





"""simple docstring"""





import math
import random
from typing import Any

from .hill_climbing import SearchProblem
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE = True	,  _SCREAMING_SNAKE_CASE = math.inf	,  _SCREAMING_SNAKE_CASE = -math.inf	,  _SCREAMING_SNAKE_CASE = math.inf	,  _SCREAMING_SNAKE_CASE = -math.inf	,  _SCREAMING_SNAKE_CASE = False	,  _SCREAMING_SNAKE_CASE = 100	,  _SCREAMING_SNAKE_CASE = 0.0_1	,  _SCREAMING_SNAKE_CASE = 1	,  )   ->Any:





  """simple docstring"""


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

  while not search_end:
    lowerCAmelCase__     :str											=				current_state.score()
    if best_state is None or current_score > best_state.score():
      lowerCAmelCase__     :str											=				current_state
    scores.append(_SCREAMING_SNAKE_CASE     )
    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__     :Optional[int]											=				random.randint(0	,  len(_SCREAMING_SNAKE_CASE     ) - 1     )  # picking a random neighbor
      lowerCAmelCase__     :List[str]											=				neighbors.pop(_SCREAMING_SNAKE_CASE     )
      lowerCAmelCase__     :str											=				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__     :int											=				picked_neighbor
      else:
        lowerCAmelCase__     :List[str]											=				(math.e) ** (
            change / current_temp
        )  # probability generation function
        if random.random() < probability:  # random number within probability
          lowerCAmelCase__     :int											=				picked_neighbor
    lowerCAmelCase__     :Optional[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__     :int											=				True
    else:
      lowerCAmelCase__     :int											=				next_state

  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 best_state


if __name__ == "__main__":
  def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->int:





    """simple docstring"""


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

  # starting the problem with initial coordinates (12, 47)
  __A											=						SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
  __A											=						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											=						SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
  __A											=						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 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->Dict:





    """simple docstring"""


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

  __A											=						SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
  __A											=						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											=						SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
  __A											=						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 shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
  from PIL import Image

  from transformers import (
      AutoProcessor,
      BertTokenizerFast,
      BlipImageProcessor,
      GPTaTokenizer,
      InstructBlipProcessor,
      PreTrainedTokenizerFast,
  )






@require_vision
class    _lowerCAmelCase  (	unittest.TestCase			):
       """simple docstring"""




       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Any											=				tempfile.mkdtemp()

         lowerCAmelCase__     :List[Any]											=				BlipImageProcessor()
         lowerCAmelCase__     :Union[str, Any]											=				GPTaTokenizer.from_pretrained('hf-internal-testing/tiny-random-GPT2Model' )
         lowerCAmelCase__     :Union[str, Any]											=				BertTokenizerFast.from_pretrained('hf-internal-testing/tiny-random-bert' )

         lowerCAmelCase__     :List[str]											=				InstructBlipProcessor(__UpperCAmelCase       ,					__UpperCAmelCase       ,					__UpperCAmelCase )

         processor.save_pretrained(self.tmpdirname )






       def 	snake_case		(       self       ,					**__UpperCAmelCase ):



         '''simple docstring'''

         return AutoProcessor.from_pretrained(self.tmpdirname       ,					**__UpperCAmelCase ).tokenizer






       def 	snake_case		(       self       ,					**__UpperCAmelCase ):



         '''simple docstring'''

         return AutoProcessor.from_pretrained(self.tmpdirname       ,					**__UpperCAmelCase ).image_processor






       def 	snake_case		(       self       ,					**__UpperCAmelCase ):



         '''simple docstring'''

         return AutoProcessor.from_pretrained(self.tmpdirname       ,					**__UpperCAmelCase ).qformer_tokenizer






       def 	snake_case		(       self ):



         '''simple docstring'''

         shutil.rmtree(self.tmpdirname )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Optional[Any]											=				[np.random.randint(2_5_5       ,					size=(3, 3_0, 4_0_0)       ,					dtype=np.uinta )]

         lowerCAmelCase__     :Dict											=				[Image.fromarray(np.moveaxis(__UpperCAmelCase       ,					0       ,					-1 ) ) for x in image_inputs]

         return image_inputs






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :List[str]											=				InstructBlipProcessor(
             tokenizer=self.get_tokenizer()       ,					image_processor=self.get_image_processor()       ,					qformer_tokenizer=self.get_qformer_tokenizer()       ,					)
         processor.save_pretrained(self.tmpdirname )

         lowerCAmelCase__     :Tuple											=				self.get_tokenizer(bos_token='(BOS)'       ,					eos_token='(EOS)' )
         lowerCAmelCase__     :str											=				self.get_image_processor(do_normalize=__UpperCAmelCase       ,					padding_value=1.0 )

         lowerCAmelCase__     :Dict											=				InstructBlipProcessor.from_pretrained(
             self.tmpdirname       ,					bos_token='(BOS)'       ,					eos_token='(EOS)'       ,					do_normalize=__UpperCAmelCase       ,					padding_value=1.0 )

         self.assertEqual(processor.tokenizer.get_vocab()       ,					tokenizer_add_kwargs.get_vocab() )
         self.assertIsInstance(processor.tokenizer       ,					__UpperCAmelCase )

         self.assertEqual(processor.image_processor.to_json_string()       ,					image_processor_add_kwargs.to_json_string() )
         self.assertIsInstance(processor.image_processor       ,					__UpperCAmelCase )
         self.assertIsInstance(processor.qformer_tokenizer       ,					__UpperCAmelCase )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Optional[Any]											=				self.get_image_processor()
         lowerCAmelCase__     :List[Any]											=				self.get_tokenizer()
         lowerCAmelCase__     :Optional[int]											=				self.get_qformer_tokenizer()

         lowerCAmelCase__     :str											=				InstructBlipProcessor(
             tokenizer=__UpperCAmelCase       ,					image_processor=__UpperCAmelCase       ,					qformer_tokenizer=__UpperCAmelCase )

         lowerCAmelCase__     :Dict											=				self.prepare_image_inputs()

         lowerCAmelCase__     :List[str]											=				image_processor(__UpperCAmelCase       ,					return_tensors='np' )
         lowerCAmelCase__     :Optional[Any]											=				processor(images=__UpperCAmelCase       ,					return_tensors='np' )

         for key in input_feat_extract.keys():
           self.assertAlmostEqual(input_feat_extract[key].sum()       ,					input_processor[key].sum()       ,					delta=1E-2 )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Union[str, Any]											=				self.get_image_processor()
         lowerCAmelCase__     :Optional[int]											=				self.get_tokenizer()
         lowerCAmelCase__     :Optional[int]											=				self.get_qformer_tokenizer()

         lowerCAmelCase__     :Any											=				InstructBlipProcessor(
             tokenizer=__UpperCAmelCase       ,					image_processor=__UpperCAmelCase       ,					qformer_tokenizer=__UpperCAmelCase )

         lowerCAmelCase__     :Optional[int]											=				'lower newer'

         lowerCAmelCase__     :Dict											=				processor(text=__UpperCAmelCase )

         lowerCAmelCase__     :Union[str, Any]											=				tokenizer(__UpperCAmelCase       ,					return_token_type_ids=__UpperCAmelCase )
         lowerCAmelCase__     :Tuple											=				qformer_tokenizer(__UpperCAmelCase       ,					return_token_type_ids=__UpperCAmelCase )

         for key in encoded_tokens.keys():
           self.assertListEqual(encoded_tokens[key]       ,					encoded_processor[key] )

         for key in encoded_tokens_qformer.keys():
           self.assertListEqual(encoded_tokens_qformer[key]       ,					encoded_processor['qformer_' + key] )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Optional[Any]											=				self.get_image_processor()
         lowerCAmelCase__     :Optional[int]											=				self.get_tokenizer()
         lowerCAmelCase__     :str											=				self.get_qformer_tokenizer()

         lowerCAmelCase__     :Dict											=				InstructBlipProcessor(
             tokenizer=__UpperCAmelCase       ,					image_processor=__UpperCAmelCase       ,					qformer_tokenizer=__UpperCAmelCase )

         lowerCAmelCase__     :Union[str, Any]											=				'lower newer'
         lowerCAmelCase__     :Dict											=				self.prepare_image_inputs()

         lowerCAmelCase__     :Tuple											=				processor(text=__UpperCAmelCase       ,					images=__UpperCAmelCase )

         self.assertListEqual(
             list(inputs.keys() )       ,					['input_ids', 'attention_mask', 'qformer_input_ids', 'qformer_attention_mask', 'pixel_values']       ,					)

         # test if it raises when no input is passed
         with pytest.raises(__UpperCAmelCase ):
           processor()






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Tuple											=				self.get_image_processor()
         lowerCAmelCase__     :Dict											=				self.get_tokenizer()
         lowerCAmelCase__     :Optional[int]											=				self.get_qformer_tokenizer()

         lowerCAmelCase__     :int											=				InstructBlipProcessor(
             tokenizer=__UpperCAmelCase       ,					image_processor=__UpperCAmelCase       ,					qformer_tokenizer=__UpperCAmelCase )

         lowerCAmelCase__     :List[str]											=				[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

         lowerCAmelCase__     :Tuple											=				processor.batch_decode(__UpperCAmelCase )
         lowerCAmelCase__     :Optional[int]											=				tokenizer.batch_decode(__UpperCAmelCase )

         self.assertListEqual(__UpperCAmelCase       ,					__UpperCAmelCase )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__     :Tuple											=				self.get_image_processor()
         lowerCAmelCase__     :Optional[int]											=				self.get_tokenizer()
         lowerCAmelCase__     :Dict											=				self.get_qformer_tokenizer()

         lowerCAmelCase__     :Optional[Any]											=				InstructBlipProcessor(
             tokenizer=__UpperCAmelCase       ,					image_processor=__UpperCAmelCase       ,					qformer_tokenizer=__UpperCAmelCase )

         lowerCAmelCase__     :Optional[int]											=				'lower newer'
         lowerCAmelCase__     :Optional[int]											=				self.prepare_image_inputs()

         lowerCAmelCase__     :int											=				processor(text=__UpperCAmelCase       ,					images=__UpperCAmelCase )

         self.assertListEqual(
             list(inputs.keys() )       ,					['input_ids', 'attention_mask', 'qformer_input_ids', 'qformer_attention_mask', 'pixel_values']       ,					)
