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[Styling] stylify using ruff (huggingface#5841)
* ruff format * not need to use doc-builder's black styling as the doc is styled in ruff * make fix-copies * comment * use run_ruff
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Lines changed: 430 additions & 297 deletions

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‎.github/workflows/pr_quality.yml‎

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@@ -27,9 +27,8 @@ jobs:
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pip install .[quality]
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- name: Check quality
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run: |
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black --check examples tests src utils scripts
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ruff examples tests src utils scripts
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doc-builder style src/diffusers docs/source --max_len 119 --check_only --path_to_docs docs/source
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ruff check examples tests src utils scripts
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ruff format examples tests src utils scripts --check
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check_repository_consistency:
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runs-on: ubuntu-latest

‎CONTRIBUTING.md‎

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@@ -410,7 +410,7 @@ Diffusers has grown a lot. Here is the command for it:
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$ make test
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```
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🧨 Diffusers relies on `black` and `isort` to format its source code
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🧨 Diffusers relies on `ruff` and `isort` to format its source code
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consistently. After you make changes, apply automatic style corrections and code verifications
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that can't be automated in one go with:
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‎Makefile‎

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@@ -9,8 +9,8 @@ modified_only_fixup:
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$(eval modified_py_files := $(shell python utils/get_modified_files.py $(check_dirs)))
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@if test -n "$(modified_py_files)"; then \
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echo "Checking/fixing $(modified_py_files)"; \
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black $(modified_py_files); \
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ruff $(modified_py_files); \
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ruff check $(modified_py_files) --fix; \
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ruff format $(modified_py_files);\
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else \
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echo "No library .py files were modified"; \
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fi
@@ -40,23 +40,21 @@ repo-consistency:
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# this target runs checks on all files
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quality:
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black --check $(check_dirs)
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ruff $(check_dirs)
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doc-builder style src/diffusers docs/source --max_len 119 --check_only --path_to_docs docs/source
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ruff check $(check_dirs) setup.py
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ruff format --check $(check_dirs) setup.py
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python utils/check_doc_toc.py
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# Format source code automatically and check is there are any problems left that need manual fixing
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extra_style_checks:
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python utils/custom_init_isort.py
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doc-builder style src/diffusers docs/source --max_len 119 --path_to_docs docs/source
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python utils/check_doc_toc.py --fix_and_overwrite
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# this target runs checks on all files and potentially modifies some of them
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style:
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black $(check_dirs)
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ruff $(check_dirs) --fix
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ruff check $(check_dirs) setup.py --fix
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ruff format $(check_dirs) setup.py
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${MAKE} autogenerate_code
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${MAKE} extra_style_checks
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‎examples/community/composable_stable_diffusion.py‎

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@@ -65,6 +65,7 @@ class ComposableStableDiffusionPipeline(DiffusionPipeline):
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feature_extractor ([`CLIPImageProcessor`]):
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Model that extracts features from generated images to be used as inputs for the `safety_checker`.
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"""
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_optional_components = ["safety_checker", "feature_extractor"]
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def __init__(

‎examples/community/latent_consistency_img2img.py‎

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@@ -564,9 +564,7 @@ def __init__(
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self.betas = torch.linspace(beta_start, beta_end, num_train_timesteps, dtype=torch.float32)
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elif beta_schedule == "scaled_linear":
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# this schedule is very specific to the latent diffusion model.
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self.betas = (
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torch.linspace(beta_start**0.5, beta_end**0.5, num_train_timesteps, dtype=torch.float32) ** 2
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)
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self.betas = torch.linspace(beta_start**0.5, beta_end**0.5, num_train_timesteps, dtype=torch.float32) ** 2
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elif beta_schedule == "squaredcos_cap_v2":
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# Glide cosine schedule
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self.betas = betas_for_alpha_bar(num_train_timesteps)

‎examples/community/latent_consistency_txt2img.py‎

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@@ -469,9 +469,7 @@ def __init__(
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self.betas = torch.linspace(beta_start, beta_end, num_train_timesteps, dtype=torch.float32)
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elif beta_schedule == "scaled_linear":
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# this schedule is very specific to the latent diffusion model.
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self.betas = (
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torch.linspace(beta_start**0.5, beta_end**0.5, num_train_timesteps, dtype=torch.float32) ** 2
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)
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self.betas = torch.linspace(beta_start**0.5, beta_end**0.5, num_train_timesteps, dtype=torch.float32) ** 2
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elif beta_schedule == "squaredcos_cap_v2":
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# Glide cosine schedule
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self.betas = betas_for_alpha_bar(num_train_timesteps)

‎examples/community/lpw_stable_diffusion.py‎

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@@ -56,10 +56,10 @@ def parse_prompt_attention(text):
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(abc) - increases attention to abc by a multiplier of 1.1
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(abc:3.12) - increases attention to abc by a multiplier of 3.12
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[abc] - decreases attention to abc by a multiplier of 1.1
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\( - literal character '('
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\[ - literal character '['
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\) - literal character ')'
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\] - literal character ']'
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\\( - literal character '('
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\\[ - literal character '['
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\\) - literal character ')'
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\\] - literal character ']'
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\\ - literal character '\'
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anything else - just text
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>>> parse_prompt_attention('normal text')
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[['an ', 1.0], ['important', 1.1], [' word', 1.0]]
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>>> parse_prompt_attention('(unbalanced')
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[['unbalanced', 1.1]]
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>>> parse_prompt_attention('\(literal\]')
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>>> parse_prompt_attention('\\(literal\\]')
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[['(literal]', 1.0]]
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>>> parse_prompt_attention('(unnecessary)(parens)')
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[['unnecessaryparens', 1.1]]

‎examples/community/lpw_stable_diffusion_onnx.py‎

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@@ -82,10 +82,10 @@ def parse_prompt_attention(text):
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(abc) - increases attention to abc by a multiplier of 1.1
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(abc:3.12) - increases attention to abc by a multiplier of 3.12
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[abc] - decreases attention to abc by a multiplier of 1.1
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\( - literal character '('
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\[ - literal character '['
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\) - literal character ')'
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\] - literal character ']'
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\\( - literal character '('
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\\[ - literal character '['
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\\) - literal character ')'
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\\] - literal character ']'
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\\ - literal character '\'
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anything else - just text
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>>> parse_prompt_attention('normal text')
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[['an ', 1.0], ['important', 1.1], [' word', 1.0]]
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>>> parse_prompt_attention('(unbalanced')
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[['unbalanced', 1.1]]
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>>> parse_prompt_attention('\(literal\]')
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>>> parse_prompt_attention('\\(literal\\]')
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[['(literal]', 1.0]]
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>>> parse_prompt_attention('(unnecessary)(parens)')
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[['unnecessaryparens', 1.1]]
@@ -433,6 +433,7 @@ class OnnxStableDiffusionLongPromptWeightingPipeline(OnnxStableDiffusionPipeline
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This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods the
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library implements for all the pipelines (such as downloading or saving, running on a particular device, etc.)
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"""
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if version.parse(version.parse(diffusers.__version__).base_version) >= version.parse("0.9.0"):
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def __init__(

‎examples/community/lpw_stable_diffusion_xl.py‎

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@@ -46,10 +46,10 @@ def parse_prompt_attention(text):
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(abc) - increases attention to abc by a multiplier of 1.1
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(abc:3.12) - increases attention to abc by a multiplier of 3.12
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[abc] - decreases attention to abc by a multiplier of 1.1
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\( - literal character '('
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\[ - literal character '['
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\) - literal character ')'
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\] - literal character ']'
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\\( - literal character '('
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\\[ - literal character '['
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\\) - literal character ')'
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\\] - literal character ']'
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\\ - literal character '\'
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anything else - just text
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@@ -59,7 +59,7 @@ def parse_prompt_attention(text):
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[['an ', 1.0], ['important', 1.1], [' word', 1.0]]
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>>> parse_prompt_attention('(unbalanced')
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[['unbalanced', 1.1]]
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>>> parse_prompt_attention('\(literal\]')
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>>> parse_prompt_attention('\\(literal\\]')
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[['(literal]', 1.0]]
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>>> parse_prompt_attention('(unnecessary)(parens)')
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[['unnecessaryparens', 1.1]]

‎examples/community/magic_mix.py‎

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@@ -127,9 +127,9 @@ def __call__(
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timesteps=t,
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)
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input = (mix_factor * latents) + (
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1 - mix_factor
132-
) * orig_latents # interpolating between layout noise and conditionally generated noise to preserve layout sematics
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input = (
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(mix_factor * latents) + (1 - mix_factor) * orig_latents
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) # interpolating between layout noise and conditionally generated noise to preserve layout sematics
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input = torch.cat([input] * 2)
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else: # content generation phase

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