
"""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    _UpperCAmelCase(   unittest.TestCase     ):



  def 						UpperCAmelCase							( self)	->	Dict:






       '''simple docstring'''
       _UpperCamelCase										=  tempfile.mkdtemp()

       _UpperCamelCase										=  BlipImageProcessor()
       _UpperCamelCase										=  GPTaTokenizer.from_pretrained('''hf-internal-testing/tiny-random-GPT2Model''')
       _UpperCamelCase										=  BertTokenizerFast.from_pretrained('''hf-internal-testing/tiny-random-bert''')

       _UpperCamelCase										=  InstructBlipProcessor(SCREAMING_SNAKE_CASE_    ,		SCREAMING_SNAKE_CASE_    ,		SCREAMING_SNAKE_CASE_)

       processor.save_pretrained(self.tmpdirname)



  def 						UpperCAmelCase							( self    ,		**__a)	->	str:






       '''simple docstring'''
       return AutoProcessor.from_pretrained(self.tmpdirname    ,		**SCREAMING_SNAKE_CASE_).tokenizer



  def 						UpperCAmelCase							( self    ,		**__a)	->	List[str]:






       '''simple docstring'''
       return AutoProcessor.from_pretrained(self.tmpdirname    ,		**SCREAMING_SNAKE_CASE_).image_processor



  def 						UpperCAmelCase							( self    ,		**__a)	->	Optional[int]:






       '''simple docstring'''
       return AutoProcessor.from_pretrained(self.tmpdirname    ,		**SCREAMING_SNAKE_CASE_).qformer_tokenizer



  def 						UpperCAmelCase							( self)	->	int:






       '''simple docstring'''
       shutil.rmtree(self.tmpdirname)



  def 						UpperCAmelCase							( self)	->	Dict:






       '''simple docstring'''
       _UpperCamelCase										=  [np.random.randint(2_55    ,		size=(3, 30, 4_00)    ,		dtype=np.uinta)]

       _UpperCamelCase										=  [Image.fromarray(np.moveaxis(SCREAMING_SNAKE_CASE_    ,		0    ,		-1)) for x in image_inputs]

       return image_inputs



  def 						UpperCAmelCase							( self)	->	str:






       '''simple docstring'''
       _UpperCamelCase										=  InstructBlipProcessor(
           tokenizer=self.get_tokenizer()    ,		image_processor=self.get_image_processor()    ,		qformer_tokenizer=self.get_qformer_tokenizer()    ,		)
       processor.save_pretrained(self.tmpdirname)

       _UpperCamelCase										=  self.get_tokenizer(bos_token='''(BOS)'''    ,		eos_token='''(EOS)''')
       _UpperCamelCase										=  self.get_image_processor(do_normalize=SCREAMING_SNAKE_CASE_    ,		padding_value=1.0)

       _UpperCamelCase										=  InstructBlipProcessor.from_pretrained(
           self.tmpdirname    ,		bos_token='''(BOS)'''    ,		eos_token='''(EOS)'''    ,		do_normalize=SCREAMING_SNAKE_CASE_    ,		padding_value=1.0)

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

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



  def 						UpperCAmelCase							( self)	->	Optional[Any]:






       '''simple docstring'''
       _UpperCamelCase										=  self.get_image_processor()
       _UpperCamelCase										=  self.get_tokenizer()
       _UpperCamelCase										=  self.get_qformer_tokenizer()

       _UpperCamelCase										=  InstructBlipProcessor(
           tokenizer=SCREAMING_SNAKE_CASE_    ,		image_processor=SCREAMING_SNAKE_CASE_    ,		qformer_tokenizer=SCREAMING_SNAKE_CASE_)

       _UpperCamelCase										=  self.prepare_image_inputs()

       _UpperCamelCase										=  image_processor(SCREAMING_SNAKE_CASE_    ,		return_tensors='''np''')
       _UpperCamelCase										=  processor(images=SCREAMING_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)	->	Union[str, Any]:






       '''simple docstring'''
       _UpperCamelCase										=  self.get_image_processor()
       _UpperCamelCase										=  self.get_tokenizer()
       _UpperCamelCase										=  self.get_qformer_tokenizer()

       _UpperCamelCase										=  InstructBlipProcessor(
           tokenizer=SCREAMING_SNAKE_CASE_    ,		image_processor=SCREAMING_SNAKE_CASE_    ,		qformer_tokenizer=SCREAMING_SNAKE_CASE_)

       _UpperCamelCase										=  """lower newer"""

       _UpperCamelCase										=  processor(text=SCREAMING_SNAKE_CASE_)

       _UpperCamelCase										=  tokenizer(SCREAMING_SNAKE_CASE_    ,		return_token_type_ids=SCREAMING_SNAKE_CASE_)
       _UpperCamelCase										=  qformer_tokenizer(SCREAMING_SNAKE_CASE_    ,		return_token_type_ids=SCREAMING_SNAKE_CASE_)

       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 						UpperCAmelCase							( self)	->	List[str]:






       '''simple docstring'''
       _UpperCamelCase										=  self.get_image_processor()
       _UpperCamelCase										=  self.get_tokenizer()
       _UpperCamelCase										=  self.get_qformer_tokenizer()

       _UpperCamelCase										=  InstructBlipProcessor(
           tokenizer=SCREAMING_SNAKE_CASE_    ,		image_processor=SCREAMING_SNAKE_CASE_    ,		qformer_tokenizer=SCREAMING_SNAKE_CASE_)

       _UpperCamelCase										=  """lower newer"""
       _UpperCamelCase										=  self.prepare_image_inputs()

       _UpperCamelCase										=  processor(text=SCREAMING_SNAKE_CASE_    ,		images=SCREAMING_SNAKE_CASE_)

       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(SCREAMING_SNAKE_CASE_):
            processor()



  def 						UpperCAmelCase							( self)	->	List[Any]:






       '''simple docstring'''
       _UpperCamelCase										=  self.get_image_processor()
       _UpperCamelCase										=  self.get_tokenizer()
       _UpperCamelCase										=  self.get_qformer_tokenizer()

       _UpperCamelCase										=  InstructBlipProcessor(
           tokenizer=SCREAMING_SNAKE_CASE_    ,		image_processor=SCREAMING_SNAKE_CASE_    ,		qformer_tokenizer=SCREAMING_SNAKE_CASE_)

       _UpperCamelCase										=  [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

       _UpperCamelCase										=  processor.batch_decode(SCREAMING_SNAKE_CASE_)
       _UpperCamelCase										=  tokenizer.batch_decode(SCREAMING_SNAKE_CASE_)

       self.assertListEqual(SCREAMING_SNAKE_CASE_    ,		SCREAMING_SNAKE_CASE_)




  def 						UpperCAmelCase							( self)	->	str:






       '''simple docstring'''
       _UpperCamelCase										=  self.get_image_processor()
       _UpperCamelCase										=  self.get_tokenizer()
       _UpperCamelCase										=  self.get_qformer_tokenizer()

       _UpperCamelCase										=  InstructBlipProcessor(
           tokenizer=SCREAMING_SNAKE_CASE_    ,		image_processor=SCREAMING_SNAKE_CASE_    ,		qformer_tokenizer=SCREAMING_SNAKE_CASE_)

       _UpperCamelCase										=  """lower newer"""
       _UpperCamelCase										=  self.prepare_image_inputs()

       _UpperCamelCase										=  processor(text=SCREAMING_SNAKE_CASE_    ,		images=SCREAMING_SNAKE_CASE_)

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








"""simple docstring"""





from __future__ import annotations



def 				lowerCamelCase__		(      __snake_case,					__snake_case     )							->		Optional[int]:


					"""simple docstring"""





					if len(__snake_case     ) <= 1 or n <= 1:
										return

					insert_next(__snake_case,					n - 1     )
					rec_insertion_sort(__snake_case,					n - 1     )



def 				lowerCamelCase__		(      __snake_case,					__snake_case     )							->		Dict:


					"""simple docstring"""





					if index >= len(__snake_case     ) or collection[index - 1] <= collection[index]:
										return

					# Swaps adjacent elements since they are not in ascending order
					_UpperCamelCase			,  _UpperCamelCase										=  (
					    collection[index],
					    collection[index - 1],
					)

					insert_next(__snake_case,					index + 1     )


if __name__ == "__main__":
				_a														=		input("""Enter integers separated by spaces: """)
				_a														=		[int(num) for num in numbers.split()]
				rec_insertion_sort(number_list, len(number_list))
				print(number_list)






