




import string
from math import logaa

def    UpperCAmelCase_				( __UpperCAmelCase		:      str     ,     __UpperCAmelCase		:      str				)   ->					int:
      SCREAMING_SNAKE_CASE_      		=     document.translate(
          str.maketrans(''     ,     ''     ,     string.punctuation				)				).replace('\n'     ,     ''				)
      SCREAMING_SNAKE_CASE_      		=     document_without_punctuation.split(' '				)  # word tokenization
      return len([word for word in tokenize_document if word.lower() == term.lower()]				)

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

def    UpperCAmelCase_				( __UpperCAmelCase		:      int     ,     __UpperCAmelCase		:      int     ,     __UpperCAmelCase		:      int=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    UpperCAmelCase_				( __UpperCAmelCase		:      int     ,     __UpperCAmelCase		:      int				)   ->					float:
      return round(tf * idf     ,     3				)





import warnings

from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor


lowerCamelCase__					:  Union[str, Any]      							=				logging.get_logger(__name__)





class 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE   ):


 '''simple docstring'''







 def __init__(				self    :						Dict							,							*_lowerCAmelCase    :						Optional[Any]							,							**_lowerCAmelCase    :						Any		):
       warnings.warn(
           'The class LayoutLMv2FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
           ' Please use LayoutLMv2ImageProcessor instead.'							,							_lowerCAmelCase							,							)
       super().__init__(*_lowerCAmelCase							,							**_lowerCAmelCase		)