




from math import ceil







def lowerCamelCase__       (      _lowercase			,						_lowercase				):

     '''simple docstring'''


     UpperCAmelCase_      :							Union[str, Any]       =      list(range(0			,						_lowercase				)				)

     UpperCAmelCase_      :							Optional[int]       =      [item for sublist in list(device_map.values()				) for item in sublist]

     # Duplicate check
     UpperCAmelCase_      :							List[Any]       =      []
     for i in device_map_blocks:
          if device_map_blocks.count(_lowercase				) > 1 and i not in duplicate_blocks:
               duplicate_blocks.append(_lowercase				)
    # Missing blocks
     UpperCAmelCase_      :							Any       =      [i for i in blocks if i not in device_map_blocks]
     UpperCAmelCase_      :							Union[str, Any]       =      [i for i in device_map_blocks if i not in blocks]

     if len(_lowercase				) != 0:
          raise ValueError(
              '''Duplicate attention blocks specified in device_map. Attention blocks must be specified to one device.'''
              ''' These attention blocks were specified more than once: ''' + str(_lowercase				)				)
     if len(_lowercase				) != 0:
          raise ValueError(
              '''There are attention blocks for this model that are not specified in the device_map. Add these attention '''
              '''blocks to a device on the device_map: ''' + str(_lowercase				)				)
     if len(_lowercase				) != 0:
          raise ValueError(
              '''The device_map contains more attention blocks than this model has. Remove these from the device_map:'''
              + str(_lowercase				)				)







def lowerCamelCase__       (      _lowercase			,						_lowercase				):

     '''simple docstring'''


     UpperCAmelCase_      :							Dict       =      list(range(_lowercase				)				)
     UpperCAmelCase_      :							Optional[Any]       =      int(ceil(n_layers / len(_lowercase				)				)				)
     UpperCAmelCase_      :							str       =      [layers[i : i + n_blocks] for i in range(0			,						_lowercase			,						_lowercase				)]

     return dict(zip(_lowercase			,						_lowercase				)				)





def lowerCamelCase__       (      _lowercase			,						_lowercase				):

     '''simple docstring'''


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







def lowerCamelCase__       (      _lowercase			,						_lowercase=0				):

     '''simple docstring'''


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







def lowerCamelCase__       (      _lowercase			,						_lowercase			,						_lowercase=float('''inf'''				)				):

     '''simple docstring'''


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







def lowerCamelCase__       (      _lowercase			,						_lowercase			,						_lowercase=float('''inf'''				)				):

     '''simple docstring'''


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







def lowerCamelCase__       (      _lowercase			,						_lowercase			,						_lowercase				):

     '''simple docstring'''


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

     # recursion
     UpperCAmelCase_      :							Optional[int]       =      points_counts // 2
     UpperCAmelCase_      :							List[Any]       =      closest_pair_of_points_sqr(
         _lowercase			,						points_sorted_on_y[:mid]			,						_lowercase				)
     UpperCAmelCase_      :							Dict       =      closest_pair_of_points_sqr(
         _lowercase			,						points_sorted_on_y[mid:]			,						points_counts - mid				)
     UpperCAmelCase_      :							Union[str, Any]       =      min(_lowercase			,						_lowercase				)
     UpperCAmelCase_      :							str       =      []
     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_      :							Optional[Any]       =      dis_between_closest_in_strip(
         _lowercase			,						len(_lowercase				)			,						_lowercase				)
     return min(_lowercase			,						_lowercase				)







def lowerCamelCase__       (      _lowercase			,						_lowercase				):

     '''simple docstring'''


     UpperCAmelCase_      :							Tuple       =      column_based_sort(_lowercase			,						column=0				)
     UpperCAmelCase_      :							List[Any]       =      column_based_sort(_lowercase			,						column=1				)
     return (
         closest_pair_of_points_sqr(
             _lowercase			,						_lowercase			,						_lowercase				)
     ) ** 0.5


if __name__ == "__main__":
     __a          =			[(2, 3), (12, 30), (40, 50), (5, 1), (12, 10), (3, 4)]
     print('Distance:', closest_pair_of_points(points, len(points)))