

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 		__magic_name__     (				unittest.TestCase				):

   '''simple docstring'''




   def 					_UpperCAmelCase					(							self			)				->       Any:






     """simple docstring"""






     a__    =tempfile.mkdtemp()

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

     a__    =GitProcessor(SCREAMING_SNAKE_CASE_,       SCREAMING_SNAKE_CASE_			)

     processor.save_pretrained(self.tmpdirname			)



   def 					_UpperCAmelCase					(							self,       **lowercase_			)				->       Union[str, Any]:






     """simple docstring"""






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



   def 					_UpperCAmelCase					(							self,       **lowercase_			)				->       List[str]:






     """simple docstring"""






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



   def 					_UpperCAmelCase					(							self			)				->       int:






     """simple docstring"""






     shutil.rmtree(self.tmpdirname			)



   def 					_UpperCAmelCase					(							self			)				->       Tuple:






     """simple docstring"""






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

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

     return image_inputs



   def 					_UpperCAmelCase					(							self			)				->       str:






     """simple docstring"""






     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=SCREAMING_SNAKE_CASE_,       padding_value=1.0			)

     a__    =GitProcessor.from_pretrained(
         self.tmpdirname,       bos_token='''(BOS)''',       eos_token='''(EOS)''',       do_normalize=SCREAMING_SNAKE_CASE_,       padding_value=1.0			)

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

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



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






     """simple docstring"""






     a__    =self.get_image_processor()
     a__    =self.get_tokenizer()

     a__    =GitProcessor(tokenizer=SCREAMING_SNAKE_CASE_,       image_processor=SCREAMING_SNAKE_CASE_			)

     a__    =self.prepare_image_inputs()

     a__    =image_processor(SCREAMING_SNAKE_CASE_,       return_tensors='''np'''			)
     a__    =processor(images=SCREAMING_SNAKE_CASE_,       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 					_UpperCAmelCase					(							self			)				->       Dict:






     """simple docstring"""






     a__    =self.get_image_processor()
     a__    =self.get_tokenizer()

     a__    =GitProcessor(tokenizer=SCREAMING_SNAKE_CASE_,       image_processor=SCREAMING_SNAKE_CASE_			)

     a__    ='lower newer'

     a__    =processor(text=SCREAMING_SNAKE_CASE_			)

     a__    =tokenizer(SCREAMING_SNAKE_CASE_,       return_token_type_ids=SCREAMING_SNAKE_CASE_			)

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



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






     """simple docstring"""






     a__    =self.get_image_processor()
     a__    =self.get_tokenizer()

     a__    =GitProcessor(tokenizer=SCREAMING_SNAKE_CASE_,       image_processor=SCREAMING_SNAKE_CASE_			)

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

     a__    =processor(text=SCREAMING_SNAKE_CASE_,       images=SCREAMING_SNAKE_CASE_			)

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

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



   def 					_UpperCAmelCase					(							self			)				->       str:






     """simple docstring"""






     a__    =self.get_image_processor()
     a__    =self.get_tokenizer()

     a__    =GitProcessor(tokenizer=SCREAMING_SNAKE_CASE_,       image_processor=SCREAMING_SNAKE_CASE_			)

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

     a__    =processor.batch_decode(SCREAMING_SNAKE_CASE_			)
     a__    =tokenizer.batch_decode(SCREAMING_SNAKE_CASE_			)

     self.assertListEqual(SCREAMING_SNAKE_CASE_,       SCREAMING_SNAKE_CASE_			)



   def 					_UpperCAmelCase					(							self			)				->       Dict:






     """simple docstring"""






     a__    =self.get_image_processor()
     a__    =self.get_tokenizer()

     a__    =GitProcessor(tokenizer=SCREAMING_SNAKE_CASE_,       image_processor=SCREAMING_SNAKE_CASE_			)

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

     a__    =processor(text=SCREAMING_SNAKE_CASE_,       images=SCREAMING_SNAKE_CASE_			)

     # 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"""







import pytest

from datasets.utils.version import Version

@pytest.mark.parametrize(
    'other, expected_equality'       ,  [
        (Version('1.0.0'		), True),
        ('1.0.0', True),
        (Version('2.0.0'		), False),
        ('2.0.0', False),
        ('1', False),
        ('a', False),
        (1, False),
        (None, False),
    ]       ,  )
def 							UpperCamelCase_       (       lowerCAmelCase__ :							List[Any]       ,  lowerCAmelCase__ :							List[Any]		)		->  Tuple:

  """simple docstring"""




  lowerCAmelCase_  :							List[str]								=					Version('1.0.0'		)
  assert (version == other) is expected_equality
  assert (version != other) is not expected_equality
  assert (hash(lowerCAmelCase__		) == hash(lowerCAmelCase__		)) is expected_equality





