"""simple docstring"""



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

import yaml







class _lowerCAmelCase    (				yaml.SafeLoader     ):







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						)     ->		str:

       '''simple docstring'''




       snake_case   :				Union[str, Any]				 =   [self.constructed_objects[key_node] for key_node, _ in node.value]
       snake_case   :				Dict				 =   [tuple(UpperCamelCase__						) if isinstance(UpperCamelCase__						,     UpperCamelCase__						) else key for key in keys]
       snake_case   :				str				 =   Counter(UpperCamelCase__						)
       snake_case   :				Any				 =   [key for key in counter if counter[key] > 1]
       if duplicate_keys:
           raise TypeError(F'Got duplicate yaml keys: {duplicate_keys}'						)







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						,     UpperCamelCase__=False						)     ->		str:

       '''simple docstring'''




       snake_case   :				List[str]				 =   super().construct_mapping(UpperCamelCase__						,     deep=UpperCamelCase__						)
       self._check_no_duplicates_on_constructed_node(UpperCamelCase__						)
       return mapping







def   __lowerCAmelCase						(						lowercase  :  str			)     ->						Tuple[Optional[str], str]:


    """simple docstring"""





    snake_case   :				Any				 =   list(readme_content.splitlines()			)
    if full_content and full_content[0] == "---" and "---" in full_content[1:]:
        snake_case   :				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(lowercase			)







class _lowerCAmelCase    (				snake_case_     ):
   # class attributes
   __UpperCAmelCase			:	Union[str, Any]							  =  {'''train_eval_index'''}  # train-eval-index in the YAML metadata







   @classmethod
   def 			lowerCamelCase		(     cls						,     UpperCamelCase__						)     ->		"DatasetMetadata":

       '''simple docstring'''




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







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						)     ->		List[str]:

       '''simple docstring'''




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







   def 			lowerCamelCase		(     self						,     UpperCamelCase__ = None						)     ->		str:

       '''simple docstring'''




       if readme_content is not None:
           snake_case   :				Tuple				 =   _split_yaml_from_readme(UpperCamelCase__						)
           snake_case   :				Optional[int]				 =   "---\n" + self.to_yaml_string() + "---\n" + content
       else:
           snake_case   :				List[Any]				 =   "---\n" + self.to_yaml_string() + "---\n"
       return full_content







   @classmethod
   def 			lowerCamelCase		(     cls						,     UpperCamelCase__						)     ->		"DatasetMetadata":

       '''simple docstring'''




       snake_case   :				List[str]				 =   yaml.load(UpperCamelCase__						,     Loader=_NoDuplicateSafeLoader						) or {}

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







   def 			lowerCamelCase		(     self						)     ->		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=UpperCamelCase__						,     allow_unicode=UpperCamelCase__						,     encoding="utf-8"						,     ).decode("utf-8"						)



__snake_case             =   {
    """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

  __snake_case             =   ArgumentParser(usage="""Validate the yaml metadata block of a README.md file.""")
  ap.add_argument("""readme_filepath""")
  __snake_case             =   ap.parse_args()

  __snake_case             =   Path(args.readme_filepath)
  __snake_case             =   DatasetMetadata.from_readme(readme_filepath)
  print(dataset_metadata)
  dataset_metadata.to_readme(readme_filepath)









"""simple docstring"""



from __future__ import annotations

import numpy as np







def   __lowerCAmelCase						(						lowercase  :  list[float]			)     ->						Any:


    """simple docstring"""





    return np.maximum(0						,							lowercase			)


if __name__ == "__main__":
  print(np.array(relu([-1, 0, 5])))  # --> [0, 0, 5]





