from __future__ import annotations

UpperCAmelCase							=       "Alexander Joslin"






def 					SCREAMING_SNAKE_CASE_			(		lowerCAmelCase_: int     ):

						if number <= 0:
												snake_case_     :			Dict       =       f"n must be greater than 0. Got n = {number}"
												raise ValueError(lowerCAmelCase_     )

						snake_case_     :			Tuple       =       [number + 1] * (number + 1)

						# starting position
						snake_case_     :			Union[str, Any]       =       0
						for i in range(1 ,	lowerCAmelCase_     ):
												snake_case_     :			int       =       min(table[i + 1] ,	table[i] + 1     )
												# check if out of bounds
												if i * 2 <= number:
																		snake_case_     :			Tuple       =       min(table[i * 2] ,	table[i] + 1     )
												# check if out of bounds
												if i * 3 <= number:
																		snake_case_     :			Dict       =       min(table[i * 3] ,	table[i] + 1     )
						return table[number]


if __name__ == "__main__":
					import doctest

					doctest.testmod()




from typing import TYPE_CHECKING

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


UpperCAmelCase							=       {
    "configuration_nystromformer": ["NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "NystromformerConfig"],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase							=       [
         "NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
         "NystromformerForMaskedLM",
         "NystromformerForMultipleChoice",
         "NystromformerForQuestionAnswering",
         "NystromformerForSequenceClassification",
         "NystromformerForTokenClassification",
         "NystromformerLayer",
         "NystromformerModel",
         "NystromformerPreTrainedModel",
     ]


if TYPE_CHECKING:
     from .configuration_nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_nystromformer import (
              NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              NystromformerForMaskedLM,
              NystromformerForMultipleChoice,
              NystromformerForQuestionAnswering,
              NystromformerForSequenceClassification,
              NystromformerForTokenClassification,
              NystromformerLayer,
              NystromformerModel,
              NystromformerPreTrainedModel,
          )


else:
     import sys

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



