






def _UpperCAmelCase   (	a						:	str  ,					a						:	int ):
							snake_case__	  =       word.split()

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

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


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

	testmod()








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a__       =     {
    """configuration_lilt""": ["""LILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LiltConfig"""],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a__       =     [
	    """LILT_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """LiltForQuestionAnswering""",
	    """LiltForSequenceClassification""",
	    """LiltForTokenClassification""",
	    """LiltModel""",
	    """LiltPreTrainedModel""",
	]

if TYPE_CHECKING:
	from .configuration_lilt import LILT_PRETRAINED_CONFIG_ARCHIVE_MAP, LiltConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_lilt import (
		    LILT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    LiltForQuestionAnswering,
		    LiltForSequenceClassification,
		    LiltForTokenClassification,
		    LiltModel,
		    LiltPreTrainedModel,
		)

else:
	import sys

	a__       =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
