_diffusion/test_stable_diffusion_img2img.py
  and
• https://github.com/huggingface/diffusers/blob/main/tests/pipelines/stable_diffusion/test_stable_diffusion.py

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