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        UpperCAmelCase_					(				unittest.TestCase     ):




    def     __lowerCamelCase			(       self	: Tuple )						->			List[Any]:
      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     __lowerCamelCase			(       self	: str   ,   **lowerCAmelCase	: int )						->			List[str]:
      return AutoProcessor.from_pretrained(self.tmpdirname   ,   **__lowercase ).tokenizer




    def     __lowerCamelCase			(       self	: List[Any]   ,   **lowerCAmelCase	: List[Any] )						->			Optional[int]:
      return AutoProcessor.from_pretrained(self.tmpdirname   ,   **__lowercase ).image_processor




    def     __lowerCamelCase			(       self	: Optional[Any] )						->			Optional[Any]:
      shutil.rmtree(self.tmpdirname )




    def     __lowerCamelCase			(       self	: Dict )						->			List[Any]:
      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     __lowerCamelCase			(       self	: List[str] )						->			int:
      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     __lowerCamelCase			(       self	: Optional[int] )						->			List[str]:
      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     __lowerCamelCase			(       self	: Any )						->			Optional[Any]:
      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     __lowerCamelCase			(       self	: Optional[int] )						->			Dict:
      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     __lowerCamelCase			(       self	: Tuple )						->			List[Any]:
      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     __lowerCamelCase			(       self	: Optional[int] )						->			int:
      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    snake_case   (				A     )				->				str:




	'''simple docstring'''


	if not isinstance(A		,  A     ):
		lowerCamelCase_				:						int				  =				(
		    'operation can not be conducted on a object of type '
		    f"{type(A     ).__name__}"
		)
		raise TypeError(A     )
	lowerCamelCase_				:						List[Any]				  =				''
	for _ in range(0		,  32     ):
		bit_string += str(number % 2     )
		lowerCamelCase_				:						int				  =				number >> 1
	return bit_string






def    snake_case   (				A     )				->				str:




	'''simple docstring'''


	if number < 0:
		raise ValueError('the value of input must be positive'     )
	elif isinstance(A		,  A     ):
		raise TypeError('Input value must be a \'int\' type'     )
	elif isinstance(A		,  A     ):
		raise TypeError('\'<\' not supported between instances of \'str\' and \'int\''     )
	lowerCamelCase_				:						Any				  =				0
	# iterator over [1 to 32],since we are dealing with 32 bit integer
	for _ in range(1		,  33     ):
		# left shift the bits by unity
		lowerCamelCase_				:						Any				  =				result << 1
		# get the end bit
		lowerCamelCase_				:						Any				  =				number % 2
		# right shift the bits by unity
		lowerCamelCase_				:						Optional[Any]				  =				number >> 1
		# add that bit to our ans
		lowerCamelCase_				:						Dict				  =				result | end_bit
	return get_reverse_bit_string(A     )


if __name__ == "__main__":
							import doctest

							doctest.testmod()
