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upload required packages

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  1. .gitattributes +1 -0
  2. UltraEdit +0 -1
  3. UltraEdit/README.md +120 -0
  4. UltraEdit/app.py +149 -0
  5. UltraEdit/diffusers/.github/ISSUE_TEMPLATE/bug-report.yml +106 -0
  6. UltraEdit/diffusers/.github/ISSUE_TEMPLATE/config.yml +4 -0
  7. UltraEdit/diffusers/.github/ISSUE_TEMPLATE/feature_request.md +20 -0
  8. UltraEdit/diffusers/.github/ISSUE_TEMPLATE/feedback.md +12 -0
  9. UltraEdit/diffusers/.github/ISSUE_TEMPLATE/new-model-addition.yml +31 -0
  10. UltraEdit/diffusers/.github/ISSUE_TEMPLATE/translate.md +29 -0
  11. UltraEdit/diffusers/.github/PULL_REQUEST_TEMPLATE.md +60 -0
  12. UltraEdit/diffusers/.github/actions/setup-miniconda/action.yml +146 -0
  13. UltraEdit/diffusers/.github/workflows/benchmark.yml +53 -0
  14. UltraEdit/diffusers/.github/workflows/build_docker_images.yml +101 -0
  15. UltraEdit/diffusers/.github/workflows/build_documentation.yml +27 -0
  16. UltraEdit/diffusers/.github/workflows/build_pr_documentation.yml +23 -0
  17. UltraEdit/diffusers/.github/workflows/mirror_community_pipeline.yml +89 -0
  18. UltraEdit/diffusers/.github/workflows/nightly_tests.yml +414 -0
  19. UltraEdit/diffusers/.github/workflows/notify_slack_about_release.yml +23 -0
  20. UltraEdit/diffusers/.github/workflows/pr_dependency_test.yml +36 -0
  21. UltraEdit/diffusers/.github/workflows/pr_flax_dependency_test.yml +38 -0
  22. UltraEdit/diffusers/.github/workflows/pr_test_fetcher.yml +174 -0
  23. UltraEdit/diffusers/.github/workflows/pr_test_peft_backend.yml +131 -0
  24. UltraEdit/diffusers/.github/workflows/pr_tests.yml +233 -0
  25. UltraEdit/diffusers/.github/workflows/pr_torch_dependency_test.yml +36 -0
  26. UltraEdit/diffusers/.github/workflows/push_tests.yml +435 -0
  27. UltraEdit/diffusers/.github/workflows/push_tests_fast.yml +124 -0
  28. UltraEdit/diffusers/.github/workflows/push_tests_mps.yml +75 -0
  29. UltraEdit/diffusers/.github/workflows/pypi_publish.yaml +81 -0
  30. UltraEdit/diffusers/.github/workflows/run_tests_from_a_pr.yml +73 -0
  31. UltraEdit/diffusers/.github/workflows/ssh-runner.yml +46 -0
  32. UltraEdit/diffusers/.github/workflows/stale.yml +27 -0
  33. UltraEdit/diffusers/.github/workflows/trufflehog.yml +15 -0
  34. UltraEdit/diffusers/.github/workflows/typos.yml +14 -0
  35. UltraEdit/diffusers/.github/workflows/update_metadata.yml +30 -0
  36. UltraEdit/diffusers/.github/workflows/upload_pr_documentation.yml +16 -0
  37. UltraEdit/diffusers/.gitignore +178 -0
  38. UltraEdit/diffusers/CITATION.cff +52 -0
  39. UltraEdit/diffusers/CODE_OF_CONDUCT.md +130 -0
  40. UltraEdit/diffusers/CONTRIBUTING.md +505 -0
  41. UltraEdit/diffusers/LICENSE +201 -0
  42. UltraEdit/diffusers/MANIFEST.in +2 -0
  43. UltraEdit/diffusers/Makefile +96 -0
  44. UltraEdit/diffusers/PHILOSOPHY.md +110 -0
  45. UltraEdit/diffusers/README.md +248 -0
  46. UltraEdit/diffusers/_typos.toml +13 -0
  47. UltraEdit/diffusers/benchmarks/base_classes.py +346 -0
  48. UltraEdit/diffusers/benchmarks/benchmark_controlnet.py +26 -0
  49. UltraEdit/diffusers/benchmarks/benchmark_ip_adapters.py +32 -0
  50. UltraEdit/diffusers/benchmarks/benchmark_sd_img.py +29 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ *.png filter=lfs diff=lfs merge=lfs -text
UltraEdit DELETED
@@ -1 +0,0 @@
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- Subproject commit d47eb6c3b8a2be9eef88f09155c17e6792234968
 
 
UltraEdit/README.md ADDED
@@ -0,0 +1,120 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # UltraEdit
2
+ This repository contains code, models, and datasets for UltraEdit.
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+
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+ ## Introduction
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+ **UltraEdit**, a large-scale (~4M editing samples), automatically generated dataset for instruction-based image editing. Our key idea is to address the drawbacks in existing image editing datasets like InstructPix2Pix and MagicBrush, and provide a systematic approach to producing massive and high-quality image editing samples.
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+
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+ **UltraEdit** offers several distinct advantages:
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+
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+ 1. It features a broader range of editing instructions by leveraging the creativity of large language models (LLMs) alongside in-context editing examples from human raters.
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+ 2. Its data sources are based on real images, including photographs and artworks, which provide greater diversity and reduced bias compared to datasets solely generated by text-to-image models.
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+ 3. It also supports region-based editing, enhanced by high-quality, automatically produced region annotations.
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+
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+ Our experiments show that canonical diffusion-based editing baselines trained on **UltraEdit** set new records on various benchmarks.
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+ Our analysis further confirms the crucial role of real image anchors and region-based editing data.
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+
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+ ## Training
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+
18
+ **Setup: **
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+
20
+ ```
21
+ pip install -r requirements
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+
23
+ cd diffusers && pip install -e .
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+ ```
25
+
26
+ ### Training with stable-diffusion3
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+
28
+ **Stage 1: Free-form image editing**
29
+
30
+ ```shell
31
+ bash scripts/run_sft_512_sd3_stage1.sh
32
+ ```
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+
34
+ **Stage 2: Mix training**
35
+
36
+ ```shell
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+ bash scripts/run_sft_512_with_mask_sd3_stage2.sh
38
+ ```
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+
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+ ### Training with stable-diffusion-xl
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+
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+ **Stage 1: Free-form image editing**
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+
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+ ```shell
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+ bash scripts/run_sft_512_sdxl_stage1.sh
46
+ ```
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+
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+ [//]: # (**Stage 2: Mix training**)
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+
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+ [//]: # ()
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+ [//]: # (```shell)
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+
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+ [//]: # (bash scripts/run_sft_512_with_mask_sd3_stage2.sh)
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+
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+ [//]: # (```)
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+
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+
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+ ### Training with stable-diffusion1.5
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+
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+ **Stage 1: Free-form image editing**
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+
62
+ ```shell
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+ bash scripts/run_sft_512_sd15_stage1.sh
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+ ```
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+
66
+ **Stage 2: Mix training**
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+
68
+ ```shell
69
+ bash scripts/run_sft_512_with_mask_sd15_stage2.sh
70
+ ```
71
+
72
+ ## Example
73
+ Below is an example of how to use our pipeline for image editing. Given an input image and a mask image, the model can generate the edited result according to the provided prompt.
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+
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+ <p float="left">
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+ <img src="images/input.png" width="200" />
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+ <img src="images/mask_img.png" width="200" style="border-left:1px solid black;" />
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+ <img src="images/editing_result.png" width="200" style="border-left:1px solid black;" />
79
+ </p>
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+
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+ ```python
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+ # For Editing with SD3
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+ import torch
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+ from diffusers import StableDiffusion3InstructPix2PixPipeline
85
+ from diffusers.utils import load_image
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+ import requests
87
+ import PIL.Image
88
+ import PIL.ImageOps
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+ pipe = StableDiffusion3InstructPix2PixPipeline.from_pretrained("BleachNick/SD3_UltraEdit_w_mask", torch_dtype=torch.float16)
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+ pipe = pipe.to("cuda")
91
+ prompt="What if the horse wears a hat?"
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+ img = load_image("input.png").resize((512, 512))
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+ mask_img = load_image("mask_img.png").resize(img.size)
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+ # For free form Editing, seed a blank mask
95
+ # mask_img = PIL.Image.new("RGB", img.size, (255, 255, 255))
96
+ image = pipe(
97
+ prompt,
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+ image=img,
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+ mask_img=mask_img,
100
+ negative_prompt="",
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+ num_inference_steps=50,
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+ image_guidance_scale=1.5,
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+ guidance_scale=7.5,
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+ ).images[0]
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+ image.save("edited_image.png")
106
+ # display image
107
+ ```
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+
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+
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+ [//]: # ()
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+ [//]: # (## License)
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+
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+ [//]: # ()
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+ [//]: # (This project is licensed under the terms of the MIT license. See the [LICENSE]&#40;LICENSE.md&#41; file for details.)
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+
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+ [//]: # ()
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+ [//]: # (## Contact)
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+
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+ [//]: # ()
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+ [//]: # (For any questions or issues, please open an issue on GitHub or contact us at support@example.com.)
UltraEdit/app.py ADDED
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1
+ import spaces
2
+ import torch
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+ from diffusers import StableDiffusion3InstructPix2PixPipeline, SD3Transformer2DModel
4
+ import gradio as gr
5
+ import PIL.Image
6
+ import numpy as np
7
+ from PIL import Image, ImageOps
8
+
9
+
10
+ pipe = StableDiffusion3InstructPix2PixPipeline.from_pretrained("BleachNick/SD3_UltraEdit_w_mask", torch_dtype=torch.float16)
11
+
12
+ pipe = pipe.to("cuda")
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+
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+
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+
16
+ @spaces.GPU(duration=20)
17
+ def generate(image_mask, prompt, num_inference_steps=50, image_guidance_scale=1.6, guidance_scale=7.5, seed=255):
18
+ def is_blank_mask(mask_img):
19
+ # Convert the mask to a numpy array and check if all values are 0 (black/transparent)
20
+ mask_array = np.array(mask_img.convert('L')) # Convert to luminance to simplify the check
21
+ return np.all(mask_array == 0)
22
+ # Set the seed for reproducibility
23
+ seed = int(seed)
24
+ generator = torch.manual_seed(seed)
25
+
26
+ img = image_mask["background"].convert("RGB")
27
+ mask_img = image_mask["layers"][0].getchannel('A').convert("RGB")
28
+
29
+ # Central crop to desired size
30
+ desired_size = (512, 512)
31
+
32
+ img = ImageOps.fit(img, desired_size, method=Image.LANCZOS, centering=(0.5, 0.5))
33
+ mask_img = ImageOps.fit(mask_img, desired_size, method=Image.LANCZOS, centering=(0.5, 0.5))
34
+
35
+ if is_blank_mask(mask_img):
36
+ # Create a mask of the same size with all values set to 255 (white)
37
+ mask_img = PIL.Image.new('RGB', img.size, color=(255, 255, 255))
38
+ mask_img = mask_img.convert('RGB')
39
+
40
+ image = pipe(
41
+ prompt,
42
+ image=img,
43
+ mask_img=mask_img,
44
+ num_inference_steps=num_inference_steps,
45
+ image_guidance_scale=image_guidance_scale,
46
+ guidance_scale=guidance_scale,
47
+ generator=generator
48
+ ).images[0]
49
+
50
+ return image
51
+
52
+ example_lists=[
53
+
54
+ [['UltraEdit/images/example_images/1-input.png','UltraEdit/images/example_images/1-mask.png','UltraEdit/images/example_images/1-merged.png'], "Add a moon in the sky", 20, 1.5, 12.5,255],
55
+
56
+ [['UltraEdit/images/example_images/1-input.png','UltraEdit/images/example_images/1-input.png','UltraEdit/images/example_images/1-input.png'], "Add a moon in the sky", 20, 1.5, 6.5,255],
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+
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+ [['UltraEdit/images/example_images/2-input.png','UltraEdit/images/example_images/2-mask.png','UltraEdit/images/example_images/2-merged.png'], "add cherry blossoms", 20, 1.5, 12.5,255],
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+
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+ [['UltraEdit/images/example_images/3-input.png','UltraEdit/images/example_images/3-mask.png','UltraEdit/images/example_images/3-merged.png'], "Please dress her in a short purple wedding dress adorned with white floral embroidery.", 20, 1.5, 6.5,255],
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+
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+ [['UltraEdit/images/example_images/4-input.png','UltraEdit/images/example_images/4-mask.png','UltraEdit/images/example_images/4-merged.png'], "give her a chief's headdress.", 20, 1.5, 7.5, 24555]
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+
64
+ ]
65
+ mask_ex_list = []
66
+ for exp in example_lists:
67
+ ex_dict= {}
68
+ ex_dict['background'] = exp[0][0]
69
+ ex_dict['layers'] = [exp[0][1],exp[0][2]]
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+ ex_dict['composite'] = exp[0][2]
71
+ re_list = [ex_dict, exp[1],exp[2],exp[3],exp[4],exp[5]]
72
+ mask_ex_list.append(re_list)
73
+
74
+ # image_mask_input = gr.ImageMask(label="Input Image", type="pil", brush_color="#000000", elem_id="inputmask",
75
+ # shape=(512, 512))
76
+ image_mask_input = gr.ImageMask(sources='upload',type="pil",label="Input Image: Mask with pen or leave unmasked",transforms=(),layers=False)
77
+ prompt_input = gr.Textbox(label="Prompt")
78
+ num_inference_steps_input = gr.Slider(minimum=0, maximum=100, value=50, label="Number of Inference Steps")
79
+ image_guidance_scale_input = gr.Slider(minimum=0.0, maximum=2.5, value=1.5, label="Image Guidance Scale")
80
+ guidance_scale_input = gr.Slider(minimum=0.0, maximum=17.5, value=12.5, label="Guidance Scale")
81
+ seed_input = gr.Textbox(value="255", label="Random Seed")
82
+
83
+ inputs = [image_mask_input, prompt_input, num_inference_steps_input, image_guidance_scale_input, guidance_scale_input,
84
+ seed_input]
85
+ outputs = gr.Image(label="Generated Image")
86
+
87
+
88
+ # Custom HTML content
89
+ article_html = """
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+ <div style="text-align: center; max-width: 1000px; margin: 20px auto; font-family: Arial, sans-serif;">
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+ <h2 style="font-weight: 900; font-size: 2.5rem; margin-bottom: 0.5rem;">
92
+ 🖼️ UltraEdit for Fine-Grained Image Editing
93
+ </h2>
94
+ <div style="margin-bottom: 1rem;">
95
+ <h3 style="font-weight: 500; font-size: 1.25rem; margin: 0;">
96
+ </h3>
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+ <p style="font-weight: 400; font-size: 1rem; margin: 0.5rem 0;">
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+ Haozhe Zhao<sup>1*</sup>, Xiaojian Ma<sup>2*</sup>, Liang Chen<sup>1</sup>, Shuzheng Si<sup>1</sup>, Rujie Wu<sup>1</sup>,
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+ Kaikai An<sup>1</sup>, Peiyu Yu<sup>3</sup>, Minjia Zhang<sup>4</sup>, Qing Li<sup>2</sup>, Baobao Chang<sup>2</sup>
100
+ </p>
101
+ <p style="font-weight: 400; font-size: 1rem; margin: 0;">
102
+ <sup>1</sup>Peking University, <sup>2</sup>BIGAI, <sup>3</sup>UCLA, <sup>4</sup>UIUC
103
+ </p>
104
+ </div>
105
+ <div style="margin: 1rem 0; display: flex; justify-content: center; gap: 1.5rem; flex-wrap: wrap;">
106
+ <a href="https://huggingface.co/datasets/BleachNick/UltraEdit" style="display: flex; align-items: center; text-decoration: none; color: blue; font-weight: bold; gap: 0.5rem;">
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+ <img src="https://huggingface.co/front/assets/huggingface_logo-noborder.svg" alt="Dataset_4M" style="height: 20px; vertical-align: middle;"> Dataset
108
+ </a>
109
+ <a href="https://huggingface.co/datasets/BleachNick/UltraEdit_500k" style="display: flex; align-items: center; text-decoration: none; color: blue; font-weight: bold; gap: 0.5rem;">
110
+ <img src="https://huggingface.co/front/assets/huggingface_logo-noborder.svg" alt="Dataset_500k" style="height: 20px; vertical-align: middle;"> Dataset_500k
111
+ </a>
112
+ <a href="https://ultra-editing.github.io/" style="display: flex; align-items: center; text-decoration: none; color: blue; font-weight: bold; gap: 0.5rem;">
113
+ <span style="font-size: 20px; vertical-align: middle;">🔗</span> Page
114
+ </a>
115
+ <a href="https://huggingface.co/BleachNick/SD3_UltraEdit_w_mask" style="display: flex; align-items: center; text-decoration: none; color: blue; font-weight: bold; gap: 0.5rem;">
116
+ <img src="https://huggingface.co/front/assets/huggingface_logo-noborder.svg" alt="Checkpoint" style="height: 20px; vertical-align: middle;"> Checkpoint
117
+ </a>
118
+ <a href="https://github.com/HaozheZhao/UltraEdit" style="display: flex; align-items: center; text-decoration: none; color: blue; font-weight: bold; gap: 0.5rem;">
119
+ <img src="https://upload.wikimedia.org/wikipedia/commons/9/91/Octicons-mark-github.svg" alt="GitHub" style="height: 20px; vertical-align: middle;"> GitHub
120
+ </a>
121
+ </div>
122
+ <div style="text-align: left; margin: 0 auto; font-size: 1rem; line-height: 1.5;">
123
+ <p>
124
+ <b>UltraEdit</b> is a dataset designed for fine-grained, instruction-based image editing. It contains over 4 million free-form image editing samples and more than 100,000 region-based image editing samples, automatically generated with real images as anchors.
125
+ </p>
126
+ <p>
127
+ This demo allows you to perform image editing using the <a href="https://huggingface.co/stabilityai/stable-diffusion-3-medium-diffusers" style="color: blue; text-decoration: none;">Stable Diffusion 3</a> model trained with this extensive dataset. It supports both free-form (without mask) and region-based (with mask) image editing. Use the sliders to adjust the inference steps and guidance scales, and provide a seed for reproducibility. The image guidance scale of 1.5 and text guidance scale of 7.5 / 12.5 is a good start for free-from/region-based image editing.
128
+ </p>
129
+ </div>
130
+ </div>
131
+ """
132
+ html='''
133
+ <div style="text-align: left; margin-top: 2rem; font-size: 0.85rem; color: gray;">
134
+ <p>
135
+ <b>Usage Instructions:</b> You need to upload the images and prompts for editing. Use the pen tool to mark the areas you want to edit. If no region is marked, it will resort to free-form editing.
136
+ </p>
137
+ </div>
138
+ '''
139
+ demo = gr.Interface(
140
+ fn=generate,
141
+ inputs=inputs,
142
+ outputs=outputs,
143
+ description=article_html, # Add article parameter
144
+ article = html,
145
+ examples=mask_ex_list
146
+ )
147
+
148
+ demo.queue().launch()
149
+
UltraEdit/diffusers/.github/ISSUE_TEMPLATE/bug-report.yml ADDED
@@ -0,0 +1,106 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: "\U0001F41B Bug Report"
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+ description: Report a bug on Diffusers
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+ labels: [ "bug" ]
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+ body:
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+ - type: markdown
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+ attributes:
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+ value: |
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+ Thanks a lot for taking the time to file this issue 🤗.
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+ Issues do not only help to improve the library, but also publicly document common problems, questions, workflows for the whole community!
10
+ Thus, issues are of the same importance as pull requests when contributing to this library ❤️.
11
+ In order to make your issue as **useful for the community as possible**, let's try to stick to some simple guidelines:
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+ - 1. Please try to be as precise and concise as possible.
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+ *Give your issue a fitting title. Assume that someone which very limited knowledge of Diffusers can understand your issue. Add links to the source code, documentation other issues, pull requests etc...*
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+ - 2. If your issue is about something not working, **always** provide a reproducible code snippet. The reader should be able to reproduce your issue by **only copy-pasting your code snippet into a Python shell**.
15
+ *The community cannot solve your issue if it cannot reproduce it. If your bug is related to training, add your training script and make everything needed to train public. Otherwise, just add a simple Python code snippet.*
16
+ - 3. Add the **minimum** amount of code / context that is needed to understand, reproduce your issue.
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+ *Make the life of maintainers easy. `diffusers` is getting many issues every day. Make sure your issue is about one bug and one bug only. Make sure you add only the context, code needed to understand your issues - nothing more. Generally, every issue is a way of documenting this library, try to make it a good documentation entry.*
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+ - 4. For issues related to community pipelines (i.e., the pipelines located in the `examples/community` folder), please tag the author of the pipeline in your issue thread as those pipelines are not maintained.
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+ - type: markdown
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+ attributes:
21
+ value: |
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+ For more in-detail information on how to write good issues you can have a look [here](https://huggingface.co/course/chapter8/5?fw=pt).
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+ - type: textarea
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+ id: bug-description
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+ attributes:
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+ label: Describe the bug
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+ description: A clear and concise description of what the bug is. If you intend to submit a pull request for this issue, tell us in the description. Thanks!
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+ placeholder: Bug description
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+ validations:
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+ required: true
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+ - type: textarea
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+ id: reproduction
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+ attributes:
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+ label: Reproduction
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+ description: Please provide a minimal reproducible code which we can copy/paste and reproduce the issue.
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+ placeholder: Reproduction
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+ validations:
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+ required: true
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+ - type: textarea
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+ id: logs
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+ attributes:
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+ label: Logs
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+ description: "Please include the Python logs if you can."
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+ render: shell
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+ - type: textarea
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+ id: system-info
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+ attributes:
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+ label: System Info
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+ description: Please share your system info with us. You can run the command `diffusers-cli env` and copy-paste its output below.
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+ placeholder: Diffusers version, platform, Python version, ...
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+ - type: textarea
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+ label: Who can help?
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+ description: |
58
+ Your issue will be replied to more quickly if you can figure out the right person to tag with @.
59
+ If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
60
+
61
+ All issues are read by one of the core maintainers, so if you don't know who to tag, just leave this blank and
62
+ a core maintainer will ping the right person.
63
+
64
+ Please tag a maximum of 2 people.
65
+
66
+ Questions on DiffusionPipeline (Saving, Loading, From pretrained, ...):
67
+
68
+ Questions on pipelines:
69
+ - Stable Diffusion @yiyixuxu @DN6 @sayakpaul
70
+ - Stable Diffusion XL @yiyixuxu @sayakpaul @DN6
71
+ - Kandinsky @yiyixuxu
72
+ - ControlNet @sayakpaul @yiyixuxu @DN6
73
+ - T2I Adapter @sayakpaul @yiyixuxu @DN6
74
+ - IF @DN6
75
+ - Text-to-Video / Video-to-Video @DN6 @sayakpaul
76
+ - Wuerstchen @DN6
77
+ - Other: @yiyixuxu @DN6
78
+
79
+ Questions on models:
80
+ - UNet @DN6 @yiyixuxu @sayakpaul
81
+ - VAE @sayakpaul @DN6 @yiyixuxu
82
+ - Transformers/Attention @DN6 @yiyixuxu @sayakpaul @DN6
83
+
84
+ Questions on Schedulers: @yiyixuxu
85
+
86
+ Questions on LoRA: @sayakpaul
87
+
88
+ Questions on Textual Inversion: @sayakpaul
89
+
90
+ Questions on Training:
91
+ - DreamBooth @sayakpaul
92
+ - Text-to-Image Fine-tuning @sayakpaul
93
+ - Textual Inversion @sayakpaul
94
+ - ControlNet @sayakpaul
95
+
96
+ Questions on Tests: @DN6 @sayakpaul @yiyixuxu
97
+
98
+ Questions on Documentation: @stevhliu
99
+
100
+ Questions on JAX- and MPS-related things: @pcuenca
101
+
102
+ Questions on audio pipelines: @DN6
103
+
104
+
105
+
106
+ placeholder: "@Username ..."
UltraEdit/diffusers/.github/ISSUE_TEMPLATE/config.yml ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ contact_links:
2
+ - name: Questions / Discussions
3
+ url: https://github.com/huggingface/diffusers/discussions
4
+ about: General usage questions and community discussions
UltraEdit/diffusers/.github/ISSUE_TEMPLATE/feature_request.md ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ name: "\U0001F680 Feature Request"
3
+ about: Suggest an idea for this project
4
+ title: ''
5
+ labels: ''
6
+ assignees: ''
7
+
8
+ ---
9
+
10
+ **Is your feature request related to a problem? Please describe.**
11
+ A clear and concise description of what the problem is. Ex. I'm always frustrated when [...].
12
+
13
+ **Describe the solution you'd like.**
14
+ A clear and concise description of what you want to happen.
15
+
16
+ **Describe alternatives you've considered.**
17
+ A clear and concise description of any alternative solutions or features you've considered.
18
+
19
+ **Additional context.**
20
+ Add any other context or screenshots about the feature request here.
UltraEdit/diffusers/.github/ISSUE_TEMPLATE/feedback.md ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ name: "💬 Feedback about API Design"
3
+ about: Give feedback about the current API design
4
+ title: ''
5
+ labels: ''
6
+ assignees: ''
7
+
8
+ ---
9
+
10
+ **What API design would you like to have changed or added to the library? Why?**
11
+
12
+ **What use case would this enable or better enable? Can you give us a code example?**
UltraEdit/diffusers/.github/ISSUE_TEMPLATE/new-model-addition.yml ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: "\U0001F31F New Model/Pipeline/Scheduler Addition"
2
+ description: Submit a proposal/request to implement a new diffusion model/pipeline/scheduler
3
+ labels: [ "New model/pipeline/scheduler" ]
4
+
5
+ body:
6
+ - type: textarea
7
+ id: description-request
8
+ validations:
9
+ required: true
10
+ attributes:
11
+ label: Model/Pipeline/Scheduler description
12
+ description: |
13
+ Put any and all important information relative to the model/pipeline/scheduler
14
+
15
+ - type: checkboxes
16
+ id: information-tasks
17
+ attributes:
18
+ label: Open source status
19
+ description: |
20
+ Please note that if the model implementation isn't available or if the weights aren't open-source, we are less likely to implement it in `diffusers`.
21
+ options:
22
+ - label: "The model implementation is available."
23
+ - label: "The model weights are available (Only relevant if addition is not a scheduler)."
24
+
25
+ - type: textarea
26
+ id: additional-info
27
+ attributes:
28
+ label: Provide useful links for the implementation
29
+ description: |
30
+ Please provide information regarding the implementation, the weights, and the authors.
31
+ Please mention the authors by @gh-username if you're aware of their usernames.
UltraEdit/diffusers/.github/ISSUE_TEMPLATE/translate.md ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ name: 🌐 Translating a New Language?
3
+ about: Start a new translation effort in your language
4
+ title: '[<languageCode>] Translating docs to <languageName>'
5
+ labels: WIP
6
+ assignees: ''
7
+
8
+ ---
9
+
10
+ <!--
11
+ Note: Please search to see if an issue already exists for the language you are trying to translate.
12
+ -->
13
+
14
+ Hi!
15
+
16
+ Let's bring the documentation to all the <languageName>-speaking community 🌐.
17
+
18
+ Who would want to translate? Please follow the 🤗 [TRANSLATING guide](https://github.com/huggingface/diffusers/blob/main/docs/TRANSLATING.md). Here is a list of the files ready for translation. Let us know in this issue if you'd like to translate any, and we'll add your name to the list.
19
+
20
+ Some notes:
21
+
22
+ * Please translate using an informal tone (imagine you are talking with a friend about Diffusers 🤗).
23
+ * Please translate in a gender-neutral way.
24
+ * Add your translations to the folder called `<languageCode>` inside the [source folder](https://github.com/huggingface/diffusers/tree/main/docs/source).
25
+ * Register your translation in `<languageCode>/_toctree.yml`; please follow the order of the [English version](https://github.com/huggingface/diffusers/blob/main/docs/source/en/_toctree.yml).
26
+ * Once you're finished, open a pull request and tag this issue by including #issue-number in the description, where issue-number is the number of this issue. Please ping @stevhliu for review.
27
+ * 🙋 If you'd like others to help you with the translation, you can also post in the 🤗 [forums](https://discuss.huggingface.co/c/discussion-related-to-httpsgithubcomhuggingfacediffusers/63).
28
+
29
+ Thank you so much for your help! 🤗
UltraEdit/diffusers/.github/PULL_REQUEST_TEMPLATE.md ADDED
@@ -0,0 +1,60 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # What does this PR do?
2
+
3
+ <!--
4
+ Congratulations! You've made it this far! You're not quite done yet though.
5
+
6
+ Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
7
+
8
+ Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change.
9
+
10
+ Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost.
11
+ -->
12
+
13
+ <!-- Remove if not applicable -->
14
+
15
+ Fixes # (issue)
16
+
17
+
18
+ ## Before submitting
19
+ - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
20
+ - [ ] Did you read the [contributor guideline](https://github.com/huggingface/diffusers/blob/main/CONTRIBUTING.md)?
21
+ - [ ] Did you read our [philosophy doc](https://github.com/huggingface/diffusers/blob/main/PHILOSOPHY.md) (important for complex PRs)?
22
+ - [ ] Was this discussed/approved via a GitHub issue or the [forum](https://discuss.huggingface.co/c/discussion-related-to-httpsgithubcomhuggingfacediffusers/63)? Please add a link to it if that's the case.
23
+ - [ ] Did you make sure to update the documentation with your changes? Here are the
24
+ [documentation guidelines](https://github.com/huggingface/diffusers/tree/main/docs), and
25
+ [here are tips on formatting docstrings](https://github.com/huggingface/diffusers/tree/main/docs#writing-source-documentation).
26
+ - [ ] Did you write any new necessary tests?
27
+
28
+
29
+ ## Who can review?
30
+
31
+ Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
32
+ members/contributors who may be interested in your PR.
33
+
34
+ <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @.
35
+
36
+ If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
37
+ Please tag fewer than 3 people.
38
+
39
+ Core library:
40
+
41
+ - Schedulers: @yiyixuxu
42
+ - Pipelines: @sayakpaul @yiyixuxu @DN6
43
+ - Training examples: @sayakpaul
44
+ - Docs: @stevhliu and @sayakpaul
45
+ - JAX and MPS: @pcuenca
46
+ - Audio: @sanchit-gandhi
47
+ - General functionalities: @sayakpaul @yiyixuxu @DN6
48
+
49
+ Integrations:
50
+
51
+ - deepspeed: HF Trainer/Accelerate: @pacman100
52
+
53
+ HF projects:
54
+
55
+ - accelerate: [different repo](https://github.com/huggingface/accelerate)
56
+ - datasets: [different repo](https://github.com/huggingface/datasets)
57
+ - transformers: [different repo](https://github.com/huggingface/transformers)
58
+ - safetensors: [different repo](https://github.com/huggingface/safetensors)
59
+
60
+ -->
UltraEdit/diffusers/.github/actions/setup-miniconda/action.yml ADDED
@@ -0,0 +1,146 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Set up conda environment for testing
2
+
3
+ description: Sets up miniconda in your ${RUNNER_TEMP} environment and gives you the ${CONDA_RUN} environment variable so you don't have to worry about polluting non-empeheral runners anymore
4
+
5
+ inputs:
6
+ python-version:
7
+ description: If set to any value, don't use sudo to clean the workspace
8
+ required: false
9
+ type: string
10
+ default: "3.9"
11
+ miniconda-version:
12
+ description: Miniconda version to install
13
+ required: false
14
+ type: string
15
+ default: "4.12.0"
16
+ environment-file:
17
+ description: Environment file to install dependencies from
18
+ required: false
19
+ type: string
20
+ default: ""
21
+
22
+ runs:
23
+ using: composite
24
+ steps:
25
+ # Use the same trick from https://github.com/marketplace/actions/setup-miniconda
26
+ # to refresh the cache daily. This is kind of optional though
27
+ - name: Get date
28
+ id: get-date
29
+ shell: bash
30
+ run: echo "today=$(/bin/date -u '+%Y%m%d')d" >> $GITHUB_OUTPUT
31
+ - name: Setup miniconda cache
32
+ id: miniconda-cache
33
+ uses: actions/cache@v2
34
+ with:
35
+ path: ${{ runner.temp }}/miniconda
36
+ key: miniconda-${{ runner.os }}-${{ runner.arch }}-${{ inputs.python-version }}-${{ steps.get-date.outputs.today }}
37
+ - name: Install miniconda (${{ inputs.miniconda-version }})
38
+ if: steps.miniconda-cache.outputs.cache-hit != 'true'
39
+ env:
40
+ MINICONDA_VERSION: ${{ inputs.miniconda-version }}
41
+ shell: bash -l {0}
42
+ run: |
43
+ MINICONDA_INSTALL_PATH="${RUNNER_TEMP}/miniconda"
44
+ mkdir -p "${MINICONDA_INSTALL_PATH}"
45
+ case ${RUNNER_OS}-${RUNNER_ARCH} in
46
+ Linux-X64)
47
+ MINICONDA_ARCH="Linux-x86_64"
48
+ ;;
49
+ macOS-ARM64)
50
+ MINICONDA_ARCH="MacOSX-arm64"
51
+ ;;
52
+ macOS-X64)
53
+ MINICONDA_ARCH="MacOSX-x86_64"
54
+ ;;
55
+ *)
56
+ echo "::error::Platform ${RUNNER_OS}-${RUNNER_ARCH} currently unsupported using this action"
57
+ exit 1
58
+ ;;
59
+ esac
60
+ MINICONDA_URL="https://repo.anaconda.com/miniconda/Miniconda3-py39_${MINICONDA_VERSION}-${MINICONDA_ARCH}.sh"
61
+ curl -fsSL "${MINICONDA_URL}" -o "${MINICONDA_INSTALL_PATH}/miniconda.sh"
62
+ bash "${MINICONDA_INSTALL_PATH}/miniconda.sh" -b -u -p "${MINICONDA_INSTALL_PATH}"
63
+ rm -rf "${MINICONDA_INSTALL_PATH}/miniconda.sh"
64
+ - name: Update GitHub path to include miniconda install
65
+ shell: bash
66
+ run: |
67
+ MINICONDA_INSTALL_PATH="${RUNNER_TEMP}/miniconda"
68
+ echo "${MINICONDA_INSTALL_PATH}/bin" >> $GITHUB_PATH
69
+ - name: Setup miniconda env cache (with env file)
70
+ id: miniconda-env-cache-env-file
71
+ if: ${{ runner.os }} == 'macOS' && ${{ inputs.environment-file }} != ''
72
+ uses: actions/cache@v2
73
+ with:
74
+ path: ${{ runner.temp }}/conda-python-${{ inputs.python-version }}
75
+ key: miniconda-env-${{ runner.os }}-${{ runner.arch }}-${{ inputs.python-version }}-${{ steps.get-date.outputs.today }}-${{ hashFiles(inputs.environment-file) }}
76
+ - name: Setup miniconda env cache (without env file)
77
+ id: miniconda-env-cache
78
+ if: ${{ runner.os }} == 'macOS' && ${{ inputs.environment-file }} == ''
79
+ uses: actions/cache@v2
80
+ with:
81
+ path: ${{ runner.temp }}/conda-python-${{ inputs.python-version }}
82
+ key: miniconda-env-${{ runner.os }}-${{ runner.arch }}-${{ inputs.python-version }}-${{ steps.get-date.outputs.today }}
83
+ - name: Setup conda environment with python (v${{ inputs.python-version }})
84
+ if: steps.miniconda-env-cache-env-file.outputs.cache-hit != 'true' && steps.miniconda-env-cache.outputs.cache-hit != 'true'
85
+ shell: bash
86
+ env:
87
+ PYTHON_VERSION: ${{ inputs.python-version }}
88
+ ENV_FILE: ${{ inputs.environment-file }}
89
+ run: |
90
+ CONDA_BASE_ENV="${RUNNER_TEMP}/conda-python-${PYTHON_VERSION}"
91
+ ENV_FILE_FLAG=""
92
+ if [[ -f "${ENV_FILE}" ]]; then
93
+ ENV_FILE_FLAG="--file ${ENV_FILE}"
94
+ elif [[ -n "${ENV_FILE}" ]]; then
95
+ echo "::warning::Specified env file (${ENV_FILE}) not found, not going to include it"
96
+ fi
97
+ conda create \
98
+ --yes \
99
+ --prefix "${CONDA_BASE_ENV}" \
100
+ "python=${PYTHON_VERSION}" \
101
+ ${ENV_FILE_FLAG} \
102
+ cmake=3.22 \
103
+ conda-build=3.21 \
104
+ ninja=1.10 \
105
+ pkg-config=0.29 \
106
+ wheel=0.37
107
+ - name: Clone the base conda environment and update GitHub env
108
+ shell: bash
109
+ env:
110
+ PYTHON_VERSION: ${{ inputs.python-version }}
111
+ CONDA_BASE_ENV: ${{ runner.temp }}/conda-python-${{ inputs.python-version }}
112
+ run: |
113
+ CONDA_ENV="${RUNNER_TEMP}/conda_environment_${GITHUB_RUN_ID}"
114
+ conda create \
115
+ --yes \
116
+ --prefix "${CONDA_ENV}" \
117
+ --clone "${CONDA_BASE_ENV}"
118
+ # TODO: conda-build could not be cloned because it hardcodes the path, so it
119
+ # could not be cached
120
+ conda install --yes -p ${CONDA_ENV} conda-build=3.21
121
+ echo "CONDA_ENV=${CONDA_ENV}" >> "${GITHUB_ENV}"
122
+ echo "CONDA_RUN=conda run -p ${CONDA_ENV} --no-capture-output" >> "${GITHUB_ENV}"
123
+ echo "CONDA_BUILD=conda run -p ${CONDA_ENV} conda-build" >> "${GITHUB_ENV}"
124
+ echo "CONDA_INSTALL=conda install -p ${CONDA_ENV}" >> "${GITHUB_ENV}"
125
+ - name: Get disk space usage and throw an error for low disk space
126
+ shell: bash
127
+ run: |
128
+ echo "Print the available disk space for manual inspection"
129
+ df -h
130
+ # Set the minimum requirement space to 4GB
131
+ MINIMUM_AVAILABLE_SPACE_IN_GB=4
132
+ MINIMUM_AVAILABLE_SPACE_IN_KB=$(($MINIMUM_AVAILABLE_SPACE_IN_GB * 1024 * 1024))
133
+ # Use KB to avoid floating point warning like 3.1GB
134
+ df -k | tr -s ' ' | cut -d' ' -f 4,9 | while read -r LINE;
135
+ do
136
+ AVAIL=$(echo $LINE | cut -f1 -d' ')
137
+ MOUNT=$(echo $LINE | cut -f2 -d' ')
138
+ if [ "$MOUNT" = "/" ]; then
139
+ if [ "$AVAIL" -lt "$MINIMUM_AVAILABLE_SPACE_IN_KB" ]; then
140
+ echo "There is only ${AVAIL}KB free space left in $MOUNT, which is less than the minimum requirement of ${MINIMUM_AVAILABLE_SPACE_IN_KB}KB. Please help create an issue to PyTorch Release Engineering via https://github.com/pytorch/test-infra/issues and provide the link to the workflow run."
141
+ exit 1;
142
+ else
143
+ echo "There is ${AVAIL}KB free space left in $MOUNT, continue"
144
+ fi
145
+ fi
146
+ done
UltraEdit/diffusers/.github/workflows/benchmark.yml ADDED
@@ -0,0 +1,53 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Benchmarking tests
2
+
3
+ on:
4
+ workflow_dispatch:
5
+ schedule:
6
+ - cron: "30 1 1,15 * *" # every 2 weeks on the 1st and the 15th of every month at 1:30 AM
7
+
8
+ env:
9
+ DIFFUSERS_IS_CI: yes
10
+ HF_HOME: /mnt/cache
11
+ OMP_NUM_THREADS: 8
12
+ MKL_NUM_THREADS: 8
13
+
14
+ jobs:
15
+ torch_pipelines_cuda_benchmark_tests:
16
+ name: Torch Core Pipelines CUDA Benchmarking Tests
17
+ strategy:
18
+ fail-fast: false
19
+ max-parallel: 1
20
+ runs-on: [single-gpu, nvidia-gpu, a10, ci]
21
+ container:
22
+ image: diffusers/diffusers-pytorch-cuda
23
+ options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/ --gpus 0
24
+ steps:
25
+ - name: Checkout diffusers
26
+ uses: actions/checkout@v3
27
+ with:
28
+ fetch-depth: 2
29
+ - name: NVIDIA-SMI
30
+ run: |
31
+ nvidia-smi
32
+ - name: Install dependencies
33
+ run: |
34
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
35
+ python -m uv pip install -e [quality,test]
36
+ python -m uv pip install pandas peft
37
+ - name: Environment
38
+ run: |
39
+ python utils/print_env.py
40
+ - name: Diffusers Benchmarking
41
+ env:
42
+ HF_TOKEN: ${{ secrets.DIFFUSERS_BOT_TOKEN }}
43
+ BASE_PATH: benchmark_outputs
44
+ run: |
45
+ export TOTAL_GPU_MEMORY=$(python -c "import torch; print(torch.cuda.get_device_properties(0).total_memory / (1024**3))")
46
+ cd benchmarks && mkdir ${BASE_PATH} && python run_all.py && python push_results.py
47
+
48
+ - name: Test suite reports artifacts
49
+ if: ${{ always() }}
50
+ uses: actions/upload-artifact@v2
51
+ with:
52
+ name: benchmark_test_reports
53
+ path: benchmarks/benchmark_outputs
UltraEdit/diffusers/.github/workflows/build_docker_images.yml ADDED
@@ -0,0 +1,101 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Test, build, and push Docker images
2
+
3
+ on:
4
+ pull_request: # During PRs, we just check if the changes Dockerfiles can be successfully built
5
+ branches:
6
+ - main
7
+ paths:
8
+ - "docker/**"
9
+ workflow_dispatch:
10
+ schedule:
11
+ - cron: "0 0 * * *" # every day at midnight
12
+
13
+ concurrency:
14
+ group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
15
+ cancel-in-progress: true
16
+
17
+ env:
18
+ REGISTRY: diffusers
19
+ CI_SLACK_CHANNEL: ${{ secrets.CI_DOCKER_CHANNEL }}
20
+
21
+ jobs:
22
+ test-build-docker-images:
23
+ runs-on: [ self-hosted, intel-cpu, 8-cpu, ci ]
24
+ if: github.event_name == 'pull_request'
25
+ steps:
26
+ - name: Set up Docker Buildx
27
+ uses: docker/setup-buildx-action@v1
28
+
29
+ - name: Check out code
30
+ uses: actions/checkout@v3
31
+
32
+ - name: Find Changed Dockerfiles
33
+ id: file_changes
34
+ uses: jitterbit/get-changed-files@v1
35
+ with:
36
+ format: 'space-delimited'
37
+ token: ${{ secrets.GITHUB_TOKEN }}
38
+
39
+ - name: Build Changed Docker Images
40
+ run: |
41
+ CHANGED_FILES="${{ steps.file_changes.outputs.all }}"
42
+ for FILE in $CHANGED_FILES; do
43
+ if [[ "$FILE" == docker/*Dockerfile ]]; then
44
+ DOCKER_PATH="${FILE%/Dockerfile}"
45
+ DOCKER_TAG=$(basename "$DOCKER_PATH")
46
+ echo "Building Docker image for $DOCKER_TAG"
47
+ docker build -t "$DOCKER_TAG" "$DOCKER_PATH"
48
+ fi
49
+ done
50
+ if: steps.file_changes.outputs.all != ''
51
+
52
+ build-and-push-docker-images:
53
+ runs-on: [ self-hosted, intel-cpu, 8-cpu, ci ]
54
+ if: github.event_name != 'pull_request'
55
+
56
+ permissions:
57
+ contents: read
58
+ packages: write
59
+
60
+ strategy:
61
+ fail-fast: false
62
+ matrix:
63
+ image-name:
64
+ - diffusers-pytorch-cpu
65
+ - diffusers-pytorch-cuda
66
+ - diffusers-pytorch-compile-cuda
67
+ - diffusers-pytorch-xformers-cuda
68
+ - diffusers-flax-cpu
69
+ - diffusers-flax-tpu
70
+ - diffusers-onnxruntime-cpu
71
+ - diffusers-onnxruntime-cuda
72
+ - diffusers-doc-builder
73
+
74
+ steps:
75
+ - name: Checkout repository
76
+ uses: actions/checkout@v3
77
+ - name: Set up Docker Buildx
78
+ uses: docker/setup-buildx-action@v1
79
+ - name: Login to Docker Hub
80
+ uses: docker/login-action@v2
81
+ with:
82
+ username: ${{ env.REGISTRY }}
83
+ password: ${{ secrets.DOCKERHUB_TOKEN }}
84
+ - name: Build and push
85
+ uses: docker/build-push-action@v3
86
+ with:
87
+ no-cache: true
88
+ context: ./docker/${{ matrix.image-name }}
89
+ push: true
90
+ tags: ${{ env.REGISTRY }}/${{ matrix.image-name }}:latest
91
+
92
+ - name: Post to a Slack channel
93
+ id: slack
94
+ uses: huggingface/hf-workflows/.github/actions/post-slack@main
95
+ with:
96
+ # Slack channel id, channel name, or user id to post message.
97
+ # See also: https://api.slack.com/methods/chat.postMessage#channels
98
+ slack_channel: ${{ env.CI_SLACK_CHANNEL }}
99
+ title: "🤗 Results of the ${{ matrix.image-name }} Docker Image build"
100
+ status: ${{ job.status }}
101
+ slack_token: ${{ secrets.SLACK_CIFEEDBACK_BOT_TOKEN }}
UltraEdit/diffusers/.github/workflows/build_documentation.yml ADDED
@@ -0,0 +1,27 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Build documentation
2
+
3
+ on:
4
+ push:
5
+ branches:
6
+ - main
7
+ - doc-builder*
8
+ - v*-release
9
+ - v*-patch
10
+ paths:
11
+ - "src/diffusers/**.py"
12
+ - "examples/**"
13
+ - "docs/**"
14
+
15
+ jobs:
16
+ build:
17
+ uses: huggingface/doc-builder/.github/workflows/build_main_documentation.yml@main
18
+ with:
19
+ commit_sha: ${{ github.sha }}
20
+ install_libgl1: true
21
+ package: diffusers
22
+ notebook_folder: diffusers_doc
23
+ languages: en ko zh ja pt
24
+ custom_container: diffusers/diffusers-doc-builder
25
+ secrets:
26
+ token: ${{ secrets.HUGGINGFACE_PUSH }}
27
+ hf_token: ${{ secrets.HF_DOC_BUILD_PUSH }}
UltraEdit/diffusers/.github/workflows/build_pr_documentation.yml ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Build PR Documentation
2
+
3
+ on:
4
+ pull_request:
5
+ paths:
6
+ - "src/diffusers/**.py"
7
+ - "examples/**"
8
+ - "docs/**"
9
+
10
+ concurrency:
11
+ group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
12
+ cancel-in-progress: true
13
+
14
+ jobs:
15
+ build:
16
+ uses: huggingface/doc-builder/.github/workflows/build_pr_documentation.yml@main
17
+ with:
18
+ commit_sha: ${{ github.event.pull_request.head.sha }}
19
+ pr_number: ${{ github.event.number }}
20
+ install_libgl1: true
21
+ package: diffusers
22
+ languages: en ko zh ja pt
23
+ custom_container: diffusers/diffusers-doc-builder
UltraEdit/diffusers/.github/workflows/mirror_community_pipeline.yml ADDED
@@ -0,0 +1,89 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Mirror Community Pipeline
2
+
3
+ on:
4
+ # Push changes on the main branch
5
+ push:
6
+ branches:
7
+ - main
8
+ paths:
9
+ - 'examples/community/**.py'
10
+
11
+ # And on tag creation (e.g. `v0.28.1`)
12
+ tags:
13
+ - '*'
14
+
15
+ # Manual trigger with ref input
16
+ workflow_dispatch:
17
+ inputs:
18
+ ref:
19
+ description: "Either 'main' or a tag ref"
20
+ required: true
21
+ default: 'main'
22
+
23
+ jobs:
24
+ mirror_community_pipeline:
25
+ runs-on: ubuntu-latest
26
+ steps:
27
+ # Checkout to correct ref
28
+ # If workflow dispatch
29
+ # If ref is 'main', set:
30
+ # CHECKOUT_REF=refs/heads/main
31
+ # PATH_IN_REPO=main
32
+ # Else it must be a tag. Set:
33
+ # CHECKOUT_REF=refs/tags/{tag}
34
+ # PATH_IN_REPO={tag}
35
+ # If not workflow dispatch
36
+ # If ref is 'refs/heads/main' => set 'main'
37
+ # Else it must be a tag => set {tag}
38
+ - name: Set checkout_ref and path_in_repo
39
+ run: |
40
+ if [ "${{ github.event_name }}" == "workflow_dispatch" ]; then
41
+ if [ -z "${{ github.event.inputs.ref }}" ]; then
42
+ echo "Error: Missing ref input"
43
+ exit 1
44
+ elif [ "${{ github.event.inputs.ref }}" == "main" ]; then
45
+ echo "CHECKOUT_REF=refs/heads/main" >> $GITHUB_ENV
46
+ echo "PATH_IN_REPO=main" >> $GITHUB_ENV
47
+ else
48
+ echo "CHECKOUT_REF=refs/tags/${{ github.event.inputs.ref }}" >> $GITHUB_ENV
49
+ echo "PATH_IN_REPO=${{ github.event.inputs.ref }}" >> $GITHUB_ENV
50
+ fi
51
+ elif [ "${{ github.ref }}" == "refs/heads/main" ]; then
52
+ echo "CHECKOUT_REF=${{ github.ref }}" >> $GITHUB_ENV
53
+ echo "PATH_IN_REPO=main" >> $GITHUB_ENV
54
+ else
55
+ # e.g. refs/tags/v0.28.1 -> v0.28.1
56
+ echo "CHECKOUT_REF=${{ github.ref }}" >> $GITHUB_ENV
57
+ echo "PATH_IN_REPO=$(echo ${{ github.ref }} | sed 's/^refs\/tags\///')" >> $GITHUB_ENV
58
+ fi
59
+ - name: Print env vars
60
+ run: |
61
+ echo "CHECKOUT_REF: ${{ env.CHECKOUT_REF }}"
62
+ echo "PATH_IN_REPO: ${{ env.PATH_IN_REPO }}"
63
+ - uses: actions/checkout@v3
64
+ with:
65
+ ref: ${{ env.CHECKOUT_REF }}
66
+
67
+ # Setup + install dependencies
68
+ - name: Set up Python
69
+ uses: actions/setup-python@v4
70
+ with:
71
+ python-version: "3.10"
72
+ - name: Install dependencies
73
+ run: |
74
+ python -m pip install --upgrade pip
75
+ pip install --upgrade huggingface_hub
76
+
77
+ # Check secret is set
78
+ - name: whoami
79
+ run: huggingface-cli whoami
80
+ env:
81
+ HF_TOKEN: ${{ secrets.HF_TOKEN_MIRROR_COMMUNITY_PIPELINES }}
82
+
83
+ # Push to HF! (under subfolder based on checkout ref)
84
+ # https://huggingface.co/datasets/diffusers/community-pipelines-mirror
85
+ - name: Mirror community pipeline to HF
86
+ run: huggingface-cli upload diffusers/community-pipelines-mirror ./examples/community ${PATH_IN_REPO} --repo-type dataset
87
+ env:
88
+ PATH_IN_REPO: ${{ env.PATH_IN_REPO }}
89
+ HF_TOKEN: ${{ secrets.HF_TOKEN_MIRROR_COMMUNITY_PIPELINES }}
UltraEdit/diffusers/.github/workflows/nightly_tests.yml ADDED
@@ -0,0 +1,414 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Nightly and release tests on main/release branch
2
+
3
+ on:
4
+ workflow_dispatch:
5
+ schedule:
6
+ - cron: "0 0 * * *" # every day at midnight
7
+
8
+ env:
9
+ DIFFUSERS_IS_CI: yes
10
+ HF_HOME: /mnt/cache
11
+ OMP_NUM_THREADS: 8
12
+ MKL_NUM_THREADS: 8
13
+ PYTEST_TIMEOUT: 600
14
+ RUN_SLOW: yes
15
+ RUN_NIGHTLY: yes
16
+ PIPELINE_USAGE_CUTOFF: 5000
17
+ SLACK_API_TOKEN: ${{ secrets.SLACK_CIFEEDBACK_BOT_TOKEN }}
18
+
19
+ jobs:
20
+ setup_torch_cuda_pipeline_matrix:
21
+ name: Setup Torch Pipelines Matrix
22
+ runs-on: diffusers/diffusers-pytorch-cpu
23
+ outputs:
24
+ pipeline_test_matrix: ${{ steps.fetch_pipeline_matrix.outputs.pipeline_test_matrix }}
25
+ steps:
26
+ - name: Checkout diffusers
27
+ uses: actions/checkout@v3
28
+ with:
29
+ fetch-depth: 2
30
+ - name: Set up Python
31
+ uses: actions/setup-python@v4
32
+ with:
33
+ python-version: "3.8"
34
+ - name: Install dependencies
35
+ run: |
36
+ pip install -e .
37
+ pip install huggingface_hub
38
+ - name: Fetch Pipeline Matrix
39
+ id: fetch_pipeline_matrix
40
+ run: |
41
+ matrix=$(python utils/fetch_torch_cuda_pipeline_test_matrix.py)
42
+ echo $matrix
43
+ echo "pipeline_test_matrix=$matrix" >> $GITHUB_OUTPUT
44
+
45
+ - name: Pipeline Tests Artifacts
46
+ if: ${{ always() }}
47
+ uses: actions/upload-artifact@v2
48
+ with:
49
+ name: test-pipelines.json
50
+ path: reports
51
+
52
+ run_nightly_tests_for_torch_pipelines:
53
+ name: Torch Pipelines CUDA Nightly Tests
54
+ needs: setup_torch_cuda_pipeline_matrix
55
+ strategy:
56
+ fail-fast: false
57
+ matrix:
58
+ module: ${{ fromJson(needs.setup_torch_cuda_pipeline_matrix.outputs.pipeline_test_matrix) }}
59
+ runs-on: [single-gpu, nvidia-gpu, t4, ci]
60
+ container:
61
+ image: diffusers/diffusers-pytorch-cuda
62
+ options: --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface/diffusers:/mnt/cache/ --gpus 0
63
+ steps:
64
+ - name: Checkout diffusers
65
+ uses: actions/checkout@v3
66
+ with:
67
+ fetch-depth: 2
68
+ - name: NVIDIA-SMI
69
+ run: nvidia-smi
70
+
71
+ - name: Install dependencies
72
+ run: |
73
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
74
+ python -m uv pip install -e [quality,test]
75
+ python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
76
+ python -m uv pip install pytest-reportlog
77
+
78
+ - name: Environment
79
+ run: |
80
+ python utils/print_env.py
81
+
82
+ - name: Nightly PyTorch CUDA checkpoint (pipelines) tests
83
+ env:
84
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
85
+ # https://pytorch.org/docs/stable/notes/randomness.html#avoiding-nondeterministic-algorithms
86
+ CUBLAS_WORKSPACE_CONFIG: :16:8
87
+ run: |
88
+ python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
89
+ -s -v -k "not Flax and not Onnx" \
90
+ --make-reports=tests_pipeline_${{ matrix.module }}_cuda \
91
+ --report-log=tests_pipeline_${{ matrix.module }}_cuda.log \
92
+ tests/pipelines/${{ matrix.module }}
93
+
94
+ - name: Failure short reports
95
+ if: ${{ failure() }}
96
+ run: |
97
+ cat reports/tests_pipeline_${{ matrix.module }}_cuda_stats.txt
98
+ cat reports/tests_pipeline_${{ matrix.module }}_cuda_failures_short.txt
99
+
100
+ - name: Test suite reports artifacts
101
+ if: ${{ always() }}
102
+ uses: actions/upload-artifact@v2
103
+ with:
104
+ name: pipeline_${{ matrix.module }}_test_reports
105
+ path: reports
106
+
107
+ - name: Generate Report and Notify Channel
108
+ if: always()
109
+ run: |
110
+ pip install slack_sdk tabulate
111
+ python scripts/log_reports.py >> $GITHUB_STEP_SUMMARY
112
+
113
+ run_nightly_tests_for_other_torch_modules:
114
+ name: Torch Non-Pipelines CUDA Nightly Tests
115
+ runs-on: [single-gpu, nvidia-gpu, t4, ci]
116
+ container:
117
+ image: diffusers/diffusers-pytorch-cuda
118
+ options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/ --gpus 0
119
+ defaults:
120
+ run:
121
+ shell: bash
122
+ strategy:
123
+ matrix:
124
+ module: [models, schedulers, others, examples]
125
+ steps:
126
+ - name: Checkout diffusers
127
+ uses: actions/checkout@v3
128
+ with:
129
+ fetch-depth: 2
130
+
131
+ - name: Install dependencies
132
+ run: |
133
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
134
+ python -m uv pip install -e [quality,test]
135
+ python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
136
+ python -m uv pip install pytest-reportlog
137
+
138
+ - name: Environment
139
+ run: python utils/print_env.py
140
+
141
+ - name: Run nightly PyTorch CUDA tests for non-pipeline modules
142
+ if: ${{ matrix.module != 'examples'}}
143
+ env:
144
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
145
+ # https://pytorch.org/docs/stable/notes/randomness.html#avoiding-nondeterministic-algorithms
146
+ CUBLAS_WORKSPACE_CONFIG: :16:8
147
+ run: |
148
+ python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
149
+ -s -v -k "not Flax and not Onnx" \
150
+ --make-reports=tests_torch_${{ matrix.module }}_cuda \
151
+ --report-log=tests_torch_${{ matrix.module }}_cuda.log \
152
+ tests/${{ matrix.module }}
153
+
154
+ - name: Run nightly example tests with Torch
155
+ if: ${{ matrix.module == 'examples' }}
156
+ env:
157
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
158
+ # https://pytorch.org/docs/stable/notes/randomness.html#avoiding-nondeterministic-algorithms
159
+ CUBLAS_WORKSPACE_CONFIG: :16:8
160
+ run: |
161
+ python -m uv pip install peft@git+https://github.com/huggingface/peft.git
162
+ python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
163
+ -s -v --make-reports=examples_torch_cuda \
164
+ --report-log=examples_torch_cuda.log \
165
+ examples/
166
+
167
+ - name: Failure short reports
168
+ if: ${{ failure() }}
169
+ run: |
170
+ cat reports/tests_torch_${{ matrix.module }}_cuda_stats.txt
171
+ cat reports/tests_torch_${{ matrix.module }}_cuda_failures_short.txt
172
+
173
+ - name: Test suite reports artifacts
174
+ if: ${{ always() }}
175
+ uses: actions/upload-artifact@v2
176
+ with:
177
+ name: torch_${{ matrix.module }}_cuda_test_reports
178
+ path: reports
179
+
180
+ - name: Generate Report and Notify Channel
181
+ if: always()
182
+ run: |
183
+ pip install slack_sdk tabulate
184
+ python scripts/log_reports.py >> $GITHUB_STEP_SUMMARY
185
+
186
+ run_lora_nightly_tests:
187
+ name: Nightly LoRA Tests with PEFT and TORCH
188
+ runs-on: [single-gpu, nvidia-gpu, t4, ci]
189
+ container:
190
+ image: diffusers/diffusers-pytorch-cuda
191
+ options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/ --gpus 0
192
+ defaults:
193
+ run:
194
+ shell: bash
195
+ steps:
196
+ - name: Checkout diffusers
197
+ uses: actions/checkout@v3
198
+ with:
199
+ fetch-depth: 2
200
+
201
+ - name: Install dependencies
202
+ run: |
203
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
204
+ python -m uv pip install -e [quality,test]
205
+ python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
206
+ python -m uv pip install peft@git+https://github.com/huggingface/peft.git
207
+ python -m uv pip install pytest-reportlog
208
+
209
+ - name: Environment
210
+ run: python utils/print_env.py
211
+
212
+ - name: Run nightly LoRA tests with PEFT and Torch
213
+ env:
214
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
215
+ # https://pytorch.org/docs/stable/notes/randomness.html#avoiding-nondeterministic-algorithms
216
+ CUBLAS_WORKSPACE_CONFIG: :16:8
217
+ run: |
218
+ python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
219
+ -s -v -k "not Flax and not Onnx" \
220
+ --make-reports=tests_torch_lora_cuda \
221
+ --report-log=tests_torch_lora_cuda.log \
222
+ tests/lora
223
+
224
+ - name: Failure short reports
225
+ if: ${{ failure() }}
226
+ run: |
227
+ cat reports/tests_torch_lora_cuda_stats.txt
228
+ cat reports/tests_torch_lora_cuda_failures_short.txt
229
+
230
+ - name: Test suite reports artifacts
231
+ if: ${{ always() }}
232
+ uses: actions/upload-artifact@v2
233
+ with:
234
+ name: torch_lora_cuda_test_reports
235
+ path: reports
236
+
237
+ - name: Generate Report and Notify Channel
238
+ if: always()
239
+ run: |
240
+ pip install slack_sdk tabulate
241
+ python scripts/log_reports.py >> $GITHUB_STEP_SUMMARY
242
+
243
+ run_flax_tpu_tests:
244
+ name: Nightly Flax TPU Tests
245
+ runs-on: docker-tpu
246
+ if: github.event_name == 'schedule'
247
+
248
+ container:
249
+ image: diffusers/diffusers-flax-tpu
250
+ options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/ --privileged
251
+ defaults:
252
+ run:
253
+ shell: bash
254
+ steps:
255
+ - name: Checkout diffusers
256
+ uses: actions/checkout@v3
257
+ with:
258
+ fetch-depth: 2
259
+
260
+ - name: Install dependencies
261
+ run: |
262
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
263
+ python -m uv pip install -e [quality,test]
264
+ python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
265
+ python -m uv pip install pytest-reportlog
266
+
267
+ - name: Environment
268
+ run: python utils/print_env.py
269
+
270
+ - name: Run nightly Flax TPU tests
271
+ env:
272
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
273
+ run: |
274
+ python -m pytest -n 0 \
275
+ -s -v -k "Flax" \
276
+ --make-reports=tests_flax_tpu \
277
+ --report-log=tests_flax_tpu.log \
278
+ tests/
279
+
280
+ - name: Failure short reports
281
+ if: ${{ failure() }}
282
+ run: |
283
+ cat reports/tests_flax_tpu_stats.txt
284
+ cat reports/tests_flax_tpu_failures_short.txt
285
+
286
+ - name: Test suite reports artifacts
287
+ if: ${{ always() }}
288
+ uses: actions/upload-artifact@v2
289
+ with:
290
+ name: flax_tpu_test_reports
291
+ path: reports
292
+
293
+ - name: Generate Report and Notify Channel
294
+ if: always()
295
+ run: |
296
+ pip install slack_sdk tabulate
297
+ python scripts/log_reports.py >> $GITHUB_STEP_SUMMARY
298
+
299
+ run_nightly_onnx_tests:
300
+ name: Nightly ONNXRuntime CUDA tests on Ubuntu
301
+ runs-on: [single-gpu, nvidia-gpu, t4, ci]
302
+ container:
303
+ image: diffusers/diffusers-onnxruntime-cuda
304
+ options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
305
+
306
+ steps:
307
+ - name: Checkout diffusers
308
+ uses: actions/checkout@v3
309
+ with:
310
+ fetch-depth: 2
311
+
312
+ - name: NVIDIA-SMI
313
+ run: nvidia-smi
314
+
315
+ - name: Install dependencies
316
+ run: |
317
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
318
+ python -m uv pip install -e [quality,test]
319
+ python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
320
+ python -m uv pip install pytest-reportlog
321
+
322
+ - name: Environment
323
+ run: python utils/print_env.py
324
+
325
+ - name: Run nightly ONNXRuntime CUDA tests
326
+ env:
327
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
328
+ run: |
329
+ python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
330
+ -s -v -k "Onnx" \
331
+ --make-reports=tests_onnx_cuda \
332
+ --report-log=tests_onnx_cuda.log \
333
+ tests/
334
+
335
+ - name: Failure short reports
336
+ if: ${{ failure() }}
337
+ run: |
338
+ cat reports/tests_onnx_cuda_stats.txt
339
+ cat reports/tests_onnx_cuda_failures_short.txt
340
+
341
+ - name: Test suite reports artifacts
342
+ if: ${{ always() }}
343
+ uses: actions/upload-artifact@v2
344
+ with:
345
+ name: ${{ matrix.config.report }}_test_reports
346
+ path: reports
347
+
348
+ - name: Generate Report and Notify Channel
349
+ if: always()
350
+ run: |
351
+ pip install slack_sdk tabulate
352
+ python scripts/log_reports.py >> $GITHUB_STEP_SUMMARY
353
+
354
+ run_nightly_tests_apple_m1:
355
+ name: Nightly PyTorch MPS tests on MacOS
356
+ runs-on: [ self-hosted, apple-m1 ]
357
+ if: github.event_name == 'schedule'
358
+
359
+ steps:
360
+ - name: Checkout diffusers
361
+ uses: actions/checkout@v3
362
+ with:
363
+ fetch-depth: 2
364
+
365
+ - name: Clean checkout
366
+ shell: arch -arch arm64 bash {0}
367
+ run: |
368
+ git clean -fxd
369
+
370
+ - name: Setup miniconda
371
+ uses: ./.github/actions/setup-miniconda
372
+ with:
373
+ python-version: 3.9
374
+
375
+ - name: Install dependencies
376
+ shell: arch -arch arm64 bash {0}
377
+ run: |
378
+ ${CONDA_RUN} python -m pip install --upgrade pip uv
379
+ ${CONDA_RUN} python -m uv pip install -e [quality,test]
380
+ ${CONDA_RUN} python -m uv pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cpu
381
+ ${CONDA_RUN} python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate
382
+ ${CONDA_RUN} python -m uv pip install pytest-reportlog
383
+
384
+ - name: Environment
385
+ shell: arch -arch arm64 bash {0}
386
+ run: |
387
+ ${CONDA_RUN} python utils/print_env.py
388
+
389
+ - name: Run nightly PyTorch tests on M1 (MPS)
390
+ shell: arch -arch arm64 bash {0}
391
+ env:
392
+ HF_HOME: /System/Volumes/Data/mnt/cache
393
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
394
+ run: |
395
+ ${CONDA_RUN} python -m pytest -n 1 -s -v --make-reports=tests_torch_mps \
396
+ --report-log=tests_torch_mps.log \
397
+ tests/
398
+
399
+ - name: Failure short reports
400
+ if: ${{ failure() }}
401
+ run: cat reports/tests_torch_mps_failures_short.txt
402
+
403
+ - name: Test suite reports artifacts
404
+ if: ${{ always() }}
405
+ uses: actions/upload-artifact@v2
406
+ with:
407
+ name: torch_mps_test_reports
408
+ path: reports
409
+
410
+ - name: Generate Report and Notify Channel
411
+ if: always()
412
+ run: |
413
+ pip install slack_sdk tabulate
414
+ python scripts/log_reports.py >> $GITHUB_STEP_SUMMARY
UltraEdit/diffusers/.github/workflows/notify_slack_about_release.yml ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Notify Slack about a release
2
+
3
+ on:
4
+ workflow_dispatch:
5
+ release:
6
+ types: [published]
7
+
8
+ jobs:
9
+ build:
10
+ runs-on: ubuntu-latest
11
+
12
+ steps:
13
+ - uses: actions/checkout@v3
14
+
15
+ - name: Setup Python
16
+ uses: actions/setup-python@v4
17
+ with:
18
+ python-version: '3.8'
19
+
20
+ - name: Notify Slack about the release
21
+ env:
22
+ SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK_URL }}
23
+ run: pip install requests && python utils/notify_slack_about_release.py
UltraEdit/diffusers/.github/workflows/pr_dependency_test.yml ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Run dependency tests
2
+
3
+ on:
4
+ pull_request:
5
+ branches:
6
+ - main
7
+ paths:
8
+ - "src/diffusers/**.py"
9
+ push:
10
+ branches:
11
+ - main
12
+
13
+ concurrency:
14
+ group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
15
+ cancel-in-progress: true
16
+
17
+ jobs:
18
+ check_dependencies:
19
+ runs-on: ubuntu-latest
20
+ steps:
21
+ - uses: actions/checkout@v3
22
+ - name: Set up Python
23
+ uses: actions/setup-python@v4
24
+ with:
25
+ python-version: "3.8"
26
+ - name: Install dependencies
27
+ run: |
28
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
29
+ python -m pip install --upgrade pip uv
30
+ python -m uv pip install -e .
31
+ python -m uv pip install pytest
32
+ - name: Check for soft dependencies
33
+ run: |
34
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
35
+ pytest tests/others/test_dependencies.py
36
+
UltraEdit/diffusers/.github/workflows/pr_flax_dependency_test.yml ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Run Flax dependency tests
2
+
3
+ on:
4
+ pull_request:
5
+ branches:
6
+ - main
7
+ paths:
8
+ - "src/diffusers/**.py"
9
+ push:
10
+ branches:
11
+ - main
12
+
13
+ concurrency:
14
+ group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
15
+ cancel-in-progress: true
16
+
17
+ jobs:
18
+ check_flax_dependencies:
19
+ runs-on: ubuntu-latest
20
+ steps:
21
+ - uses: actions/checkout@v3
22
+ - name: Set up Python
23
+ uses: actions/setup-python@v4
24
+ with:
25
+ python-version: "3.8"
26
+ - name: Install dependencies
27
+ run: |
28
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
29
+ python -m pip install --upgrade pip uv
30
+ python -m uv pip install -e .
31
+ python -m uv pip install "jax[cpu]>=0.2.16,!=0.3.2"
32
+ python -m uv pip install "flax>=0.4.1"
33
+ python -m uv pip install "jaxlib>=0.1.65"
34
+ python -m uv pip install pytest
35
+ - name: Check for soft dependencies
36
+ run: |
37
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
38
+ pytest tests/others/test_dependencies.py
UltraEdit/diffusers/.github/workflows/pr_test_fetcher.yml ADDED
@@ -0,0 +1,174 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Fast tests for PRs - Test Fetcher
2
+
3
+ on: workflow_dispatch
4
+
5
+ env:
6
+ DIFFUSERS_IS_CI: yes
7
+ OMP_NUM_THREADS: 4
8
+ MKL_NUM_THREADS: 4
9
+ PYTEST_TIMEOUT: 60
10
+
11
+ concurrency:
12
+ group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
13
+ cancel-in-progress: true
14
+
15
+ jobs:
16
+ setup_pr_tests:
17
+ name: Setup PR Tests
18
+ runs-on: [ self-hosted, intel-cpu, 8-cpu, ci ]
19
+ container:
20
+ image: diffusers/diffusers-pytorch-cpu
21
+ options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
22
+ defaults:
23
+ run:
24
+ shell: bash
25
+ outputs:
26
+ matrix: ${{ steps.set_matrix.outputs.matrix }}
27
+ test_map: ${{ steps.set_matrix.outputs.test_map }}
28
+ steps:
29
+ - name: Checkout diffusers
30
+ uses: actions/checkout@v3
31
+ with:
32
+ fetch-depth: 0
33
+ - name: Install dependencies
34
+ run: |
35
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
36
+ python -m uv pip install -e [quality,test]
37
+ - name: Environment
38
+ run: |
39
+ python utils/print_env.py
40
+ echo $(git --version)
41
+ - name: Fetch Tests
42
+ run: |
43
+ python utils/tests_fetcher.py | tee test_preparation.txt
44
+ - name: Report fetched tests
45
+ uses: actions/upload-artifact@v3
46
+ with:
47
+ name: test_fetched
48
+ path: test_preparation.txt
49
+ - id: set_matrix
50
+ name: Create Test Matrix
51
+ # The `keys` is used as GitHub actions matrix for jobs, i.e. `models`, `pipelines`, etc.
52
+ # The `test_map` is used to get the actual identified test files under each key.
53
+ # If no test to run (so no `test_map.json` file), create a dummy map (empty matrix will fail)
54
+ run: |
55
+ if [ -f test_map.json ]; then
56
+ keys=$(python3 -c 'import json; fp = open("test_map.json"); test_map = json.load(fp); fp.close(); d = list(test_map.keys()); print(json.dumps(d))')
57
+ test_map=$(python3 -c 'import json; fp = open("test_map.json"); test_map = json.load(fp); fp.close(); print(json.dumps(test_map))')
58
+ else
59
+ keys=$(python3 -c 'keys = ["dummy"]; print(keys)')
60
+ test_map=$(python3 -c 'test_map = {"dummy": []}; print(test_map)')
61
+ fi
62
+ echo $keys
63
+ echo $test_map
64
+ echo "matrix=$keys" >> $GITHUB_OUTPUT
65
+ echo "test_map=$test_map" >> $GITHUB_OUTPUT
66
+
67
+ run_pr_tests:
68
+ name: Run PR Tests
69
+ needs: setup_pr_tests
70
+ if: contains(fromJson(needs.setup_pr_tests.outputs.matrix), 'dummy') != true
71
+ strategy:
72
+ fail-fast: false
73
+ max-parallel: 2
74
+ matrix:
75
+ modules: ${{ fromJson(needs.setup_pr_tests.outputs.matrix) }}
76
+ runs-on: [ self-hosted, intel-cpu, 8-cpu, ci ]
77
+ container:
78
+ image: diffusers/diffusers-pytorch-cpu
79
+ options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
80
+ defaults:
81
+ run:
82
+ shell: bash
83
+ steps:
84
+ - name: Checkout diffusers
85
+ uses: actions/checkout@v3
86
+ with:
87
+ fetch-depth: 2
88
+
89
+ - name: Install dependencies
90
+ run: |
91
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
92
+ python -m pip install -e [quality,test]
93
+ python -m pip install accelerate
94
+
95
+ - name: Environment
96
+ run: |
97
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
98
+ python utils/print_env.py
99
+
100
+ - name: Run all selected tests on CPU
101
+ run: |
102
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
103
+ python -m pytest -n 2 --dist=loadfile -v --make-reports=${{ matrix.modules }}_tests_cpu ${{ fromJson(needs.setup_pr_tests.outputs.test_map)[matrix.modules] }}
104
+
105
+ - name: Failure short reports
106
+ if: ${{ failure() }}
107
+ continue-on-error: true
108
+ run: |
109
+ cat reports/${{ matrix.modules }}_tests_cpu_stats.txt
110
+ cat reports/${{ matrix.modules }}_tests_cpu_failures_short.txt
111
+
112
+ - name: Test suite reports artifacts
113
+ if: ${{ always() }}
114
+ uses: actions/upload-artifact@v3
115
+ with:
116
+ name: ${{ matrix.modules }}_test_reports
117
+ path: reports
118
+
119
+ run_staging_tests:
120
+ strategy:
121
+ fail-fast: false
122
+ matrix:
123
+ config:
124
+ - name: Hub tests for models, schedulers, and pipelines
125
+ framework: hub_tests_pytorch
126
+ runner: [ self-hosted, intel-cpu, 8-cpu, ci ]
127
+ image: diffusers/diffusers-pytorch-cpu
128
+ report: torch_hub
129
+
130
+ name: ${{ matrix.config.name }}
131
+ runs-on: ${{ matrix.config.runner }}
132
+ container:
133
+ image: ${{ matrix.config.image }}
134
+ options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
135
+
136
+ defaults:
137
+ run:
138
+ shell: bash
139
+
140
+ steps:
141
+ - name: Checkout diffusers
142
+ uses: actions/checkout@v3
143
+ with:
144
+ fetch-depth: 2
145
+
146
+ - name: Install dependencies
147
+ run: |
148
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
149
+ python -m pip install -e [quality,test]
150
+
151
+ - name: Environment
152
+ run: |
153
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
154
+ python utils/print_env.py
155
+
156
+ - name: Run Hub tests for models, schedulers, and pipelines on a staging env
157
+ if: ${{ matrix.config.framework == 'hub_tests_pytorch' }}
158
+ run: |
159
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
160
+ HUGGINGFACE_CO_STAGING=true python -m pytest \
161
+ -m "is_staging_test" \
162
+ --make-reports=tests_${{ matrix.config.report }} \
163
+ tests
164
+
165
+ - name: Failure short reports
166
+ if: ${{ failure() }}
167
+ run: cat reports/tests_${{ matrix.config.report }}_failures_short.txt
168
+
169
+ - name: Test suite reports artifacts
170
+ if: ${{ always() }}
171
+ uses: actions/upload-artifact@v2
172
+ with:
173
+ name: pr_${{ matrix.config.report }}_test_reports
174
+ path: reports
UltraEdit/diffusers/.github/workflows/pr_test_peft_backend.yml ADDED
@@ -0,0 +1,131 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Fast tests for PRs - PEFT backend
2
+
3
+ on:
4
+ pull_request:
5
+ branches:
6
+ - main
7
+ paths:
8
+ - "src/diffusers/**.py"
9
+ - "tests/**.py"
10
+
11
+ concurrency:
12
+ group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
13
+ cancel-in-progress: true
14
+
15
+ env:
16
+ DIFFUSERS_IS_CI: yes
17
+ OMP_NUM_THREADS: 4
18
+ MKL_NUM_THREADS: 4
19
+ PYTEST_TIMEOUT: 60
20
+
21
+ jobs:
22
+ check_code_quality:
23
+ runs-on: ubuntu-latest
24
+ steps:
25
+ - uses: actions/checkout@v3
26
+ - name: Set up Python
27
+ uses: actions/setup-python@v4
28
+ with:
29
+ python-version: "3.8"
30
+ - name: Install dependencies
31
+ run: |
32
+ python -m pip install --upgrade pip
33
+ pip install .[quality]
34
+ - name: Check quality
35
+ run: make quality
36
+ - name: Check if failure
37
+ if: ${{ failure() }}
38
+ run: |
39
+ echo "Quality check failed. Please ensure the right dependency versions are installed with 'pip install -e .[quality]' and run 'make style && make quality'" >> $GITHUB_STEP_SUMMARY
40
+
41
+ check_repository_consistency:
42
+ needs: check_code_quality
43
+ runs-on: ubuntu-latest
44
+ steps:
45
+ - uses: actions/checkout@v3
46
+ - name: Set up Python
47
+ uses: actions/setup-python@v4
48
+ with:
49
+ python-version: "3.8"
50
+ - name: Install dependencies
51
+ run: |
52
+ python -m pip install --upgrade pip
53
+ pip install .[quality]
54
+ - name: Check repo consistency
55
+ run: |
56
+ python utils/check_copies.py
57
+ python utils/check_dummies.py
58
+ make deps_table_check_updated
59
+ - name: Check if failure
60
+ if: ${{ failure() }}
61
+ run: |
62
+ echo "Repo consistency check failed. Please ensure the right dependency versions are installed with 'pip install -e .[quality]' and run 'make fix-copies'" >> $GITHUB_STEP_SUMMARY
63
+
64
+ run_fast_tests:
65
+ needs: [check_code_quality, check_repository_consistency]
66
+ strategy:
67
+ fail-fast: false
68
+ matrix:
69
+ lib-versions: ["main", "latest"]
70
+
71
+
72
+ name: LoRA - ${{ matrix.lib-versions }}
73
+
74
+ runs-on: [ self-hosted, intel-cpu, 8-cpu, ci ]
75
+
76
+ container:
77
+ image: diffusers/diffusers-pytorch-cpu
78
+ options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
79
+
80
+ defaults:
81
+ run:
82
+ shell: bash
83
+
84
+ steps:
85
+ - name: Checkout diffusers
86
+ uses: actions/checkout@v3
87
+ with:
88
+ fetch-depth: 2
89
+
90
+ - name: Install dependencies
91
+ run: |
92
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
93
+ python -m uv pip install -e [quality,test]
94
+ if [ "${{ matrix.lib-versions }}" == "main" ]; then
95
+ python -m pip install -U peft@git+https://github.com/huggingface/peft.git
96
+ python -m uv pip install -U transformers@git+https://github.com/huggingface/transformers.git
97
+ python -m uv pip install -U accelerate@git+https://github.com/huggingface/accelerate.git
98
+ else
99
+ python -m uv pip install -U peft transformers accelerate
100
+ fi
101
+
102
+ - name: Environment
103
+ run: |
104
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
105
+ python utils/print_env.py
106
+
107
+ - name: Run fast PyTorch LoRA CPU tests with PEFT backend
108
+ run: |
109
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
110
+ python -m pytest -n 4 --max-worker-restart=0 --dist=loadfile \
111
+ -s -v \
112
+ --make-reports=tests_${{ matrix.config.report }} \
113
+ tests/lora/
114
+ python -m pytest -n 4 --max-worker-restart=0 --dist=loadfile \
115
+ -s -v \
116
+ --make-reports=tests_models_lora_${{ matrix.config.report }} \
117
+ tests/models/ -k "lora"
118
+
119
+
120
+ - name: Failure short reports
121
+ if: ${{ failure() }}
122
+ run: |
123
+ cat reports/tests_${{ matrix.config.report }}_failures_short.txt
124
+ cat reports/tests_models_lora_${{ matrix.config.report }}_failures_short.txt
125
+
126
+ - name: Test suite reports artifacts
127
+ if: ${{ always() }}
128
+ uses: actions/upload-artifact@v2
129
+ with:
130
+ name: pr_${{ matrix.config.report }}_test_reports
131
+ path: reports
UltraEdit/diffusers/.github/workflows/pr_tests.yml ADDED
@@ -0,0 +1,233 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Fast tests for PRs
2
+
3
+ on:
4
+ pull_request:
5
+ branches:
6
+ - main
7
+ paths:
8
+ - "src/diffusers/**.py"
9
+ - "benchmarks/**.py"
10
+ - "examples/**.py"
11
+ - "scripts/**.py"
12
+ - "tests/**.py"
13
+ - ".github/**.yml"
14
+ - "utils/**.py"
15
+ push:
16
+ branches:
17
+ - ci-*
18
+
19
+ concurrency:
20
+ group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
21
+ cancel-in-progress: true
22
+
23
+ env:
24
+ DIFFUSERS_IS_CI: yes
25
+ OMP_NUM_THREADS: 4
26
+ MKL_NUM_THREADS: 4
27
+ PYTEST_TIMEOUT: 60
28
+
29
+ jobs:
30
+ check_code_quality:
31
+ runs-on: ubuntu-latest
32
+ steps:
33
+ - uses: actions/checkout@v3
34
+ - name: Set up Python
35
+ uses: actions/setup-python@v4
36
+ with:
37
+ python-version: "3.8"
38
+ - name: Install dependencies
39
+ run: |
40
+ python -m pip install --upgrade pip
41
+ pip install .[quality]
42
+ - name: Check quality
43
+ run: make quality
44
+ - name: Check if failure
45
+ if: ${{ failure() }}
46
+ run: |
47
+ echo "Quality check failed. Please ensure the right dependency versions are installed with 'pip install -e .[quality]' and run 'make style && make quality'" >> $GITHUB_STEP_SUMMARY
48
+
49
+ check_repository_consistency:
50
+ needs: check_code_quality
51
+ runs-on: ubuntu-latest
52
+ steps:
53
+ - uses: actions/checkout@v3
54
+ - name: Set up Python
55
+ uses: actions/setup-python@v4
56
+ with:
57
+ python-version: "3.8"
58
+ - name: Install dependencies
59
+ run: |
60
+ python -m pip install --upgrade pip
61
+ pip install .[quality]
62
+ - name: Check repo consistency
63
+ run: |
64
+ python utils/check_copies.py
65
+ python utils/check_dummies.py
66
+ make deps_table_check_updated
67
+ - name: Check if failure
68
+ if: ${{ failure() }}
69
+ run: |
70
+ echo "Repo consistency check failed. Please ensure the right dependency versions are installed with 'pip install -e .[quality]' and run 'make fix-copies'" >> $GITHUB_STEP_SUMMARY
71
+
72
+ run_fast_tests:
73
+ needs: [check_code_quality, check_repository_consistency]
74
+ strategy:
75
+ fail-fast: false
76
+ matrix:
77
+ config:
78
+ - name: Fast PyTorch Pipeline CPU tests
79
+ framework: pytorch_pipelines
80
+ runner: [ self-hosted, intel-cpu, 32-cpu, 256-ram, ci ]
81
+ image: diffusers/diffusers-pytorch-cpu
82
+ report: torch_cpu_pipelines
83
+ - name: Fast PyTorch Models & Schedulers CPU tests
84
+ framework: pytorch_models
85
+ runner: [ self-hosted, intel-cpu, 8-cpu, ci ]
86
+ image: diffusers/diffusers-pytorch-cpu
87
+ report: torch_cpu_models_schedulers
88
+ - name: Fast Flax CPU tests
89
+ framework: flax
90
+ runner: [ self-hosted, intel-cpu, 8-cpu, ci ]
91
+ image: diffusers/diffusers-flax-cpu
92
+ report: flax_cpu
93
+ - name: PyTorch Example CPU tests
94
+ framework: pytorch_examples
95
+ runner: [ self-hosted, intel-cpu, 8-cpu, ci ]
96
+ image: diffusers/diffusers-pytorch-cpu
97
+ report: torch_example_cpu
98
+
99
+ name: ${{ matrix.config.name }}
100
+
101
+ runs-on: ${{ matrix.config.runner }}
102
+
103
+ container:
104
+ image: ${{ matrix.config.image }}
105
+ options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
106
+
107
+ defaults:
108
+ run:
109
+ shell: bash
110
+
111
+ steps:
112
+ - name: Checkout diffusers
113
+ uses: actions/checkout@v3
114
+ with:
115
+ fetch-depth: 2
116
+
117
+ - name: Install dependencies
118
+ run: |
119
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
120
+ python -m uv pip install -e [quality,test]
121
+ python -m uv pip install accelerate
122
+
123
+ - name: Environment
124
+ run: |
125
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
126
+ python utils/print_env.py
127
+
128
+ - name: Run fast PyTorch Pipeline CPU tests
129
+ if: ${{ matrix.config.framework == 'pytorch_pipelines' }}
130
+ run: |
131
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
132
+ python -m pytest -n 8 --max-worker-restart=0 --dist=loadfile \
133
+ -s -v -k "not Flax and not Onnx" \
134
+ --make-reports=tests_${{ matrix.config.report }} \
135
+ tests/pipelines
136
+
137
+ - name: Run fast PyTorch Model Scheduler CPU tests
138
+ if: ${{ matrix.config.framework == 'pytorch_models' }}
139
+ run: |
140
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
141
+ python -m pytest -n 4 --max-worker-restart=0 --dist=loadfile \
142
+ -s -v -k "not Flax and not Onnx and not Dependency" \
143
+ --make-reports=tests_${{ matrix.config.report }} \
144
+ tests/models tests/schedulers tests/others
145
+
146
+ - name: Run fast Flax TPU tests
147
+ if: ${{ matrix.config.framework == 'flax' }}
148
+ run: |
149
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
150
+ python -m pytest -n 4 --max-worker-restart=0 --dist=loadfile \
151
+ -s -v -k "Flax" \
152
+ --make-reports=tests_${{ matrix.config.report }} \
153
+ tests
154
+
155
+ - name: Run example PyTorch CPU tests
156
+ if: ${{ matrix.config.framework == 'pytorch_examples' }}
157
+ run: |
158
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
159
+ python -m uv pip install peft timm
160
+ python -m pytest -n 4 --max-worker-restart=0 --dist=loadfile \
161
+ --make-reports=tests_${{ matrix.config.report }} \
162
+ examples
163
+
164
+ - name: Failure short reports
165
+ if: ${{ failure() }}
166
+ run: cat reports/tests_${{ matrix.config.report }}_failures_short.txt
167
+
168
+ - name: Test suite reports artifacts
169
+ if: ${{ always() }}
170
+ uses: actions/upload-artifact@v2
171
+ with:
172
+ name: pr_${{ matrix.config.report }}_test_reports
173
+ path: reports
174
+
175
+ run_staging_tests:
176
+ needs: [check_code_quality, check_repository_consistency]
177
+ strategy:
178
+ fail-fast: false
179
+ matrix:
180
+ config:
181
+ - name: Hub tests for models, schedulers, and pipelines
182
+ framework: hub_tests_pytorch
183
+ runner: [ self-hosted, intel-cpu, 8-cpu, ci ]
184
+ image: diffusers/diffusers-pytorch-cpu
185
+ report: torch_hub
186
+
187
+ name: ${{ matrix.config.name }}
188
+
189
+ runs-on: ${{ matrix.config.runner }}
190
+
191
+ container:
192
+ image: ${{ matrix.config.image }}
193
+ options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
194
+
195
+ defaults:
196
+ run:
197
+ shell: bash
198
+
199
+ steps:
200
+ - name: Checkout diffusers
201
+ uses: actions/checkout@v3
202
+ with:
203
+ fetch-depth: 2
204
+
205
+ - name: Install dependencies
206
+ run: |
207
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
208
+ python -m uv pip install -e [quality,test]
209
+
210
+ - name: Environment
211
+ run: |
212
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
213
+ python utils/print_env.py
214
+
215
+ - name: Run Hub tests for models, schedulers, and pipelines on a staging env
216
+ if: ${{ matrix.config.framework == 'hub_tests_pytorch' }}
217
+ run: |
218
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
219
+ HUGGINGFACE_CO_STAGING=true python -m pytest \
220
+ -m "is_staging_test" \
221
+ --make-reports=tests_${{ matrix.config.report }} \
222
+ tests
223
+
224
+ - name: Failure short reports
225
+ if: ${{ failure() }}
226
+ run: cat reports/tests_${{ matrix.config.report }}_failures_short.txt
227
+
228
+ - name: Test suite reports artifacts
229
+ if: ${{ always() }}
230
+ uses: actions/upload-artifact@v2
231
+ with:
232
+ name: pr_${{ matrix.config.report }}_test_reports
233
+ path: reports
UltraEdit/diffusers/.github/workflows/pr_torch_dependency_test.yml ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Run Torch dependency tests
2
+
3
+ on:
4
+ pull_request:
5
+ branches:
6
+ - main
7
+ paths:
8
+ - "src/diffusers/**.py"
9
+ push:
10
+ branches:
11
+ - main
12
+
13
+ concurrency:
14
+ group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
15
+ cancel-in-progress: true
16
+
17
+ jobs:
18
+ check_torch_dependencies:
19
+ runs-on: ubuntu-latest
20
+ steps:
21
+ - uses: actions/checkout@v3
22
+ - name: Set up Python
23
+ uses: actions/setup-python@v4
24
+ with:
25
+ python-version: "3.8"
26
+ - name: Install dependencies
27
+ run: |
28
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
29
+ python -m pip install --upgrade pip uv
30
+ python -m uv pip install -e .
31
+ python -m uv pip install torch torchvision torchaudio
32
+ python -m uv pip install pytest
33
+ - name: Check for soft dependencies
34
+ run: |
35
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
36
+ pytest tests/others/test_dependencies.py
UltraEdit/diffusers/.github/workflows/push_tests.yml ADDED
@@ -0,0 +1,435 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Slow Tests on main
2
+
3
+ on:
4
+ push:
5
+ branches:
6
+ - main
7
+ paths:
8
+ - "src/diffusers/**.py"
9
+ - "examples/**.py"
10
+ - "tests/**.py"
11
+
12
+ env:
13
+ DIFFUSERS_IS_CI: yes
14
+ HF_HOME: /mnt/cache
15
+ OMP_NUM_THREADS: 8
16
+ MKL_NUM_THREADS: 8
17
+ PYTEST_TIMEOUT: 600
18
+ RUN_SLOW: yes
19
+ PIPELINE_USAGE_CUTOFF: 50000
20
+
21
+ jobs:
22
+ setup_torch_cuda_pipeline_matrix:
23
+ name: Setup Torch Pipelines CUDA Slow Tests Matrix
24
+ runs-on: [ self-hosted, intel-cpu, 8-cpu, ci ]
25
+ container:
26
+ image: diffusers/diffusers-pytorch-cpu
27
+ outputs:
28
+ pipeline_test_matrix: ${{ steps.fetch_pipeline_matrix.outputs.pipeline_test_matrix }}
29
+ steps:
30
+ - name: Checkout diffusers
31
+ uses: actions/checkout@v3
32
+ with:
33
+ fetch-depth: 2
34
+ - name: Install dependencies
35
+ run: |
36
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
37
+ python -m uv pip install -e [quality,test]
38
+ - name: Environment
39
+ run: |
40
+ python utils/print_env.py
41
+ - name: Fetch Pipeline Matrix
42
+ id: fetch_pipeline_matrix
43
+ run: |
44
+ matrix=$(python utils/fetch_torch_cuda_pipeline_test_matrix.py)
45
+ echo $matrix
46
+ echo "pipeline_test_matrix=$matrix" >> $GITHUB_OUTPUT
47
+ - name: Pipeline Tests Artifacts
48
+ if: ${{ always() }}
49
+ uses: actions/upload-artifact@v2
50
+ with:
51
+ name: test-pipelines.json
52
+ path: reports
53
+
54
+ torch_pipelines_cuda_tests:
55
+ name: Torch Pipelines CUDA Slow Tests
56
+ needs: setup_torch_cuda_pipeline_matrix
57
+ strategy:
58
+ fail-fast: false
59
+ max-parallel: 8
60
+ matrix:
61
+ module: ${{ fromJson(needs.setup_torch_cuda_pipeline_matrix.outputs.pipeline_test_matrix) }}
62
+ runs-on: [single-gpu, nvidia-gpu, t4, ci]
63
+ container:
64
+ image: diffusers/diffusers-pytorch-cuda
65
+ options: --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface/diffusers:/mnt/cache/ --gpus 0
66
+ steps:
67
+ - name: Checkout diffusers
68
+ uses: actions/checkout@v3
69
+ with:
70
+ fetch-depth: 2
71
+ - name: NVIDIA-SMI
72
+ run: |
73
+ nvidia-smi
74
+ - name: Install dependencies
75
+ run: |
76
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
77
+ python -m uv pip install -e [quality,test]
78
+ python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
79
+ - name: Environment
80
+ run: |
81
+ python utils/print_env.py
82
+ - name: Slow PyTorch CUDA checkpoint tests on Ubuntu
83
+ env:
84
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
85
+ # https://pytorch.org/docs/stable/notes/randomness.html#avoiding-nondeterministic-algorithms
86
+ CUBLAS_WORKSPACE_CONFIG: :16:8
87
+ run: |
88
+ python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
89
+ -s -v -k "not Flax and not Onnx" \
90
+ --make-reports=tests_pipeline_${{ matrix.module }}_cuda \
91
+ tests/pipelines/${{ matrix.module }}
92
+ - name: Failure short reports
93
+ if: ${{ failure() }}
94
+ run: |
95
+ cat reports/tests_pipeline_${{ matrix.module }}_cuda_stats.txt
96
+ cat reports/tests_pipeline_${{ matrix.module }}_cuda_failures_short.txt
97
+ - name: Test suite reports artifacts
98
+ if: ${{ always() }}
99
+ uses: actions/upload-artifact@v2
100
+ with:
101
+ name: pipeline_${{ matrix.module }}_test_reports
102
+ path: reports
103
+
104
+ torch_cuda_tests:
105
+ name: Torch CUDA Tests
106
+ runs-on: [single-gpu, nvidia-gpu, t4, ci]
107
+ container:
108
+ image: diffusers/diffusers-pytorch-cuda
109
+ options: --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface/diffusers:/mnt/cache/ --gpus 0
110
+ defaults:
111
+ run:
112
+ shell: bash
113
+ strategy:
114
+ matrix:
115
+ module: [models, schedulers, lora, others, single_file]
116
+ steps:
117
+ - name: Checkout diffusers
118
+ uses: actions/checkout@v3
119
+ with:
120
+ fetch-depth: 2
121
+
122
+ - name: Install dependencies
123
+ run: |
124
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
125
+ python -m uv pip install -e [quality,test]
126
+ python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
127
+
128
+ - name: Environment
129
+ run: |
130
+ python utils/print_env.py
131
+
132
+ - name: Run slow PyTorch CUDA tests
133
+ env:
134
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
135
+ # https://pytorch.org/docs/stable/notes/randomness.html#avoiding-nondeterministic-algorithms
136
+ CUBLAS_WORKSPACE_CONFIG: :16:8
137
+ run: |
138
+ python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
139
+ -s -v -k "not Flax and not Onnx" \
140
+ --make-reports=tests_torch_cuda \
141
+ tests/${{ matrix.module }}
142
+
143
+ - name: Failure short reports
144
+ if: ${{ failure() }}
145
+ run: |
146
+ cat reports/tests_torch_cuda_stats.txt
147
+ cat reports/tests_torch_cuda_failures_short.txt
148
+
149
+ - name: Test suite reports artifacts
150
+ if: ${{ always() }}
151
+ uses: actions/upload-artifact@v2
152
+ with:
153
+ name: torch_cuda_test_reports
154
+ path: reports
155
+
156
+ peft_cuda_tests:
157
+ name: PEFT CUDA Tests
158
+ runs-on: [single-gpu, nvidia-gpu, t4, ci]
159
+ container:
160
+ image: diffusers/diffusers-pytorch-cuda
161
+ options: --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface/diffusers:/mnt/cache/ --gpus 0
162
+ defaults:
163
+ run:
164
+ shell: bash
165
+ steps:
166
+ - name: Checkout diffusers
167
+ uses: actions/checkout@v3
168
+ with:
169
+ fetch-depth: 2
170
+
171
+ - name: Install dependencies
172
+ run: |
173
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
174
+ python -m uv pip install -e [quality,test]
175
+ python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
176
+ python -m pip install -U peft@git+https://github.com/huggingface/peft.git
177
+
178
+ - name: Environment
179
+ run: |
180
+ python utils/print_env.py
181
+
182
+ - name: Run slow PEFT CUDA tests
183
+ env:
184
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
185
+ # https://pytorch.org/docs/stable/notes/randomness.html#avoiding-nondeterministic-algorithms
186
+ CUBLAS_WORKSPACE_CONFIG: :16:8
187
+ run: |
188
+ python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
189
+ -s -v -k "not Flax and not Onnx and not PEFTLoRALoading" \
190
+ --make-reports=tests_peft_cuda \
191
+ tests/lora/
192
+ python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
193
+ -s -v -k "lora and not Flax and not Onnx and not PEFTLoRALoading" \
194
+ --make-reports=tests_peft_cuda_models_lora \
195
+ tests/models/
196
+
197
+ - name: Failure short reports
198
+ if: ${{ failure() }}
199
+ run: |
200
+ cat reports/tests_peft_cuda_stats.txt
201
+ cat reports/tests_peft_cuda_failures_short.txt
202
+ cat reports/tests_peft_cuda_models_lora_failures_short.txt
203
+
204
+ - name: Test suite reports artifacts
205
+ if: ${{ always() }}
206
+ uses: actions/upload-artifact@v2
207
+ with:
208
+ name: torch_peft_test_reports
209
+ path: reports
210
+
211
+ flax_tpu_tests:
212
+ name: Flax TPU Tests
213
+ runs-on: docker-tpu
214
+ container:
215
+ image: diffusers/diffusers-flax-tpu
216
+ options: --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/ --privileged
217
+ defaults:
218
+ run:
219
+ shell: bash
220
+ steps:
221
+ - name: Checkout diffusers
222
+ uses: actions/checkout@v3
223
+ with:
224
+ fetch-depth: 2
225
+
226
+ - name: Install dependencies
227
+ run: |
228
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
229
+ python -m uv pip install -e [quality,test]
230
+ python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
231
+
232
+ - name: Environment
233
+ run: |
234
+ python utils/print_env.py
235
+
236
+ - name: Run slow Flax TPU tests
237
+ env:
238
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
239
+ run: |
240
+ python -m pytest -n 0 \
241
+ -s -v -k "Flax" \
242
+ --make-reports=tests_flax_tpu \
243
+ tests/
244
+
245
+ - name: Failure short reports
246
+ if: ${{ failure() }}
247
+ run: |
248
+ cat reports/tests_flax_tpu_stats.txt
249
+ cat reports/tests_flax_tpu_failures_short.txt
250
+
251
+ - name: Test suite reports artifacts
252
+ if: ${{ always() }}
253
+ uses: actions/upload-artifact@v2
254
+ with:
255
+ name: flax_tpu_test_reports
256
+ path: reports
257
+
258
+ onnx_cuda_tests:
259
+ name: ONNX CUDA Tests
260
+ runs-on: [single-gpu, nvidia-gpu, t4, ci]
261
+ container:
262
+ image: diffusers/diffusers-onnxruntime-cuda
263
+ options: --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/ --gpus 0
264
+ defaults:
265
+ run:
266
+ shell: bash
267
+ steps:
268
+ - name: Checkout diffusers
269
+ uses: actions/checkout@v3
270
+ with:
271
+ fetch-depth: 2
272
+
273
+ - name: Install dependencies
274
+ run: |
275
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
276
+ python -m uv pip install -e [quality,test]
277
+ python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
278
+
279
+ - name: Environment
280
+ run: |
281
+ python utils/print_env.py
282
+
283
+ - name: Run slow ONNXRuntime CUDA tests
284
+ env:
285
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
286
+ run: |
287
+ python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
288
+ -s -v -k "Onnx" \
289
+ --make-reports=tests_onnx_cuda \
290
+ tests/
291
+
292
+ - name: Failure short reports
293
+ if: ${{ failure() }}
294
+ run: |
295
+ cat reports/tests_onnx_cuda_stats.txt
296
+ cat reports/tests_onnx_cuda_failures_short.txt
297
+
298
+ - name: Test suite reports artifacts
299
+ if: ${{ always() }}
300
+ uses: actions/upload-artifact@v2
301
+ with:
302
+ name: onnx_cuda_test_reports
303
+ path: reports
304
+
305
+ run_torch_compile_tests:
306
+ name: PyTorch Compile CUDA tests
307
+
308
+ runs-on: [single-gpu, nvidia-gpu, t4, ci]
309
+
310
+ container:
311
+ image: diffusers/diffusers-pytorch-compile-cuda
312
+ options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
313
+
314
+ steps:
315
+ - name: Checkout diffusers
316
+ uses: actions/checkout@v3
317
+ with:
318
+ fetch-depth: 2
319
+
320
+ - name: NVIDIA-SMI
321
+ run: |
322
+ nvidia-smi
323
+ - name: Install dependencies
324
+ run: |
325
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
326
+ python -m uv pip install -e [quality,test,training]
327
+ - name: Environment
328
+ run: |
329
+ python utils/print_env.py
330
+ - name: Run example tests on GPU
331
+ env:
332
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
333
+ run: |
334
+ python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile -s -v -k "compile" --make-reports=tests_torch_compile_cuda tests/
335
+ - name: Failure short reports
336
+ if: ${{ failure() }}
337
+ run: cat reports/tests_torch_compile_cuda_failures_short.txt
338
+
339
+ - name: Test suite reports artifacts
340
+ if: ${{ always() }}
341
+ uses: actions/upload-artifact@v2
342
+ with:
343
+ name: torch_compile_test_reports
344
+ path: reports
345
+
346
+ run_xformers_tests:
347
+ name: PyTorch xformers CUDA tests
348
+
349
+ runs-on: [single-gpu, nvidia-gpu, t4, ci]
350
+
351
+ container:
352
+ image: diffusers/diffusers-pytorch-xformers-cuda
353
+ options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
354
+
355
+ steps:
356
+ - name: Checkout diffusers
357
+ uses: actions/checkout@v3
358
+ with:
359
+ fetch-depth: 2
360
+
361
+ - name: NVIDIA-SMI
362
+ run: |
363
+ nvidia-smi
364
+ - name: Install dependencies
365
+ run: |
366
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
367
+ python -m uv pip install -e [quality,test,training]
368
+ - name: Environment
369
+ run: |
370
+ python utils/print_env.py
371
+ - name: Run example tests on GPU
372
+ env:
373
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
374
+ run: |
375
+ python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile -s -v -k "xformers" --make-reports=tests_torch_xformers_cuda tests/
376
+ - name: Failure short reports
377
+ if: ${{ failure() }}
378
+ run: cat reports/tests_torch_xformers_cuda_failures_short.txt
379
+
380
+ - name: Test suite reports artifacts
381
+ if: ${{ always() }}
382
+ uses: actions/upload-artifact@v2
383
+ with:
384
+ name: torch_xformers_test_reports
385
+ path: reports
386
+
387
+ run_examples_tests:
388
+ name: Examples PyTorch CUDA tests on Ubuntu
389
+
390
+ runs-on: [single-gpu, nvidia-gpu, t4, ci]
391
+
392
+ container:
393
+ image: diffusers/diffusers-pytorch-cuda
394
+ options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
395
+
396
+ steps:
397
+ - name: Checkout diffusers
398
+ uses: actions/checkout@v3
399
+ with:
400
+ fetch-depth: 2
401
+
402
+ - name: NVIDIA-SMI
403
+ run: |
404
+ nvidia-smi
405
+
406
+ - name: Install dependencies
407
+ run: |
408
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
409
+ python -m uv pip install -e [quality,test,training]
410
+
411
+ - name: Environment
412
+ run: |
413
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
414
+ python utils/print_env.py
415
+
416
+ - name: Run example tests on GPU
417
+ env:
418
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
419
+ run: |
420
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
421
+ python -m uv pip install timm
422
+ python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile -s -v --make-reports=examples_torch_cuda examples/
423
+
424
+ - name: Failure short reports
425
+ if: ${{ failure() }}
426
+ run: |
427
+ cat reports/examples_torch_cuda_stats.txt
428
+ cat reports/examples_torch_cuda_failures_short.txt
429
+
430
+ - name: Test suite reports artifacts
431
+ if: ${{ always() }}
432
+ uses: actions/upload-artifact@v2
433
+ with:
434
+ name: examples_test_reports
435
+ path: reports
UltraEdit/diffusers/.github/workflows/push_tests_fast.yml ADDED
@@ -0,0 +1,124 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Fast tests on main
2
+
3
+ on:
4
+ push:
5
+ branches:
6
+ - main
7
+ paths:
8
+ - "src/diffusers/**.py"
9
+ - "examples/**.py"
10
+ - "tests/**.py"
11
+
12
+ concurrency:
13
+ group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
14
+ cancel-in-progress: true
15
+
16
+ env:
17
+ DIFFUSERS_IS_CI: yes
18
+ HF_HOME: /mnt/cache
19
+ OMP_NUM_THREADS: 8
20
+ MKL_NUM_THREADS: 8
21
+ PYTEST_TIMEOUT: 600
22
+ RUN_SLOW: no
23
+
24
+ jobs:
25
+ run_fast_tests:
26
+ strategy:
27
+ fail-fast: false
28
+ matrix:
29
+ config:
30
+ - name: Fast PyTorch CPU tests on Ubuntu
31
+ framework: pytorch
32
+ runner: [ self-hosted, intel-cpu, 8-cpu, ci ]
33
+ image: diffusers/diffusers-pytorch-cpu
34
+ report: torch_cpu
35
+ - name: Fast Flax CPU tests on Ubuntu
36
+ framework: flax
37
+ runner: [ self-hosted, intel-cpu, 8-cpu, ci ]
38
+ image: diffusers/diffusers-flax-cpu
39
+ report: flax_cpu
40
+ - name: Fast ONNXRuntime CPU tests on Ubuntu
41
+ framework: onnxruntime
42
+ runner: [ self-hosted, intel-cpu, 8-cpu, ci ]
43
+ image: diffusers/diffusers-onnxruntime-cpu
44
+ report: onnx_cpu
45
+ - name: PyTorch Example CPU tests on Ubuntu
46
+ framework: pytorch_examples
47
+ runner: [ self-hosted, intel-cpu, 8-cpu, ci ]
48
+ image: diffusers/diffusers-pytorch-cpu
49
+ report: torch_example_cpu
50
+
51
+ name: ${{ matrix.config.name }}
52
+
53
+ runs-on: ${{ matrix.config.runner }}
54
+
55
+ container:
56
+ image: ${{ matrix.config.image }}
57
+ options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
58
+
59
+ defaults:
60
+ run:
61
+ shell: bash
62
+
63
+ steps:
64
+ - name: Checkout diffusers
65
+ uses: actions/checkout@v3
66
+ with:
67
+ fetch-depth: 2
68
+
69
+ - name: Install dependencies
70
+ run: |
71
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
72
+ python -m uv pip install -e [quality,test]
73
+
74
+ - name: Environment
75
+ run: |
76
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
77
+ python utils/print_env.py
78
+
79
+ - name: Run fast PyTorch CPU tests
80
+ if: ${{ matrix.config.framework == 'pytorch' }}
81
+ run: |
82
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
83
+ python -m pytest -n 4 --max-worker-restart=0 --dist=loadfile \
84
+ -s -v -k "not Flax and not Onnx" \
85
+ --make-reports=tests_${{ matrix.config.report }} \
86
+ tests/
87
+
88
+ - name: Run fast Flax TPU tests
89
+ if: ${{ matrix.config.framework == 'flax' }}
90
+ run: |
91
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
92
+ python -m pytest -n 4 --max-worker-restart=0 --dist=loadfile \
93
+ -s -v -k "Flax" \
94
+ --make-reports=tests_${{ matrix.config.report }} \
95
+ tests/
96
+
97
+ - name: Run fast ONNXRuntime CPU tests
98
+ if: ${{ matrix.config.framework == 'onnxruntime' }}
99
+ run: |
100
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
101
+ python -m pytest -n 4 --max-worker-restart=0 --dist=loadfile \
102
+ -s -v -k "Onnx" \
103
+ --make-reports=tests_${{ matrix.config.report }} \
104
+ tests/
105
+
106
+ - name: Run example PyTorch CPU tests
107
+ if: ${{ matrix.config.framework == 'pytorch_examples' }}
108
+ run: |
109
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
110
+ python -m uv pip install peft timm
111
+ python -m pytest -n 4 --max-worker-restart=0 --dist=loadfile \
112
+ --make-reports=tests_${{ matrix.config.report }} \
113
+ examples
114
+
115
+ - name: Failure short reports
116
+ if: ${{ failure() }}
117
+ run: cat reports/tests_${{ matrix.config.report }}_failures_short.txt
118
+
119
+ - name: Test suite reports artifacts
120
+ if: ${{ always() }}
121
+ uses: actions/upload-artifact@v2
122
+ with:
123
+ name: pr_${{ matrix.config.report }}_test_reports
124
+ path: reports
UltraEdit/diffusers/.github/workflows/push_tests_mps.yml ADDED
@@ -0,0 +1,75 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Fast mps tests on main
2
+
3
+ on:
4
+ push:
5
+ branches:
6
+ - main
7
+ paths:
8
+ - "src/diffusers/**.py"
9
+ - "tests/**.py"
10
+
11
+ env:
12
+ DIFFUSERS_IS_CI: yes
13
+ HF_HOME: /mnt/cache
14
+ OMP_NUM_THREADS: 8
15
+ MKL_NUM_THREADS: 8
16
+ PYTEST_TIMEOUT: 600
17
+ RUN_SLOW: no
18
+
19
+ concurrency:
20
+ group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
21
+ cancel-in-progress: true
22
+
23
+ jobs:
24
+ run_fast_tests_apple_m1:
25
+ name: Fast PyTorch MPS tests on MacOS
26
+ runs-on: macos-13-xlarge
27
+
28
+ steps:
29
+ - name: Checkout diffusers
30
+ uses: actions/checkout@v3
31
+ with:
32
+ fetch-depth: 2
33
+
34
+ - name: Clean checkout
35
+ shell: arch -arch arm64 bash {0}
36
+ run: |
37
+ git clean -fxd
38
+
39
+ - name: Setup miniconda
40
+ uses: ./.github/actions/setup-miniconda
41
+ with:
42
+ python-version: 3.9
43
+
44
+ - name: Install dependencies
45
+ shell: arch -arch arm64 bash {0}
46
+ run: |
47
+ ${CONDA_RUN} python -m pip install --upgrade pip uv
48
+ ${CONDA_RUN} python -m uv pip install -e [quality,test]
49
+ ${CONDA_RUN} python -m uv pip install torch torchvision torchaudio
50
+ ${CONDA_RUN} python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate.git
51
+ ${CONDA_RUN} python -m uv pip install transformers --upgrade
52
+
53
+ - name: Environment
54
+ shell: arch -arch arm64 bash {0}
55
+ run: |
56
+ ${CONDA_RUN} python utils/print_env.py
57
+
58
+ - name: Run fast PyTorch tests on M1 (MPS)
59
+ shell: arch -arch arm64 bash {0}
60
+ env:
61
+ HF_HOME: /System/Volumes/Data/mnt/cache
62
+ HF_TOKEN: ${{ secrets.HF_TOKEN }}
63
+ run: |
64
+ ${CONDA_RUN} python -m pytest -n 0 -s -v --make-reports=tests_torch_mps tests/
65
+
66
+ - name: Failure short reports
67
+ if: ${{ failure() }}
68
+ run: cat reports/tests_torch_mps_failures_short.txt
69
+
70
+ - name: Test suite reports artifacts
71
+ if: ${{ always() }}
72
+ uses: actions/upload-artifact@v2
73
+ with:
74
+ name: pr_torch_mps_test_reports
75
+ path: reports
UltraEdit/diffusers/.github/workflows/pypi_publish.yaml ADDED
@@ -0,0 +1,81 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Adapted from https://blog.deepjyoti30.dev/pypi-release-github-action
2
+
3
+ name: PyPI release
4
+
5
+ on:
6
+ workflow_dispatch:
7
+ push:
8
+ tags:
9
+ - "*"
10
+
11
+ jobs:
12
+ find-and-checkout-latest-branch:
13
+ runs-on: ubuntu-latest
14
+ outputs:
15
+ latest_branch: ${{ steps.set_latest_branch.outputs.latest_branch }}
16
+ steps:
17
+ - name: Checkout Repo
18
+ uses: actions/checkout@v3
19
+
20
+ - name: Set up Python
21
+ uses: actions/setup-python@v4
22
+ with:
23
+ python-version: '3.8'
24
+
25
+ - name: Fetch latest branch
26
+ id: fetch_latest_branch
27
+ run: |
28
+ pip install -U requests packaging
29
+ LATEST_BRANCH=$(python utils/fetch_latest_release_branch.py)
30
+ echo "Latest branch: $LATEST_BRANCH"
31
+ echo "latest_branch=$LATEST_BRANCH" >> $GITHUB_ENV
32
+
33
+ - name: Set latest branch output
34
+ id: set_latest_branch
35
+ run: echo "::set-output name=latest_branch::${{ env.latest_branch }}"
36
+
37
+ release:
38
+ needs: find-and-checkout-latest-branch
39
+ runs-on: ubuntu-latest
40
+
41
+ steps:
42
+ - name: Checkout Repo
43
+ uses: actions/checkout@v3
44
+ with:
45
+ ref: ${{ needs.find-and-checkout-latest-branch.outputs.latest_branch }}
46
+
47
+ - name: Setup Python
48
+ uses: actions/setup-python@v4
49
+ with:
50
+ python-version: "3.8"
51
+
52
+ - name: Install dependencies
53
+ run: |
54
+ python -m pip install --upgrade pip
55
+ pip install -U setuptools wheel twine
56
+ pip install -U torch --index-url https://download.pytorch.org/whl/cpu
57
+ pip install -U transformers
58
+
59
+ - name: Build the dist files
60
+ run: python setup.py bdist_wheel && python setup.py sdist
61
+
62
+ - name: Publish to the test PyPI
63
+ env:
64
+ TWINE_USERNAME: ${{ secrets.TEST_PYPI_USERNAME }}
65
+ TWINE_PASSWORD: ${{ secrets.TEST_PYPI_PASSWORD }}
66
+ run: twine upload dist/* -r pypitest --repository-url=https://test.pypi.org/legacy/
67
+
68
+ - name: Test installing diffusers and importing
69
+ run: |
70
+ pip install diffusers && pip uninstall diffusers -y
71
+ pip install -i https://testpypi.python.org/pypi diffusers
72
+ python -c "from diffusers import __version__; print(__version__)"
73
+ python -c "from diffusers import DiffusionPipeline; pipe = DiffusionPipeline.from_pretrained('fusing/unet-ldm-dummy-update'); pipe()"
74
+ python -c "from diffusers import DiffusionPipeline; pipe = DiffusionPipeline.from_pretrained('hf-internal-testing/tiny-stable-diffusion-pipe', safety_checker=None); pipe('ah suh du')"
75
+ python -c "from diffusers import *"
76
+
77
+ - name: Publish to PyPI
78
+ env:
79
+ TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
80
+ TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
81
+ run: twine upload dist/* -r pypi
UltraEdit/diffusers/.github/workflows/run_tests_from_a_pr.yml ADDED
@@ -0,0 +1,73 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Check running SLOW tests from a PR (only GPU)
2
+
3
+ on:
4
+ workflow_dispatch:
5
+ inputs:
6
+ docker_image:
7
+ default: 'diffusers/diffusers-pytorch-cuda'
8
+ description: 'Name of the Docker image'
9
+ required: true
10
+ branch:
11
+ description: 'PR Branch to test on'
12
+ required: true
13
+ test:
14
+ description: 'Tests to run (e.g.: `tests/models`).'
15
+ required: true
16
+
17
+ env:
18
+ DIFFUSERS_IS_CI: yes
19
+ IS_GITHUB_CI: "1"
20
+ HF_HOME: /mnt/cache
21
+ OMP_NUM_THREADS: 8
22
+ MKL_NUM_THREADS: 8
23
+ PYTEST_TIMEOUT: 600
24
+ RUN_SLOW: yes
25
+
26
+ jobs:
27
+ run_tests:
28
+ name: "Run a test on our runner from a PR"
29
+ runs-on: [single-gpu, nvidia-gpu, t4, ci]
30
+ container:
31
+ image: ${{ github.event.inputs.docker_image }}
32
+ options: --gpus 0 --privileged --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
33
+
34
+ steps:
35
+ - name: Validate test files input
36
+ id: validate_test_files
37
+ env:
38
+ PY_TEST: ${{ github.event.inputs.test }}
39
+ run: |
40
+ if [[ ! "$PY_TEST" =~ ^tests/ ]]; then
41
+ echo "Error: The input string must start with 'tests/'."
42
+ exit 1
43
+ fi
44
+
45
+ if [[ ! "$PY_TEST" =~ ^tests/(models|pipelines) ]]; then
46
+ echo "Error: The input string must contain either 'models' or 'pipelines' after 'tests/'."
47
+ exit 1
48
+ fi
49
+
50
+ if [[ "$PY_TEST" == *";"* ]]; then
51
+ echo "Error: The input string must not contain ';'."
52
+ exit 1
53
+ fi
54
+ echo "$PY_TEST"
55
+
56
+ - name: Checkout PR branch
57
+ uses: actions/checkout@v4
58
+ with:
59
+ ref: ${{ github.event.inputs.branch }}
60
+ repository: ${{ github.event.pull_request.head.repo.full_name }}
61
+
62
+
63
+ - name: Install pytest
64
+ run: |
65
+ python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
66
+ python -m uv pip install -e [quality,test]
67
+ python -m uv pip install peft
68
+
69
+ - name: Run tests
70
+ env:
71
+ PY_TEST: ${{ github.event.inputs.test }}
72
+ run: |
73
+ pytest "$PY_TEST"
UltraEdit/diffusers/.github/workflows/ssh-runner.yml ADDED
@@ -0,0 +1,46 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: SSH into runners
2
+
3
+ on:
4
+ workflow_dispatch:
5
+ inputs:
6
+ runner_type:
7
+ description: 'Type of runner to test (a10 or t4)'
8
+ required: true
9
+ docker_image:
10
+ description: 'Name of the Docker image'
11
+ required: true
12
+
13
+ env:
14
+ IS_GITHUB_CI: "1"
15
+ HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
16
+ HF_HOME: /mnt/cache
17
+ DIFFUSERS_IS_CI: yes
18
+ OMP_NUM_THREADS: 8
19
+ MKL_NUM_THREADS: 8
20
+ RUN_SLOW: yes
21
+
22
+ jobs:
23
+ ssh_runner:
24
+ name: "SSH"
25
+ runs-on: [single-gpu, nvidia-gpu, "${{ github.event.inputs.runner_type }}", ci]
26
+ container:
27
+ image: ${{ github.event.inputs.docker_image }}
28
+ options: --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface/diffusers:/mnt/cache/ --gpus 0 --privileged
29
+
30
+ steps:
31
+ - name: Checkout diffusers
32
+ uses: actions/checkout@v3
33
+ with:
34
+ fetch-depth: 2
35
+
36
+ - name: NVIDIA-SMI
37
+ run: |
38
+ nvidia-smi
39
+
40
+ - name: Tailscale # In order to be able to SSH when a test fails
41
+ uses: huggingface/tailscale-action@main
42
+ with:
43
+ authkey: ${{ secrets.TAILSCALE_SSH_AUTHKEY }}
44
+ slackChannel: ${{ secrets.SLACK_CIFEEDBACK_CHANNEL }}
45
+ slackToken: ${{ secrets.SLACK_CIFEEDBACK_BOT_TOKEN }}
46
+ waitForSSH: true
UltraEdit/diffusers/.github/workflows/stale.yml ADDED
@@ -0,0 +1,27 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Stale Bot
2
+
3
+ on:
4
+ schedule:
5
+ - cron: "0 15 * * *"
6
+
7
+ jobs:
8
+ close_stale_issues:
9
+ name: Close Stale Issues
10
+ if: github.repository == 'huggingface/diffusers'
11
+ runs-on: ubuntu-latest
12
+ env:
13
+ GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
14
+ steps:
15
+ - uses: actions/checkout@v2
16
+
17
+ - name: Setup Python
18
+ uses: actions/setup-python@v1
19
+ with:
20
+ python-version: 3.8
21
+
22
+ - name: Install requirements
23
+ run: |
24
+ pip install PyGithub
25
+ - name: Close stale issues
26
+ run: |
27
+ python utils/stale.py
UltraEdit/diffusers/.github/workflows/trufflehog.yml ADDED
@@ -0,0 +1,15 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ on:
2
+ push:
3
+
4
+ name: Secret Leaks
5
+
6
+ jobs:
7
+ trufflehog:
8
+ runs-on: ubuntu-latest
9
+ steps:
10
+ - name: Checkout code
11
+ uses: actions/checkout@v4
12
+ with:
13
+ fetch-depth: 0
14
+ - name: Secret Scanning
15
+ uses: trufflesecurity/trufflehog@main
UltraEdit/diffusers/.github/workflows/typos.yml ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Check typos
2
+
3
+ on:
4
+ workflow_dispatch:
5
+
6
+ jobs:
7
+ build:
8
+ runs-on: ubuntu-latest
9
+
10
+ steps:
11
+ - uses: actions/checkout@v3
12
+
13
+ - name: typos-action
14
+ uses: crate-ci/typos@v1.12.4
UltraEdit/diffusers/.github/workflows/update_metadata.yml ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Update Diffusers metadata
2
+
3
+ on:
4
+ workflow_dispatch:
5
+ push:
6
+ branches:
7
+ - main
8
+ - update_diffusers_metadata*
9
+
10
+ jobs:
11
+ update_metadata:
12
+ runs-on: ubuntu-22.04
13
+ defaults:
14
+ run:
15
+ shell: bash -l {0}
16
+
17
+ steps:
18
+ - uses: actions/checkout@v3
19
+
20
+ - name: Setup environment
21
+ run: |
22
+ pip install --upgrade pip
23
+ pip install datasets pandas
24
+ pip install .[torch]
25
+
26
+ - name: Update metadata
27
+ env:
28
+ HF_TOKEN: ${{ secrets.SAYAK_HF_TOKEN }}
29
+ run: |
30
+ python utils/update_metadata.py --commit_sha ${{ github.sha }}
UltraEdit/diffusers/.github/workflows/upload_pr_documentation.yml ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: Upload PR Documentation
2
+
3
+ on:
4
+ workflow_run:
5
+ workflows: ["Build PR Documentation"]
6
+ types:
7
+ - completed
8
+
9
+ jobs:
10
+ build:
11
+ uses: huggingface/doc-builder/.github/workflows/upload_pr_documentation.yml@main
12
+ with:
13
+ package_name: diffusers
14
+ secrets:
15
+ hf_token: ${{ secrets.HF_DOC_BUILD_PUSH }}
16
+ comment_bot_token: ${{ secrets.COMMENT_BOT_TOKEN }}
UltraEdit/diffusers/.gitignore ADDED
@@ -0,0 +1,178 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Initially taken from GitHub's Python gitignore file
2
+
3
+ # Byte-compiled / optimized / DLL files
4
+ __pycache__/
5
+ *.py[cod]
6
+ *$py.class
7
+
8
+ # C extensions
9
+ *.so
10
+
11
+ # tests and logs
12
+ tests/fixtures/cached_*_text.txt
13
+ logs/
14
+ lightning_logs/
15
+ lang_code_data/
16
+
17
+ # Distribution / packaging
18
+ .Python
19
+ build/
20
+ develop-eggs/
21
+ dist/
22
+ downloads/
23
+ eggs/
24
+ .eggs/
25
+ lib/
26
+ lib64/
27
+ parts/
28
+ sdist/
29
+ var/
30
+ wheels/
31
+ *.egg-info/
32
+ .installed.cfg
33
+ *.egg
34
+ MANIFEST
35
+
36
+ # PyInstaller
37
+ # Usually these files are written by a Python script from a template
38
+ # before PyInstaller builds the exe, so as to inject date/other infos into it.
39
+ *.manifest
40
+ *.spec
41
+
42
+ # Installer logs
43
+ pip-log.txt
44
+ pip-delete-this-directory.txt
45
+
46
+ # Unit test / coverage reports
47
+ htmlcov/
48
+ .tox/
49
+ .nox/
50
+ .coverage
51
+ .coverage.*
52
+ .cache
53
+ nosetests.xml
54
+ coverage.xml
55
+ *.cover
56
+ .hypothesis/
57
+ .pytest_cache/
58
+
59
+ # Translations
60
+ *.mo
61
+ *.pot
62
+
63
+ # Django stuff:
64
+ *.log
65
+ local_settings.py
66
+ db.sqlite3
67
+
68
+ # Flask stuff:
69
+ instance/
70
+ .webassets-cache
71
+
72
+ # Scrapy stuff:
73
+ .scrapy
74
+
75
+ # Sphinx documentation
76
+ docs/_build/
77
+
78
+ # PyBuilder
79
+ target/
80
+
81
+ # Jupyter Notebook
82
+ .ipynb_checkpoints
83
+
84
+ # IPython
85
+ profile_default/
86
+ ipython_config.py
87
+
88
+ # pyenv
89
+ .python-version
90
+
91
+ # celery beat schedule file
92
+ celerybeat-schedule
93
+
94
+ # SageMath parsed files
95
+ *.sage.py
96
+
97
+ # Environments
98
+ .env
99
+ .venv
100
+ env/
101
+ venv/
102
+ ENV/
103
+ env.bak/
104
+ venv.bak/
105
+
106
+ # Spyder project settings
107
+ .spyderproject
108
+ .spyproject
109
+
110
+ # Rope project settings
111
+ .ropeproject
112
+
113
+ # mkdocs documentation
114
+ /site
115
+
116
+ # mypy
117
+ .mypy_cache/
118
+ .dmypy.json
119
+ dmypy.json
120
+
121
+ # Pyre type checker
122
+ .pyre/
123
+
124
+ # vscode
125
+ .vs
126
+ .vscode
127
+
128
+ # Pycharm
129
+ .idea
130
+
131
+ # TF code
132
+ tensorflow_code
133
+
134
+ # Models
135
+ proc_data
136
+
137
+ # examples
138
+ runs
139
+ /runs_old
140
+ /wandb
141
+ /examples/runs
142
+ /examples/**/*.args
143
+ /examples/rag/sweep
144
+
145
+ # data
146
+ /data
147
+ serialization_dir
148
+
149
+ # emacs
150
+ *.*~
151
+ debug.env
152
+
153
+ # vim
154
+ .*.swp
155
+
156
+ # ctags
157
+ tags
158
+
159
+ # pre-commit
160
+ .pre-commit*
161
+
162
+ # .lock
163
+ *.lock
164
+
165
+ # DS_Store (MacOS)
166
+ .DS_Store
167
+
168
+ # RL pipelines may produce mp4 outputs
169
+ *.mp4
170
+
171
+ # dependencies
172
+ /transformers
173
+
174
+ # ruff
175
+ .ruff_cache
176
+
177
+ # wandb
178
+ wandb
UltraEdit/diffusers/CITATION.cff ADDED
@@ -0,0 +1,52 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ cff-version: 1.2.0
2
+ title: 'Diffusers: State-of-the-art diffusion models'
3
+ message: >-
4
+ If you use this software, please cite it using the
5
+ metadata from this file.
6
+ type: software
7
+ authors:
8
+ - given-names: Patrick
9
+ family-names: von Platen
10
+ - given-names: Suraj
11
+ family-names: Patil
12
+ - given-names: Anton
13
+ family-names: Lozhkov
14
+ - given-names: Pedro
15
+ family-names: Cuenca
16
+ - given-names: Nathan
17
+ family-names: Lambert
18
+ - given-names: Kashif
19
+ family-names: Rasul
20
+ - given-names: Mishig
21
+ family-names: Davaadorj
22
+ - given-names: Dhruv
23
+ family-names: Nair
24
+ - given-names: Sayak
25
+ family-names: Paul
26
+ - given-names: Steven
27
+ family-names: Liu
28
+ - given-names: William
29
+ family-names: Berman
30
+ - given-names: Yiyi
31
+ family-names: Xu
32
+ - given-names: Thomas
33
+ family-names: Wolf
34
+ repository-code: 'https://github.com/huggingface/diffusers'
35
+ abstract: >-
36
+ Diffusers provides pretrained diffusion models across
37
+ multiple modalities, such as vision and audio, and serves
38
+ as a modular toolbox for inference and training of
39
+ diffusion models.
40
+ keywords:
41
+ - deep-learning
42
+ - pytorch
43
+ - image-generation
44
+ - hacktoberfest
45
+ - diffusion
46
+ - text2image
47
+ - image2image
48
+ - score-based-generative-modeling
49
+ - stable-diffusion
50
+ - stable-diffusion-diffusers
51
+ license: Apache-2.0
52
+ version: 0.12.1
UltraEdit/diffusers/CODE_OF_CONDUCT.md ADDED
@@ -0,0 +1,130 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+ # Contributor Covenant Code of Conduct
3
+
4
+ ## Our Pledge
5
+
6
+ We as members, contributors, and leaders pledge to make participation in our
7
+ community a harassment-free experience for everyone, regardless of age, body
8
+ size, visible or invisible disability, ethnicity, sex characteristics, gender
9
+ identity and expression, level of experience, education, socio-economic status,
10
+ nationality, personal appearance, race, caste, color, religion, or sexual identity
11
+ and orientation.
12
+
13
+ We pledge to act and interact in ways that contribute to an open, welcoming,
14
+ diverse, inclusive, and healthy community.
15
+
16
+ ## Our Standards
17
+
18
+ Examples of behavior that contributes to a positive environment for our
19
+ community include:
20
+
21
+ * Demonstrating empathy and kindness toward other people
22
+ * Being respectful of differing opinions, viewpoints, and experiences
23
+ * Giving and gracefully accepting constructive feedback
24
+ * Accepting responsibility and apologizing to those affected by our mistakes,
25
+ and learning from the experience
26
+ * Focusing on what is best not just for us as individuals, but for the
27
+ overall Diffusers community
28
+
29
+ Examples of unacceptable behavior include:
30
+
31
+ * The use of sexualized language or imagery, and sexual attention or
32
+ advances of any kind
33
+ * Trolling, insulting or derogatory comments, and personal or political attacks
34
+ * Public or private harassment
35
+ * Publishing others' private information, such as a physical or email
36
+ address, without their explicit permission
37
+ * Spamming issues or PRs with links to projects unrelated to this library
38
+ * Other conduct which could reasonably be considered inappropriate in a
39
+ professional setting
40
+
41
+ ## Enforcement Responsibilities
42
+
43
+ Community leaders are responsible for clarifying and enforcing our standards of
44
+ acceptable behavior and will take appropriate and fair corrective action in
45
+ response to any behavior that they deem inappropriate, threatening, offensive,
46
+ or harmful.
47
+
48
+ Community leaders have the right and responsibility to remove, edit, or reject
49
+ comments, commits, code, wiki edits, issues, and other contributions that are
50
+ not aligned to this Code of Conduct, and will communicate reasons for moderation
51
+ decisions when appropriate.
52
+
53
+ ## Scope
54
+
55
+ This Code of Conduct applies within all community spaces, and also applies when
56
+ an individual is officially representing the community in public spaces.
57
+ Examples of representing our community include using an official e-mail address,
58
+ posting via an official social media account, or acting as an appointed
59
+ representative at an online or offline event.
60
+
61
+ ## Enforcement
62
+
63
+ Instances of abusive, harassing, or otherwise unacceptable behavior may be
64
+ reported to the community leaders responsible for enforcement at
65
+ feedback@huggingface.co.
66
+ All complaints will be reviewed and investigated promptly and fairly.
67
+
68
+ All community leaders are obligated to respect the privacy and security of the
69
+ reporter of any incident.
70
+
71
+ ## Enforcement Guidelines
72
+
73
+ Community leaders will follow these Community Impact Guidelines in determining
74
+ the consequences for any action they deem in violation of this Code of Conduct:
75
+
76
+ ### 1. Correction
77
+
78
+ **Community Impact**: Use of inappropriate language or other behavior deemed
79
+ unprofessional or unwelcome in the community.
80
+
81
+ **Consequence**: A private, written warning from community leaders, providing
82
+ clarity around the nature of the violation and an explanation of why the
83
+ behavior was inappropriate. A public apology may be requested.
84
+
85
+ ### 2. Warning
86
+
87
+ **Community Impact**: A violation through a single incident or series
88
+ of actions.
89
+
90
+ **Consequence**: A warning with consequences for continued behavior. No
91
+ interaction with the people involved, including unsolicited interaction with
92
+ those enforcing the Code of Conduct, for a specified period of time. This
93
+ includes avoiding interactions in community spaces as well as external channels
94
+ like social media. Violating these terms may lead to a temporary or
95
+ permanent ban.
96
+
97
+ ### 3. Temporary Ban
98
+
99
+ **Community Impact**: A serious violation of community standards, including
100
+ sustained inappropriate behavior.
101
+
102
+ **Consequence**: A temporary ban from any sort of interaction or public
103
+ communication with the community for a specified period of time. No public or
104
+ private interaction with the people involved, including unsolicited interaction
105
+ with those enforcing the Code of Conduct, is allowed during this period.
106
+ Violating these terms may lead to a permanent ban.
107
+
108
+ ### 4. Permanent Ban
109
+
110
+ **Community Impact**: Demonstrating a pattern of violation of community
111
+ standards, including sustained inappropriate behavior, harassment of an
112
+ individual, or aggression toward or disparagement of classes of individuals.
113
+
114
+ **Consequence**: A permanent ban from any sort of public interaction within
115
+ the community.
116
+
117
+ ## Attribution
118
+
119
+ This Code of Conduct is adapted from the [Contributor Covenant][homepage],
120
+ version 2.1, available at
121
+ https://www.contributor-covenant.org/version/2/1/code_of_conduct.html.
122
+
123
+ Community Impact Guidelines were inspired by [Mozilla's code of conduct
124
+ enforcement ladder](https://github.com/mozilla/diversity).
125
+
126
+ [homepage]: https://www.contributor-covenant.org
127
+
128
+ For answers to common questions about this code of conduct, see the FAQ at
129
+ https://www.contributor-covenant.org/faq. Translations are available at
130
+ https://www.contributor-covenant.org/translations.
UltraEdit/diffusers/CONTRIBUTING.md ADDED
@@ -0,0 +1,505 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <!--Copyright 2024 The HuggingFace Team. All rights reserved.
2
+
3
+ Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
4
+ the License. You may obtain a copy of the License at
5
+
6
+ http://www.apache.org/licenses/LICENSE-2.0
7
+
8
+ Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
9
+ an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
10
+ specific language governing permissions and limitations under the License.
11
+ -->
12
+
13
+ # How to contribute to Diffusers 🧨
14
+
15
+ We ❤️ contributions from the open-source community! Everyone is welcome, and all types of participation –not just code– are valued and appreciated. Answering questions, helping others, reaching out, and improving the documentation are all immensely valuable to the community, so don't be afraid and get involved if you're up for it!
16
+
17
+ Everyone is encouraged to start by saying 👋 in our public Discord channel. We discuss the latest trends in diffusion models, ask questions, show off personal projects, help each other with contributions, or just hang out ☕. <a href="https://discord.gg/G7tWnz98XR"><img alt="Join us on Discord" src="https://img.shields.io/discord/823813159592001537?color=5865F2&logo=Discord&logoColor=white"></a>
18
+
19
+ Whichever way you choose to contribute, we strive to be part of an open, welcoming, and kind community. Please, read our [code of conduct](https://github.com/huggingface/diffusers/blob/main/CODE_OF_CONDUCT.md) and be mindful to respect it during your interactions. We also recommend you become familiar with the [ethical guidelines](https://huggingface.co/docs/diffusers/conceptual/ethical_guidelines) that guide our project and ask you to adhere to the same principles of transparency and responsibility.
20
+
21
+ We enormously value feedback from the community, so please do not be afraid to speak up if you believe you have valuable feedback that can help improve the library - every message, comment, issue, and pull request (PR) is read and considered.
22
+
23
+ ## Overview
24
+
25
+ You can contribute in many ways ranging from answering questions on issues to adding new diffusion models to
26
+ the core library.
27
+
28
+ In the following, we give an overview of different ways to contribute, ranked by difficulty in ascending order. All of them are valuable to the community.
29
+
30
+ * 1. Asking and answering questions on [the Diffusers discussion forum](https://discuss.huggingface.co/c/discussion-related-to-httpsgithubcomhuggingfacediffusers) or on [Discord](https://discord.gg/G7tWnz98XR).
31
+ * 2. Opening new issues on [the GitHub Issues tab](https://github.com/huggingface/diffusers/issues/new/choose).
32
+ * 3. Answering issues on [the GitHub Issues tab](https://github.com/huggingface/diffusers/issues).
33
+ * 4. Fix a simple issue, marked by the "Good first issue" label, see [here](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22).
34
+ * 5. Contribute to the [documentation](https://github.com/huggingface/diffusers/tree/main/docs/source).
35
+ * 6. Contribute a [Community Pipeline](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3Acommunity-examples).
36
+ * 7. Contribute to the [examples](https://github.com/huggingface/diffusers/tree/main/examples).
37
+ * 8. Fix a more difficult issue, marked by the "Good second issue" label, see [here](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22Good+second+issue%22).
38
+ * 9. Add a new pipeline, model, or scheduler, see ["New Pipeline/Model"](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22New+pipeline%2Fmodel%22) and ["New scheduler"](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22New+scheduler%22) issues. For this contribution, please have a look at [Design Philosophy](https://github.com/huggingface/diffusers/blob/main/PHILOSOPHY.md).
39
+
40
+ As said before, **all contributions are valuable to the community**.
41
+ In the following, we will explain each contribution a bit more in detail.
42
+
43
+ For all contributions 4-9, you will need to open a PR. It is explained in detail how to do so in [Opening a pull request](#how-to-open-a-pr).
44
+
45
+ ### 1. Asking and answering questions on the Diffusers discussion forum or on the Diffusers Discord
46
+
47
+ Any question or comment related to the Diffusers library can be asked on the [discussion forum](https://discuss.huggingface.co/c/discussion-related-to-httpsgithubcomhuggingfacediffusers/) or on [Discord](https://discord.gg/G7tWnz98XR). Such questions and comments include (but are not limited to):
48
+ - Reports of training or inference experiments in an attempt to share knowledge
49
+ - Presentation of personal projects
50
+ - Questions to non-official training examples
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+ - Project proposals
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+ - General feedback
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+ - Paper summaries
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+ - Asking for help on personal projects that build on top of the Diffusers library
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+ - General questions
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+ - Ethical questions regarding diffusion models
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+ - ...
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+
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+ Every question that is asked on the forum or on Discord actively encourages the community to publicly
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+ share knowledge and might very well help a beginner in the future that has the same question you're
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+ having. Please do pose any questions you might have.
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+ In the same spirit, you are of immense help to the community by answering such questions because this way you are publicly documenting knowledge for everybody to learn from.
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+
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+ **Please** keep in mind that the more effort you put into asking or answering a question, the higher
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+ the quality of the publicly documented knowledge. In the same way, well-posed and well-answered questions create a high-quality knowledge database accessible to everybody, while badly posed questions or answers reduce the overall quality of the public knowledge database.
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+ In short, a high quality question or answer is *precise*, *concise*, *relevant*, *easy-to-understand*, *accessible*, and *well-formated/well-posed*. For more information, please have a look through the [How to write a good issue](#how-to-write-a-good-issue) section.
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+
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+ **NOTE about channels**:
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+ [*The forum*](https://discuss.huggingface.co/c/discussion-related-to-httpsgithubcomhuggingfacediffusers/63) is much better indexed by search engines, such as Google. Posts are ranked by popularity rather than chronologically. Hence, it's easier to look up questions and answers that we posted some time ago.
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+ In addition, questions and answers posted in the forum can easily be linked to.
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+ In contrast, *Discord* has a chat-like format that invites fast back-and-forth communication.
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+ While it will most likely take less time for you to get an answer to your question on Discord, your
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+ question won't be visible anymore over time. Also, it's much harder to find information that was posted a while back on Discord. We therefore strongly recommend using the forum for high-quality questions and answers in an attempt to create long-lasting knowledge for the community. If discussions on Discord lead to very interesting answers and conclusions, we recommend posting the results on the forum to make the information more available for future readers.
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+
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+ ### 2. Opening new issues on the GitHub issues tab
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+
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+ The 🧨 Diffusers library is robust and reliable thanks to the users who notify us of
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+ the problems they encounter. So thank you for reporting an issue.
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+
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+ Remember, GitHub issues are reserved for technical questions directly related to the Diffusers library, bug reports, feature requests, or feedback on the library design.
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+
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+ In a nutshell, this means that everything that is **not** related to the **code of the Diffusers library** (including the documentation) should **not** be asked on GitHub, but rather on either the [forum](https://discuss.huggingface.co/c/discussion-related-to-httpsgithubcomhuggingfacediffusers/63) or [Discord](https://discord.gg/G7tWnz98XR).
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+
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+ **Please consider the following guidelines when opening a new issue**:
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+ - Make sure you have searched whether your issue has already been asked before (use the search bar on GitHub under Issues).
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+ - Please never report a new issue on another (related) issue. If another issue is highly related, please
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+ open a new issue nevertheless and link to the related issue.
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+ - Make sure your issue is written in English. Please use one of the great, free online translation services, such as [DeepL](https://www.deepl.com/translator) to translate from your native language to English if you are not comfortable in English.
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+ - Check whether your issue might be solved by updating to the newest Diffusers version. Before posting your issue, please make sure that `python -c "import diffusers; print(diffusers.__version__)"` is higher or matches the latest Diffusers version.
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+ - Remember that the more effort you put into opening a new issue, the higher the quality of your answer will be and the better the overall quality of the Diffusers issues.
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+
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+ New issues usually include the following.
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+
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+ #### 2.1. Reproducible, minimal bug reports
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+
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+ A bug report should always have a reproducible code snippet and be as minimal and concise as possible.
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+ This means in more detail:
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+ - Narrow the bug down as much as you can, **do not just dump your whole code file**.
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+ - Format your code.
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+ - Do not include any external libraries except for Diffusers depending on them.
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+ - **Always** provide all necessary information about your environment; for this, you can run: `diffusers-cli env` in your shell and copy-paste the displayed information to the issue.
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+ - Explain the issue. If the reader doesn't know what the issue is and why it is an issue, she cannot solve it.
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+ - **Always** make sure the reader can reproduce your issue with as little effort as possible. If your code snippet cannot be run because of missing libraries or undefined variables, the reader cannot help you. Make sure your reproducible code snippet is as minimal as possible and can be copy-pasted into a simple Python shell.
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+ - If in order to reproduce your issue a model and/or dataset is required, make sure the reader has access to that model or dataset. You can always upload your model or dataset to the [Hub](https://huggingface.co) to make it easily downloadable. Try to keep your model and dataset as small as possible, to make the reproduction of your issue as effortless as possible.
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+
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+ For more information, please have a look through the [How to write a good issue](#how-to-write-a-good-issue) section.
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+
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+ You can open a bug report [here](https://github.com/huggingface/diffusers/issues/new?assignees=&labels=bug&projects=&template=bug-report.yml).
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+
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+ #### 2.2. Feature requests
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+
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+ A world-class feature request addresses the following points:
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+
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+ 1. Motivation first:
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+ * Is it related to a problem/frustration with the library? If so, please explain
116
+ why. Providing a code snippet that demonstrates the problem is best.
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+ * Is it related to something you would need for a project? We'd love to hear
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+ about it!
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+ * Is it something you worked on and think could benefit the community?
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+ Awesome! Tell us what problem it solved for you.
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+ 2. Write a *full paragraph* describing the feature;
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+ 3. Provide a **code snippet** that demonstrates its future use;
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+ 4. In case this is related to a paper, please attach a link;
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+ 5. Attach any additional information (drawings, screenshots, etc.) you think may help.
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+
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+ You can open a feature request [here](https://github.com/huggingface/diffusers/issues/new?assignees=&labels=&template=feature_request.md&title=).
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+
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+ #### 2.3 Feedback
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+
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+ Feedback about the library design and why it is good or not good helps the core maintainers immensely to build a user-friendly library. To understand the philosophy behind the current design philosophy, please have a look [here](https://huggingface.co/docs/diffusers/conceptual/philosophy). If you feel like a certain design choice does not fit with the current design philosophy, please explain why and how it should be changed. If a certain design choice follows the design philosophy too much, hence restricting use cases, explain why and how it should be changed.
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+ If a certain design choice is very useful for you, please also leave a note as this is great feedback for future design decisions.
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+
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+ You can open an issue about feedback [here](https://github.com/huggingface/diffusers/issues/new?assignees=&labels=&template=feedback.md&title=).
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+
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+ #### 2.4 Technical questions
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+
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+ Technical questions are mainly about why certain code of the library was written in a certain way, or what a certain part of the code does. Please make sure to link to the code in question and please provide detail on
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+ why this part of the code is difficult to understand.
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+
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+ You can open an issue about a technical question [here](https://github.com/huggingface/diffusers/issues/new?assignees=&labels=bug&template=bug-report.yml).
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+
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+ #### 2.5 Proposal to add a new model, scheduler, or pipeline
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+
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+ If the diffusion model community released a new model, pipeline, or scheduler that you would like to see in the Diffusers library, please provide the following information:
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+
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+ * Short description of the diffusion pipeline, model, or scheduler and link to the paper or public release.
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+ * Link to any of its open-source implementation.
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+ * Link to the model weights if they are available.
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+
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+ If you are willing to contribute to the model yourself, let us know so we can best guide you. Also, don't forget
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+ to tag the original author of the component (model, scheduler, pipeline, etc.) by GitHub handle if you can find it.
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+
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+ You can open a request for a model/pipeline/scheduler [here](https://github.com/huggingface/diffusers/issues/new?assignees=&labels=New+model%2Fpipeline%2Fscheduler&template=new-model-addition.yml).
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+
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+ ### 3. Answering issues on the GitHub issues tab
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+
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+ Answering issues on GitHub might require some technical knowledge of Diffusers, but we encourage everybody to give it a try even if you are not 100% certain that your answer is correct.
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+ Some tips to give a high-quality answer to an issue:
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+ - Be as concise and minimal as possible.
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+ - Stay on topic. An answer to the issue should concern the issue and only the issue.
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+ - Provide links to code, papers, or other sources that prove or encourage your point.
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+ - Answer in code. If a simple code snippet is the answer to the issue or shows how the issue can be solved, please provide a fully reproducible code snippet.
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+
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+ Also, many issues tend to be simply off-topic, duplicates of other issues, or irrelevant. It is of great
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+ help to the maintainers if you can answer such issues, encouraging the author of the issue to be
166
+ more precise, provide the link to a duplicated issue or redirect them to [the forum](https://discuss.huggingface.co/c/discussion-related-to-httpsgithubcomhuggingfacediffusers/63) or [Discord](https://discord.gg/G7tWnz98XR).
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+
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+ If you have verified that the issued bug report is correct and requires a correction in the source code,
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+ please have a look at the next sections.
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+
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+ For all of the following contributions, you will need to open a PR. It is explained in detail how to do so in the [Opening a pull request](#how-to-open-a-pr) section.
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+
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+ ### 4. Fixing a "Good first issue"
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+
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+ *Good first issues* are marked by the [Good first issue](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22) label. Usually, the issue already
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+ explains how a potential solution should look so that it is easier to fix.
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+ If the issue hasn't been closed and you would like to try to fix this issue, you can just leave a message "I would like to try this issue.". There are usually three scenarios:
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+ - a.) The issue description already proposes a fix. In this case and if the solution makes sense to you, you can open a PR or draft PR to fix it.
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+ - b.) The issue description does not propose a fix. In this case, you can ask what a proposed fix could look like and someone from the Diffusers team should answer shortly. If you have a good idea of how to fix it, feel free to directly open a PR.
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+ - c.) There is already an open PR to fix the issue, but the issue hasn't been closed yet. If the PR has gone stale, you can simply open a new PR and link to the stale PR. PRs often go stale if the original contributor who wanted to fix the issue suddenly cannot find the time anymore to proceed. This often happens in open-source and is very normal. In this case, the community will be very happy if you give it a new try and leverage the knowledge of the existing PR. If there is already a PR and it is active, you can help the author by giving suggestions, reviewing the PR or even asking whether you can contribute to the PR.
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+
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+
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+ ### 5. Contribute to the documentation
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+
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+ A good library **always** has good documentation! The official documentation is often one of the first points of contact for new users of the library, and therefore contributing to the documentation is a **highly
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+ valuable contribution**.
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+
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+ Contributing to the library can have many forms:
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+
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+ - Correcting spelling or grammatical errors.
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+ - Correct incorrect formatting of the docstring. If you see that the official documentation is weirdly displayed or a link is broken, we are very happy if you take some time to correct it.
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+ - Correct the shape or dimensions of a docstring input or output tensor.
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+ - Clarify documentation that is hard to understand or incorrect.
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+ - Update outdated code examples.
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+ - Translating the documentation to another language.
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+
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+ Anything displayed on [the official Diffusers doc page](https://huggingface.co/docs/diffusers/index) is part of the official documentation and can be corrected, adjusted in the respective [documentation source](https://github.com/huggingface/diffusers/tree/main/docs/source).
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+
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+ Please have a look at [this page](https://github.com/huggingface/diffusers/tree/main/docs) on how to verify changes made to the documentation locally.
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+
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+
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+ ### 6. Contribute a community pipeline
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+
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+ [Pipelines](https://huggingface.co/docs/diffusers/api/pipelines/overview) are usually the first point of contact between the Diffusers library and the user.
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+ Pipelines are examples of how to use Diffusers [models](https://huggingface.co/docs/diffusers/api/models/overview) and [schedulers](https://huggingface.co/docs/diffusers/api/schedulers/overview).
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+ We support two types of pipelines:
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+
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+ - Official Pipelines
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+ - Community Pipelines
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+
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+ Both official and community pipelines follow the same design and consist of the same type of components.
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+
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+ Official pipelines are tested and maintained by the core maintainers of Diffusers. Their code
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+ resides in [src/diffusers/pipelines](https://github.com/huggingface/diffusers/tree/main/src/diffusers/pipelines).
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+ In contrast, community pipelines are contributed and maintained purely by the **community** and are **not** tested.
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+ They reside in [examples/community](https://github.com/huggingface/diffusers/tree/main/examples/community) and while they can be accessed via the [PyPI diffusers package](https://pypi.org/project/diffusers/), their code is not part of the PyPI distribution.
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+
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+ The reason for the distinction is that the core maintainers of the Diffusers library cannot maintain and test all
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+ possible ways diffusion models can be used for inference, but some of them may be of interest to the community.
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+ Officially released diffusion pipelines,
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+ such as Stable Diffusion are added to the core src/diffusers/pipelines package which ensures
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+ high quality of maintenance, no backward-breaking code changes, and testing.
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+ More bleeding edge pipelines should be added as community pipelines. If usage for a community pipeline is high, the pipeline can be moved to the official pipelines upon request from the community. This is one of the ways we strive to be a community-driven library.
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+
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+ To add a community pipeline, one should add a <name-of-the-community>.py file to [examples/community](https://github.com/huggingface/diffusers/tree/main/examples/community) and adapt the [examples/community/README.md](https://github.com/huggingface/diffusers/tree/main/examples/community/README.md) to include an example of the new pipeline.
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+
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+ An example can be seen [here](https://github.com/huggingface/diffusers/pull/2400).
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+
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+ Community pipeline PRs are only checked at a superficial level and ideally they should be maintained by their original authors.
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+
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+ Contributing a community pipeline is a great way to understand how Diffusers models and schedulers work. Having contributed a community pipeline is usually the first stepping stone to contributing an official pipeline to the
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+ core package.
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+
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+ ### 7. Contribute to training examples
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+
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+ Diffusers examples are a collection of training scripts that reside in [examples](https://github.com/huggingface/diffusers/tree/main/examples).
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+
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+ We support two types of training examples:
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+
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+ - Official training examples
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+ - Research training examples
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+
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+ Research training examples are located in [examples/research_projects](https://github.com/huggingface/diffusers/tree/main/examples/research_projects) whereas official training examples include all folders under [examples](https://github.com/huggingface/diffusers/tree/main/examples) except the `research_projects` and `community` folders.
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+ The official training examples are maintained by the Diffusers' core maintainers whereas the research training examples are maintained by the community.
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+ This is because of the same reasons put forward in [6. Contribute a community pipeline](#6-contribute-a-community-pipeline) for official pipelines vs. community pipelines: It is not feasible for the core maintainers to maintain all possible training methods for diffusion models.
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+ If the Diffusers core maintainers and the community consider a certain training paradigm to be too experimental or not popular enough, the corresponding training code should be put in the `research_projects` folder and maintained by the author.
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+
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+ Both official training and research examples consist of a directory that contains one or more training scripts, a requirements.txt file, and a README.md file. In order for the user to make use of the
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+ training examples, it is required to clone the repository:
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+
251
+ ```bash
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+ git clone https://github.com/huggingface/diffusers
253
+ ```
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+
255
+ as well as to install all additional dependencies required for training:
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+
257
+ ```bash
258
+ pip install -r /examples/<your-example-folder>/requirements.txt
259
+ ```
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+
261
+ Therefore when adding an example, the `requirements.txt` file shall define all pip dependencies required for your training example so that once all those are installed, the user can run the example's training script. See, for example, the [DreamBooth `requirements.txt` file](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/requirements.txt).
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+
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+ Training examples of the Diffusers library should adhere to the following philosophy:
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+ - All the code necessary to run the examples should be found in a single Python file.
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+ - One should be able to run the example from the command line with `python <your-example>.py --args`.
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+ - Examples should be kept simple and serve as **an example** on how to use Diffusers for training. The purpose of example scripts is **not** to create state-of-the-art diffusion models, but rather to reproduce known training schemes without adding too much custom logic. As a byproduct of this point, our examples also strive to serve as good educational materials.
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+
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+ To contribute an example, it is highly recommended to look at already existing examples such as [dreambooth](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/train_dreambooth.py) to get an idea of how they should look like.
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+ We strongly advise contributors to make use of the [Accelerate library](https://github.com/huggingface/accelerate) as it's tightly integrated
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+ with Diffusers.
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+ Once an example script works, please make sure to add a comprehensive `README.md` that states how to use the example exactly. This README should include:
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+ - An example command on how to run the example script as shown [here e.g.](https://github.com/huggingface/diffusers/tree/main/examples/dreambooth#running-locally-with-pytorch).
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+ - A link to some training results (logs, models, ...) that show what the user can expect as shown [here e.g.](https://api.wandb.ai/report/patrickvonplaten/xm6cd5q5).
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+ - If you are adding a non-official/research training example, **please don't forget** to add a sentence that you are maintaining this training example which includes your git handle as shown [here](https://github.com/huggingface/diffusers/tree/main/examples/research_projects/intel_opts#diffusers-examples-with-intel-optimizations).
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+
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+ If you are contributing to the official training examples, please also make sure to add a test to [examples/test_examples.py](https://github.com/huggingface/diffusers/blob/main/examples/test_examples.py). This is not necessary for non-official training examples.
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+
278
+ ### 8. Fixing a "Good second issue"
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+
280
+ *Good second issues* are marked by the [Good second issue](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22Good+second+issue%22) label. Good second issues are
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+ usually more complicated to solve than [Good first issues](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22).
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+ The issue description usually gives less guidance on how to fix the issue and requires
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+ a decent understanding of the library by the interested contributor.
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+ If you are interested in tackling a good second issue, feel free to open a PR to fix it and link the PR to the issue. If you see that a PR has already been opened for this issue but did not get merged, have a look to understand why it wasn't merged and try to open an improved PR.
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+ Good second issues are usually more difficult to get merged compared to good first issues, so don't hesitate to ask for help from the core maintainers. If your PR is almost finished the core maintainers can also jump into your PR and commit to it in order to get it merged.
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+
287
+ ### 9. Adding pipelines, models, schedulers
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+
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+ Pipelines, models, and schedulers are the most important pieces of the Diffusers library.
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+ They provide easy access to state-of-the-art diffusion technologies and thus allow the community to
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+ build powerful generative AI applications.
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+
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+ By adding a new model, pipeline, or scheduler you might enable a new powerful use case for any of the user interfaces relying on Diffusers which can be of immense value for the whole generative AI ecosystem.
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+
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+ Diffusers has a couple of open feature requests for all three components - feel free to gloss over them
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+ if you don't know yet what specific component you would like to add:
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+ - [Model or pipeline](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22New+pipeline%2Fmodel%22)
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+ - [Scheduler](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22New+scheduler%22)
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+
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+ Before adding any of the three components, it is strongly recommended that you give the [Philosophy guide](https://github.com/huggingface/diffusers/blob/main/PHILOSOPHY.md) a read to better understand the design of any of the three components. Please be aware that
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+ we cannot merge model, scheduler, or pipeline additions that strongly diverge from our design philosophy
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+ as it will lead to API inconsistencies. If you fundamentally disagree with a design choice, please
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+ open a [Feedback issue](https://github.com/huggingface/diffusers/issues/new?assignees=&labels=&template=feedback.md&title=) instead so that it can be discussed whether a certain design
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+ pattern/design choice shall be changed everywhere in the library and whether we shall update our design philosophy. Consistency across the library is very important for us.
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+
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+ Please make sure to add links to the original codebase/paper to the PR and ideally also ping the
307
+ original author directly on the PR so that they can follow the progress and potentially help with questions.
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+
309
+ If you are unsure or stuck in the PR, don't hesitate to leave a message to ask for a first review or help.
310
+
311
+ ## How to write a good issue
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+
313
+ **The better your issue is written, the higher the chances that it will be quickly resolved.**
314
+
315
+ 1. Make sure that you've used the correct template for your issue. You can pick between *Bug Report*, *Feature Request*, *Feedback about API Design*, *New model/pipeline/scheduler addition*, *Forum*, or a blank issue. Make sure to pick the correct one when opening [a new issue](https://github.com/huggingface/diffusers/issues/new/choose).
316
+ 2. **Be precise**: Give your issue a fitting title. Try to formulate your issue description as simple as possible. The more precise you are when submitting an issue, the less time it takes to understand the issue and potentially solve it. Make sure to open an issue for one issue only and not for multiple issues. If you found multiple issues, simply open multiple issues. If your issue is a bug, try to be as precise as possible about what bug it is - you should not just write "Error in diffusers".
317
+ 3. **Reproducibility**: No reproducible code snippet == no solution. If you encounter a bug, maintainers **have to be able to reproduce** it. Make sure that you include a code snippet that can be copy-pasted into a Python interpreter to reproduce the issue. Make sure that your code snippet works, *i.e.* that there are no missing imports or missing links to images, ... Your issue should contain an error message **and** a code snippet that can be copy-pasted without any changes to reproduce the exact same error message. If your issue is using local model weights or local data that cannot be accessed by the reader, the issue cannot be solved. If you cannot share your data or model, try to make a dummy model or dummy data.
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+ 4. **Minimalistic**: Try to help the reader as much as you can to understand the issue as quickly as possible by staying as concise as possible. Remove all code / all information that is irrelevant to the issue. If you have found a bug, try to create the easiest code example you can to demonstrate your issue, do not just dump your whole workflow into the issue as soon as you have found a bug. E.g., if you train a model and get an error at some point during the training, you should first try to understand what part of the training code is responsible for the error and try to reproduce it with a couple of lines. Try to use dummy data instead of full datasets.
319
+ 5. Add links. If you are referring to a certain naming, method, or model make sure to provide a link so that the reader can better understand what you mean. If you are referring to a specific PR or issue, make sure to link it to your issue. Do not assume that the reader knows what you are talking about. The more links you add to your issue the better.
320
+ 6. Formatting. Make sure to nicely format your issue by formatting code into Python code syntax, and error messages into normal code syntax. See the [official GitHub formatting docs](https://docs.github.com/en/get-started/writing-on-github/getting-started-with-writing-and-formatting-on-github/basic-writing-and-formatting-syntax) for more information.
321
+ 7. Think of your issue not as a ticket to be solved, but rather as a beautiful entry to a well-written encyclopedia. Every added issue is a contribution to publicly available knowledge. By adding a nicely written issue you not only make it easier for maintainers to solve your issue, but you are helping the whole community to better understand a certain aspect of the library.
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+
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+ ## How to write a good PR
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+
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+ 1. Be a chameleon. Understand existing design patterns and syntax and make sure your code additions flow seamlessly into the existing code base. Pull requests that significantly diverge from existing design patterns or user interfaces will not be merged.
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+ 2. Be laser focused. A pull request should solve one problem and one problem only. Make sure to not fall into the trap of "also fixing another problem while we're adding it". It is much more difficult to review pull requests that solve multiple, unrelated problems at once.
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+ 3. If helpful, try to add a code snippet that displays an example of how your addition can be used.
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+ 4. The title of your pull request should be a summary of its contribution.
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+ 5. If your pull request addresses an issue, please mention the issue number in
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+ the pull request description to make sure they are linked (and people
331
+ consulting the issue know you are working on it);
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+ 6. To indicate a work in progress please prefix the title with `[WIP]`. These
333
+ are useful to avoid duplicated work, and to differentiate it from PRs ready
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+ to be merged;
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+ 7. Try to formulate and format your text as explained in [How to write a good issue](#how-to-write-a-good-issue).
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+ 8. Make sure existing tests pass;
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+ 9. Add high-coverage tests. No quality testing = no merge.
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+ - If you are adding new `@slow` tests, make sure they pass using
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+ `RUN_SLOW=1 python -m pytest tests/test_my_new_model.py`.
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+ CircleCI does not run the slow tests, but GitHub Actions does every night!
341
+ 10. All public methods must have informative docstrings that work nicely with markdown. See [`pipeline_latent_diffusion.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion.py) for an example.
342
+ 11. Due to the rapidly growing repository, it is important to make sure that no files that would significantly weigh down the repository are added. This includes images, videos, and other non-text files. We prefer to leverage a hf.co hosted `dataset` like
343
+ [`hf-internal-testing`](https://huggingface.co/hf-internal-testing) or [huggingface/documentation-images](https://huggingface.co/datasets/huggingface/documentation-images) to place these files.
344
+ If an external contribution, feel free to add the images to your PR and ask a Hugging Face member to migrate your images
345
+ to this dataset.
346
+
347
+ ## How to open a PR
348
+
349
+ Before writing code, we strongly advise you to search through the existing PRs or
350
+ issues to make sure that nobody is already working on the same thing. If you are
351
+ unsure, it is always a good idea to open an issue to get some feedback.
352
+
353
+ You will need basic `git` proficiency to be able to contribute to
354
+ 🧨 Diffusers. `git` is not the easiest tool to use but it has the greatest
355
+ manual. Type `git --help` in a shell and enjoy. If you prefer books, [Pro
356
+ Git](https://git-scm.com/book/en/v2) is a very good reference.
357
+
358
+ Follow these steps to start contributing ([supported Python versions](https://github.com/huggingface/diffusers/blob/42f25d601a910dceadaee6c44345896b4cfa9928/setup.py#L270)):
359
+
360
+ 1. Fork the [repository](https://github.com/huggingface/diffusers) by
361
+ clicking on the 'Fork' button on the repository's page. This creates a copy of the code
362
+ under your GitHub user account.
363
+
364
+ 2. Clone your fork to your local disk, and add the base repository as a remote:
365
+
366
+ ```bash
367
+ $ git clone git@github.com:<your GitHub handle>/diffusers.git
368
+ $ cd diffusers
369
+ $ git remote add upstream https://github.com/huggingface/diffusers.git
370
+ ```
371
+
372
+ 3. Create a new branch to hold your development changes:
373
+
374
+ ```bash
375
+ $ git checkout -b a-descriptive-name-for-my-changes
376
+ ```
377
+
378
+ **Do not** work on the `main` branch.
379
+
380
+ 4. Set up a development environment by running the following command in a virtual environment:
381
+
382
+ ```bash
383
+ $ pip install -e ".[dev]"
384
+ ```
385
+
386
+ If you have already cloned the repo, you might need to `git pull` to get the most recent changes in the
387
+ library.
388
+
389
+ 5. Develop the features on your branch.
390
+
391
+ As you work on the features, you should make sure that the test suite
392
+ passes. You should run the tests impacted by your changes like this:
393
+
394
+ ```bash
395
+ $ pytest tests/<TEST_TO_RUN>.py
396
+ ```
397
+
398
+ Before you run the tests, please make sure you install the dependencies required for testing. You can do so
399
+ with this command:
400
+
401
+ ```bash
402
+ $ pip install -e ".[test]"
403
+ ```
404
+
405
+ You can also run the full test suite with the following command, but it takes
406
+ a beefy machine to produce a result in a decent amount of time now that
407
+ Diffusers has grown a lot. Here is the command for it:
408
+
409
+ ```bash
410
+ $ make test
411
+ ```
412
+
413
+ 🧨 Diffusers relies on `ruff` and `isort` to format its source code
414
+ consistently. After you make changes, apply automatic style corrections and code verifications
415
+ that can't be automated in one go with:
416
+
417
+ ```bash
418
+ $ make style
419
+ ```
420
+
421
+ 🧨 Diffusers also uses `ruff` and a few custom scripts to check for coding mistakes. Quality
422
+ control runs in CI, however, you can also run the same checks with:
423
+
424
+ ```bash
425
+ $ make quality
426
+ ```
427
+
428
+ Once you're happy with your changes, add changed files using `git add` and
429
+ make a commit with `git commit` to record your changes locally:
430
+
431
+ ```bash
432
+ $ git add modified_file.py
433
+ $ git commit -m "A descriptive message about your changes."
434
+ ```
435
+
436
+ It is a good idea to sync your copy of the code with the original
437
+ repository regularly. This way you can quickly account for changes:
438
+
439
+ ```bash
440
+ $ git pull upstream main
441
+ ```
442
+
443
+ Push the changes to your account using:
444
+
445
+ ```bash
446
+ $ git push -u origin a-descriptive-name-for-my-changes
447
+ ```
448
+
449
+ 6. Once you are satisfied, go to the
450
+ webpage of your fork on GitHub. Click on 'Pull request' to send your changes
451
+ to the project maintainers for review.
452
+
453
+ 7. It's ok if maintainers ask you for changes. It happens to core contributors
454
+ too! So everyone can see the changes in the Pull request, work in your local
455
+ branch and push the changes to your fork. They will automatically appear in
456
+ the pull request.
457
+
458
+ ### Tests
459
+
460
+ An extensive test suite is included to test the library behavior and several examples. Library tests can be found in
461
+ the [tests folder](https://github.com/huggingface/diffusers/tree/main/tests).
462
+
463
+ We like `pytest` and `pytest-xdist` because it's faster. From the root of the
464
+ repository, here's how to run tests with `pytest` for the library:
465
+
466
+ ```bash
467
+ $ python -m pytest -n auto --dist=loadfile -s -v ./tests/
468
+ ```
469
+
470
+ In fact, that's how `make test` is implemented!
471
+
472
+ You can specify a smaller set of tests in order to test only the feature
473
+ you're working on.
474
+
475
+ By default, slow tests are skipped. Set the `RUN_SLOW` environment variable to
476
+ `yes` to run them. This will download many gigabytes of models — make sure you
477
+ have enough disk space and a good Internet connection, or a lot of patience!
478
+
479
+ ```bash
480
+ $ RUN_SLOW=yes python -m pytest -n auto --dist=loadfile -s -v ./tests/
481
+ ```
482
+
483
+ `unittest` is fully supported, here's how to run tests with it:
484
+
485
+ ```bash
486
+ $ python -m unittest discover -s tests -t . -v
487
+ $ python -m unittest discover -s examples -t examples -v
488
+ ```
489
+
490
+ ### Syncing forked main with upstream (HuggingFace) main
491
+
492
+ To avoid pinging the upstream repository which adds reference notes to each upstream PR and sends unnecessary notifications to the developers involved in these PRs,
493
+ when syncing the main branch of a forked repository, please, follow these steps:
494
+ 1. When possible, avoid syncing with the upstream using a branch and PR on the forked repository. Instead, merge directly into the forked main.
495
+ 2. If a PR is absolutely necessary, use the following steps after checking out your branch:
496
+ ```bash
497
+ $ git checkout -b your-branch-for-syncing
498
+ $ git pull --squash --no-commit upstream main
499
+ $ git commit -m '<your message without GitHub references>'
500
+ $ git push --set-upstream origin your-branch-for-syncing
501
+ ```
502
+
503
+ ### Style guide
504
+
505
+ For documentation strings, 🧨 Diffusers follows the [Google style](https://google.github.io/styleguide/pyguide.html).
UltraEdit/diffusers/LICENSE ADDED
@@ -0,0 +1,201 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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UltraEdit/diffusers/MANIFEST.in ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ include LICENSE
2
+ include src/diffusers/utils/model_card_template.md
UltraEdit/diffusers/Makefile ADDED
@@ -0,0 +1,96 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ .PHONY: deps_table_update modified_only_fixup extra_style_checks quality style fixup fix-copies test test-examples
2
+
3
+ # make sure to test the local checkout in scripts and not the pre-installed one (don't use quotes!)
4
+ export PYTHONPATH = src
5
+
6
+ check_dirs := examples scripts src tests utils benchmarks
7
+
8
+ modified_only_fixup:
9
+ $(eval modified_py_files := $(shell python utils/get_modified_files.py $(check_dirs)))
10
+ @if test -n "$(modified_py_files)"; then \
11
+ echo "Checking/fixing $(modified_py_files)"; \
12
+ ruff check $(modified_py_files) --fix; \
13
+ ruff format $(modified_py_files);\
14
+ else \
15
+ echo "No library .py files were modified"; \
16
+ fi
17
+
18
+ # Update src/diffusers/dependency_versions_table.py
19
+
20
+ deps_table_update:
21
+ @python setup.py deps_table_update
22
+
23
+ deps_table_check_updated:
24
+ @md5sum src/diffusers/dependency_versions_table.py > md5sum.saved
25
+ @python setup.py deps_table_update
26
+ @md5sum -c --quiet md5sum.saved || (printf "\nError: the version dependency table is outdated.\nPlease run 'make fixup' or 'make style' and commit the changes.\n\n" && exit 1)
27
+ @rm md5sum.saved
28
+
29
+ # autogenerating code
30
+
31
+ autogenerate_code: deps_table_update
32
+
33
+ # Check that the repo is in a good state
34
+
35
+ repo-consistency:
36
+ python utils/check_dummies.py
37
+ python utils/check_repo.py
38
+ python utils/check_inits.py
39
+
40
+ # this target runs checks on all files
41
+
42
+ quality:
43
+ ruff check $(check_dirs) setup.py
44
+ ruff format --check $(check_dirs) setup.py
45
+ doc-builder style src/diffusers docs/source --max_len 119 --check_only
46
+ python utils/check_doc_toc.py
47
+
48
+ # Format source code automatically and check is there are any problems left that need manual fixing
49
+
50
+ extra_style_checks:
51
+ python utils/custom_init_isort.py
52
+ python utils/check_doc_toc.py --fix_and_overwrite
53
+
54
+ # this target runs checks on all files and potentially modifies some of them
55
+
56
+ style:
57
+ ruff check $(check_dirs) setup.py --fix
58
+ ruff format $(check_dirs) setup.py
59
+ doc-builder style src/diffusers docs/source --max_len 119
60
+ ${MAKE} autogenerate_code
61
+ ${MAKE} extra_style_checks
62
+
63
+ # Super fast fix and check target that only works on relevant modified files since the branch was made
64
+
65
+ fixup: modified_only_fixup extra_style_checks autogenerate_code repo-consistency
66
+
67
+ # Make marked copies of snippets of codes conform to the original
68
+
69
+ fix-copies:
70
+ python utils/check_copies.py --fix_and_overwrite
71
+ python utils/check_dummies.py --fix_and_overwrite
72
+
73
+ # Run tests for the library
74
+
75
+ test:
76
+ python -m pytest -n auto --dist=loadfile -s -v ./tests/
77
+
78
+ # Run tests for examples
79
+
80
+ test-examples:
81
+ python -m pytest -n auto --dist=loadfile -s -v ./examples/
82
+
83
+
84
+ # Release stuff
85
+
86
+ pre-release:
87
+ python utils/release.py
88
+
89
+ pre-patch:
90
+ python utils/release.py --patch
91
+
92
+ post-release:
93
+ python utils/release.py --post_release
94
+
95
+ post-patch:
96
+ python utils/release.py --post_release --patch
UltraEdit/diffusers/PHILOSOPHY.md ADDED
@@ -0,0 +1,110 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <!--Copyright 2024 The HuggingFace Team. All rights reserved.
2
+
3
+ Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
4
+ the License. You may obtain a copy of the License at
5
+
6
+ http://www.apache.org/licenses/LICENSE-2.0
7
+
8
+ Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
9
+ an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
10
+ specific language governing permissions and limitations under the License.
11
+ -->
12
+
13
+ # Philosophy
14
+
15
+ 🧨 Diffusers provides **state-of-the-art** pretrained diffusion models across multiple modalities.
16
+ Its purpose is to serve as a **modular toolbox** for both inference and training.
17
+
18
+ We aim at building a library that stands the test of time and therefore take API design very seriously.
19
+
20
+ In a nutshell, Diffusers is built to be a natural extension of PyTorch. Therefore, most of our design choices are based on [PyTorch's Design Principles](https://pytorch.org/docs/stable/community/design.html#pytorch-design-philosophy). Let's go over the most important ones:
21
+
22
+ ## Usability over Performance
23
+
24
+ - While Diffusers has many built-in performance-enhancing features (see [Memory and Speed](https://huggingface.co/docs/diffusers/optimization/fp16)), models are always loaded with the highest precision and lowest optimization. Therefore, by default diffusion pipelines are always instantiated on CPU with float32 precision if not otherwise defined by the user. This ensures usability across different platforms and accelerators and means that no complex installations are required to run the library.
25
+ - Diffusers aims to be a **light-weight** package and therefore has very few required dependencies, but many soft dependencies that can improve performance (such as `accelerate`, `safetensors`, `onnx`, etc...). We strive to keep the library as lightweight as possible so that it can be added without much concern as a dependency on other packages.
26
+ - Diffusers prefers simple, self-explainable code over condensed, magic code. This means that short-hand code syntaxes such as lambda functions, and advanced PyTorch operators are often not desired.
27
+
28
+ ## Simple over easy
29
+
30
+ As PyTorch states, **explicit is better than implicit** and **simple is better than complex**. This design philosophy is reflected in multiple parts of the library:
31
+ - We follow PyTorch's API with methods like [`DiffusionPipeline.to`](https://huggingface.co/docs/diffusers/main/en/api/diffusion_pipeline#diffusers.DiffusionPipeline.to) to let the user handle device management.
32
+ - Raising concise error messages is preferred to silently correct erroneous input. Diffusers aims at teaching the user, rather than making the library as easy to use as possible.
33
+ - Complex model vs. scheduler logic is exposed instead of magically handled inside. Schedulers/Samplers are separated from diffusion models with minimal dependencies on each other. This forces the user to write the unrolled denoising loop. However, the separation allows for easier debugging and gives the user more control over adapting the denoising process or switching out diffusion models or schedulers.
34
+ - Separately trained components of the diffusion pipeline, *e.g.* the text encoder, the UNet, and the variational autoencoder, each has their own model class. This forces the user to handle the interaction between the different model components, and the serialization format separates the model components into different files. However, this allows for easier debugging and customization. DreamBooth or Textual Inversion training
35
+ is very simple thanks to Diffusers' ability to separate single components of the diffusion pipeline.
36
+
37
+ ## Tweakable, contributor-friendly over abstraction
38
+
39
+ For large parts of the library, Diffusers adopts an important design principle of the [Transformers library](https://github.com/huggingface/transformers), which is to prefer copy-pasted code over hasty abstractions. This design principle is very opinionated and stands in stark contrast to popular design principles such as [Don't repeat yourself (DRY)](https://en.wikipedia.org/wiki/Don%27t_repeat_yourself).
40
+ In short, just like Transformers does for modeling files, Diffusers prefers to keep an extremely low level of abstraction and very self-contained code for pipelines and schedulers.
41
+ Functions, long code blocks, and even classes can be copied across multiple files which at first can look like a bad, sloppy design choice that makes the library unmaintainable.
42
+ **However**, this design has proven to be extremely successful for Transformers and makes a lot of sense for community-driven, open-source machine learning libraries because:
43
+ - Machine Learning is an extremely fast-moving field in which paradigms, model architectures, and algorithms are changing rapidly, which therefore makes it very difficult to define long-lasting code abstractions.
44
+ - Machine Learning practitioners like to be able to quickly tweak existing code for ideation and research and therefore prefer self-contained code over one that contains many abstractions.
45
+ - Open-source libraries rely on community contributions and therefore must build a library that is easy to contribute to. The more abstract the code, the more dependencies, the harder to read, and the harder to contribute to. Contributors simply stop contributing to very abstract libraries out of fear of breaking vital functionality. If contributing to a library cannot break other fundamental code, not only is it more inviting for potential new contributors, but it is also easier to review and contribute to multiple parts in parallel.
46
+
47
+ At Hugging Face, we call this design the **single-file policy** which means that almost all of the code of a certain class should be written in a single, self-contained file. To read more about the philosophy, you can have a look
48
+ at [this blog post](https://huggingface.co/blog/transformers-design-philosophy).
49
+
50
+ In Diffusers, we follow this philosophy for both pipelines and schedulers, but only partly for diffusion models. The reason we don't follow this design fully for diffusion models is because almost all diffusion pipelines, such
51
+ as [DDPM](https://huggingface.co/docs/diffusers/api/pipelines/ddpm), [Stable Diffusion](https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion/overview#stable-diffusion-pipelines), [unCLIP (DALL·E 2)](https://huggingface.co/docs/diffusers/api/pipelines/unclip) and [Imagen](https://imagen.research.google/) all rely on the same diffusion model, the [UNet](https://huggingface.co/docs/diffusers/api/models/unet2d-cond).
52
+
53
+ Great, now you should have generally understood why 🧨 Diffusers is designed the way it is 🤗.
54
+ We try to apply these design principles consistently across the library. Nevertheless, there are some minor exceptions to the philosophy or some unlucky design choices. If you have feedback regarding the design, we would ❤️ to hear it [directly on GitHub](https://github.com/huggingface/diffusers/issues/new?assignees=&labels=&template=feedback.md&title=).
55
+
56
+ ## Design Philosophy in Details
57
+
58
+ Now, let's look a bit into the nitty-gritty details of the design philosophy. Diffusers essentially consists of three major classes: [pipelines](https://github.com/huggingface/diffusers/tree/main/src/diffusers/pipelines), [models](https://github.com/huggingface/diffusers/tree/main/src/diffusers/models), and [schedulers](https://github.com/huggingface/diffusers/tree/main/src/diffusers/schedulers).
59
+ Let's walk through more detailed design decisions for each class.
60
+
61
+ ### Pipelines
62
+
63
+ Pipelines are designed to be easy to use (therefore do not follow [*Simple over easy*](#simple-over-easy) 100%), are not feature complete, and should loosely be seen as examples of how to use [models](#models) and [schedulers](#schedulers) for inference.
64
+
65
+ The following design principles are followed:
66
+ - Pipelines follow the single-file policy. All pipelines can be found in individual directories under src/diffusers/pipelines. One pipeline folder corresponds to one diffusion paper/project/release. Multiple pipeline files can be gathered in one pipeline folder, as it’s done for [`src/diffusers/pipelines/stable-diffusion`](https://github.com/huggingface/diffusers/tree/main/src/diffusers/pipelines/stable_diffusion). If pipelines share similar functionality, one can make use of the [#Copied from mechanism](https://github.com/huggingface/diffusers/blob/125d783076e5bd9785beb05367a2d2566843a271/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_img2img.py#L251).
67
+ - Pipelines all inherit from [`DiffusionPipeline`].
68
+ - Every pipeline consists of different model and scheduler components, that are documented in the [`model_index.json` file](https://huggingface.co/runwayml/stable-diffusion-v1-5/blob/main/model_index.json), are accessible under the same name as attributes of the pipeline and can be shared between pipelines with [`DiffusionPipeline.components`](https://huggingface.co/docs/diffusers/main/en/api/diffusion_pipeline#diffusers.DiffusionPipeline.components) function.
69
+ - Every pipeline should be loadable via the [`DiffusionPipeline.from_pretrained`](https://huggingface.co/docs/diffusers/main/en/api/diffusion_pipeline#diffusers.DiffusionPipeline.from_pretrained) function.
70
+ - Pipelines should be used **only** for inference.
71
+ - Pipelines should be very readable, self-explanatory, and easy to tweak.
72
+ - Pipelines should be designed to build on top of each other and be easy to integrate into higher-level APIs.
73
+ - Pipelines are **not** intended to be feature-complete user interfaces. For future complete user interfaces one should rather have a look at [InvokeAI](https://github.com/invoke-ai/InvokeAI), [Diffuzers](https://github.com/abhishekkrthakur/diffuzers), and [lama-cleaner](https://github.com/Sanster/lama-cleaner).
74
+ - Every pipeline should have one and only one way to run it via a `__call__` method. The naming of the `__call__` arguments should be shared across all pipelines.
75
+ - Pipelines should be named after the task they are intended to solve.
76
+ - In almost all cases, novel diffusion pipelines shall be implemented in a new pipeline folder/file.
77
+
78
+ ### Models
79
+
80
+ Models are designed as configurable toolboxes that are natural extensions of [PyTorch's Module class](https://pytorch.org/docs/stable/generated/torch.nn.Module.html). They only partly follow the **single-file policy**.
81
+
82
+ The following design principles are followed:
83
+ - Models correspond to **a type of model architecture**. *E.g.* the [`UNet2DConditionModel`] class is used for all UNet variations that expect 2D image inputs and are conditioned on some context.
84
+ - All models can be found in [`src/diffusers/models`](https://github.com/huggingface/diffusers/tree/main/src/diffusers/models) and every model architecture shall be defined in its file, e.g. [`unet_2d_condition.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/unet_2d_condition.py), [`transformer_2d.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/transformer_2d.py), etc...
85
+ - Models **do not** follow the single-file policy and should make use of smaller model building blocks, such as [`attention.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention.py), [`resnet.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/resnet.py), [`embeddings.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/embeddings.py), etc... **Note**: This is in stark contrast to Transformers' modeling files and shows that models do not really follow the single-file policy.
86
+ - Models intend to expose complexity, just like PyTorch's `Module` class, and give clear error messages.
87
+ - Models all inherit from `ModelMixin` and `ConfigMixin`.
88
+ - Models can be optimized for performance when it doesn’t demand major code changes, keep backward compatibility, and give significant memory or compute gain.
89
+ - Models should by default have the highest precision and lowest performance setting.
90
+ - To integrate new model checkpoints whose general architecture can be classified as an architecture that already exists in Diffusers, the existing model architecture shall be adapted to make it work with the new checkpoint. One should only create a new file if the model architecture is fundamentally different.
91
+ - Models should be designed to be easily extendable to future changes. This can be achieved by limiting public function arguments, configuration arguments, and "foreseeing" future changes, *e.g.* it is usually better to add `string` "...type" arguments that can easily be extended to new future types instead of boolean `is_..._type` arguments. Only the minimum amount of changes shall be made to existing architectures to make a new model checkpoint work.
92
+ - The model design is a difficult trade-off between keeping code readable and concise and supporting many model checkpoints. For most parts of the modeling code, classes shall be adapted for new model checkpoints, while there are some exceptions where it is preferred to add new classes to make sure the code is kept concise and
93
+ readable long-term, such as [UNet blocks](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/unet_2d_blocks.py) and [Attention processors](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
94
+
95
+ ### Schedulers
96
+
97
+ Schedulers are responsible to guide the denoising process for inference as well as to define a noise schedule for training. They are designed as individual classes with loadable configuration files and strongly follow the **single-file policy**.
98
+
99
+ The following design principles are followed:
100
+ - All schedulers are found in [`src/diffusers/schedulers`](https://github.com/huggingface/diffusers/tree/main/src/diffusers/schedulers).
101
+ - Schedulers are **not** allowed to import from large utils files and shall be kept very self-contained.
102
+ - One scheduler Python file corresponds to one scheduler algorithm (as might be defined in a paper).
103
+ - If schedulers share similar functionalities, we can make use of the `#Copied from` mechanism.
104
+ - Schedulers all inherit from `SchedulerMixin` and `ConfigMixin`.
105
+ - Schedulers can be easily swapped out with the [`ConfigMixin.from_config`](https://huggingface.co/docs/diffusers/main/en/api/configuration#diffusers.ConfigMixin.from_config) method as explained in detail [here](./docs/source/en/using-diffusers/schedulers.md).
106
+ - Every scheduler has to have a `set_num_inference_steps`, and a `step` function. `set_num_inference_steps(...)` has to be called before every denoising process, *i.e.* before `step(...)` is called.
107
+ - Every scheduler exposes the timesteps to be "looped over" via a `timesteps` attribute, which is an array of timesteps the model will be called upon.
108
+ - The `step(...)` function takes a predicted model output and the "current" sample (x_t) and returns the "previous", slightly more denoised sample (x_t-1).
109
+ - Given the complexity of diffusion schedulers, the `step` function does not expose all the complexity and can be a bit of a "black box".
110
+ - In almost all cases, novel schedulers shall be implemented in a new scheduling file.
UltraEdit/diffusers/README.md ADDED
@@ -0,0 +1,248 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <!---
2
+ Copyright 2022 - The HuggingFace Team. All rights reserved.
3
+
4
+ Licensed under the Apache License, Version 2.0 (the "License");
5
+ you may not use this file except in compliance with the License.
6
+ You may obtain a copy of the License at
7
+
8
+ http://www.apache.org/licenses/LICENSE-2.0
9
+
10
+ Unless required by applicable law or agreed to in writing, software
11
+ distributed under the License is distributed on an "AS IS" BASIS,
12
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
+ See the License for the specific language governing permissions and
14
+ limitations under the License.
15
+ -->
16
+
17
+ <p align="center">
18
+ <br>
19
+ <img src="https://raw.githubusercontent.com/huggingface/diffusers/main/docs/source/en/imgs/diffusers_library.jpg" width="400"/>
20
+ <br>
21
+ <p>
22
+ <p align="center">
23
+ <a href="https://github.com/huggingface/diffusers/blob/main/LICENSE">
24
+ <img alt="GitHub" src="https://img.shields.io/github/license/huggingface/datasets.svg?color=blue">
25
+ </a>
26
+ <a href="https://github.com/huggingface/diffusers/releases">
27
+ <img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/diffusers.svg">
28
+ </a>
29
+ <a href="https://pepy.tech/project/diffusers">
30
+ <img alt="GitHub release" src="https://static.pepy.tech/badge/diffusers/month">
31
+ </a>
32
+ <a href="CODE_OF_CONDUCT.md">
33
+ <img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-2.1-4baaaa.svg">
34
+ </a>
35
+ <a href="https://twitter.com/diffuserslib">
36
+ <img alt="X account" src="https://img.shields.io/twitter/url/https/twitter.com/diffuserslib.svg?style=social&label=Follow%20%40diffuserslib">
37
+ </a>
38
+ </p>
39
+
40
+ 🤗 Diffusers is the go-to library for state-of-the-art pretrained diffusion models for generating images, audio, and even 3D structures of molecules. Whether you're looking for a simple inference solution or training your own diffusion models, 🤗 Diffusers is a modular toolbox that supports both. Our library is designed with a focus on [usability over performance](https://huggingface.co/docs/diffusers/conceptual/philosophy#usability-over-performance), [simple over easy](https://huggingface.co/docs/diffusers/conceptual/philosophy#simple-over-easy), and [customizability over abstractions](https://huggingface.co/docs/diffusers/conceptual/philosophy#tweakable-contributorfriendly-over-abstraction).
41
+
42
+ 🤗 Diffusers offers three core components:
43
+
44
+ - State-of-the-art [diffusion pipelines](https://huggingface.co/docs/diffusers/api/pipelines/overview) that can be run in inference with just a few lines of code.
45
+ - Interchangeable noise [schedulers](https://huggingface.co/docs/diffusers/api/schedulers/overview) for different diffusion speeds and output quality.
46
+ - Pretrained [models](https://huggingface.co/docs/diffusers/api/models/overview) that can be used as building blocks, and combined with schedulers, for creating your own end-to-end diffusion systems.
47
+
48
+ ## Installation
49
+
50
+ We recommend installing 🤗 Diffusers in a virtual environment from PyPI or Conda. For more details about installing [PyTorch](https://pytorch.org/get-started/locally/) and [Flax](https://flax.readthedocs.io/en/latest/#installation), please refer to their official documentation.
51
+
52
+ ### PyTorch
53
+
54
+ With `pip` (official package):
55
+
56
+ ```bash
57
+ pip install --upgrade diffusers[torch]
58
+ ```
59
+
60
+ With `conda` (maintained by the community):
61
+
62
+ ```sh
63
+ conda install -c conda-forge diffusers
64
+ ```
65
+
66
+ ### Flax
67
+
68
+ With `pip` (official package):
69
+
70
+ ```bash
71
+ pip install --upgrade diffusers[flax]
72
+ ```
73
+
74
+ ### Apple Silicon (M1/M2) support
75
+
76
+ Please refer to the [How to use Stable Diffusion in Apple Silicon](https://huggingface.co/docs/diffusers/optimization/mps) guide.
77
+
78
+ ## Quickstart
79
+
80
+ Generating outputs is super easy with 🤗 Diffusers. To generate an image from text, use the `from_pretrained` method to load any pretrained diffusion model (browse the [Hub](https://huggingface.co/models?library=diffusers&sort=downloads) for 25.000+ checkpoints):
81
+
82
+ ```python
83
+ from diffusers import DiffusionPipeline
84
+ import torch
85
+
86
+ pipeline = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16)
87
+ pipeline.to("cuda")
88
+ pipeline("An image of a squirrel in Picasso style").images[0]
89
+ ```
90
+
91
+ You can also dig into the models and schedulers toolbox to build your own diffusion system:
92
+
93
+ ```python
94
+ from diffusers import DDPMScheduler, UNet2DModel
95
+ from PIL import Image
96
+ import torch
97
+
98
+ scheduler = DDPMScheduler.from_pretrained("google/ddpm-cat-256")
99
+ model = UNet2DModel.from_pretrained("google/ddpm-cat-256").to("cuda")
100
+ scheduler.set_timesteps(50)
101
+
102
+ sample_size = model.config.sample_size
103
+ noise = torch.randn((1, 3, sample_size, sample_size), device="cuda")
104
+ input = noise
105
+
106
+ for t in scheduler.timesteps:
107
+ with torch.no_grad():
108
+ noisy_residual = model(input, t).sample
109
+ prev_noisy_sample = scheduler.step(noisy_residual, t, input).prev_sample
110
+ input = prev_noisy_sample
111
+
112
+ image = (input / 2 + 0.5).clamp(0, 1)
113
+ image = image.cpu().permute(0, 2, 3, 1).numpy()[0]
114
+ image = Image.fromarray((image * 255).round().astype("uint8"))
115
+ image
116
+ ```
117
+
118
+ Check out the [Quickstart](https://huggingface.co/docs/diffusers/quicktour) to launch your diffusion journey today!
119
+
120
+ ## How to navigate the documentation
121
+
122
+ | **Documentation** | **What can I learn?** |
123
+ |---------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
124
+ | [Tutorial](https://huggingface.co/docs/diffusers/tutorials/tutorial_overview) | A basic crash course for learning how to use the library's most important features like using models and schedulers to build your own diffusion system, and training your own diffusion model. |
125
+ | [Loading](https://huggingface.co/docs/diffusers/using-diffusers/loading_overview) | Guides for how to load and configure all the components (pipelines, models, and schedulers) of the library, as well as how to use different schedulers. |
126
+ | [Pipelines for inference](https://huggingface.co/docs/diffusers/using-diffusers/pipeline_overview) | Guides for how to use pipelines for different inference tasks, batched generation, controlling generated outputs and randomness, and how to contribute a pipeline to the library. |
127
+ | [Optimization](https://huggingface.co/docs/diffusers/optimization/opt_overview) | Guides for how to optimize your diffusion model to run faster and consume less memory. |
128
+ | [Training](https://huggingface.co/docs/diffusers/training/overview) | Guides for how to train a diffusion model for different tasks with different training techniques. |
129
+ ## Contribution
130
+
131
+ We ❤️ contributions from the open-source community!
132
+ If you want to contribute to this library, please check out our [Contribution guide](https://github.com/huggingface/diffusers/blob/main/CONTRIBUTING.md).
133
+ You can look out for [issues](https://github.com/huggingface/diffusers/issues) you'd like to tackle to contribute to the library.
134
+ - See [Good first issues](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22) for general opportunities to contribute
135
+ - See [New model/pipeline](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22New+pipeline%2Fmodel%22) to contribute exciting new diffusion models / diffusion pipelines
136
+ - See [New scheduler](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22New+scheduler%22)
137
+
138
+ Also, say 👋 in our public Discord channel <a href="https://discord.gg/G7tWnz98XR"><img alt="Join us on Discord" src="https://img.shields.io/discord/823813159592001537?color=5865F2&logo=discord&logoColor=white"></a>. We discuss the hottest trends about diffusion models, help each other with contributions, personal projects or just hang out ☕.
139
+
140
+
141
+ ## Popular Tasks & Pipelines
142
+
143
+ <table>
144
+ <tr>
145
+ <th>Task</th>
146
+ <th>Pipeline</th>
147
+ <th>🤗 Hub</th>
148
+ </tr>
149
+ <tr style="border-top: 2px solid black">
150
+ <td>Unconditional Image Generation</td>
151
+ <td><a href="https://huggingface.co/docs/diffusers/api/pipelines/ddpm"> DDPM </a></td>
152
+ <td><a href="https://huggingface.co/google/ddpm-ema-church-256"> google/ddpm-ema-church-256 </a></td>
153
+ </tr>
154
+ <tr style="border-top: 2px solid black">
155
+ <td>Text-to-Image</td>
156
+ <td><a href="https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion/text2img">Stable Diffusion Text-to-Image</a></td>
157
+ <td><a href="https://huggingface.co/runwayml/stable-diffusion-v1-5"> runwayml/stable-diffusion-v1-5 </a></td>
158
+ </tr>
159
+ <tr>
160
+ <td>Text-to-Image</td>
161
+ <td><a href="https://huggingface.co/docs/diffusers/api/pipelines/unclip">unCLIP</a></td>
162
+ <td><a href="https://huggingface.co/kakaobrain/karlo-v1-alpha"> kakaobrain/karlo-v1-alpha </a></td>
163
+ </tr>
164
+ <tr>
165
+ <td>Text-to-Image</td>
166
+ <td><a href="https://huggingface.co/docs/diffusers/api/pipelines/deepfloyd_if">DeepFloyd IF</a></td>
167
+ <td><a href="https://huggingface.co/DeepFloyd/IF-I-XL-v1.0"> DeepFloyd/IF-I-XL-v1.0 </a></td>
168
+ </tr>
169
+ <tr>
170
+ <td>Text-to-Image</td>
171
+ <td><a href="https://huggingface.co/docs/diffusers/api/pipelines/kandinsky">Kandinsky</a></td>
172
+ <td><a href="https://huggingface.co/kandinsky-community/kandinsky-2-2-decoder"> kandinsky-community/kandinsky-2-2-decoder </a></td>
173
+ </tr>
174
+ <tr style="border-top: 2px solid black">
175
+ <td>Text-guided Image-to-Image</td>
176
+ <td><a href="https://huggingface.co/docs/diffusers/api/pipelines/controlnet">ControlNet</a></td>
177
+ <td><a href="https://huggingface.co/lllyasviel/sd-controlnet-canny"> lllyasviel/sd-controlnet-canny </a></td>
178
+ </tr>
179
+ <tr>
180
+ <td>Text-guided Image-to-Image</td>
181
+ <td><a href="https://huggingface.co/docs/diffusers/api/pipelines/pix2pix">InstructPix2Pix</a></td>
182
+ <td><a href="https://huggingface.co/timbrooks/instruct-pix2pix"> timbrooks/instruct-pix2pix </a></td>
183
+ </tr>
184
+ <tr>
185
+ <td>Text-guided Image-to-Image</td>
186
+ <td><a href="https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion/img2img">Stable Diffusion Image-to-Image</a></td>
187
+ <td><a href="https://huggingface.co/runwayml/stable-diffusion-v1-5"> runwayml/stable-diffusion-v1-5 </a></td>
188
+ </tr>
189
+ <tr style="border-top: 2px solid black">
190
+ <td>Text-guided Image Inpainting</td>
191
+ <td><a href="https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion/inpaint">Stable Diffusion Inpainting</a></td>
192
+ <td><a href="https://huggingface.co/runwayml/stable-diffusion-inpainting"> runwayml/stable-diffusion-inpainting </a></td>
193
+ </tr>
194
+ <tr style="border-top: 2px solid black">
195
+ <td>Image Variation</td>
196
+ <td><a href="https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion/image_variation">Stable Diffusion Image Variation</a></td>
197
+ <td><a href="https://huggingface.co/lambdalabs/sd-image-variations-diffusers"> lambdalabs/sd-image-variations-diffusers </a></td>
198
+ </tr>
199
+ <tr style="border-top: 2px solid black">
200
+ <td>Super Resolution</td>
201
+ <td><a href="https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion/upscale">Stable Diffusion Upscale</a></td>
202
+ <td><a href="https://huggingface.co/stabilityai/stable-diffusion-x4-upscaler"> stabilityai/stable-diffusion-x4-upscaler </a></td>
203
+ </tr>
204
+ <tr>
205
+ <td>Super Resolution</td>
206
+ <td><a href="https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion/latent_upscale">Stable Diffusion Latent Upscale</a></td>
207
+ <td><a href="https://huggingface.co/stabilityai/sd-x2-latent-upscaler"> stabilityai/sd-x2-latent-upscaler </a></td>
208
+ </tr>
209
+ </table>
210
+
211
+ ## Popular libraries using 🧨 Diffusers
212
+
213
+ - https://github.com/microsoft/TaskMatrix
214
+ - https://github.com/invoke-ai/InvokeAI
215
+ - https://github.com/apple/ml-stable-diffusion
216
+ - https://github.com/Sanster/lama-cleaner
217
+ - https://github.com/IDEA-Research/Grounded-Segment-Anything
218
+ - https://github.com/ashawkey/stable-dreamfusion
219
+ - https://github.com/deep-floyd/IF
220
+ - https://github.com/bentoml/BentoML
221
+ - https://github.com/bmaltais/kohya_ss
222
+ - +11.000 other amazing GitHub repositories 💪
223
+
224
+ Thank you for using us ❤️.
225
+
226
+ ## Credits
227
+
228
+ This library concretizes previous work by many different authors and would not have been possible without their great research and implementations. We'd like to thank, in particular, the following implementations which have helped us in our development and without which the API could not have been as polished today:
229
+
230
+ - @CompVis' latent diffusion models library, available [here](https://github.com/CompVis/latent-diffusion)
231
+ - @hojonathanho original DDPM implementation, available [here](https://github.com/hojonathanho/diffusion) as well as the extremely useful translation into PyTorch by @pesser, available [here](https://github.com/pesser/pytorch_diffusion)
232
+ - @ermongroup's DDIM implementation, available [here](https://github.com/ermongroup/ddim)
233
+ - @yang-song's Score-VE and Score-VP implementations, available [here](https://github.com/yang-song/score_sde_pytorch)
234
+
235
+ We also want to thank @heejkoo for the very helpful overview of papers, code and resources on diffusion models, available [here](https://github.com/heejkoo/Awesome-Diffusion-Models) as well as @crowsonkb and @rromb for useful discussions and insights.
236
+
237
+ ## Citation
238
+
239
+ ```bibtex
240
+ @misc{von-platen-etal-2022-diffusers,
241
+ author = {Patrick von Platen and Suraj Patil and Anton Lozhkov and Pedro Cuenca and Nathan Lambert and Kashif Rasul and Mishig Davaadorj and Dhruv Nair and Sayak Paul and William Berman and Yiyi Xu and Steven Liu and Thomas Wolf},
242
+ title = {Diffusers: State-of-the-art diffusion models},
243
+ year = {2022},
244
+ publisher = {GitHub},
245
+ journal = {GitHub repository},
246
+ howpublished = {\url{https://github.com/huggingface/diffusers}}
247
+ }
248
+ ```
UltraEdit/diffusers/_typos.toml ADDED
@@ -0,0 +1,13 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Files for typos
2
+ # Instruction: https://github.com/marketplace/actions/typos-action#getting-started
3
+
4
+ [default.extend-identifiers]
5
+
6
+ [default.extend-words]
7
+ NIN="NIN" # NIN is used in scripts/convert_ncsnpp_original_checkpoint_to_diffusers.py
8
+ nd="np" # nd may be np (numpy)
9
+ parms="parms" # parms is used in scripts/convert_original_stable_diffusion_to_diffusers.py
10
+
11
+
12
+ [files]
13
+ extend-exclude = ["_typos.toml"]
UltraEdit/diffusers/benchmarks/base_classes.py ADDED
@@ -0,0 +1,346 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import os
2
+ import sys
3
+
4
+ import torch
5
+
6
+ from diffusers import (
7
+ AutoPipelineForImage2Image,
8
+ AutoPipelineForInpainting,
9
+ AutoPipelineForText2Image,
10
+ ControlNetModel,
11
+ LCMScheduler,
12
+ StableDiffusionAdapterPipeline,
13
+ StableDiffusionControlNetPipeline,
14
+ StableDiffusionXLAdapterPipeline,
15
+ StableDiffusionXLControlNetPipeline,
16
+ T2IAdapter,
17
+ WuerstchenCombinedPipeline,
18
+ )
19
+ from diffusers.utils import load_image
20
+
21
+
22
+ sys.path.append(".")
23
+
24
+ from utils import ( # noqa: E402
25
+ BASE_PATH,
26
+ PROMPT,
27
+ BenchmarkInfo,
28
+ benchmark_fn,
29
+ bytes_to_giga_bytes,
30
+ flush,
31
+ generate_csv_dict,
32
+ write_to_csv,
33
+ )
34
+
35
+
36
+ RESOLUTION_MAPPING = {
37
+ "runwayml/stable-diffusion-v1-5": (512, 512),
38
+ "lllyasviel/sd-controlnet-canny": (512, 512),
39
+ "diffusers/controlnet-canny-sdxl-1.0": (1024, 1024),
40
+ "TencentARC/t2iadapter_canny_sd14v1": (512, 512),
41
+ "TencentARC/t2i-adapter-canny-sdxl-1.0": (1024, 1024),
42
+ "stabilityai/stable-diffusion-2-1": (768, 768),
43
+ "stabilityai/stable-diffusion-xl-base-1.0": (1024, 1024),
44
+ "stabilityai/stable-diffusion-xl-refiner-1.0": (1024, 1024),
45
+ "stabilityai/sdxl-turbo": (512, 512),
46
+ }
47
+
48
+
49
+ class BaseBenchmak:
50
+ pipeline_class = None
51
+
52
+ def __init__(self, args):
53
+ super().__init__()
54
+
55
+ def run_inference(self, args):
56
+ raise NotImplementedError
57
+
58
+ def benchmark(self, args):
59
+ raise NotImplementedError
60
+
61
+ def get_result_filepath(self, args):
62
+ pipeline_class_name = str(self.pipe.__class__.__name__)
63
+ name = (
64
+ args.ckpt.replace("/", "_")
65
+ + "_"
66
+ + pipeline_class_name
67
+ + f"-bs@{args.batch_size}-steps@{args.num_inference_steps}-mco@{args.model_cpu_offload}-compile@{args.run_compile}.csv"
68
+ )
69
+ filepath = os.path.join(BASE_PATH, name)
70
+ return filepath
71
+
72
+
73
+ class TextToImageBenchmark(BaseBenchmak):
74
+ pipeline_class = AutoPipelineForText2Image
75
+
76
+ def __init__(self, args):
77
+ pipe = self.pipeline_class.from_pretrained(args.ckpt, torch_dtype=torch.float16)
78
+ pipe = pipe.to("cuda")
79
+
80
+ if args.run_compile:
81
+ if not isinstance(pipe, WuerstchenCombinedPipeline):
82
+ pipe.unet.to(memory_format=torch.channels_last)
83
+ print("Run torch compile")
84
+ pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
85
+
86
+ if hasattr(pipe, "movq") and getattr(pipe, "movq", None) is not None:
87
+ pipe.movq.to(memory_format=torch.channels_last)
88
+ pipe.movq = torch.compile(pipe.movq, mode="reduce-overhead", fullgraph=True)
89
+ else:
90
+ print("Run torch compile")
91
+ pipe.decoder = torch.compile(pipe.decoder, mode="reduce-overhead", fullgraph=True)
92
+ pipe.vqgan = torch.compile(pipe.vqgan, mode="reduce-overhead", fullgraph=True)
93
+
94
+ pipe.set_progress_bar_config(disable=True)
95
+ self.pipe = pipe
96
+
97
+ def run_inference(self, pipe, args):
98
+ _ = pipe(
99
+ prompt=PROMPT,
100
+ num_inference_steps=args.num_inference_steps,
101
+ num_images_per_prompt=args.batch_size,
102
+ )
103
+
104
+ def benchmark(self, args):
105
+ flush()
106
+
107
+ print(f"[INFO] {self.pipe.__class__.__name__}: Running benchmark with: {vars(args)}\n")
108
+
109
+ time = benchmark_fn(self.run_inference, self.pipe, args) # in seconds.
110
+ memory = bytes_to_giga_bytes(torch.cuda.max_memory_allocated()) # in GBs.
111
+ benchmark_info = BenchmarkInfo(time=time, memory=memory)
112
+
113
+ pipeline_class_name = str(self.pipe.__class__.__name__)
114
+ flush()
115
+ csv_dict = generate_csv_dict(
116
+ pipeline_cls=pipeline_class_name, ckpt=args.ckpt, args=args, benchmark_info=benchmark_info
117
+ )
118
+ filepath = self.get_result_filepath(args)
119
+ write_to_csv(filepath, csv_dict)
120
+ print(f"Logs written to: {filepath}")
121
+ flush()
122
+
123
+
124
+ class TurboTextToImageBenchmark(TextToImageBenchmark):
125
+ def __init__(self, args):
126
+ super().__init__(args)
127
+
128
+ def run_inference(self, pipe, args):
129
+ _ = pipe(
130
+ prompt=PROMPT,
131
+ num_inference_steps=args.num_inference_steps,
132
+ num_images_per_prompt=args.batch_size,
133
+ guidance_scale=0.0,
134
+ )
135
+
136
+
137
+ class LCMLoRATextToImageBenchmark(TextToImageBenchmark):
138
+ lora_id = "latent-consistency/lcm-lora-sdxl"
139
+
140
+ def __init__(self, args):
141
+ super().__init__(args)
142
+ self.pipe.load_lora_weights(self.lora_id)
143
+ self.pipe.fuse_lora()
144
+ self.pipe.unload_lora_weights()
145
+ self.pipe.scheduler = LCMScheduler.from_config(self.pipe.scheduler.config)
146
+
147
+ def get_result_filepath(self, args):
148
+ pipeline_class_name = str(self.pipe.__class__.__name__)
149
+ name = (
150
+ self.lora_id.replace("/", "_")
151
+ + "_"
152
+ + pipeline_class_name
153
+ + f"-bs@{args.batch_size}-steps@{args.num_inference_steps}-mco@{args.model_cpu_offload}-compile@{args.run_compile}.csv"
154
+ )
155
+ filepath = os.path.join(BASE_PATH, name)
156
+ return filepath
157
+
158
+ def run_inference(self, pipe, args):
159
+ _ = pipe(
160
+ prompt=PROMPT,
161
+ num_inference_steps=args.num_inference_steps,
162
+ num_images_per_prompt=args.batch_size,
163
+ guidance_scale=1.0,
164
+ )
165
+
166
+ def benchmark(self, args):
167
+ flush()
168
+
169
+ print(f"[INFO] {self.pipe.__class__.__name__}: Running benchmark with: {vars(args)}\n")
170
+
171
+ time = benchmark_fn(self.run_inference, self.pipe, args) # in seconds.
172
+ memory = bytes_to_giga_bytes(torch.cuda.max_memory_allocated()) # in GBs.
173
+ benchmark_info = BenchmarkInfo(time=time, memory=memory)
174
+
175
+ pipeline_class_name = str(self.pipe.__class__.__name__)
176
+ flush()
177
+ csv_dict = generate_csv_dict(
178
+ pipeline_cls=pipeline_class_name, ckpt=self.lora_id, args=args, benchmark_info=benchmark_info
179
+ )
180
+ filepath = self.get_result_filepath(args)
181
+ write_to_csv(filepath, csv_dict)
182
+ print(f"Logs written to: {filepath}")
183
+ flush()
184
+
185
+
186
+ class ImageToImageBenchmark(TextToImageBenchmark):
187
+ pipeline_class = AutoPipelineForImage2Image
188
+ url = "https://huggingface.co/datasets/diffusers/docs-images/resolve/main/benchmarking/1665_Girl_with_a_Pearl_Earring.jpg"
189
+ image = load_image(url).convert("RGB")
190
+
191
+ def __init__(self, args):
192
+ super().__init__(args)
193
+ self.image = self.image.resize(RESOLUTION_MAPPING[args.ckpt])
194
+
195
+ def run_inference(self, pipe, args):
196
+ _ = pipe(
197
+ prompt=PROMPT,
198
+ image=self.image,
199
+ num_inference_steps=args.num_inference_steps,
200
+ num_images_per_prompt=args.batch_size,
201
+ )
202
+
203
+
204
+ class TurboImageToImageBenchmark(ImageToImageBenchmark):
205
+ def __init__(self, args):
206
+ super().__init__(args)
207
+
208
+ def run_inference(self, pipe, args):
209
+ _ = pipe(
210
+ prompt=PROMPT,
211
+ image=self.image,
212
+ num_inference_steps=args.num_inference_steps,
213
+ num_images_per_prompt=args.batch_size,
214
+ guidance_scale=0.0,
215
+ strength=0.5,
216
+ )
217
+
218
+
219
+ class InpaintingBenchmark(ImageToImageBenchmark):
220
+ pipeline_class = AutoPipelineForInpainting
221
+ mask_url = "https://huggingface.co/datasets/diffusers/docs-images/resolve/main/benchmarking/overture-creations-5sI6fQgYIuo_mask.png"
222
+ mask = load_image(mask_url).convert("RGB")
223
+
224
+ def __init__(self, args):
225
+ super().__init__(args)
226
+ self.image = self.image.resize(RESOLUTION_MAPPING[args.ckpt])
227
+ self.mask = self.mask.resize(RESOLUTION_MAPPING[args.ckpt])
228
+
229
+ def run_inference(self, pipe, args):
230
+ _ = pipe(
231
+ prompt=PROMPT,
232
+ image=self.image,
233
+ mask_image=self.mask,
234
+ num_inference_steps=args.num_inference_steps,
235
+ num_images_per_prompt=args.batch_size,
236
+ )
237
+
238
+
239
+ class IPAdapterTextToImageBenchmark(TextToImageBenchmark):
240
+ url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/load_neg_embed.png"
241
+ image = load_image(url)
242
+
243
+ def __init__(self, args):
244
+ pipe = self.pipeline_class.from_pretrained(args.ckpt, torch_dtype=torch.float16).to("cuda")
245
+ pipe.load_ip_adapter(
246
+ args.ip_adapter_id[0],
247
+ subfolder="models" if "sdxl" not in args.ip_adapter_id[1] else "sdxl_models",
248
+ weight_name=args.ip_adapter_id[1],
249
+ )
250
+
251
+ if args.run_compile:
252
+ pipe.unet.to(memory_format=torch.channels_last)
253
+ print("Run torch compile")
254
+ pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
255
+
256
+ pipe.set_progress_bar_config(disable=True)
257
+ self.pipe = pipe
258
+
259
+ def run_inference(self, pipe, args):
260
+ _ = pipe(
261
+ prompt=PROMPT,
262
+ ip_adapter_image=self.image,
263
+ num_inference_steps=args.num_inference_steps,
264
+ num_images_per_prompt=args.batch_size,
265
+ )
266
+
267
+
268
+ class ControlNetBenchmark(TextToImageBenchmark):
269
+ pipeline_class = StableDiffusionControlNetPipeline
270
+ aux_network_class = ControlNetModel
271
+ root_ckpt = "runwayml/stable-diffusion-v1-5"
272
+
273
+ url = "https://huggingface.co/datasets/diffusers/docs-images/resolve/main/benchmarking/canny_image_condition.png"
274
+ image = load_image(url).convert("RGB")
275
+
276
+ def __init__(self, args):
277
+ aux_network = self.aux_network_class.from_pretrained(args.ckpt, torch_dtype=torch.float16)
278
+ pipe = self.pipeline_class.from_pretrained(self.root_ckpt, controlnet=aux_network, torch_dtype=torch.float16)
279
+ pipe = pipe.to("cuda")
280
+
281
+ pipe.set_progress_bar_config(disable=True)
282
+ self.pipe = pipe
283
+
284
+ if args.run_compile:
285
+ pipe.unet.to(memory_format=torch.channels_last)
286
+ pipe.controlnet.to(memory_format=torch.channels_last)
287
+
288
+ print("Run torch compile")
289
+ pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
290
+ pipe.controlnet = torch.compile(pipe.controlnet, mode="reduce-overhead", fullgraph=True)
291
+
292
+ self.image = self.image.resize(RESOLUTION_MAPPING[args.ckpt])
293
+
294
+ def run_inference(self, pipe, args):
295
+ _ = pipe(
296
+ prompt=PROMPT,
297
+ image=self.image,
298
+ num_inference_steps=args.num_inference_steps,
299
+ num_images_per_prompt=args.batch_size,
300
+ )
301
+
302
+
303
+ class ControlNetSDXLBenchmark(ControlNetBenchmark):
304
+ pipeline_class = StableDiffusionXLControlNetPipeline
305
+ root_ckpt = "stabilityai/stable-diffusion-xl-base-1.0"
306
+
307
+ def __init__(self, args):
308
+ super().__init__(args)
309
+
310
+
311
+ class T2IAdapterBenchmark(ControlNetBenchmark):
312
+ pipeline_class = StableDiffusionAdapterPipeline
313
+ aux_network_class = T2IAdapter
314
+ root_ckpt = "CompVis/stable-diffusion-v1-4"
315
+
316
+ url = "https://huggingface.co/datasets/diffusers/docs-images/resolve/main/benchmarking/canny_for_adapter.png"
317
+ image = load_image(url).convert("L")
318
+
319
+ def __init__(self, args):
320
+ aux_network = self.aux_network_class.from_pretrained(args.ckpt, torch_dtype=torch.float16)
321
+ pipe = self.pipeline_class.from_pretrained(self.root_ckpt, adapter=aux_network, torch_dtype=torch.float16)
322
+ pipe = pipe.to("cuda")
323
+
324
+ pipe.set_progress_bar_config(disable=True)
325
+ self.pipe = pipe
326
+
327
+ if args.run_compile:
328
+ pipe.unet.to(memory_format=torch.channels_last)
329
+ pipe.adapter.to(memory_format=torch.channels_last)
330
+
331
+ print("Run torch compile")
332
+ pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
333
+ pipe.adapter = torch.compile(pipe.adapter, mode="reduce-overhead", fullgraph=True)
334
+
335
+ self.image = self.image.resize(RESOLUTION_MAPPING[args.ckpt])
336
+
337
+
338
+ class T2IAdapterSDXLBenchmark(T2IAdapterBenchmark):
339
+ pipeline_class = StableDiffusionXLAdapterPipeline
340
+ root_ckpt = "stabilityai/stable-diffusion-xl-base-1.0"
341
+
342
+ url = "https://huggingface.co/datasets/diffusers/docs-images/resolve/main/benchmarking/canny_for_adapter_sdxl.png"
343
+ image = load_image(url)
344
+
345
+ def __init__(self, args):
346
+ super().__init__(args)
UltraEdit/diffusers/benchmarks/benchmark_controlnet.py ADDED
@@ -0,0 +1,26 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import argparse
2
+ import sys
3
+
4
+
5
+ sys.path.append(".")
6
+ from base_classes import ControlNetBenchmark, ControlNetSDXLBenchmark # noqa: E402
7
+
8
+
9
+ if __name__ == "__main__":
10
+ parser = argparse.ArgumentParser()
11
+ parser.add_argument(
12
+ "--ckpt",
13
+ type=str,
14
+ default="lllyasviel/sd-controlnet-canny",
15
+ choices=["lllyasviel/sd-controlnet-canny", "diffusers/controlnet-canny-sdxl-1.0"],
16
+ )
17
+ parser.add_argument("--batch_size", type=int, default=1)
18
+ parser.add_argument("--num_inference_steps", type=int, default=50)
19
+ parser.add_argument("--model_cpu_offload", action="store_true")
20
+ parser.add_argument("--run_compile", action="store_true")
21
+ args = parser.parse_args()
22
+
23
+ benchmark_pipe = (
24
+ ControlNetBenchmark(args) if args.ckpt == "lllyasviel/sd-controlnet-canny" else ControlNetSDXLBenchmark(args)
25
+ )
26
+ benchmark_pipe.benchmark(args)
UltraEdit/diffusers/benchmarks/benchmark_ip_adapters.py ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import argparse
2
+ import sys
3
+
4
+
5
+ sys.path.append(".")
6
+ from base_classes import IPAdapterTextToImageBenchmark # noqa: E402
7
+
8
+
9
+ IP_ADAPTER_CKPTS = {
10
+ "runwayml/stable-diffusion-v1-5": ("h94/IP-Adapter", "ip-adapter_sd15.bin"),
11
+ "stabilityai/stable-diffusion-xl-base-1.0": ("h94/IP-Adapter", "ip-adapter_sdxl.bin"),
12
+ }
13
+
14
+
15
+ if __name__ == "__main__":
16
+ parser = argparse.ArgumentParser()
17
+ parser.add_argument(
18
+ "--ckpt",
19
+ type=str,
20
+ default="runwayml/stable-diffusion-v1-5",
21
+ choices=list(IP_ADAPTER_CKPTS.keys()),
22
+ )
23
+ parser.add_argument("--batch_size", type=int, default=1)
24
+ parser.add_argument("--num_inference_steps", type=int, default=50)
25
+ parser.add_argument("--model_cpu_offload", action="store_true")
26
+ parser.add_argument("--run_compile", action="store_true")
27
+ args = parser.parse_args()
28
+
29
+ args.ip_adapter_id = IP_ADAPTER_CKPTS[args.ckpt]
30
+ benchmark_pipe = IPAdapterTextToImageBenchmark(args)
31
+ args.ckpt = f"{args.ckpt} (IP-Adapter)"
32
+ benchmark_pipe.benchmark(args)
UltraEdit/diffusers/benchmarks/benchmark_sd_img.py ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import argparse
2
+ import sys
3
+
4
+
5
+ sys.path.append(".")
6
+ from base_classes import ImageToImageBenchmark, TurboImageToImageBenchmark # noqa: E402
7
+
8
+
9
+ if __name__ == "__main__":
10
+ parser = argparse.ArgumentParser()
11
+ parser.add_argument(
12
+ "--ckpt",
13
+ type=str,
14
+ default="runwayml/stable-diffusion-v1-5",
15
+ choices=[
16
+ "runwayml/stable-diffusion-v1-5",
17
+ "stabilityai/stable-diffusion-2-1",
18
+ "stabilityai/stable-diffusion-xl-refiner-1.0",
19
+ "stabilityai/sdxl-turbo",
20
+ ],
21
+ )
22
+ parser.add_argument("--batch_size", type=int, default=1)
23
+ parser.add_argument("--num_inference_steps", type=int, default=50)
24
+ parser.add_argument("--model_cpu_offload", action="store_true")
25
+ parser.add_argument("--run_compile", action="store_true")
26
+ args = parser.parse_args()
27
+
28
+ benchmark_pipe = ImageToImageBenchmark(args) if "turbo" not in args.ckpt else TurboImageToImageBenchmark(args)
29
+ benchmark_pipe.benchmark(args)