

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, BertTokenizer, BlipImageProcessor, BlipProcessor, PreTrainedTokenizerFast






@require_vision
class 		_lowerCamelCase		(   unittest.TestCase    ):
    def 						UpperCamelCase_				(  self   )       ->					str:
     SCREAMING_SNAKE_CASE__:   List[str]=      tempfile.mkdtemp()

     SCREAMING_SNAKE_CASE__:   Optional[Any]=      BlipImageProcessor()
     SCREAMING_SNAKE_CASE__:   Dict=      BertTokenizer.from_pretrained('''hf-internal-testing/tiny-random-BertModel'''   )

     SCREAMING_SNAKE_CASE__:   str=      BlipProcessor(snake_case_ , snake_case_   )

     processor.save_pretrained(self.tmpdirname   )
    def 						UpperCamelCase_				(  self , **lowerCAmelCase   )       ->					List[Any]:
     return AutoProcessor.from_pretrained(self.tmpdirname , **snake_case_   ).tokenizer
    def 						UpperCamelCase_				(  self , **lowerCAmelCase   )       ->					Any:
     return AutoProcessor.from_pretrained(self.tmpdirname , **snake_case_   ).image_processor
    def 						UpperCamelCase_				(  self   )       ->					List[Any]:
     shutil.rmtree(self.tmpdirname   )
    def 						UpperCamelCase_				(  self   )       ->					List[Any]:
     SCREAMING_SNAKE_CASE__:   Tuple=      [np.random.randint(255 , size=(3, 30, 400) , dtype=np.uinta   )]

     SCREAMING_SNAKE_CASE__:   str=      [Image.fromarray(np.moveaxis(snake_case_ , 0 , -1   )   ) for x in image_inputs]

     return image_inputs
    def 						UpperCamelCase_				(  self   )       ->					Dict:
     SCREAMING_SNAKE_CASE__:   List[str]=      BlipProcessor(tokenizer=self.get_tokenizer() , image_processor=self.get_image_processor()   )
     processor.save_pretrained(self.tmpdirname   )

     SCREAMING_SNAKE_CASE__:   List[str]=      self.get_tokenizer(bos_token='''(BOS)''' , eos_token='''(EOS)'''   )
     SCREAMING_SNAKE_CASE__:   str=      self.get_image_processor(do_normalize=snake_case_ , padding_value=1.0   )

     SCREAMING_SNAKE_CASE__:   int=      BlipProcessor.from_pretrained(
         self.tmpdirname , bos_token='''(BOS)''' , eos_token='''(EOS)''' , do_normalize=snake_case_ , padding_value=1.0   )

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

     self.assertEqual(processor.image_processor.to_json_string() , image_processor_add_kwargs.to_json_string()   )
     self.assertIsInstance(processor.image_processor , snake_case_   )
    def 						UpperCamelCase_				(  self   )       ->					List[Any]:
     SCREAMING_SNAKE_CASE__:   Optional[int]=      self.get_image_processor()
     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      self.get_tokenizer()

     SCREAMING_SNAKE_CASE__:   Optional[int]=      BlipProcessor(tokenizer=snake_case_ , image_processor=snake_case_   )

     SCREAMING_SNAKE_CASE__:   List[Any]=      self.prepare_image_inputs()

     SCREAMING_SNAKE_CASE__:   List[str]=      image_processor(snake_case_ , return_tensors='''np'''   )
     SCREAMING_SNAKE_CASE__:   List[str]=      processor(images=snake_case_ , 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 						UpperCamelCase_				(  self   )       ->					Dict:
     SCREAMING_SNAKE_CASE__:   List[Any]=      self.get_image_processor()
     SCREAMING_SNAKE_CASE__:   Tuple=      self.get_tokenizer()

     SCREAMING_SNAKE_CASE__:   Any=      BlipProcessor(tokenizer=snake_case_ , image_processor=snake_case_   )

     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      '''lower newer'''

     SCREAMING_SNAKE_CASE__:   Any=      processor(text=snake_case_   )

     SCREAMING_SNAKE_CASE__:   List[str]=      tokenizer(snake_case_ , return_token_type_ids=snake_case_   )

     for key in encoded_tok.keys():
      self.assertListEqual(encoded_tok[key] , encoded_processor[key]   )
    def 						UpperCamelCase_				(  self   )       ->					Dict:
     SCREAMING_SNAKE_CASE__:   Optional[int]=      self.get_image_processor()
     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      self.get_tokenizer()

     SCREAMING_SNAKE_CASE__:   Any=      BlipProcessor(tokenizer=snake_case_ , image_processor=snake_case_   )

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

     SCREAMING_SNAKE_CASE__:   List[str]=      processor(text=snake_case_ , images=snake_case_   )

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

     # test if it raises when no input is passed
     with pytest.raises(snake_case_   ):
      processor()
    def 						UpperCamelCase_				(  self   )       ->					int:
     SCREAMING_SNAKE_CASE__:   str=      self.get_image_processor()
     SCREAMING_SNAKE_CASE__:   Optional[int]=      self.get_tokenizer()

     SCREAMING_SNAKE_CASE__:   str=      BlipProcessor(tokenizer=snake_case_ , image_processor=snake_case_   )

     SCREAMING_SNAKE_CASE__:   Tuple=      [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

     SCREAMING_SNAKE_CASE__:   List[Any]=      processor.batch_decode(snake_case_   )
     SCREAMING_SNAKE_CASE__:   Dict=      tokenizer.batch_decode(snake_case_   )

     self.assertListEqual(snake_case_ , snake_case_   )



    def 						UpperCamelCase_				(  self   )       ->					Optional[int]:
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      self.get_image_processor()
     SCREAMING_SNAKE_CASE__:   Any=      self.get_tokenizer()

     SCREAMING_SNAKE_CASE__:   Dict=      BlipProcessor(tokenizer=snake_case_ , image_processor=snake_case_   )

     SCREAMING_SNAKE_CASE__:   Dict=      '''lower newer'''
     SCREAMING_SNAKE_CASE__:   List[Any]=      self.prepare_image_inputs()

     SCREAMING_SNAKE_CASE__:   List[str]=      processor(text=snake_case_ , images=snake_case_   )

     # For now the processor supports only ['pixel_values', 'input_ids', 'attention_mask']
     self.assertListEqual(list(inputs.keys()   ) , ['''pixel_values''', '''input_ids''', '''attention_mask''']   )


def 			A__      (	snake_case_ :		list      ):

 if len(snake_case_      ) < 2:
  return collection

 def circle_sort_util(snake_case_ :		list       ,				snake_case_ :		int       ,				snake_case_ :		int      ) -> bool:
  SCREAMING_SNAKE_CASE__:   Dict=      False

  if low == high:
   return swapped

  SCREAMING_SNAKE_CASE__:   str=      low
  SCREAMING_SNAKE_CASE__:   Optional[int]=      high

  while left < right:
   if collection[left] > collection[right]:
    SCREAMING_SNAKE_CASE__,	SCREAMING_SNAKE_CASE__:   Optional[int]=      (
        collection[right],
        collection[left],
    )
    SCREAMING_SNAKE_CASE__:   List[Any]=      True

   left += 1
   right -= 1

  if left == right and collection[left] > collection[right + 1]:
   SCREAMING_SNAKE_CASE__,	SCREAMING_SNAKE_CASE__:   List[str]=      (
       collection[right + 1],
       collection[left],
   )

   SCREAMING_SNAKE_CASE__:   List[str]=      True

  SCREAMING_SNAKE_CASE__:   Dict=      low + int((high - low) / 2      )
  SCREAMING_SNAKE_CASE__:   str=      circle_sort_util(snake_case_       ,				snake_case_       ,				snake_case_      )
  SCREAMING_SNAKE_CASE__:   List[Any]=      circle_sort_util(snake_case_       ,				mid + 1       ,				snake_case_      )

  return swapped or left_swap or right_swap

 SCREAMING_SNAKE_CASE__:   Optional[int]=      True

 while is_not_sorted is True:
  SCREAMING_SNAKE_CASE__:   Tuple=      circle_sort_util(snake_case_       ,				0       ,				len(snake_case_      ) - 1      )

 return collection


if __name__ == "__main__":
      lowercase_     :   Tuple 				=				input('Enter numbers separated by a comma:\n').strip()
      lowercase_     :   str 				=				[int(item) for item in user_input.split(',')]
      print(circle_sort(unsorted))

