






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__A      =				{
    'configuration_biogpt': ['BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BioGptConfig'],
    'tokenization_biogpt': ['BioGptTokenizer'],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__A      =				[
				    'BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'BioGptForCausalLM',
				    'BioGptForTokenClassification',
				    'BioGptForSequenceClassification',
				    'BioGptModel',
				    'BioGptPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
				from .tokenization_biogpt import BioGptTokenizer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_biogpt import (
								    BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    BioGptForCausalLM,
								    BioGptForSequenceClassification,
								    BioGptForTokenClassification,
								    BioGptModel,
								    BioGptPreTrainedModel,
								)


else:
				import sys

				__A      =				_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)














def      __A					(     _lowercase					,			_lowercase ):

					'''simple docstring'''







					_A								= word.split()

					def justify(_lowercase					,			_lowercase					,			_lowercase ) -> str:
										_A								= max_width - width
										_A								= len(_lowercase )
										if len(_lowercase ) == 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								= 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								= spaces_to_insert_between_words * [
															    overall_spaces_count // spaces_to_insert_between_words
															]
															_A								= (
															    overall_spaces_count % spaces_to_insert_between_words
															)
															# distribute spaces via round robin to the left words
															for i in range(_lowercase ):
																				num_spaces_between_words_list[i] += 1
															_A								= []
															for i in range(_lowercase ):
																				# 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(_lowercase )

					_A								= []
					_A								= []
					_A								= 0
					for word in words:
										if width + len(_lowercase ) + len(_lowercase ) <= 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(_lowercase )
															width += len(_lowercase )
										else:
															# justify the line and add it to result
															answer.append(justify(_lowercase					,			_lowercase					,			_lowercase ) )
															# reset new line and new width
															_A							,_A								= [word], len(_lowercase )
					_A								= max_width - width - len(_lowercase )
					answer.append(''' '''.join(_lowercase ) + (remaining_spaces + 1) * ''' ''' )
					return answer


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

				testmod()



