



import argparse
from collections import defaultdict

import yaml


a     :    Optional[Any]      						=					"""docs/source/en/_toctree.yml"""



def    __lowerCamelCase						(      _lowercase	)   ->    Tuple:
							UpperCAmelCase  :	Any							  =	defaultdict(snake_case__	)
							for doc in model_doc:
														counts[doc["local"]] += 1
							UpperCAmelCase  :	Any							  =	[key for key, value in counts.items() if value > 1]

							UpperCAmelCase  :	Optional[Any]							  =	[]
							for duplicate_key in duplicates:
														UpperCAmelCase  :	Dict							  =	list({doc["""title"""] for doc in model_doc if doc["""local"""] == duplicate_key}	)
														if len(snake_case__	) > 1:
																					raise ValueError(
																					    F'''{duplicate_key} is present several times in the documentation table of content at '''
																					    """`docs/source/en/_toctree.yml` with different *Title* values. Choose one of those and remove the """
																					    """others."""	)
														# Only add this once
														new_doc.append({"""local""": duplicate_key, """title""": titles[0]}	)

							# Add none duplicate-keys
							new_doc.extend([doc for doc in model_doc if counts[doc["""local"""]] == 1]	)

							# Sort
							return sorted(snake_case__			,       key=lambda _lowercase	: s["title"].lower()	)



def    __lowerCamelCase						(      _lowercase=False	)   ->    int:

							with open(snake_case__			,       encoding="""utf-8"""	) as f:
														UpperCAmelCase  :	Union[str, Any]							  =	yaml.safe_load(f.read()	)

							# Get to the API doc
							UpperCAmelCase  :	int							  =	0
							while content[api_idx]["title"] != "API":
														api_idx += 1
							UpperCAmelCase  :	List[Any]							  =	content[api_idx]["""sections"""]

							# Then to the model doc
							UpperCAmelCase  :	Optional[int]							  =	0
							while api_doc[model_idx]["title"] != "Models":
														model_idx += 1

							UpperCAmelCase  :	List[str]							  =	api_doc[model_idx]["""sections"""]

							UpperCAmelCase  :	List[str]							  =	[(idx, section) for idx, section in enumerate(snake_case__	) if """sections""" in section]
							UpperCAmelCase  :	Optional[Any]							  =	False
							for idx, modality_doc in modalities_docs:
														UpperCAmelCase  :	int							  =	modality_doc["""sections"""]
														UpperCAmelCase  :	Tuple							  =	clean_model_doc_toc(snake_case__	)

														if old_modality_doc != new_modality_doc:
																					UpperCAmelCase  :	Optional[Any]							  =	True
																					if overwrite:
																												UpperCAmelCase  :	Optional[int]							  =	new_modality_doc

							if diff:
														if overwrite:
																					UpperCAmelCase  :	Optional[int]							  =	model_doc
																					UpperCAmelCase  :	Union[str, Any]							  =	api_doc
																					with open(snake_case__			,       """w"""			,       encoding="""utf-8"""	) as f:
																												f.write(yaml.dump(snake_case__			,       allow_unicode=snake_case__	)	)
														else:
																					raise ValueError(
																					    """The model doc part of the table of content is not properly sorted, run `make style` to fix this."""	)


if __name__ == "__main__":
							a     :    Tuple      						=					argparse.ArgumentParser()
							parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
							a     :    int      						=					parser.parse_args()

							check_model_doc(args.fix_and_overwrite)






'''simple docstring'''




from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
							from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline

