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| """ |
| Utility that checks that modules like attention processors are listed in the documentation file. |
| |
| ```bash |
| python utils/check_support_list.py |
| ``` |
| |
| It has no auto-fix mode. |
| """ |
|
|
| import os |
| import re |
|
|
|
|
| |
| REPO_PATH = "." |
|
|
|
|
| def read_documented_classes(doc_path, autodoc_regex=r"\[\[autodoc\]\]\s([^\n]+)"): |
| """ |
| Reads documented classes from a doc file using a regex to find lines like [[autodoc]] my.module.Class. |
| Returns a list of documented class names (just the class name portion). |
| """ |
| with open(os.path.join(REPO_PATH, doc_path), "r") as f: |
| doctext = f.read() |
| matches = re.findall(autodoc_regex, doctext) |
| return [match.split(".")[-1] for match in matches] |
|
|
|
|
| def read_source_classes(src_path, class_regex, exclude_conditions=None): |
| """ |
| Reads class names from a source file using a regex that captures class definitions. |
| Optionally exclude classes based on a list of conditions (functions that take class name and return bool). |
| """ |
| if exclude_conditions is None: |
| exclude_conditions = [] |
| with open(os.path.join(REPO_PATH, src_path), "r") as f: |
| doctext = f.read() |
| classes = re.findall(class_regex, doctext) |
| |
| filtered_classes = [c for c in classes if not any(cond(c) for cond in exclude_conditions)] |
| return filtered_classes |
|
|
|
|
| def check_documentation(doc_path, src_path, doc_regex, src_regex, exclude_conditions=None): |
| """ |
| Generic function to check if all classes defined in `src_path` are documented in `doc_path`. |
| Returns a set of undocumented class names. |
| """ |
| documented = set(read_documented_classes(doc_path, doc_regex)) |
| source_classes = set(read_source_classes(src_path, src_regex, exclude_conditions=exclude_conditions)) |
|
|
| |
| undocumented = sorted(source_classes - documented) |
| return undocumented |
|
|
|
|
| if __name__ == "__main__": |
| |
| checks = { |
| "Attention Processors": { |
| "doc_path": "docs/source/en/api/attnprocessor.md", |
| "src_path": "src/diffusers/models/attention_processor.py", |
| "doc_regex": r"\[\[autodoc\]\]\s([^\n]+)", |
| "src_regex": r"class\s+(\w+Processor(?:\d*_?\d*))[:(]", |
| "exclude_conditions": [lambda c: "LoRA" in c, lambda c: c == "Attention"], |
| }, |
| "Image Processors": { |
| "doc_path": "docs/source/en/api/image_processor.md", |
| "src_path": "src/diffusers/image_processor.py", |
| "doc_regex": r"\[\[autodoc\]\]\s([^\n]+)", |
| "src_regex": r"class\s+(\w+Processor(?:\d*_?\d*))[:(]", |
| }, |
| "Activations": { |
| "doc_path": "docs/source/en/api/activations.md", |
| "src_path": "src/diffusers/models/activations.py", |
| "doc_regex": r"\[\[autodoc\]\]\s([^\n]+)", |
| "src_regex": r"class\s+(\w+)\s*\(.*?nn\.Module.*?\):", |
| }, |
| "Normalizations": { |
| "doc_path": "docs/source/en/api/normalization.md", |
| "src_path": "src/diffusers/models/normalization.py", |
| "doc_regex": r"\[\[autodoc\]\]\s([^\n]+)", |
| "src_regex": r"class\s+(\w+)\s*\(.*?nn\.Module.*?\):", |
| "exclude_conditions": [ |
| |
| lambda c: c == "LayerNorm" |
| ], |
| }, |
| "LoRA Mixins": { |
| "doc_path": "docs/source/en/api/loaders/lora.md", |
| "src_path": "src/diffusers/loaders/lora_pipeline.py", |
| "doc_regex": r"\[\[autodoc\]\]\s([^\n]+)", |
| "src_regex": r"class\s+(\w+LoraLoaderMixin(?:\d*_?\d*))[:(]", |
| }, |
| } |
|
|
| missing_items = {} |
| for category, params in checks.items(): |
| undocumented = check_documentation( |
| doc_path=params["doc_path"], |
| src_path=params["src_path"], |
| doc_regex=params["doc_regex"], |
| src_regex=params["src_regex"], |
| exclude_conditions=params.get("exclude_conditions"), |
| ) |
| if undocumented: |
| missing_items[category] = undocumented |
|
|
| |
| if missing_items: |
| error_msg = ["Some classes are not documented properly:\n"] |
| for category, classes in missing_items.items(): |
| error_msg.append(f"- {category}: {', '.join(sorted(classes))}") |
| raise ValueError("\n".join(error_msg)) |
|
|