"""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, BertTokenizer, CLIPImageProcessor, GitProcessor, PreTrainedTokenizerFast






@require_vision
class 							__snake_case(					unittest.TestCase	):


    '''simple docstring'''





    def 						_a							(  self	):




         '''simple docstring'''



         __A					:					List[Any]								=		tempfile.mkdtemp()

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

         __A					:					List[str]								=		GitProcessor(__lowerCamelCase					,       __lowerCamelCase	)

         processor.save_pretrained(self.tmpdirname	)
    def 						_a							(  self					,       **__lowerCamelCase	):




         '''simple docstring'''



         return AutoProcessor.from_pretrained(self.tmpdirname					,       **__lowerCamelCase	).tokenizer
    def 						_a							(  self					,       **__lowerCamelCase	):




         '''simple docstring'''



         return AutoProcessor.from_pretrained(self.tmpdirname					,       **__lowerCamelCase	).image_processor
    def 						_a							(  self	):




         '''simple docstring'''



         shutil.rmtree(self.tmpdirname	)
    def 						_a							(  self	):




         '''simple docstring'''



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

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

         return image_inputs
    def 						_a							(  self	):




         '''simple docstring'''



         __A					:					Any								=		GitProcessor(tokenizer=self.get_tokenizer()					,       image_processor=self.get_image_processor()	)
         processor.save_pretrained(self.tmpdirname	)

         __A					:					int								=		self.get_tokenizer(bos_token='(BOS)'					,       eos_token='(EOS)'	)
         __A					:					List[Any]								=		self.get_image_processor(do_normalize=__lowerCamelCase					,       padding_value=1.0	)

         __A					:					List[Any]								=		GitProcessor.from_pretrained(
             self.tmpdirname					,       bos_token='(BOS)'					,       eos_token='(EOS)'					,       do_normalize=__lowerCamelCase					,       padding_value=1.0	)

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

         self.assertEqual(processor.image_processor.to_json_string()					,       image_processor_add_kwargs.to_json_string()	)
         self.assertIsInstance(processor.image_processor					,       __lowerCamelCase	)
    def 						_a							(  self	):




         '''simple docstring'''



         __A					:					Optional[Any]								=		self.get_image_processor()
         __A					:					str								=		self.get_tokenizer()

         __A					:					str								=		GitProcessor(tokenizer=__lowerCamelCase					,       image_processor=__lowerCamelCase	)

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

         __A					:					Dict								=		image_processor(__lowerCamelCase					,       return_tensors='np'	)
         __A					:					str								=		processor(images=__lowerCamelCase					,       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 						_a							(  self	):




         '''simple docstring'''



         __A					:					Optional[Any]								=		self.get_image_processor()
         __A					:					Tuple								=		self.get_tokenizer()

         __A					:					int								=		GitProcessor(tokenizer=__lowerCamelCase					,       image_processor=__lowerCamelCase	)

         __A					:					str								=		'lower newer'

         __A					:					Any								=		processor(text=__lowerCamelCase	)

         __A					:					Tuple								=		tokenizer(__lowerCamelCase					,       return_token_type_ids=__lowerCamelCase	)

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




         '''simple docstring'''



         __A					:					Union[str, Any]								=		self.get_image_processor()
         __A					:					Union[str, Any]								=		self.get_tokenizer()

         __A					:					Union[str, Any]								=		GitProcessor(tokenizer=__lowerCamelCase					,       image_processor=__lowerCamelCase	)

         __A					:					int								=		'lower newer'
         __A					:					Dict								=		self.prepare_image_inputs()

         __A					:					str								=		processor(text=__lowerCamelCase					,       images=__lowerCamelCase	)

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

         # test if it raises when no input is passed
         with pytest.raises(__lowerCamelCase	):
              processor()
    def 						_a							(  self	):




         '''simple docstring'''



         __A					:					List[str]								=		self.get_image_processor()
         __A					:					Tuple								=		self.get_tokenizer()

         __A					:					Union[str, Any]								=		GitProcessor(tokenizer=__lowerCamelCase					,       image_processor=__lowerCamelCase	)

         __A					:					Union[str, Any]								=		[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

         __A					:					int								=		processor.batch_decode(__lowerCamelCase	)
         __A					:					int								=		tokenizer.batch_decode(__lowerCamelCase	)

         self.assertListEqual(__lowerCamelCase					,       __lowerCamelCase	)

    def 						_a							(  self	):




         '''simple docstring'''



         __A					:					Optional[int]								=		self.get_image_processor()
         __A					:					Dict								=		self.get_tokenizer()

         __A					:					Union[str, Any]								=		GitProcessor(tokenizer=__lowerCamelCase					,       image_processor=__lowerCamelCase	)

         __A					:					Optional[Any]								=		'lower newer'
         __A					:					Optional[Any]								=		self.prepare_image_inputs()

         __A					:					int								=		processor(text=__lowerCamelCase					,       images=__lowerCamelCase	)

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




"""simple docstring"""







def 						_lowercase				(  _SCREAMING_SNAKE_CASE				:				list[int]						)    ->     int:







     '''simple docstring'''


     if not isinstance(_SCREAMING_SNAKE_CASE  ,       _SCREAMING_SNAKE_CASE						) or not all(
         isinstance(_SCREAMING_SNAKE_CASE  ,       _SCREAMING_SNAKE_CASE						) and item >= 0 for item in citations						):
          raise ValueError('The citations should be a list of non negative integers.'						)

     citations.sort()
     __A					:					Any								=		len(_SCREAMING_SNAKE_CASE						)

     for i in range(_SCREAMING_SNAKE_CASE						):
          if citations[len_citations - 1 - i] <= i:
               return i

     return len_citations


if __name__ == "__main__":
       import doctest

       doctest.testmod()



