code: 
  
  
  from __future__ import annotations
  
  from collections import deque
  from enum import Enum
  from math import atana, degrees
  from sys import maxsize
  
  
  
  
  
  class 					snake_case__  ( __A       ):
  	UpperCAmelCase   :							List[str]         = 1
  	UpperCAmelCase   :							List[str]         = 2
  	UpperCAmelCase   :							Optional[int]         = 3
  
  
  
  
  
  	def __repr__(  self							)		->			List[str]:
  								"""simple docstring"""
  
  
  
  
  
  
  								return f"""{self.__class__.__name__}.{self.name}"""
  
  
  
  
  
  def 						_lowerCamelCase		(							SCREAMING_SNAKE_CASE_				: tuple[int, int]	,	SCREAMING_SNAKE_CASE_				: int	,	SCREAMING_SNAKE_CASE_				: int      ):
  
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  							a_		,				a_       :   Optional[Any]			=	point
  							return degrees(atana(y - miny	,	x - minx      )      )
  
  
  
  
  
  def 						_lowerCamelCase		(							SCREAMING_SNAKE_CASE_				: tuple[int, int]	,	SCREAMING_SNAKE_CASE_				: tuple[int, int]	,	SCREAMING_SNAKE_CASE_				: tuple[int, int]      ):
  
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  							a_		,				a_       :   int			=	starting
  							a_		,				a_       :   List[str]			=	via
  							a_		,				a_       :   Dict			=	target
  							a_       :   List[Any]			=	degrees(atana(ya - ya	,	xa - xa      )      )
  							via_angle %= 3_60
  							a_       :   int			=	degrees(atana(ya - ya	,	xa - xa      )      )
  							target_angle %= 3_60
  							# 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		(							SCREAMING_SNAKE_CASE_				: list[tuple[int, int]]      ):
  
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  							if len(SCREAMING_SNAKE_CASE_      ) <= 2:
  														# There is no convex hull
  														raise ValueError("""graham_scan: argument must contain more than 3 points."""      )
  							if len(SCREAMING_SNAKE_CASE_      ) == 3:
  														return points
  							# find the lowest and the most left point
  							a_       :   List[str]			=	0
  							a_		,				a_       :   Dict			=	maxsize, maxsize
  							for i, point in enumerate(SCREAMING_SNAKE_CASE_      ):
  														a_       :   Optional[int]			=	point[0]
  														a_       :   List[Any]			=	point[1]
  														if y < miny:
  																					a_       :   Union[str, Any]			=	y
  																					a_       :   Optional[Any]			=	x
  																					a_       :   Dict			=	i
  														if y == miny and x < minx:
  																					a_       :   Dict			=	x
  																					a_       :   Dict			=	i
  
      # remove the lowest and the most left point from points for preparing for sort
  							points.pop(SCREAMING_SNAKE_CASE_      )
  
  							a_       :   Tuple			=	sorted(SCREAMING_SNAKE_CASE_	,	key=lambda SCREAMING_SNAKE_CASE_      : angle_comparer(SCREAMING_SNAKE_CASE_	,	SCREAMING_SNAKE_CASE_	,	SCREAMING_SNAKE_CASE_      )      )
  							# 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)      )
  
  							a_       :   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.
  							a_       :   Optional[Any]			=	Direction.left
  
  							for i in range(3	,	len(SCREAMING_SNAKE_CASE_      )      ):
  														while True:
  																					a_       :   List[str]			=	stack[-2]
  																					a_       :   str			=	stack[-1]
  																					a_       :   Optional[int]			=	sorted_points[i]
  																					a_       :   str			=	check_direction(SCREAMING_SNAKE_CASE_	,	SCREAMING_SNAKE_CASE_	,	SCREAMING_SNAKE_CASE_      )
  
  																					if next_direction == Direction.left:
  																												a_       :   int			=	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(SCREAMING_SNAKE_CASE_      )
  
  
  
style_context: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_sentencepiece_available,
      is_tf_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  SCREAMING_SNAKE_CASE : Optional[Any]          =    {
      "configuration_camembert": ["CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "CamembertConfig", "CamembertOnnxConfig"],
  }
  
  try:
  	if not is_sentencepiece_available():
  		raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  	pass
  else:
  	SCREAMING_SNAKE_CASE : Optional[int]          =    ["CamembertTokenizer"]
  
  try:
  	if not is_tokenizers_available():
  		raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  	pass
  else:
  	SCREAMING_SNAKE_CASE : Any          =    ["CamembertTokenizerFast"]
  
  try:
  	if not is_torch_available():
  		raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  	pass
  else:
  	SCREAMING_SNAKE_CASE : Union[str, Any]          =    [
  	    "CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
  	    "CamembertForCausalLM",
  	    "CamembertForMaskedLM",
  	    "CamembertForMultipleChoice",
  	    "CamembertForQuestionAnswering",
  	    "CamembertForSequenceClassification",
  	    "CamembertForTokenClassification",
  	    "CamembertModel",
  	    "CamembertPreTrainedModel",
  	]
  
  try:
  	if not is_tf_available():
  		raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  	pass
  else:
  	SCREAMING_SNAKE_CASE : List[Any]          =    [
  	    "TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
  	    "TFCamembertForCausalLM",
  	    "TFCamembertForMaskedLM",
  	    "TFCamembertForMultipleChoice",
  	    "TFCamembertForQuestionAnswering",
  	    "TFCamembertForSequenceClassification",
  	    "TFCamembertForTokenClassification",
  	    "TFCamembertModel",
  	    "TFCamembertPreTrainedModel",
  	]
  
  
  if TYPE_CHECKING:
  	from .configuration_camembert import CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, CamembertConfig, CamembertOnnxConfig
  
  	try:
  		if not is_sentencepiece_available():
  			raise OptionalDependencyNotAvailable()
  	except OptionalDependencyNotAvailable:
  		pass
  	else:
  		from .tokenization_camembert import CamembertTokenizer
  
  	try:
  		if not is_tokenizers_available():
  			raise OptionalDependencyNotAvailable()
  	except OptionalDependencyNotAvailable:
  		pass
  	else:
  		from .tokenization_camembert_fast import CamembertTokenizerFast
  
  	try:
  		if not is_torch_available():
  			raise OptionalDependencyNotAvailable()
  	except OptionalDependencyNotAvailable:
  		pass
  	else:
  		from .modeling_camembert import (
  		    CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
  		    CamembertForCausalLM,
  		    CamembertForMaskedLM,
  		    CamembertForMultipleChoice,
  		    CamembertForQuestionAnswering,
  		    CamembertForSequenceClassification,
  		    CamembertForTokenClassification,
  		    CamembertModel,
  		    CamembertPreTrainedModel,
  		)
  
  	try:
  		if not is_tf_available():
  			raise OptionalDependencyNotAvailable()
  	except OptionalDependencyNotAvailable:
  		pass
  	else:
  		from .modeling_tf_camembert import (
  		    TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
  		    TFCamembertForCausalLM,
  		    TFCamembertForMaskedLM,
  		    TFCamembertForMultipleChoice,
  		    TFCamembertForQuestionAnswering,
  		    TFCamembertForSequenceClassification,
  		    TFCamembertForTokenClassification,
  		    TFCamembertModel,
  		    TFCamembertPreTrainedModel,
  		)
  
  else:
  	import sys
  
  	SCREAMING_SNAKE_CASE : Any          =    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
  
  
  