






'''simple docstring'''


from collections import Counter
from pathlib import Path
from typing import Optional, Tuple

import yaml
class    _SCREAMING_SNAKE_CASE							(		yaml.SafeLoader	):


			'''simple docstring'''





			def 				A      (   self							:						List[str] ,      lowercase							:						List[Any]			)							->    int:

									'''simple docstring'''







									UpperCamelCase__         = [self.constructed_objects[key_node] for key_node, _ in node.value]
									UpperCamelCase__         = [tuple(lowercase			) if isinstance(lowercase ,      lowercase			) else key for key in keys]
									UpperCamelCase__         = Counter(lowercase			)
									UpperCamelCase__         = [key for key in counter if counter[key] > 1]
									if duplicate_keys:
															raise TypeError(f"Got duplicate yaml keys: {duplicate_keys}"			)







			def 				A      (   self							:						List[str] ,      lowercase							:						int ,      lowercase							:						str=False			)							->    Any:

									'''simple docstring'''







									UpperCamelCase__         = super().construct_mapping(lowercase ,      deep=lowercase			)
									self._check_no_duplicates_on_constructed_node(lowercase			)
									return mapping







def 	__magic_name__( _A					):
						'''simple docstring'''





						UpperCamelCase__         = list(readme_content.splitlines()					)
						if full_content and full_content[0] == "---" and "---" in full_content[1:]:
												UpperCamelCase__         = full_content[1:].index("""---"""					) + 1
												UpperCamelCase__         = """\n""".join(full_content[1:sep_idx]					)
												return yamlblock, "\n".join(full_content[sep_idx + 1 :]					)

						return None, "\n".join(_A					)
class    _SCREAMING_SNAKE_CASE							(		SCREAMING_SNAKE_CASE	):


			'''simple docstring'''





			__a							:							Tuple					     =					{"train_eval_index"}  # train-eval-index in the YAML metadata






			@classmethod
			def 				A      (   cls							:						int ,      lowercase							:						Path			)							->    "DatasetMetadata":

									'''simple docstring'''







									with open(lowercase ,      encoding="""utf-8"""			) as readme_file:
															UpperCamelCase__    ,   UpperCamelCase__         = _split_yaml_from_readme(readme_file.read()			)
									if yaml_string is not None:
															return cls.from_yaml_string(lowercase			)
									else:
															return cls()






			def 				A      (   self							:						int ,      lowercase							:						Path			)							->    Dict:

									'''simple docstring'''







									if path.exists():
															with open(lowercase ,      encoding="""utf-8"""			) as readme_file:
																					UpperCamelCase__         = readme_file.read()
									else:
															UpperCamelCase__         = None
									UpperCamelCase__         = self._to_readme(lowercase			)
									with open(lowercase ,      """w""" ,      encoding="""utf-8"""			) as readme_file:
															readme_file.write(lowercase			)






			def 				A      (   self							:						Any ,      lowercase							:						Optional[str] = None			)							->    str:

									'''simple docstring'''







									if readme_content is not None:
															UpperCamelCase__    ,   UpperCamelCase__         = _split_yaml_from_readme(lowercase			)
															UpperCamelCase__         = """---\n""" + self.to_yaml_string() + """---\n""" + content
									else:
															UpperCamelCase__         = """---\n""" + self.to_yaml_string() + """---\n"""
									return full_content






			@classmethod
			def 				A      (   cls							:						Tuple ,      lowercase							:						str			)							->    "DatasetMetadata":

									'''simple docstring'''







									UpperCamelCase__         = yaml.load(lowercase ,      Loader=_NoDuplicateSafeLoader			) or {}

									# Convert the YAML keys to DatasetMetadata fields
									UpperCamelCase__         = {
									    (key.replace("""-""" ,      """_"""			) if key.replace("""-""" ,      """_"""			) in cls._FIELDS_WITH_DASHES else key): value
									    for key, value in metadata_dict.items()
									}
									return cls(**lowercase			)







			def 				A      (   self							:						Dict			)							->    str:

									'''simple docstring'''







									return yaml.safe_dump(
									    {
									        (key.replace("""_""" ,      """-"""			) if key in self._FIELDS_WITH_DASHES else key): value
									        for key, value in self.items()
									    } ,      sort_keys=lowercase ,      allow_unicode=lowercase ,      encoding="""utf-8""" ,      ).decode("""utf-8"""			)
lowerCamelCase_				: str    	=							{
    '''image-classification''': [],
    '''translation''': [],
    '''image-segmentation''': [],
    '''fill-mask''': [],
    '''automatic-speech-recognition''': [],
    '''token-classification''': [],
    '''sentence-similarity''': [],
    '''audio-classification''': [],
    '''question-answering''': [],
    '''summarization''': [],
    '''zero-shot-classification''': [],
    '''table-to-text''': [],
    '''feature-extraction''': [],
    '''other''': [],
    '''multiple-choice''': [],
    '''text-classification''': [],
    '''text-to-image''': [],
    '''text2text-generation''': [],
    '''zero-shot-image-classification''': [],
    '''tabular-classification''': [],
    '''tabular-regression''': [],
    '''image-to-image''': [],
    '''tabular-to-text''': [],
    '''unconditional-image-generation''': [],
    '''text-retrieval''': [],
    '''text-to-speech''': [],
    '''object-detection''': [],
    '''audio-to-audio''': [],
    '''text-generation''': [],
    '''conversational''': [],
    '''table-question-answering''': [],
    '''visual-question-answering''': [],
    '''image-to-text''': [],
    '''reinforcement-learning''': [],
    '''voice-activity-detection''': [],
    '''time-series-forecasting''': [],
    '''document-question-answering''': [],
}


if __name__ == "__main__":
					from argparse import ArgumentParser

					lowerCamelCase_				: Tuple    	=							ArgumentParser(usage='''Validate the yaml metadata block of a README.md file.''')
					ap.add_argument('''readme_filepath''')
					lowerCamelCase_				: str    	=							ap.parse_args()

					lowerCamelCase_				: List[str]    	=							Path(args.readme_filepath)
					lowerCamelCase_				: Tuple    	=							DatasetMetadata.from_readme(readme_filepath)
					print(dataset_metadata)
					dataset_metadata.to_readme(readme_filepath)








'''simple docstring'''


import inspect
import unittest
class    _SCREAMING_SNAKE_CASE							(		unittest.TestCase	):


			'''simple docstring'''





			def 				A      (   self							:						Tuple			)							->    Any:

									'''simple docstring'''







									try:
															import diffusers  # noqa: F401
									except ImportError:
															assert False







			def 				A      (   self							:						Optional[int]			)							->    Union[str, Any]:

									'''simple docstring'''







									import diffusers
									from diffusers.dependency_versions_table import deps

									UpperCamelCase__         = inspect.getmembers(lowercase ,      inspect.isclass			)

									for cls_name, cls_module in all_classes:
															if "dummy_" in cls_module.__module__:
																					for backend in cls_module._backends:
																											if backend == "k_diffusion":
																																	UpperCamelCase__         = """k-diffusion"""
																											elif backend == "invisible_watermark":
																																	UpperCamelCase__         = """invisible-watermark"""
																											assert backend in deps, f"{backend} is not in the deps table!"
