






"""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 __a   (   unittest.TestCase				):



  def 						A_				(self  :		Optional[int]   )		->							List[str]:
   __A	:       Any       =	tempfile.mkdtemp()

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

   __A	:       Optional[int]       =	GitProcessor(lowercase_				,			lowercase_   )

   processor.save_pretrained(self.tmpdirname   )



  def 						A_				(self  :		Any				,			**lowercase_  :		Tuple   )		->							List[str]:
   return AutoProcessor.from_pretrained(self.tmpdirname				,			**lowercase_   ).tokenizer



  def 						A_				(self  :		List[Any]				,			**lowercase_  :		List[str]   )		->							Tuple:
   return AutoProcessor.from_pretrained(self.tmpdirname				,			**lowercase_   ).image_processor



  def 						A_				(self  :		Union[str, Any]   )		->							int:
   shutil.rmtree(self.tmpdirname   )



  def 						A_				(self  :		str   )		->							List[Any]:
   __A	:       Optional[int]       =	[np.random.randint(255				,			size=(3, 30, 400)				,			dtype=np.uinta   )]

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

   return image_inputs



  def 						A_				(self  :		Tuple   )		->							Any:
   __A	:       Tuple       =	GitProcessor(tokenizer=self.get_tokenizer()				,			image_processor=self.get_image_processor()   )
   processor.save_pretrained(self.tmpdirname   )

   __A	:       str       =	self.get_tokenizer(bos_token='(BOS)'				,			eos_token='(EOS)'   )
   __A	:       int       =	self.get_image_processor(do_normalize=lowercase_				,			padding_value=1.0   )

   __A	:       int       =	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 						A_				(self  :		int   )		->							Union[str, Any]:
   __A	:       Tuple       =	self.get_image_processor()
   __A	:       Optional[Any]       =	self.get_tokenizer()

   __A	:       Optional[Any]       =	GitProcessor(tokenizer=lowercase_				,			image_processor=lowercase_   )

   __A	:       Optional[int]       =	self.prepare_image_inputs()

   __A	:       List[str]       =	image_processor(lowercase_				,			return_tensors='np'   )
   __A	:       Tuple       =	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 						A_				(self  :		Tuple   )		->							List[str]:
   __A	:       Union[str, Any]       =	self.get_image_processor()
   __A	:       Union[str, Any]       =	self.get_tokenizer()

   __A	:       Optional[int]       =	GitProcessor(tokenizer=lowercase_				,			image_processor=lowercase_   )

   __A	:       str       =	'lower newer'

   __A	:       int       =	processor(text=lowercase_   )

   __A	:       str       =	tokenizer(lowercase_				,			return_token_type_ids=lowercase_   )

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



  def 						A_				(self  :		Union[str, Any]   )		->							str:
   __A	:       Union[str, Any]       =	self.get_image_processor()
   __A	:       Optional[Any]       =	self.get_tokenizer()

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

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

   __A	:       Union[str, Any]       =	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 						A_				(self  :		List[Any]   )		->							Any:
   __A	:       List[Any]       =	self.get_image_processor()
   __A	:       Optional[Any]       =	self.get_tokenizer()

   __A	:       Any       =	GitProcessor(tokenizer=lowercase_				,			image_processor=lowercase_   )

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

   __A	:       str       =	processor.batch_decode(lowercase_   )
   __A	:       List[Any]       =	tokenizer.batch_decode(lowercase_   )

   self.assertListEqual(lowercase_				,			lowercase_   )



  def 						A_				(self  :		Any   )		->							Dict:
   __A	:       Union[str, Any]       =	self.get_image_processor()
   __A	:       Dict       =	self.get_tokenizer()

   __A	:       Tuple       =	GitProcessor(tokenizer=lowercase_				,			image_processor=lowercase_   )

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

   __A	:       List[str]       =	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']   )













"""simple docstring"""


def 				a (     UpperCamelCase_							:				list     ,	UpperCamelCase_							:				int		)  ->		int:
 for index, item in enumerate(UpperCamelCase_		):
  if item == target:
   return index
 return -1




def 				a (     UpperCamelCase_							:				list     ,	UpperCamelCase_							:				int     ,	UpperCamelCase_							:				int     ,	UpperCamelCase_							:				int		)  ->		int:
 if not (0 <= high < len(UpperCamelCase_		) and 0 <= low < len(UpperCamelCase_		)):
  raise Exception('Invalid upper or lower bound!'		)
 if high < low:
  return -1
 if sequence[low] == target:
  return low
 if sequence[high] == target:
  return high
 return rec_linear_search(UpperCamelCase_     ,	low + 1     ,	high - 1     ,	UpperCamelCase_		)


if __name__ == "__main__":
   _UpperCamelCase   :						Any     						= input("""Enter numbers separated by comma:\n""").strip()
   _UpperCamelCase   :						Optional[Any]     						= [int(item.strip()) for item in user_input.split(""",""")]

   _UpperCamelCase   :						List[str]     						= int(input("""Enter a single number to be found in the list:\n""").strip())
   _UpperCamelCase   :						List[Any]     						= linear_search(sequence, target)
   if result != -1:
      print(f'''linear_search({sequence}, {target}) = {result}''')
   else:
      print(f'''{target} was not found in {sequence}''')





