
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase_  :	List[Any] 				=					{
    """configuration_megatron_bert""": ["""MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MegatronBertConfig"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCamelCase_  :	Optional[int] 				=					[
							    """MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """MegatronBertForCausalLM""",
							    """MegatronBertForMaskedLM""",
							    """MegatronBertForMultipleChoice""",
							    """MegatronBertForNextSentencePrediction""",
							    """MegatronBertForPreTraining""",
							    """MegatronBertForQuestionAnswering""",
							    """MegatronBertForSequenceClassification""",
							    """MegatronBertForTokenClassification""",
							    """MegatronBertModel""",
							    """MegatronBertPreTrainedModel""",
							]

if TYPE_CHECKING:
							from .configuration_megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_megatron_bert import (
														    MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MegatronBertForCausalLM,
														    MegatronBertForMaskedLM,
														    MegatronBertForMultipleChoice,
														    MegatronBertForNextSentencePrediction,
														    MegatronBertForPreTraining,
														    MegatronBertForQuestionAnswering,
														    MegatronBertForSequenceClassification,
														    MegatronBertForTokenClassification,
														    MegatronBertModel,
														    MegatronBertPreTrainedModel,
														)

else:
							import sys

							lowerCamelCase_  :	Dict 				=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)








def     A__   (  lowerCamelCase       ,      lowerCamelCase  )					->		list:
				UpperCamelCase_:							Optional[int]		=  word.split()

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

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


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

							testmod()






