

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, CLIPImageProcessor, GitProcessor, PreTrainedTokenizerFast







@require_vision
class 		__magic_name__     (				unittest.TestCase				):

   '''simple docstring'''




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






     """simple docstring"""






     a__    =tempfile.mkdtemp()

     a__    =CLIPImageProcessor()
     a__    =BertTokenizer.from_pretrained(
         '''hf-internal-testing/tiny-random-BertModel''',       model_input_names=['''input_ids''', '''attention_mask''']			)

     a__    =GitProcessor(lowercase_,       lowercase_			)

     processor.save_pretrained(self.tmpdirname			)



   def 					_UpperCAmelCase					(							self,       **lowercase_			)				->       Tuple:






     """simple docstring"""






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



   def 					_UpperCAmelCase					(							self,       **lowercase_			)				->       List[str]:






     """simple docstring"""






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



   def 					_UpperCAmelCase					(							self			)				->       Dict:






     """simple docstring"""






     shutil.rmtree(self.tmpdirname			)



   def 					_UpperCAmelCase					(							self			)				->       Optional[int]:






     """simple docstring"""






     a__    =[np.random.randint(255,       size=(3, 30, 400),       dtype=np.uinta			)]

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

     return image_inputs



   def 					_UpperCAmelCase					(							self			)				->       Union[str, Any]:






     """simple docstring"""






     a__    =GitProcessor(tokenizer=self.get_tokenizer(),       image_processor=self.get_image_processor()			)
     processor.save_pretrained(self.tmpdirname			)

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

     a__    =GitProcessor.from_pretrained(
         self.tmpdirname,       bos_token='''(BOS)''',       eos_token='''(EOS)''',       do_normalize=lowercase_,       padding_value=1.0			)

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

     self.assertEqual(processor.image_processor.to_json_string(),       image_processor_add_kwargs.to_json_string()			)
     self.assertIsInstance(processor.image_processor,       lowercase_			)



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






     """simple docstring"""






     a__    =self.get_image_processor()
     a__    =self.get_tokenizer()

     a__    =GitProcessor(tokenizer=lowercase_,       image_processor=lowercase_			)

     a__    =self.prepare_image_inputs()

     a__    =image_processor(lowercase_,       return_tensors='''np'''			)
     a__    =processor(images=lowercase_,       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"""






     a__    =self.get_image_processor()
     a__    =self.get_tokenizer()

     a__    =GitProcessor(tokenizer=lowercase_,       image_processor=lowercase_			)

     a__    ='''lower newer'''

     a__    =processor(text=lowercase_			)

     a__    =tokenizer(lowercase_,       return_token_type_ids=lowercase_			)

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



   def 					_UpperCAmelCase					(							self			)				->       Dict:






     """simple docstring"""






     a__    =self.get_image_processor()
     a__    =self.get_tokenizer()

     a__    =GitProcessor(tokenizer=lowercase_,       image_processor=lowercase_			)

     a__    ='''lower newer'''
     a__    =self.prepare_image_inputs()

     a__    =processor(text=lowercase_,       images=lowercase_			)

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

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



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






     """simple docstring"""






     a__    =self.get_image_processor()
     a__    =self.get_tokenizer()

     a__    =GitProcessor(tokenizer=lowercase_,       image_processor=lowercase_			)

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

     a__    =processor.batch_decode(lowercase_			)
     a__    =tokenizer.batch_decode(lowercase_			)

     self.assertListEqual(lowercase_,       lowercase_			)



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






     """simple docstring"""






     a__    =self.get_image_processor()
     a__    =self.get_tokenizer()

     a__    =GitProcessor(tokenizer=lowercase_,       image_processor=lowercase_			)

     a__    ='''lower newer'''
     a__    =self.prepare_image_inputs()

     a__    =processor(text=lowercase_,       images=lowercase_			)

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



def      UpperCAmelCase__							(     _A :					int      , _A :					int				):





  '''simple docstring'''







  a__    =1.0
  for i in range(1      , r + 1				):
    ret *= (n + 1 - i) / i
  return round(_A				)




def      UpperCAmelCase__							(     _A :					int				):





  '''simple docstring'''







  return choose(8 + n      , _A				) + choose(9 + n      , _A				) - 10




def      UpperCAmelCase__							(     _A :					int				):





  '''simple docstring'''







  return sum(non_bouncy_exact(_A				) for i in range(1      , n + 1				)				)




def      UpperCAmelCase__							(     _A :					int = 1_00				):





  '''simple docstring'''







  return non_bouncy_upto(_A				)


if __name__ == "__main__":
       print(f"""{solution() = }""")
