
import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class       _snake_case   (	UpperCAmelCase_  ,						unittest.TestCase							):
 __lowerCAmelCase  :     Optional[int]        =			MgpstrTokenizer
 __lowerCAmelCase  :     Dict        =			False
 __lowerCAmelCase  :     List[Any]        =			{}
 __lowerCAmelCase  :     Optional[Any]        =			False


 def      lowercase__     (					self):


   '''simple docstring'''




   super().setUp()

   # fmt: off
   lowercase__  :   str    		=      ["""[GO]""", """[s]""", """0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9""", """a""", """b""", """c""", """d""", """e""", """f""", """g""", """h""", """i""", """j""", """k""", """l""", """m""", """n""", """o""", """p""", """q""", """r""", """s""", """t""", """u""", """v""", """w""", """x""", """y""", """z"""]
   # fmt: on
   lowercase__  :   int    		=      dict(zip(SCREAMING_SNAKE_CASE_					,  range(len(SCREAMING_SNAKE_CASE_))))

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


 def      lowercase__     (					self					,  **SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   return MgpstrTokenizer.from_pretrained(self.tmpdirname					,  **SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   int    		=      """tester"""
   lowercase__  :   List[Any]    		=      """tester"""
   return input_text, output_text


 @unittest.skip("""MGP-STR always lower cases letters.""")
 def      lowercase__     (					self):


   '''simple docstring'''




   pass


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   int    		=      self.get_tokenizers(do_lower_case=SCREAMING_SNAKE_CASE_)
   for tokenizer in tokenizers:
     with self.subTest(f'{tokenizer.__class__.__name__}'):
       lowercase__  :   Any    		=      """[SPECIAL_TOKEN]"""

       tokenizer.add_special_tokens({"""cls_token""": special_token})
       lowercase__  :   int    		=      tokenizer.encode([special_token]					,  add_special_tokens=SCREAMING_SNAKE_CASE_)
       self.assertEqual(len(SCREAMING_SNAKE_CASE_)					,  1)

       lowercase__  :   Union[str, Any]    		=      tokenizer.decode(SCREAMING_SNAKE_CASE_					,  skip_special_tokens=SCREAMING_SNAKE_CASE_)
       self.assertTrue(special_token not in decoded)


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   List[Any]    		=      self.get_tokenizers()
   for tokenizer in tokenizers:
     with self.subTest(f'{tokenizer.__class__.__name__}'):
       lowercase__		,    lowercase__  :   Optional[Any]    		=      self.get_input_output_texts(SCREAMING_SNAKE_CASE_)

       lowercase__  :   str    		=      tokenizer.tokenize(SCREAMING_SNAKE_CASE_)
       lowercase__  :   Dict    		=      tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_)
       lowercase__  :   Optional[int]    		=      tokenizer.encode(SCREAMING_SNAKE_CASE_					,  add_special_tokens=SCREAMING_SNAKE_CASE_)
       self.assertListEqual(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)

       lowercase__  :   Dict    		=      tokenizer.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_)
       self.assertNotEqual(len(SCREAMING_SNAKE_CASE_)					,  0)
       lowercase__  :   Dict    		=      tokenizer.decode(SCREAMING_SNAKE_CASE_)
       self.assertIsInstance(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)

       self.assertEqual(text_a.replace(""" """					,  """""")					,  SCREAMING_SNAKE_CASE_)


 @unittest.skip("""MGP-STR tokenizer only handles one sequence.""")
 def      lowercase__     (					self):


   '''simple docstring'''




   pass



 @unittest.skip("""inputs cannot be pretokenized in MgpstrTokenizer""")
 def      lowercase__     (					self):


   '''simple docstring'''




   pass








import math
import random
from typing import Any

from .hill_climbing import SearchProblem

def 		UpperCamelCase	(      lowercase_ , lowercase_ = True , lowercase_ = math.inf , lowercase_ = -math.inf , lowercase_ = math.inf , lowercase_ = -math.inf , lowercase_ = False , lowercase_ = 1_00 , lowercase_ = 0.01 , lowercase_ = 1 , )		->	Any:


  '''simple docstring'''






  lowercase__  :   Any    		=      False
  lowercase__  :   Union[str, Any]    		=      search_prob
  lowercase__  :   int    		=      start_temperate
  lowercase__  :   Union[str, Any]    		=      []
  lowercase__  :   List[str]    		=      0
  lowercase__  :   Optional[int]    		=      None

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

  if visualization:
    from matplotlib import pyplot as plt

    plt.plot(range(lowercase_   ) , lowercase_   )
    plt.xlabel("""Iterations"""   )
    plt.ylabel("""Function values"""   )
    plt.show()
  return best_state


if __name__ == "__main__":

     def 		UpperCamelCase	(      lowercase_ , lowercase_   )		->	str:


       '''simple docstring'''






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

     # starting the problem with initial coordinates (12, 47)
     lowerCamelCase__    :		str          =   SearchProblem(x=1_2, y=4_7, step_size=1, function_to_optimize=test_fa)
     lowerCamelCase__    :		List[Any]          =   simulated_annealing(
         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()}'''
     )

     # starting the problem with initial coordinates (12, 47)
     lowerCamelCase__    :		List[Any]          =   SearchProblem(x=1_2, y=4_7, step_size=1, function_to_optimize=test_fa)
     lowerCamelCase__    :		Optional[int]          =   simulated_annealing(
         prob, find_max=True, max_x=1_0_0, min_x=5, max_y=5_0, 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	(      lowercase_ , lowercase_   )		->	Union[str, Any]:


       '''simple docstring'''






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

     lowerCamelCase__    :		Tuple          =   SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
     lowerCamelCase__    :		Union[str, 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()}'''
     )

     lowerCamelCase__    :		Dict          =   SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
     lowerCamelCase__    :		Tuple          =   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()}'''
     )






