'''simple docstring'''

from __future__ import annotations

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







class     _lowercase					(    UpperCAmelCase__      ):


 '''simple docstring'''






 _SCREAMING_SNAKE_CASE					:	str				     = 1
 _SCREAMING_SNAKE_CASE					:	int				     = 2
 _SCREAMING_SNAKE_CASE					:	List[Any]				     = 3
 def __repr__(				self       :     Union[str, Any]							)  ->   int:
  return f"""{self.__class__.__name__}.{self.name}"""







def 					UpperCamelCase_						( snake_case_	:	tuple[int, int]						,		snake_case_	:	int						,		snake_case_	:	int				) ->					float:






 '''simple docstring'''

 __lowerCAmelCase							,	__lowerCAmelCase    							=						point
 return degrees(atana(y - miny						,		x - minx				)				)







def 					UpperCamelCase_						( snake_case_	:	tuple[int, int]						,		snake_case_	:	tuple[int, int]						,		snake_case_	:	tuple[int, int]				) ->					Direction:






 '''simple docstring'''

 __lowerCAmelCase							,	__lowerCAmelCase    							=						starting
 __lowerCAmelCase							,	__lowerCAmelCase    							=						via
 __lowerCAmelCase							,	__lowerCAmelCase    							=						target
 __lowerCAmelCase    							=						degrees(atana(ya - ya						,		xa - xa				)				)
 via_angle %= 3_60
 __lowerCAmelCase    							=						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 					UpperCamelCase_						( snake_case_	:	list[tuple[int, int]]				) ->					list[tuple[int, int]]:






 '''simple docstring'''

 if len(snake_case_				) <= 2:
  # There is no convex hull
  raise ValueError("""graham_scan: argument must contain more than 3 points."""				)
 if len(snake_case_				) == 3:
  return points
 # find the lowest and the most left point
 __lowerCAmelCase    							=						0
 __lowerCAmelCase							,	__lowerCAmelCase    							=						maxsize, maxsize
 for i, point in enumerate(snake_case_				):
  __lowerCAmelCase    							=						point[0]
  __lowerCAmelCase    							=						point[1]
  if y < miny:
   __lowerCAmelCase    							=						y
   __lowerCAmelCase    							=						x
   __lowerCAmelCase    							=						i
  if y == miny and x < minx:
   __lowerCAmelCase    							=						x
   __lowerCAmelCase    							=						i

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

 __lowerCAmelCase    							=						sorted(snake_case_						,		key=lambda snake_case_				: angle_comparer(snake_case_						,		snake_case_						,		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)				)

 __lowerCAmelCase    							=						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.
 __lowerCAmelCase    							=						Direction.left

 for i in range(3						,		len(snake_case_				)				):
  while True:
   __lowerCAmelCase    							=						stack[-2]
   __lowerCAmelCase    							=						stack[-1]
   __lowerCAmelCase    							=						sorted_points[i]
   __lowerCAmelCase    							=						check_direction(snake_case_						,		snake_case_						,		snake_case_				)

   if next_direction == Direction.left:
    __lowerCAmelCase    							=						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(snake_case_				)







'''simple docstring'''

import argparse

from transformers import CanineConfig, CanineModel, CanineTokenizer, load_tf_weights_in_canine
from transformers.utils import logging


logging.set_verbosity_info()







def 					UpperCamelCase_						( snake_case_	:	List[str]						,		snake_case_	:	Optional[Any]				) ->					Tuple:






 '''simple docstring'''

 __lowerCAmelCase    							=						CanineConfig()
 __lowerCAmelCase    							=						CanineModel(snake_case_				)
 model.eval()

 print(f"""Building PyTorch model from configuration: {config}"""				)

 # Load weights from tf checkpoint
 load_tf_weights_in_canine(snake_case_						,		snake_case_						,		snake_case_				)

 # Save pytorch-model (weights and configuration)
 print(f"""Save PyTorch model to {pytorch_dump_path}"""				)
 model.save_pretrained(snake_case_				)

 # Save tokenizer files
 __lowerCAmelCase    							=						CanineTokenizer()
 print(f"""Save tokenizer files to {pytorch_dump_path}"""				)
 tokenizer.save_pretrained(snake_case_				)


if __name__ == "__main__":
 _A      :				int 				=    argparse.ArgumentParser()
 # Required parameters
 parser.add_argument(
     '''--tf_checkpoint_path''',
     default=None,
     type=str,
     required=True,
     help='''Path to the TensorFlow checkpoint. Should end with model.ckpt''',
 )
 parser.add_argument(
     '''--pytorch_dump_path''',
     default=None,
     type=str,
     required=True,
     help='''Path to a folder where the PyTorch model will be placed.''',
 )
 _A      :				Dict 				=    parser.parse_args()
 convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.pytorch_dump_path)






