


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE							    =							{
    'configuration_upernet': ['UperNetConfig'],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE							    =							[
      'UperNetForSemanticSegmentation',
      'UperNetPreTrainedModel',
  ]


if TYPE_CHECKING:
  from .configuration_upernet import UperNetConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_upernet import UperNetForSemanticSegmentation, UperNetPreTrainedModel


else:
  import sys

  SCREAMING_SNAKE_CASE							    =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)







def 		_A		(		_lowercase					,  _lowercase )					-> int:


     """simple docstring"""


     return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2






def 		_A		(		_lowercase					,  _lowercase=0 )					-> Dict:


     """simple docstring"""


     return sorted(_lowercase					,  key=lambda _lowercase : x[column] )






def 		_A		(		_lowercase					,  _lowercase					,  _lowercase=float('inf' ) )					-> List[Any]:


     """simple docstring"""


     for i in range(points_counts - 1 ):
          for j in range(i + 1					,  _lowercase ):
               __UpperCamelCase =			euclidean_distance_sqr(points[i]					,  points[j] )
               if current_dis < min_dis:
                    __UpperCamelCase =			current_dis
     return min_dis






def 		_A		(		_lowercase					,  _lowercase					,  _lowercase=float('inf' ) )					-> Tuple:


     """simple docstring"""


     for i in range(min(6					,  points_counts - 1 )					,  _lowercase ):
          for j in range(max(0					,  i - 6 )					,  _lowercase ):
               __UpperCamelCase =			euclidean_distance_sqr(points[i]					,  points[j] )
               if current_dis < min_dis:
                    __UpperCamelCase =			current_dis
     return min_dis






def 		_A		(		_lowercase					,  _lowercase					,  _lowercase )					-> Optional[Any]:


     """simple docstring"""


     if points_counts <= 3:
          return dis_between_closest_pair(_lowercase					,  _lowercase )

     # recursion
     __UpperCamelCase =			points_counts // 2
     __UpperCamelCase =			closest_pair_of_points_sqr(
         _lowercase					,  points_sorted_on_y[:mid]					,  _lowercase )
     __UpperCamelCase =			closest_pair_of_points_sqr(
         _lowercase					,  points_sorted_on_y[mid:]					,  points_counts - mid )
     __UpperCamelCase =			min(_lowercase					,  _lowercase )
     __UpperCamelCase =			[]
     for point in points_sorted_on_x:
          if abs(point[0] - points_sorted_on_x[mid][0] ) < closest_pair_dis:
               cross_strip.append(_lowercase )

     __UpperCamelCase =			dis_between_closest_in_strip(
         _lowercase					,  len(_lowercase )					,  _lowercase )
     return min(_lowercase					,  _lowercase )






def 		_A		(		_lowercase					,  _lowercase )					-> Optional[int]:


     """simple docstring"""


     __UpperCamelCase =			column_based_sort(_lowercase					,  column=0 )
     __UpperCamelCase =			column_based_sort(_lowercase					,  column=1 )
     return (
         closest_pair_of_points_sqr(
             _lowercase					,  _lowercase					,  _lowercase )
     ) ** 0.5


if __name__ == "__main__":
    __snake_case   							=						[(2, 3), (1_2, 3_0), (4_0, 5_0), (5, 1), (1_2, 1_0), (3, 4)]
    print('''Distance:''', closest_pair_of_points(points, len(points)))


