

'''simple docstring'''






import math
class      SCREAMING_SNAKE_CASE__      :




    def __init__( self    ,					lowercase__    ,					lowercase__    ,					lowercase__    ,					lowercase__      ):






          """simple docstring"""






          SCREAMING_SNAKE_CASE_				:      Any					=	x
          SCREAMING_SNAKE_CASE_				:      List[Any]					=	y
          SCREAMING_SNAKE_CASE_				:      List[Any]					=	step_size
          SCREAMING_SNAKE_CASE_				:      int					=	function_to_optimize




    def   __lowerCamelCase				( self      ):






          """simple docstring"""






          return self.function(self.x    ,					self.y      )




    def   __lowerCamelCase				( self      ):






          """simple docstring"""






          SCREAMING_SNAKE_CASE_				:      Any					=	self.step_size
          return [
              SearchProblem(lowercase__    ,					lowercase__    ,					lowercase__    ,					self.function      )
              for x, y in (
                  (self.x - step_size, self.y - step_size),
                  (self.x - step_size, self.y),
                  (self.x - step_size, self.y + step_size),
                  (self.x, self.y - step_size),
                  (self.x, self.y + step_size),
                  (self.x + step_size, self.y - step_size),
                  (self.x + step_size, self.y),
                  (self.x + step_size, self.y + step_size),
              )
          ]




    def __hash__( self      ):






          """simple docstring"""






          return hash(str(self      )      )




    def __eq__( self    ,					lowercase__      ):






          """simple docstring"""






          if isinstance(lowercase__    ,					lowercase__      ):
                return hash(str(self      )      ) == hash(str(lowercase__      )      )
          return False







    def __str__( self      ):






          """simple docstring"""






          return F"x: {self.x} y: {self.y}"






def  __lowerCamelCase      (				SCREAMING_SNAKE_CASE_					:     Optional[Any]  ,  SCREAMING_SNAKE_CASE_					:     bool = True  ,  SCREAMING_SNAKE_CASE_					:     float = math.inf  ,  SCREAMING_SNAKE_CASE_					:     float = -math.inf  ,  SCREAMING_SNAKE_CASE_					:     float = math.inf  ,  SCREAMING_SNAKE_CASE_					:     float = -math.inf  ,  SCREAMING_SNAKE_CASE_					:     bool = False  ,  SCREAMING_SNAKE_CASE_					:     int = 1_0_0_0_0  ,  )							->       SearchProblem:
      """simple docstring"""

      SCREAMING_SNAKE_CASE_				:      List[Any]					=	search_prob
      SCREAMING_SNAKE_CASE_				:      List[Any]					=	[]  # list to store the current score at each iteration
      SCREAMING_SNAKE_CASE_				:      Dict					=	0
      SCREAMING_SNAKE_CASE_				:      Optional[int]					=	False
      SCREAMING_SNAKE_CASE_				:      Union[str, Any]					=	set()
      while not solution_found and iterations < max_iter:
            visited.add(SCREAMING_SNAKE_CASE_   )
            iterations += 1
            SCREAMING_SNAKE_CASE_				:      int					=	current_state.score()
            scores.append(SCREAMING_SNAKE_CASE_   )
            SCREAMING_SNAKE_CASE_				:      Dict					=	current_state.get_neighbors()
            SCREAMING_SNAKE_CASE_				:      List[Any]					=	-math.inf
            SCREAMING_SNAKE_CASE_				:      List[Any]					=	math.inf
            SCREAMING_SNAKE_CASE_				:      Optional[int]					=	None  # to hold the next best neighbor
            for neighbor in neighbors:
                  if neighbor in visited:
                        continue  # do not want to visit the same state again
                  if (
                      neighbor.x > max_x
                      or neighbor.x < min_x
                      or neighbor.y > max_y
                      or neighbor.y < min_y
                  ):
                        continue  # neighbor outside our bounds
                  SCREAMING_SNAKE_CASE_				:      int					=	neighbor.score() - current_score
                  if find_max:  # finding max
                        # going to direction with greatest ascent
                        if change > max_change and change > 0:
                              SCREAMING_SNAKE_CASE_				:      Optional[Any]					=	change
                              SCREAMING_SNAKE_CASE_				:      Tuple					=	neighbor
                  else:  # finding min
                        # to direction with greatest descent
                        if change < min_change and change < 0:
                              SCREAMING_SNAKE_CASE_				:      Union[str, Any]					=	change
                              SCREAMING_SNAKE_CASE_				:      str					=	neighbor
            if next_state is not None:
                  # we found at least one neighbor which improved the current state
                  SCREAMING_SNAKE_CASE_				:      Any					=	next_state
            else:
                  # since we have no neighbor that improves the solution we stop the search
                  SCREAMING_SNAKE_CASE_				:      Any					=	True

      if visualization:
            from matplotlib import pyplot as plt

            plt.plot(range(SCREAMING_SNAKE_CASE_   )  ,  SCREAMING_SNAKE_CASE_   )
            plt.xlabel("Iterations"   )
            plt.ylabel("Function values"   )
            plt.show()

      return current_state


if __name__ == "__main__":
      import doctest

      doctest.testmod()


      def  __lowerCamelCase      (				SCREAMING_SNAKE_CASE_					:     Optional[Any]  ,  SCREAMING_SNAKE_CASE_					:     Tuple   )							->       Tuple:
            """simple docstring"""

            return (x**2) + (y**2)

      # starting the problem with initial coordinates (3, 4)
      snake_case_					  =	SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
      snake_case_					  =	hill_climbing(prob, find_max=False)
      print(
          'The minimum score for f(x, y) = x^2 + y^2 found via hill climbing: '
          F'''{local_min.score()}'''
      )

      # starting the problem with initial coordinates (12, 47)
      snake_case_					  =	SearchProblem(x=1_2, y=4_7, step_size=1, function_to_optimize=test_fa)
      snake_case_					  =	hill_climbing(
          prob, find_max=False, max_x=1_0_0, min_x=5, max_y=5_0, min_y=-5, visualization=True
      )
      print(
          'The minimum score for f(x, y) = x^2 + y^2 with the domain 100 > x > 5 '
          F'''and 50 > y > - 5 found via hill climbing: {local_min.score()}'''
      )


      def  __lowerCamelCase      (				SCREAMING_SNAKE_CASE_					:     Optional[Any]  ,  SCREAMING_SNAKE_CASE_					:     Union[str, Any]   )							->       Optional[Any]:
            """simple docstring"""

            return (3 * x**2) - (6 * y)

      snake_case_					  =	SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
      snake_case_					  =	hill_climbing(prob, find_max=True)





      print(
          'The maximum score for f(x, y) = x^2 + y^2 found via hill climbing: '
          F'''{local_min.score()}'''
      )




'''simple docstring'''






import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import AddedToken, PreTrainedTokenizerFast
from ...utils import logging


snake_case_					  =	logging.get_logger(__name__)

snake_case_					  =	{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

snake_case_					  =	{
    'vocab_file': {
        'TsinghuaAI/CPM-Generate': 'https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        'TsinghuaAI/CPM-Generate': 'https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/tokenizer.json',
    },
}
class      SCREAMING_SNAKE_CASE__      (    _UpperCAmelCase				):




    def __init__( self    ,					lowercase__=None    ,					lowercase__=None    ,					lowercase__=False    ,					lowercase__=True    ,					lowercase__=False    ,					lowercase__="<s>"    ,					lowercase__="</s>"    ,					lowercase__="<unk>"    ,					lowercase__="<sep>"    ,					lowercase__="<pad>"    ,					lowercase__="<cls>"    ,					lowercase__="<mask>"    ,					lowercase__=["<eop>", "<eod>"]    ,					**lowercase__    ,					):






          """simple docstring"""






          SCREAMING_SNAKE_CASE_				:      Tuple					=	AddedToken(lowercase__    ,					lstrip=lowercase__    ,					rstrip=lowercase__      ) if isinstance(lowercase__    ,					lowercase__      ) else mask_token

          super().__init__(
              vocab_file=lowercase__    ,					tokenizer_file=lowercase__    ,					do_lower_case=lowercase__    ,					remove_space=lowercase__    ,					keep_accents=lowercase__    ,					bos_token=lowercase__    ,					eos_token=lowercase__    ,					unk_token=lowercase__    ,					sep_token=lowercase__    ,					pad_token=lowercase__    ,					cls_token=lowercase__    ,					mask_token=lowercase__    ,					additional_special_tokens=lowercase__    ,					**lowercase__    ,					)

          SCREAMING_SNAKE_CASE_				:      List[str]					=	3
          SCREAMING_SNAKE_CASE_				:      Optional[int]					=	do_lower_case
          SCREAMING_SNAKE_CASE_				:      Optional[int]					=	remove_space
          SCREAMING_SNAKE_CASE_				:      Union[str, Any]					=	keep_accents
          SCREAMING_SNAKE_CASE_				:      List[str]					=	vocab_file
          SCREAMING_SNAKE_CASE_				:      List[Any]					=	False if not self.vocab_file else True

          try:
                import jieba
          except ModuleNotFoundError as error:
                raise error.__class__(
                    "You need to install jieba to use CpmTokenizer or CpmTokenizerFast. "
                    "See https://pypi.org/project/jieba/ for installation."      )
          SCREAMING_SNAKE_CASE_				:      Dict					=	jieba
          SCREAMING_SNAKE_CASE_				:      Optional[Any]					=	str.maketrans(" \n"    ,					"\u2582\u2583"      )




    def   __lowerCamelCase				( self    ,					lowercase__    ,					lowercase__ = None      ):






          """simple docstring"""






          SCREAMING_SNAKE_CASE_				:      Union[str, Any]					=	[self.sep_token_id]
          SCREAMING_SNAKE_CASE_				:      List[Any]					=	[self.cls_token_id]
          if token_ids_a is None:
                return token_ids_a + sep + cls
          return token_ids_a + sep + token_ids_a + sep + cls




    def   __lowerCamelCase				( self    ,					lowercase__    ,					lowercase__ = None      ):






          """simple docstring"""






          SCREAMING_SNAKE_CASE_				:      List[Any]					=	[self.sep_token_id]
          SCREAMING_SNAKE_CASE_				:      Dict					=	[2]

          if token_ids_a is None:
                return len(token_ids_a + sep      ) * [0] + cls_segment_id
          return len(token_ids_a + sep      ) * [0] + len(token_ids_a + sep      ) * [1] + cls_segment_id




    def   __lowerCamelCase				( self    ,					lowercase__    ,					lowercase__ = None      ):






          """simple docstring"""






          if not self.can_save_slow_tokenizer:
                raise ValueError(
                    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
                    "tokenizer."      )

          if not os.path.isdir(lowercase__      ):
                logger.error(F"Vocabulary path ({save_directory}) should be a directory"      )
                return
          SCREAMING_SNAKE_CASE_				:      str					=	os.path.join(
              lowercase__    ,					(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]      )

          if os.path.abspath(self.vocab_file      ) != os.path.abspath(lowercase__      ):
                copyfile(self.vocab_file    ,					lowercase__      )

          return (out_vocab_file,)




    def   __lowerCamelCase				( self    ,					lowercase__    ,					*lowercase__    ,					**lowercase__      ):






          """simple docstring"""






          SCREAMING_SNAKE_CASE_				:      int					=	[
              " ".join([x.translate(self.translator      ) for x in self.jieba.cut(lowercase__    ,					cut_all=lowercase__      )]      )
              for text in batch_text_or_text_pairs
          ]
          return super()._batch_encode_plus(lowercase__    ,					*lowercase__    ,					**lowercase__      )







    def   __lowerCamelCase				( self    ,					*lowercase__    ,					**lowercase__      ):






          """simple docstring"""






          SCREAMING_SNAKE_CASE_				:      Dict					=	super()._decode(*lowercase__    ,					**lowercase__      )
          SCREAMING_SNAKE_CASE_				:      str					=	text.replace(" "    ,					""      ).replace("\u2582"    ,					" "      ).replace("\u2583"    ,					"\n"      )
          return text

