



"""simple docstring"""







def     UpperCamelCase_   (   lowerCAmelCase__				:    Tuple   ,       lowerCAmelCase__				:    Tuple						)						->       Union[str, Any]:

  """simple docstring"""




  lowerCAmelCase_       :    Optional[int]								=			[1]
  for i in range(2   ,       lowerCAmelCase__						):
    factorials.append(factorials[-1] * i						)
  assert 0 <= k < factorials[-1] * n, "k out of bounds"

  lowerCAmelCase_       :    str								=			[]
  lowerCAmelCase_       :    int								=			list(range(lowerCAmelCase__						)						)

  # Find permutation
  while factorials:
    lowerCAmelCase_       :    Dict								=			factorials.pop()
    lowerCAmelCase_       :    int								=			divmod(lowerCAmelCase__   ,       lowerCAmelCase__						)
    permutation.append(elements[number]						)
    elements.remove(elements[number]						)
  permutation.append(elements[0]						)

  return permutation


if __name__ == "__main__":
 import doctest

 doctest.testmod()










"""simple docstring"""







from typing import TYPE_CHECKING

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


lowercase__		:    Optional[int]				   =     {
    """configuration_trocr""": ["""TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TrOCRConfig"""],
    """processing_trocr""": ["""TrOCRProcessor"""],
}


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__		:    Dict				   =     [
         """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

     lowercase__		:    int				   =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





