"""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, BlipImageProcessor, BlipProcessor, PreTrainedTokenizerFast


@require_vision
class 				a (						unittest.TestCase      ):


    def    lowerCAmelCase_     (    self		:     int    ):
      _UpperCAmelCase         =					tempfile.mkdtemp()

      _UpperCAmelCase         =					BlipImageProcessor()
      _UpperCAmelCase         =					BertTokenizer.from_pretrained("""hf-internal-testing/tiny-random-BertModel"""    )

      _UpperCAmelCase         =					BlipProcessor(__lowerCAmelCase      , __lowerCAmelCase    )

      processor.save_pretrained(self.tmpdirname    )


    def    lowerCAmelCase_     (    self		:     Optional[int]      , **__lowerCAmelCase		:     Optional[Any]    ):
      return AutoProcessor.from_pretrained(self.tmpdirname      , **__lowerCAmelCase    ).tokenizer


    def    lowerCAmelCase_     (    self		:     Any      , **__lowerCAmelCase		:     List[str]    ):
      return AutoProcessor.from_pretrained(self.tmpdirname      , **__lowerCAmelCase    ).image_processor


    def    lowerCAmelCase_     (    self		:     int    ):
      shutil.rmtree(self.tmpdirname    )


    def    lowerCAmelCase_     (    self		:     Any    ):
      _UpperCAmelCase         =					[np.random.randint(255      , size=(3, 30, 400)      , dtype=np.uinta    )]

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

      return image_inputs


    def    lowerCAmelCase_     (    self		:     List[Any]    ):
      _UpperCAmelCase         =					BlipProcessor(tokenizer=self.get_tokenizer()      , image_processor=self.get_image_processor()    )
      processor.save_pretrained(self.tmpdirname    )

      _UpperCAmelCase         =					self.get_tokenizer(bos_token="""(BOS)"""      , eos_token="""(EOS)"""    )
      _UpperCAmelCase         =					self.get_image_processor(do_normalize=__lowerCAmelCase      , padding_value=1.0    )

      _UpperCAmelCase         =					BlipProcessor.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    lowerCAmelCase_     (    self		:     Dict    ):
      _UpperCAmelCase         =					self.get_image_processor()
      _UpperCAmelCase         =					self.get_tokenizer()

      _UpperCAmelCase         =					BlipProcessor(tokenizer=__lowerCAmelCase      , image_processor=__lowerCAmelCase    )

      _UpperCAmelCase         =					self.prepare_image_inputs()

      _UpperCAmelCase         =					image_processor(__lowerCAmelCase      , return_tensors="""np"""    )
      _UpperCAmelCase         =					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    lowerCAmelCase_     (    self		:     List[Any]    ):
      _UpperCAmelCase         =					self.get_image_processor()
      _UpperCAmelCase         =					self.get_tokenizer()

      _UpperCAmelCase         =					BlipProcessor(tokenizer=__lowerCAmelCase      , image_processor=__lowerCAmelCase    )

      _UpperCAmelCase         =					'lower newer'

      _UpperCAmelCase         =					processor(text=__lowerCAmelCase    )

      _UpperCAmelCase         =					tokenizer(__lowerCAmelCase      , return_token_type_ids=__lowerCAmelCase    )

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


    def    lowerCAmelCase_     (    self		:     Dict    ):
      _UpperCAmelCase         =					self.get_image_processor()
      _UpperCAmelCase         =					self.get_tokenizer()

      _UpperCAmelCase         =					BlipProcessor(tokenizer=__lowerCAmelCase      , image_processor=__lowerCAmelCase    )

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

      _UpperCAmelCase         =					processor(text=__lowerCAmelCase      , images=__lowerCAmelCase    )

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

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


    def    lowerCAmelCase_     (    self		:     List[str]    ):
      _UpperCAmelCase         =					self.get_image_processor()
      _UpperCAmelCase         =					self.get_tokenizer()

      _UpperCAmelCase         =					BlipProcessor(tokenizer=__lowerCAmelCase      , image_processor=__lowerCAmelCase    )

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

      _UpperCAmelCase         =					processor.batch_decode(__lowerCAmelCase    )
      _UpperCAmelCase         =					tokenizer.batch_decode(__lowerCAmelCase    )

      self.assertListEqual(__lowerCAmelCase      , __lowerCAmelCase    )


    def    lowerCAmelCase_     (    self		:     int    ):
      _UpperCAmelCase         =					self.get_image_processor()
      _UpperCAmelCase         =					self.get_tokenizer()

      _UpperCAmelCase         =					BlipProcessor(tokenizer=__lowerCAmelCase      , image_processor=__lowerCAmelCase    )

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

      _UpperCAmelCase         =					processor(text=__lowerCAmelCase      , images=__lowerCAmelCase    )

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



def 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    str	,     SCREAMING_SNAKE_CASE_		:    str			):



     '''simple docstring'''





     if len(SCREAMING_SNAKE_CASE_			) != len(SCREAMING_SNAKE_CASE_			):
          raise ValueError('String lengths must match!'			)

     lowercase__    :   Union[str, Any]      =       0

     for chara, chara in zip(SCREAMING_SNAKE_CASE_	,     SCREAMING_SNAKE_CASE_			):
          if chara != chara:
               count += 1

     return count


if __name__ == "__main__":
       import doctest

       doctest.testmod()

