





def 					_A	(		SCREAMING_SNAKE_CASE					:       str	,	SCREAMING_SNAKE_CASE					:       int						):





  """simple docstring"""



  a__     : Union[str, Any]  =word.split()

  def justify(SCREAMING_SNAKE_CASE					:       list	,	SCREAMING_SNAKE_CASE					:       int	,	SCREAMING_SNAKE_CASE					:       int						) -> str:
    a__     : Dict  =max_width - width
    a__     : Dict  =len(SCREAMING_SNAKE_CASE						)
    if len(SCREAMING_SNAKE_CASE						) == 1:
      # if there is only word in line
      # just insert overall_spaces_count for the remainder of line
      return line[0] + " " * overall_spaces_count
    else:
      a__     : List[str]  =words_count - 1
      # num_spaces_between_words_list[i] : tells you to insert
      # num_spaces_between_words_list[i] spaces
      # after word on line[i]
      a__     : Tuple  =spaces_to_insert_between_words * [
          overall_spaces_count // spaces_to_insert_between_words
      ]
      a__     : int  =(
          overall_spaces_count % spaces_to_insert_between_words
      )
      # distribute spaces via round robin to the left words
      for i in range(SCREAMING_SNAKE_CASE						):
        num_spaces_between_words_list[i] += 1
      a__     : int  =[]
      for i in range(SCREAMING_SNAKE_CASE						):
        # add the word
        aligned_words_list.append(line[i]						)
        # add the spaces to insert
        aligned_words_list.append(num_spaces_between_words_list[i] * " "						)
      # just add the last word to the sentence
      aligned_words_list.append(line[-1]						)
      # join the aligned words list to form a justified line
      return "".join(SCREAMING_SNAKE_CASE						)

  a__     : int  =[]
  a__     : list[str]  =[]
  a__     : List[str]  =0
  for word in words:
    if width + len(SCREAMING_SNAKE_CASE						) + len(SCREAMING_SNAKE_CASE						) <= max_width:
      # keep adding words until we can fill out max_width
      # width = sum of length of all words (without overall_spaces_count)
      # len(word) = length of current word
      # len(line) = number of overall_spaces_count to insert between words
      line.append(SCREAMING_SNAKE_CASE						)
      width += len(SCREAMING_SNAKE_CASE						)
    else:
      # justify the line and add it to result
      answer.append(justify(SCREAMING_SNAKE_CASE	,	SCREAMING_SNAKE_CASE	,	SCREAMING_SNAKE_CASE						)						)
      # reset new line and new width
      a__ ,							a__     : Optional[int]  =[word], len(SCREAMING_SNAKE_CASE						)
  a__     : List[Any]  =max_width - width - len(SCREAMING_SNAKE_CASE						)
  answer.append(" ".join(SCREAMING_SNAKE_CASE						) + (remaining_spaces + 1) * " "						)
  return answer


if __name__ == "__main__":
     from doctest import testmod

     testmod()













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

from ..features import ClassLabel, Features, Image
from .base import TaskTemplate







@dataclass(frozen=UpperCamelCase__)
class     __lowerCAmelCase	(   UpperCamelCase__):
      _lowercase    : str            =      field(default="""image-classification"""						,    metadata={"""include_in_asdict_even_if_is_default""": True})
      _lowercase    : ClassVar[Features]            =      Features({"""image""": Image()})
      _lowercase    : ClassVar[Features]            =      Features({"""labels""": ClassLabel})
      _lowercase    : str            =      "image"
      _lowercase    : str            =      "labels"







      def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						List[Any]:



        '''simple docstring'''




        if self.label_column not in features:
          raise ValueError(F'''Column {self.label_column} is not present in features.'''							)
        if not isinstance(features[self.label_column]		,				lowerCAmelCase__							):
          raise ValueError(F'''Column {self.label_column} is not a ClassLabel.'''							)
        a__     : int  =copy.deepcopy(self							)
        a__     : Dict  =self.label_schema.copy()
        a__     : int  =features[self.label_column]
        a__     : str  =label_schema
        return task_template







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



        '''simple docstring'''




        return {
            self.image_column: "image",
            self.label_column: "labels",
        }






