





from queue import Queue
from typing import TYPE_CHECKING, Optional


if TYPE_CHECKING:
      from ..models.auto import AutoTokenizer



class        _lowerCAmelCase    :


  '''simple docstring'''







  def UpperCamelCase_ (      self      :					List[str]      ,				UpperCamelCase      :					Any							):


    '''simple docstring'''





    raise NotImplementedError()







  def UpperCamelCase_ (      self      :					List[Any]							):


    '''simple docstring'''





    raise NotImplementedError()




class        _lowerCAmelCase    (			UpperCAmelCase_							):


  '''simple docstring'''







  def __init__(      self      :					Any      ,				UpperCamelCase      :					"AutoTokenizer"      ,				UpperCamelCase      :					bool = False      ,				**UpperCamelCase      :					Any							):


    '''simple docstring'''





    _snake_case   :				Union[str, Any]														=	tokenizer
    _snake_case   :				Union[str, Any]														=	skip_prompt
    _snake_case   :				List[Any]														=	decode_kwargs

    # variables used in the streaming process
    _snake_case   :				List[Any]														=	[]
    _snake_case   :				Tuple														=	0
    _snake_case   :				int														=	True







  def UpperCamelCase_ (      self      :					Dict      ,				UpperCamelCase      :					Optional[int]							):


    '''simple docstring'''





    if len(value.shape							) > 1 and value.shape[0] > 1:
      raise ValueError('TextStreamer only supports batch size 1'							)
    elif len(value.shape							) > 1:
      _snake_case   :				Union[str, Any]														=	value[0]

    if self.skip_prompt and self.next_tokens_are_prompt:
      _snake_case   :				Dict														=	False
      return

    # Add the new token to the cache and decodes the entire thing.
    self.token_cache.extend(value.tolist()							)
    _snake_case   :				Union[str, Any]														=	self.tokenizer.decode(self.token_cache      ,				**self.decode_kwargs							)

    # After the symbol for a new line, we flush the cache.
    if text.endswith('\n'							):
      _snake_case   :				Tuple														=	text[self.print_len :]
      _snake_case   :				str														=	[]
      _snake_case   :				Optional[int]														=	0
    # If the last token is a CJK character, we print the characters.
    elif len(UpperCamelCase							) > 0 and self._is_chinese_char(ord(text[-1]							)							):
      _snake_case   :				str														=	text[self.print_len :]
      self.print_len += len(UpperCamelCase							)
    # Otherwise, prints until the last space char (simple heuristic to avoid printing incomplete words,
    # which may change with the subsequent token -- there are probably smarter ways to do this!)
    else:
      _snake_case   :				Optional[int]														=	text[self.print_len : text.rfind(' '							) + 1]
      self.print_len += len(UpperCamelCase							)

    self.on_finalized_text(UpperCamelCase							)







  def UpperCamelCase_ (      self      :					Dict							):


    '''simple docstring'''





    if len(self.token_cache							) > 0:
      _snake_case   :				Dict														=	self.tokenizer.decode(self.token_cache      ,				**self.decode_kwargs							)
      _snake_case   :				List[str]														=	text[self.print_len :]
      _snake_case   :				Any														=	[]
      _snake_case   :				List[str]														=	0
    else:
      _snake_case   :				Optional[int]														=	''

    _snake_case   :				int														=	True
    self.on_finalized_text(UpperCamelCase      ,				stream_end=UpperCamelCase							)







  def UpperCamelCase_ (      self      :					Tuple      ,				UpperCamelCase      :					str      ,				UpperCamelCase      :					bool = False							):


    '''simple docstring'''





    print(UpperCamelCase      ,				flush=UpperCamelCase      ,				end='' if not stream_end else None							)







  def UpperCamelCase_ (      self      :					Optional[Any]      ,				UpperCamelCase      :					Optional[Any]							):


    '''simple docstring'''





    if (
        (cp >= 0x4e00 and cp <= 0x9fff)
        or (cp >= 0x3400 and cp <= 0x4dbf)  #
        or (cp >= 0x20000 and cp <= 0x2a6df)  #
        or (cp >= 0x2a700 and cp <= 0x2b73f)  #
        or (cp >= 0x2b740 and cp <= 0x2b81f)  #
        or (cp >= 0x2b820 and cp <= 0x2ceaf)  #
        or (cp >= 0xf900 and cp <= 0xfaff)
        or (cp >= 0x2f800 and cp <= 0x2fa1f)  #
    ):  #
      return True

    return False




class        _lowerCAmelCase    (			UpperCAmelCase_							):


  '''simple docstring'''







  def __init__(      self      :					Union[str, Any]      ,				UpperCamelCase      :					"AutoTokenizer"      ,				UpperCamelCase      :					bool = False      ,				UpperCamelCase      :					Optional[float] = None      ,				**UpperCamelCase      :					Optional[Any]							):


    '''simple docstring'''





    super().__init__(UpperCamelCase      ,				UpperCamelCase      ,				**UpperCamelCase							)
    _snake_case   :				int														=	Queue()
    _snake_case   :				Tuple														=	None
    _snake_case   :				Optional[Any]														=	timeout







  def UpperCamelCase_ (      self      :					List[str]      ,				UpperCamelCase      :					str      ,				UpperCamelCase      :					bool = False							):


    '''simple docstring'''





    self.text_queue.put(UpperCamelCase      ,				timeout=self.timeout							)
    if stream_end:
      self.text_queue.put(self.stop_signal      ,				timeout=self.timeout							)







  def __iter__(      self      :					Union[str, Any]							):


    '''simple docstring'''





    return self







  def UpperCamelCase_ (      self      :					Any							):


    '''simple docstring'''





    _snake_case   :				str														=	self.text_queue.get(timeout=self.timeout							)
    if value == self.stop_signal:
      raise StopIteration()
    else:
      return value











import math
import random
from typing import Any

from .hill_climbing import SearchProblem


def     lowerCamelCase_	(      lowerCAmelCase:	Tuple    ,							lowerCAmelCase:	bool = True    ,							lowerCAmelCase:	float = math.inf    ,							lowerCAmelCase:	float = -math.inf    ,							lowerCAmelCase:	float = math.inf    ,							lowerCAmelCase:	float = -math.inf    ,							lowerCAmelCase:	bool = False    ,							lowerCAmelCase:	float = 1_00    ,							lowerCAmelCase:	float = 0.0_1    ,							lowerCAmelCase:	float = 1    ,							)->		Any:
  _snake_case   :				int														=	False
  _snake_case   :				Any														=	search_prob
  _snake_case   :				Tuple														=	start_temperate
  _snake_case   :				Any														=	[]
  _snake_case   :				List[str]														=	0
  _snake_case   :				Optional[Any]														=	None

  while not search_end:
    _snake_case   :				List[Any]														=	current_state.score()
    if best_state is None or current_score > best_state.score():
      _snake_case   :				Dict														=	current_state
    scores.append(lowerCAmelCase				)
    iterations += 1
    _snake_case   :				Optional[int]														=	None
    _snake_case   :				Union[str, Any]														=	current_state.get_neighbors()
    while (
        next_state is None and neighbors
    ):  # till we do not find a neighbor that we can move to
      _snake_case   :				Dict														=	random.randint(0    ,							len(lowerCAmelCase				) - 1				)  # picking a random neighbor
      _snake_case   :				int														=	neighbors.pop(lowerCAmelCase				)
      _snake_case   :				Union[str, Any]														=	picked_neighbor.score() - current_score

      if (
          picked_neighbor.x > max_x
          or picked_neighbor.x < min_x
          or picked_neighbor.y > max_y
          or picked_neighbor.y < min_y
      ):
        continue  # neighbor outside our bounds

      if not find_max:
        _snake_case   :				Union[str, Any]														=	change * -1  # in case we are finding minimum
      if change > 0:  # improves the solution
        _snake_case   :				Union[str, Any]														=	picked_neighbor
      else:
        _snake_case   :				Optional[Any]														=	(math.e) ** (
            change / current_temp
        )  # probability generation function
        if random.random() < probability:  # random number within probability
          _snake_case   :				int														=	picked_neighbor
    _snake_case   :				List[Any]														=	current_temp - (current_temp * rate_of_decrease)

    if current_temp < threshold_temp or next_state is None:
      # temperature below threshold, or could not find a suitable neighbor
      _snake_case   :				List[str]														=	True
    else:
      _snake_case   :				Union[str, Any]														=	next_state

  if visualization:
    from matplotlib import pyplot as plt

    plt.plot(range(lowerCAmelCase				)    ,							lowerCAmelCase				)
    plt.xlabel('Iterations'				)
    plt.ylabel('Function values'				)
    plt.show()
  return best_state


if __name__ == "__main__":


      def     lowerCamelCase_	(      lowerCAmelCase:	Any    ,							lowerCAmelCase:	List[Any]				)->		List[Any]:
        return (x**2) + (y**2)

      # starting the problem with initial coordinates (12, 47)
      lowerCAmelCase_						   =    SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
      lowerCAmelCase_						   =    simulated_annealing(
          prob, find_max=False, max_x=100, min_x=5, max_y=50, 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()}"""
      )

      # starting the problem with initial coordinates (12, 47)
      lowerCAmelCase_						   =    SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
      lowerCAmelCase_						   =    simulated_annealing(
          prob, find_max=True, max_x=100, min_x=5, max_y=50, min_y=-5, visualization=True
      )
      print(
          """The maximum 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_	(      lowerCAmelCase:	Any    ,							lowerCAmelCase:	Dict				)->		Dict:
        return (3 * x**2) - (6 * y)

      lowerCAmelCase_						   =    SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
      lowerCAmelCase_						   =    simulated_annealing(prob, find_max=False, visualization=True)
      print(
          """The minimum score for f(x, y) = 3*x^2 - 6*y found via hill climbing: """
          F"""{local_min.score()}"""
      )

      lowerCAmelCase_						   =    SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
      lowerCAmelCase_						   =    simulated_annealing(prob, find_max=True, visualization=True)







      print(
          """The maximum score for f(x, y) = 3*x^2 - 6*y found via hill climbing: """
          F"""{local_min.score()}"""
      )




