



"""simple docstring"""






import math
import random
from typing import Any

from .hill_climbing import SearchProblem






def 			snake_case_    ( A_   :						Dict,							A_   :						bool = True,							A_   :						float = math.inf,							A_   :						float = -math.inf,							A_   :						float = math.inf,							A_   :						float = -math.inf,							A_   :						bool = False,							A_   :						float = 1_00,							A_   :						float = 0.01,							A_   :						float = 1,							):


       '''simple docstring'''





       _lowerCamelCase		:							Optional[int]            =					False
       _lowerCamelCase		:							str            =					search_prob
       _lowerCamelCase		:							str            =					start_temperate
       _lowerCamelCase		:							Optional[Any]            =					[]
       _lowerCamelCase		:							int            =					0
       _lowerCamelCase		:							Any            =					None

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

       if visualization:
              from matplotlib import pyplot as plt

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


if __name__ == "__main__":






   def 			snake_case_    ( A_   :						int,							A_   :						Tuple		):


          '''simple docstring'''





          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 			snake_case_    ( A_   :						Optional[int],							A_   :						List[Any]		):


          '''simple docstring'''





          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()}"""
   )







"""simple docstring"""







import contextlib
import importlib
import io
import unittest

import transformers

# Try to import everything from transformers to ensure every object can be loaded.
from transformers import *  # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from transformers.utils import ContextManagers, find_labels, is_flax_available, is_tf_available, is_torch_available


if is_torch_available():
			from transformers import BertForPreTraining, BertForQuestionAnswering, BertForSequenceClassification

if is_tf_available():
			from transformers import TFBertForPreTraining, TFBertForQuestionAnswering, TFBertForSequenceClassification

if is_flax_available():
			from transformers import FlaxBertForPreTraining, FlaxBertForQuestionAnswering, FlaxBertForSequenceClassification


A		=						DUMMY_UNKNOWN_IDENTIFIER
# An actual model hosted on huggingface.co

A		=						'main'
# Default branch name
A		=						'f2c752cfc5c0ab6f4bdec59acea69eefbee381c2'
# One particular commit (not the top of `main`)
A		=						'aaaaaaa'
# This commit does not exist, so we should 404.

A		=						'd9e9f15bc825e4b2c9249e9578f884bbcb5e3684'
# Sha-1 of config.json on the top of `main`, for checking purposes
A		=						'4b243c475af8d0a7754e87d7d096c92e5199ec2fe168a2ee7998e3b8e9bcb1d3'

@contextlib.contextmanager
def  __SCREAMING_SNAKE_CASE		(			):
						"""simple docstring"""






						print("Welcome!" )
						yield
						print("Bye!" )

@contextlib.contextmanager
def  __SCREAMING_SNAKE_CASE		(			):
						"""simple docstring"""






						print("Bonjour!" )
						yield
						print("Au revoir!" )

class       _a  ( unittest.TestCase):



			def 				__lowercase					(			self							:				Dict		)							->					Optional[int]:
									# If the spec is missing, importlib would not be able to import the module dynamically.
									assert transformers.__spec__ is not None
									assert importlib.util.find_spec("transformers"		) is not None



class       _a  ( unittest.TestCase):



			@unittest.mock.patch("sys.stdout"   ,	new_callable=io.StringIO		)
			def 				__lowercase					(			self							:				Union[str, Any]   ,	_lowercase							:				Optional[int]		)							->					Optional[Any]:
									with ContextManagers([]		):
															print("Transformers are awesome!"		)
									# The print statement adds a new line at the end of the output
									self.assertEqual(mock_stdout.getvalue()   ,	"Transformers are awesome!\n"		)



			@unittest.mock.patch("sys.stdout"   ,	new_callable=io.StringIO		)
			def 				__lowercase					(			self							:				Any   ,	_lowercase							:				Any		)							->					Dict:
									with ContextManagers([context_en()]		):
															print("Transformers are awesome!"		)
									# The output should be wrapped with an English welcome and goodbye
									self.assertEqual(mock_stdout.getvalue()   ,	"Welcome!\nTransformers are awesome!\nBye!\n"		)



			@unittest.mock.patch("sys.stdout"   ,	new_callable=io.StringIO		)
			def 				__lowercase					(			self							:				str   ,	_lowercase							:				List[Any]		)							->					Optional[int]:
									with ContextManagers([context_fr(), context_en()]		):
															print("Transformers are awesome!"		)
									# The output should be wrapped with an English and French welcome and goodbye
									self.assertEqual(mock_stdout.getvalue()   ,	"Bonjour!\nWelcome!\nTransformers are awesome!\nBye!\nAu revoir!\n"		)



			@require_torch
			def 				__lowercase					(			self							:				Any		)							->					Union[str, Any]:
									self.assertEqual(find_labels(_lowercase		)   ,	["labels"]		)
									self.assertEqual(find_labels(_lowercase		)   ,	["labels", "next_sentence_label"]		)
									self.assertEqual(find_labels(_lowercase		)   ,	["start_positions", "end_positions"]		)

									class       _a  ( SCREAMING_SNAKE_CASE__):
												pass



									self.assertEqual(find_labels(_lowercase		)   ,	["labels"]		)



			@require_tf
			def 				__lowercase					(			self							:				Optional[Any]		)							->					int:
									self.assertEqual(find_labels(_lowercase		)   ,	["labels"]		)
									self.assertEqual(find_labels(_lowercase		)   ,	["labels", "next_sentence_label"]		)
									self.assertEqual(find_labels(_lowercase		)   ,	["start_positions", "end_positions"]		)

									class       _a  ( SCREAMING_SNAKE_CASE__):
												pass



									self.assertEqual(find_labels(_lowercase		)   ,	["labels"]		)



			@require_flax
			def 				__lowercase					(			self							:				Tuple		)							->					List[Any]:
									# Flax models don't have labels
									self.assertEqual(find_labels(_lowercase		)   ,	[]		)
									self.assertEqual(find_labels(_lowercase		)   ,	[]		)
									self.assertEqual(find_labels(_lowercase		)   ,	[]		)

									class       _a  ( SCREAMING_SNAKE_CASE__):
												pass



									self.assertEqual(find_labels(_lowercase		)   ,	[]		)



