


def 			_a  (				SCREAMING_SNAKE_CASE	:				int    , SCREAMING_SNAKE_CASE	:				List[str]     ):







 """simple docstring"""



 UpperCamelCase__					:    Dict          =   word.split()

 def justify(SCREAMING_SNAKE_CASE	:				Tuple    , SCREAMING_SNAKE_CASE	:				Any    , SCREAMING_SNAKE_CASE	:				Optional[Any]     ) -> str:
  UpperCamelCase__					:    List[Any]          =   max_width - width
  UpperCamelCase__					:    Tuple          =   len(__snake_case     )
  if len(__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:
   UpperCamelCase__					:    Optional[int]          =   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]
   UpperCamelCase__					:    Union[str, Any]          =   spaces_to_insert_between_words * [
       overall_spaces_count // spaces_to_insert_between_words
   ]
   UpperCamelCase__					:    List[Any]          =   (
       overall_spaces_count % spaces_to_insert_between_words
   )
   # distribute spaces via round robin to the left words
   for i in range(__snake_case     ):
    num_spaces_between_words_list[i] += 1
   UpperCamelCase__					:    str          =   []
   for i in range(__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(__snake_case     )

 UpperCamelCase__					:    Optional[int]          =   []
 UpperCamelCase__					:    Any          =   []
 UpperCamelCase__					:    int          =   0
 for word in words:
  if width + len(__snake_case     ) + len(__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(__snake_case     )
   width += len(__snake_case     )
  else:
   # justify the line and add it to result
   answer.append(justify(__snake_case    , __snake_case    , __snake_case     )     )
   # reset new line and new width
   UpperCamelCase__       ,				UpperCamelCase__					:    Dict          =   [word], len(__snake_case     )
 UpperCamelCase__					:    Optional[Any]          =   max_width - width - len(__snake_case     )
 answer.append(''' '''.join(__snake_case     ) + (remaining_spaces + 1) * ''' '''     )
 return answer


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

       testmod()






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


__UpperCamelCase       :       Dict						       =				{
    "configuration_trocr": ["TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP", "TrOCRConfig"],
    "processing_trocr": ["TrOCRProcessor"],
}


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase       :       Optional[int]						       =				[
           "TROCR_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TrOCRForCausalLM",
           "TrOCRPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig
       from .processing_trocr import TrOCRProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_trocr import TROCR_PRETRAINED_MODEL_ARCHIVE_LIST, TrOCRForCausalLM, TrOCRPreTrainedModel

else:
       import sys

       __UpperCamelCase       :       Tuple						       =				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


