






"""simple docstring"""







def _a			(		_snake_case = 1				,	_snake_case = 1000							):







      """simple docstring"""






      UpperCAmelCase          =	1
      UpperCAmelCase          =	0

      for divide_by_number in range(_snake_case				,	digit + 1							):
            UpperCAmelCase          =	[]
            UpperCAmelCase          =	numerator
            for _ in range(1				,	digit + 1							):
                  if now_divide in has_been_divided:
                        if longest_list_length < len(_snake_case							):
                              UpperCAmelCase          =	len(_snake_case							)
                              UpperCAmelCase          =	divide_by_number
                  else:
                        has_been_divided.append(_snake_case							)
                        UpperCAmelCase          =	now_divide * 10 % divide_by_number

      return the_digit


# Tests
if __name__ == "__main__":
  import doctest

  doctest.testmod()











"""simple docstring"""







from typing import TYPE_CHECKING

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


_UpperCamelCase					      =  {"""configuration_glpn""": ["""GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GLPNConfig"""]}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _UpperCamelCase					      =  ["""GLPNFeatureExtractor"""]
  _UpperCamelCase					      =  ["""GLPNImageProcessor"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _UpperCamelCase					      =  [
      """GLPN_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """GLPNForDepthEstimation""",
      """GLPNLayer""",
      """GLPNModel""",
      """GLPNPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_glpn import GLPNFeatureExtractor
    from .image_processing_glpn import GLPNImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_glpn import (
        GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
        GLPNForDepthEstimation,
        GLPNLayer,
        GLPNModel,
        GLPNPreTrainedModel,
    )


else:
  import sys

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



