
'''simple docstring'''




from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Value
from .base import TaskTemplate





@dataclass(frozen=__snake_case						)
class  A				(							__snake_case						):
     # `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
     __magic_name__						=		field(default='''summarization'''    ,			metadata={'''include_in_asdict_even_if_is_default''': True}						)
     __magic_name__						=		Features({'''text''': Value('''string'''						)}						)
     __magic_name__						=		Features({'''summary''': Value('''string'''						)}						)
     __magic_name__						=		"text"
     __magic_name__						=		"summary"





     @property
     def 				__lowerCAmelCase							(							self	) ->				Dict[str, str]:






         """simple docstring"""






         return {self.text_column: "text", self.summary_column: "summary"}









'''simple docstring'''





import string
from math import logaa





def 						__snake_case(				_lowerCAmelCase     ,   _lowerCAmelCase		)		-> int:
      snake_case__  :    List[str]    						=      document.translate(
          str.maketrans(""""""     ,   """"""     ,   string.punctuation		)		).replace("""\n"""     ,   """"""		)
      snake_case__  :    List[str]    						=      document_without_punctuation.split(""" """		)  # word tokenization
      return len([word for word in tokenize_document if word.lower() == term.lower()]		)





def 						__snake_case(				_lowerCAmelCase     ,   _lowerCAmelCase		)		-> tuple[int, int]:
      snake_case__  :    Dict    						=      corpus.lower().translate(
          str.maketrans(""""""     ,   """"""     ,   string.punctuation		)		)  # strip all punctuation and replace it with ''
      snake_case__  :    Any    						=      corpus_without_punctuation.split("""\n"""		)
      snake_case__  :    int    						=      term.lower()
      return (len([doc for doc in docs if term in doc]		), len(_lowerCAmelCase		))





def 						__snake_case(				_lowerCAmelCase     ,   _lowerCAmelCase     ,   _lowerCAmelCase=False		)		-> float:
      if smoothing:
            if n == 0:
                  raise ValueError("""log10(0) is undefined."""		)
            return round(1 + logaa(n / (1 + df)		)     ,   3		)

      if df == 0:
            raise ZeroDivisionError("""df must be > 0"""		)
      elif n == 0:
            raise ValueError("""log10(0) is undefined."""		)
      return round(logaa(n / df		)     ,   3		)





def 						__snake_case(				_lowerCAmelCase     ,   _lowerCAmelCase		)		-> float:
      return round(tf * idf     ,   3		)
