



import math
import random
from typing import Any

from .hill_climbing import SearchProblem


def 			UpperCamelCase(  __UpperCamelCase							:		Optional[Any]     ,__UpperCamelCase							:		bool = True     ,__UpperCamelCase							:		float = math.inf     ,__UpperCamelCase							:		float = -math.inf     ,__UpperCamelCase							:		float = math.inf     ,__UpperCamelCase							:		float = -math.inf     ,__UpperCamelCase							:		bool = False     ,__UpperCamelCase							:		float = 100     ,__UpperCamelCase							:		float = 0.0_1     ,__UpperCamelCase							:		float = 1     ,):
		lowerCAmelCase_			:     str									= False
		lowerCAmelCase_			:     Optional[Any]									= search_prob
		lowerCAmelCase_			:     int									= start_temperate
		lowerCAmelCase_			:     Any									= []
		lowerCAmelCase_			:     List[Any]									= 0
		lowerCAmelCase_			:     Union[str, Any]									= None

		while not search_end:
				lowerCAmelCase_			:     int									= current_state.score()
				if best_state is None or current_score > best_state.score():
						lowerCAmelCase_			:     Optional[int]									= current_state
				scores.append(__UpperCamelCase )
				iterations += 1
				lowerCAmelCase_			:     Tuple									= None
				lowerCAmelCase_			:     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
						lowerCAmelCase_			:     Any									= random.randint(0     ,len(__UpperCamelCase ) - 1 )  # picking a random neighbor
						lowerCAmelCase_			:     Optional[int]									= neighbors.pop(__UpperCamelCase )
						lowerCAmelCase_			:     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:
								lowerCAmelCase_			:     Optional[Any]									= change * -1  # in case we are finding minimum
						if change > 0:  # improves the solution
								lowerCAmelCase_			:     Union[str, Any]									= picked_neighbor
						else:
								lowerCAmelCase_			:     Optional[int]									= (math.e) ** (
								    change / current_temp
								)  # probability generation function
								if random.random() < probability:  # random number within probability
										lowerCAmelCase_			:     Optional[int]									= picked_neighbor
				lowerCAmelCase_			:     int									= 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
						lowerCAmelCase_			:     Optional[int]									= True
				else:
						lowerCAmelCase_			:     Optional[Any]									= next_state

		if visualization:
				from matplotlib import pyplot as plt

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


if __name__ == "__main__":


						def 			UpperCamelCase(  __UpperCamelCase							:		Dict     ,__UpperCamelCase							:		str ):
								return (x**2) + (y**2)

						# starting the problem with initial coordinates (12, 47)
						A__  :  str								=					SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
						A__  :  Tuple								=					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)
						A__  :  Union[str, Any]								=					SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
						A__  :  Tuple								=					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 			UpperCamelCase(  __UpperCamelCase							:		Optional[Any]     ,__UpperCamelCase							:		Dict ):
								return (3 * x**2) - (6 * y)

						A__  :  Optional[int]								=					SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
						A__  :  Optional[Any]								=					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()}'''
						)

						A__  :  Union[str, Any]								=					SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
						A__  :  Any								=					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()}'''
						)









'''simple docstring'''

import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin





class      snake_case    (    lowercase			,						unittest.TestCase			):





  """simple docstring"""




  _lowerCamelCase		    =  BlenderbotSmallTokenizer
  _lowerCamelCase		    =  False






  def   snake_case		(    self     ):







   """simple docstring"""
   super().setUp()

   lowerCamelCase_      =  ["__start__", "adapt", "act", "ap@@", "te", "__end__", "__unk__"]
   lowerCamelCase_      =  dict(zip(UpperCamelCase			,  range(len(UpperCamelCase     )     )     )     )

   lowerCamelCase_      =  ["#version: 0.2", "a p", "t e</w>", "ap t</w>", "a d", "ad apt</w>", "a c", "ac t</w>", ""]
   lowerCamelCase_      =  {"unk_token": "__unk__", "bos_token": "__start__", "eos_token": "__end__"}

   lowerCamelCase_      =  os.path.join(self.tmpdirname			,  VOCAB_FILES_NAMES["vocab_file"]     )
   lowerCamelCase_      =  os.path.join(self.tmpdirname			,  VOCAB_FILES_NAMES["merges_file"]     )
   with open(self.vocab_file			,  "w"			,  encoding="utf-8"     ) as fp:
    fp.write(json.dumps(UpperCamelCase     ) + "\n"     )
   with open(self.merges_file			,  "w"			,  encoding="utf-8"     ) as fp:
    fp.write("\n".join(UpperCamelCase     )     )






  def   snake_case		(    self			,  **UpperCamelCase     ):







   """simple docstring"""
   kwargs.update(self.special_tokens_map     )
   return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname			,  **UpperCamelCase     )






  def   snake_case		(    self			,  UpperCamelCase     ):







   """simple docstring"""
   lowerCamelCase_      =  "adapt act apte"
   lowerCamelCase_      =  "adapt act apte"
   return input_text, output_text






  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_      =  BlenderbotSmallTokenizer(self.vocab_file			,  self.merges_file			,  **self.special_tokens_map     )
   lowerCamelCase_      =  "adapt act apte"
   lowerCamelCase_      =  ["adapt", "act", "ap@@", "te"]
   lowerCamelCase_      =  tokenizer.tokenize(UpperCamelCase     )
   self.assertListEqual(UpperCamelCase			,  UpperCamelCase     )

   lowerCamelCase_      =  [tokenizer.bos_token] + tokens + [tokenizer.eos_token]

   lowerCamelCase_      =  [0, 1, 2, 3, 4, 5]
   self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase     )			,  UpperCamelCase     )






  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_      =  BlenderbotSmallTokenizer.from_pretrained("facebook/blenderbot-90M"     )
   assert tok("sam"     ).input_ids == [1384]
   lowerCamelCase_      =  "I am a small frog."
   lowerCamelCase_      =  tok([src_text]			,  padding=UpperCamelCase			,  truncation=UpperCamelCase     )["input_ids"]
   lowerCamelCase_      =  tok.batch_decode(UpperCamelCase			,  skip_special_tokens=UpperCamelCase			,  clean_up_tokenization_spaces=UpperCamelCase     )[0]
   assert src_text != decoded  # I wish it did!
   assert decoded == "i am a small frog ."







  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_      =  BlenderbotSmallTokenizer.from_pretrained("facebook/blenderbot-90M"     )
   lowerCamelCase_      =  "I am a small frog ."
   lowerCamelCase_      =  "."
   lowerCamelCase_      =  tok(UpperCamelCase     )["input_ids"]
   lowerCamelCase_      =  tok(UpperCamelCase     )["input_ids"]

   assert encoded[-1] == encoded_dot[0]



