
"""simple docstring"""
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple

import yaml






class      _UpperCAmelCase				(					yaml.SafeLoader):
    def 					lowerCamelCase__	(    self						,    snake_case_     ):
      _snake_case     :						str						=   [self.constructed_objects[key_node] for key_node, _ in node.value]
      _snake_case     :						Any						=   [tuple(a_     ) if isinstance(a_						,    a_     ) else key for key in keys]
      _snake_case     :						Optional[int]						=   Counter(a_     )
      _snake_case     :						Dict						=   [key for key in counter if counter[key] > 1]
      if duplicate_keys:
        raise TypeError(F'Got duplicate yaml keys: {duplicate_keys}'     )


    def 					lowerCamelCase__	(    self						,    snake_case_						,    snake_case_=False     ):
      _snake_case     :						Any						=   super().construct_mapping(a_						,    deep=a_     )
      self._check_no_duplicates_on_constructed_node(a_     )
      return mapping


def 				a__   (   a   :				str		):

  """simple docstring"""







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

  return None, "\n".join(snake_case__		)






class      _UpperCAmelCase				(					__a):
    __lowercase							: Optional[Any]  =					{"""train_eval_index"""}  # train-eval-index in the YAML metadata
    @classmethod
    def 					lowerCamelCase__	(    cls						,    snake_case_     ):



      with open(a_						,    encoding="utf-8"     ) as readme_file:
        _snake_case     :						List[Any]						=   _split_yaml_from_readme(readme_file.read()     )
      if yaml_string is not None:
        return cls.from_yaml_string(a_     )
      else:
        return cls()
    def 					lowerCamelCase__	(    self						,    snake_case_     ):



      if path.exists():
        with open(a_						,    encoding="utf-8"     ) as readme_file:
          _snake_case     :						List[str]						=   readme_file.read()
      else:
        _snake_case     :						Dict						=   None
      _snake_case     :						List[str]						=   self._to_readme(a_     )
      with open(a_						,    "w"						,    encoding="utf-8"     ) as readme_file:
        readme_file.write(a_     )
    def 					lowerCamelCase__	(    self						,    snake_case_ = None     ):



      if readme_content is not None:
        _snake_case     :						Union[str, Any]						=   _split_yaml_from_readme(a_     )
        _snake_case     :						str						=   """---\n""" + self.to_yaml_string() + """---\n""" + content
      else:
        _snake_case     :						Any						=   """---\n""" + self.to_yaml_string() + """---\n"""
      return full_content
    @classmethod
    def 					lowerCamelCase__	(    cls						,    snake_case_     ):
      _snake_case     :						int						=   yaml.load(a_						,    Loader=_NoDuplicateSafeLoader     ) or {}

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


    def 					lowerCamelCase__	(    self     ):
      return yaml.safe_dump(
          {
              (key.replace("_"						,    "-"     ) if key in self._FIELDS_WITH_DASHES else key): value
              for key, value in self.items()
          }						,    sort_keys=a_						,    allow_unicode=a_						,    encoding="utf-8"						,    ).decode("utf-8"     )


lowerCamelCase_      :			Dict					=							{
    """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_      :			str					=							ArgumentParser(usage="""Validate the yaml metadata block of a README.md file.""")
    ap.add_argument("""readme_filepath""")
    lowerCamelCase_      :			Optional[int]					=							ap.parse_args()

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



"""simple docstring"""
def 				a__   (   a   :				int		):

  """simple docstring"""







  if not isinstance(a       ,     a		):
    raise TypeError("Input value must be an 'int' type"		)

  _snake_case     :						Union[str, Any]						=   0
  while number:
    position += 1
    number >>= 1

  return position


if __name__ == "__main__":
    import doctest

    doctest.testmod()

