






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 							lowercase    (						unittest.TestCase			):






 '''simple docstring'''




 def  snake_case__				(	self) ->		Tuple:

     """simple docstring"""



     _UpperCAmelCase				:      Union[str, Any]			  =				tempfile.mkdtemp()

     _UpperCAmelCase				:      Union[str, Any]			  =				BlipImageProcessor()
     _UpperCAmelCase				:      Optional[Any]			  =				BertTokenizer.from_pretrained('''hf-internal-testing/tiny-random-BertModel''')

     _UpperCAmelCase				:      Optional[Any]			  =				BlipProcessor(UpperCAmelCase_							,  UpperCAmelCase_)

     processor.save_pretrained(self.tmpdirname)


 def  snake_case__				(	self							,  **_A) ->		Dict:

     """simple docstring"""



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


 def  snake_case__				(	self							,  **_A) ->		List[str]:

     """simple docstring"""



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


 def  snake_case__				(	self) ->		Tuple:

     """simple docstring"""



     shutil.rmtree(self.tmpdirname)


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

     """simple docstring"""



     _UpperCAmelCase				:      List[str]			  =				[np.random.randint(255							,  size=(3, 30, 400)							,  dtype=np.uinta)]

     _UpperCAmelCase				:      List[Any]			  =				[Image.fromarray(np.moveaxis(UpperCAmelCase_							,  0							,  -1)) for x in image_inputs]

     return image_inputs


 def  snake_case__				(	self) ->		Tuple:

     """simple docstring"""



     _UpperCAmelCase				:      int			  =				BlipProcessor(tokenizer=self.get_tokenizer()							,  image_processor=self.get_image_processor())
     processor.save_pretrained(self.tmpdirname)

     _UpperCAmelCase				:      Union[str, Any]			  =				self.get_tokenizer(bos_token='''(BOS)'''							,  eos_token='''(EOS)''')
     _UpperCAmelCase				:      str			  =				self.get_image_processor(do_normalize=UpperCAmelCase_							,  padding_value=1.0)

     _UpperCAmelCase				:      Dict			  =				BlipProcessor.from_pretrained(
         self.tmpdirname							,  bos_token='''(BOS)'''							,  eos_token='''(EOS)'''							,  do_normalize=UpperCAmelCase_							,  padding_value=1.0)

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

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


 def  snake_case__				(	self) ->		List[str]:

     """simple docstring"""



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

     _UpperCAmelCase				:      List[str]			  =				BlipProcessor(tokenizer=UpperCAmelCase_							,  image_processor=UpperCAmelCase_)

     _UpperCAmelCase				:      Union[str, Any]			  =				self.prepare_image_inputs()

     _UpperCAmelCase				:      str			  =				image_processor(UpperCAmelCase_							,  return_tensors='''np''')
     _UpperCAmelCase				:      Dict			  =				processor(images=UpperCAmelCase_							,  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  snake_case__				(	self) ->		Dict:

     """simple docstring"""



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

     _UpperCAmelCase				:      int			  =				BlipProcessor(tokenizer=UpperCAmelCase_							,  image_processor=UpperCAmelCase_)

     _UpperCAmelCase				:      Optional[Any]			  =				'''lower newer'''

     _UpperCAmelCase				:      Optional[Any]			  =				processor(text=UpperCAmelCase_)

     _UpperCAmelCase				:      Optional[int]			  =				tokenizer(UpperCAmelCase_							,  return_token_type_ids=UpperCAmelCase_)

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


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

     """simple docstring"""



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

     _UpperCAmelCase				:      Any			  =				BlipProcessor(tokenizer=UpperCAmelCase_							,  image_processor=UpperCAmelCase_)

     _UpperCAmelCase				:      Any			  =				'''lower newer'''
     _UpperCAmelCase				:      Dict			  =				self.prepare_image_inputs()

     _UpperCAmelCase				:      Dict			  =				processor(text=UpperCAmelCase_							,  images=UpperCAmelCase_)

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

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


 def  snake_case__				(	self) ->		Tuple:

     """simple docstring"""



     _UpperCAmelCase				:      int			  =				self.get_image_processor()
     _UpperCAmelCase				:      List[Any]			  =				self.get_tokenizer()

     _UpperCAmelCase				:      Dict			  =				BlipProcessor(tokenizer=UpperCAmelCase_							,  image_processor=UpperCAmelCase_)

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

     _UpperCAmelCase				:      str			  =				processor.batch_decode(UpperCAmelCase_)
     _UpperCAmelCase				:      Tuple			  =				tokenizer.batch_decode(UpperCAmelCase_)

     self.assertListEqual(UpperCAmelCase_							,  UpperCAmelCase_)


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

     """simple docstring"""



     _UpperCAmelCase				:      List[Any]			  =				self.get_image_processor()
     _UpperCAmelCase				:      int			  =				self.get_tokenizer()

     _UpperCAmelCase				:      int			  =				BlipProcessor(tokenizer=UpperCAmelCase_							,  image_processor=UpperCAmelCase_)

     _UpperCAmelCase				:      Optional[int]			  =				'''lower newer'''
     _UpperCAmelCase				:      str			  =				self.prepare_image_inputs()

     _UpperCAmelCase				:      Union[str, Any]			  =				processor(text=UpperCAmelCase_							,  images=UpperCAmelCase_)

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












import unittest

from knapsack import knapsack as k
class 							A_    (						unittest.TestCase			):






 '''simple docstring'''




 def  snake_case__				(	self) ->		Dict:

     """simple docstring"""



     _UpperCAmelCase				:      Optional[int]			  =				0
     _UpperCAmelCase				:      List[Any]			  =				[0]
     _UpperCAmelCase				:      Optional[Any]			  =				[0]
     _UpperCAmelCase				:      Optional[int]			  =				len(_A)
     self.assertEqual(k.knapsack(_A							,  _A							,  _A							,  _A)							,  0)

     _UpperCAmelCase				:      Optional[int]			  =				[60]
     _UpperCAmelCase				:      List[str]			  =				[10]
     _UpperCAmelCase				:      str			  =				len(_A)
     self.assertEqual(k.knapsack(_A							,  _A							,  _A							,  _A)							,  0)


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

     """simple docstring"""



     _UpperCAmelCase				:      Any			  =				3
     _UpperCAmelCase				:      int			  =				[1, 2, 3]
     _UpperCAmelCase				:      List[str]			  =				[3, 2, 1]
     _UpperCAmelCase				:      Union[str, Any]			  =				len(_A)
     self.assertEqual(k.knapsack(_A							,  _A							,  _A							,  _A)							,  5)


 def  snake_case__				(	self) ->		Tuple:

     """simple docstring"""



     _UpperCAmelCase				:      List[str]			  =				50
     _UpperCAmelCase				:      Tuple			  =				[60, 100, 120]
     _UpperCAmelCase				:      Optional[int]			  =				[10, 20, 30]
     _UpperCAmelCase				:      Optional[Any]			  =				len(_A)
     self.assertEqual(k.knapsack(_A							,  _A							,  _A							,  _A)							,  220)


if __name__ == "__main__":
  unittest.main()




