'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


snake_case__     :			Optional[Any]      			=  {'''configuration_regnet''': ['''REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RegNetConfig''']}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__     :			Union[str, Any]      			=  [
     '''REGNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''RegNetForImageClassification''',
     '''RegNetModel''',
     '''RegNetPreTrainedModel''',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__     :			Union[str, Any]      			=  [
     '''TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''TFRegNetForImageClassification''',
     '''TFRegNetModel''',
     '''TFRegNetPreTrainedModel''',
 ]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__     :			Optional[Any]      			=  [
     '''FlaxRegNetForImageClassification''',
     '''FlaxRegNetModel''',
     '''FlaxRegNetPreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_regnet import (
      REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
      RegNetForImageClassification,
      RegNetModel,
      RegNetPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_regnet import (
      TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFRegNetForImageClassification,
      TFRegNetModel,
      TFRegNetPreTrainedModel,
  )

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_regnet import (
      FlaxRegNetForImageClassification,
      FlaxRegNetModel,
      FlaxRegNetPreTrainedModel,
  )


else:
 import sys

 snake_case__     :			str      			=  _LazyModule(__name__, globals()['''__file__'''], _import_structure)







'''simple docstring'''


from __future__ import annotations

from collections import deque
from enum import Enum
from math import atana, degrees
from sys import maxsize






class      __SCREAMING_SNAKE_CASE						(       lowerCamelCase_       ):







  '''simple docstring'''






  lowerCamelCase_		:Union[str, Any]						    =		1
  lowerCamelCase_		:List[Any]						    =		2
  lowerCamelCase_		:Optional[Any]						    =		3


  def __repr__( self						):




       '''simple docstring'''

       return F'''{self.__class__.__name__}.{self.name}'''







def 					_lowerCamelCase    (      lowerCamelCase_					:							tuple[int, int]	,     lowerCamelCase_					:							int	,     lowerCamelCase_					:							int   ):



     """simple docstring"""





     UpperCAmelCase_   ,			UpperCAmelCase_							:   Any   =      point
     return degrees(atana(y - miny	,     x - minx   )   )


def 					_lowerCamelCase    (      lowerCamelCase_					:							tuple[int, int]	,     lowerCamelCase_					:							tuple[int, int]	,     lowerCamelCase_					:							tuple[int, int]   ):



     """simple docstring"""





     UpperCAmelCase_   ,			UpperCAmelCase_							:   str   =      starting
     UpperCAmelCase_   ,			UpperCAmelCase_							:   Optional[int]   =      via
     UpperCAmelCase_   ,			UpperCAmelCase_							:   Dict   =      target
     UpperCAmelCase_							:   Optional[Any]   =      degrees(atana(ya - ya	,     xa - xa   )   )
     via_angle %= 360
     UpperCAmelCase_							:   Optional[Any]   =      degrees(atana(ya - ya	,     xa - xa   )   )
     target_angle %= 360
     # t-
     #  \ \
     #   \ v
     #    \|
     #     s
     # via_angle is always lower than target_angle, if direction is left.
     # If they are same, it means they are on a same line of convex hull.
     if target_angle > via_angle:
          return Direction.left
     elif target_angle == via_angle:
          return Direction.straight
     else:
          return Direction.right





def 					_lowerCamelCase    (      lowerCamelCase_					:							list[tuple[int, int]]   ):



     """simple docstring"""





     if len(lowerCamelCase_   ) <= 2:
          # There is no convex hull
          raise ValueError('graham_scan: argument must contain more than 3 points.'   )
     if len(lowerCamelCase_   ) == 3:
          return points
     # find the lowest and the most left point
     UpperCAmelCase_							:   Dict   =      0
     UpperCAmelCase_   ,			UpperCAmelCase_							:   Union[str, Any]   =      maxsize, maxsize
     for i, point in enumerate(lowerCamelCase_   ):
          UpperCAmelCase_							:   Union[str, Any]   =      point[0]
          UpperCAmelCase_							:   List[Any]   =      point[1]
          if y < miny:
               UpperCAmelCase_							:   Dict   =      y
               UpperCAmelCase_							:   Optional[int]   =      x
               UpperCAmelCase_							:   Optional[Any]   =      i
          if y == miny and x < minx:
               UpperCAmelCase_							:   Union[str, Any]   =      x
               UpperCAmelCase_							:   Dict   =      i

    # remove the lowest and the most left point from points for preparing for sort
     points.pop(lowerCamelCase_   )

     UpperCAmelCase_							:   List[str]   =      sorted(lowerCamelCase_	,     key=lambda lowerCamelCase_   : angle_comparer(lowerCamelCase_	,     lowerCamelCase_	,     lowerCamelCase_   )   )
     # This insert actually costs complexity,
     # and you should instead add (minx, miny) into stack later.
     # I'm using insert just for easy understanding.
     sorted_points.insert(0	,     (minx, miny)   )

     UpperCAmelCase_							:   deque[tuple[int, int]]   =      deque()
     stack.append(sorted_points[0]   )
     stack.append(sorted_points[1]   )
     stack.append(sorted_points[2]   )
     # In any ways, the first 3 points line are towards left.
     # Because we sort them the angle from minx, miny.
     UpperCAmelCase_							:   List[Any]   =      Direction.left

     for i in range(3	,     len(lowerCamelCase_   )   ):
          while True:
               UpperCAmelCase_							:   Optional[Any]   =      stack[-2]
               UpperCAmelCase_							:   Optional[int]   =      stack[-1]
               UpperCAmelCase_							:   str   =      sorted_points[i]
               UpperCAmelCase_							:   Union[str, Any]   =      check_direction(lowerCamelCase_	,     lowerCamelCase_	,     lowerCamelCase_   )

               if next_direction == Direction.left:
                    UpperCAmelCase_							:   Union[str, Any]   =      Direction.left
                    break
               if next_direction == Direction.straight:
                    if current_direction == Direction.left:
                         # We keep current_direction as left.
                         # Because if the straight line keeps as straight,
                         # we want to know if this straight line is towards left.
                         break
                    elif current_direction == Direction.right:
                         # If the straight line is towards right,
                         # every previous points on those straigh line is not convex hull.
                         stack.pop()
               if next_direction == Direction.right:
                    stack.pop()
          stack.append(sorted_points[i]   )
     return list(lowerCamelCase_   )






