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       __snake_case (  unittest.TestCase ):
 def 						UpperCAmelCase__							(	self    )						->				Any:
       '''simple docstring'''





       UpperCAmelCase     :			List[str]     	=tempfile.mkdtemp()

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

       UpperCAmelCase     :			Tuple     	=GitProcessor(snake_case__		, snake_case__    )

       processor.save_pretrained(self.tmpdirname    )
 def 						UpperCAmelCase__							(	self		, **snake_case__    )						->				str:
       '''simple docstring'''





       return AutoProcessor.from_pretrained(self.tmpdirname		, **snake_case__    ).tokenizer
 def 						UpperCAmelCase__							(	self		, **snake_case__    )						->				Union[str, Any]:
       '''simple docstring'''





       return AutoProcessor.from_pretrained(self.tmpdirname		, **snake_case__    ).image_processor
 def 						UpperCAmelCase__							(	self    )						->				List[str]:
       '''simple docstring'''





       shutil.rmtree(self.tmpdirname    )
 def 						UpperCAmelCase__							(	self    )						->				Any:
       '''simple docstring'''





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

       UpperCAmelCase     :			Dict     	=[Image.fromarray(np.moveaxis(snake_case__		, 0		, -1    )    ) for x in image_inputs]

       return image_inputs
 def 						UpperCAmelCase__							(	self    )						->				Dict:
       '''simple docstring'''





       UpperCAmelCase     :			List[str]     	=GitProcessor(tokenizer=self.get_tokenizer()		, image_processor=self.get_image_processor()    )
       processor.save_pretrained(self.tmpdirname    )

       UpperCAmelCase     :			Optional[Any]     	=self.get_tokenizer(bos_token='''(BOS)'''		, eos_token='''(EOS)'''    )
       UpperCAmelCase     :			Any     	=self.get_image_processor(do_normalize=snake_case__		, padding_value=1.0    )

       UpperCAmelCase     :			List[str]     	=GitProcessor.from_pretrained(
           self.tmpdirname		, bos_token='''(BOS)'''		, eos_token='''(EOS)'''		, do_normalize=snake_case__		, padding_value=1.0    )

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

       self.assertEqual(processor.image_processor.to_json_string()		, image_processor_add_kwargs.to_json_string()    )
       self.assertIsInstance(processor.image_processor		, snake_case__    )
 def 						UpperCAmelCase__							(	self    )						->				List[Any]:
       '''simple docstring'''





       UpperCAmelCase     :			str     	=self.get_image_processor()
       UpperCAmelCase     :			str     	=self.get_tokenizer()

       UpperCAmelCase     :			int     	=GitProcessor(tokenizer=snake_case__		, image_processor=snake_case__    )

       UpperCAmelCase     :			Optional[Any]     	=self.prepare_image_inputs()

       UpperCAmelCase     :			List[str]     	=image_processor(snake_case__		, return_tensors='''np'''    )
       UpperCAmelCase     :			Optional[int]     	=processor(images=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    )						->				str:
       '''simple docstring'''





       UpperCAmelCase     :			Dict     	=self.get_image_processor()
       UpperCAmelCase     :			int     	=self.get_tokenizer()

       UpperCAmelCase     :			List[Any]     	=GitProcessor(tokenizer=snake_case__		, image_processor=snake_case__    )

       UpperCAmelCase     :			Any     	='''lower newer'''

       UpperCAmelCase     :			List[str]     	=processor(text=snake_case__    )

       UpperCAmelCase     :			Dict     	=tokenizer(snake_case__		, return_token_type_ids=snake_case__    )

       for key in encoded_tok.keys():
             self.assertListEqual(encoded_tok[key]		, encoded_processor[key]    )
 def 						UpperCAmelCase__							(	self    )						->				Optional[int]:
       '''simple docstring'''





       UpperCAmelCase     :			Tuple     	=self.get_image_processor()
       UpperCAmelCase     :			Any     	=self.get_tokenizer()

       UpperCAmelCase     :			Optional[int]     	=GitProcessor(tokenizer=snake_case__		, image_processor=snake_case__    )

       UpperCAmelCase     :			Dict     	='''lower newer'''
       UpperCAmelCase     :			str     	=self.prepare_image_inputs()

       UpperCAmelCase     :			List[Any]     	=processor(text=snake_case__		, images=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(snake_case__    ):
             processor()
 def 						UpperCAmelCase__							(	self    )						->				Tuple:
       '''simple docstring'''





       UpperCAmelCase     :			List[str]     	=self.get_image_processor()
       UpperCAmelCase     :			Optional[int]     	=self.get_tokenizer()

       UpperCAmelCase     :			Dict     	=GitProcessor(tokenizer=snake_case__		, image_processor=snake_case__    )

       UpperCAmelCase     :			Optional[int]     	=[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

       UpperCAmelCase     :			int     	=processor.batch_decode(snake_case__    )
       UpperCAmelCase     :			Tuple     	=tokenizer.batch_decode(snake_case__    )

       self.assertListEqual(snake_case__		, snake_case__    )






 def 						UpperCAmelCase__							(	self    )						->				Dict:
       '''simple docstring'''





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

       UpperCAmelCase     :			List[str]     	=GitProcessor(tokenizer=snake_case__		, image_processor=snake_case__    )

       UpperCAmelCase     :			Optional[int]     	='''lower newer'''
       UpperCAmelCase     :			Any     	=self.prepare_image_inputs()

       UpperCAmelCase     :			Any     	=processor(text=snake_case__		, images=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''']    )

from hashlib import mda, shaaaa

__snake_case         =     (shaaaa, mda)







class       __snake_case :
 def __init__(	self		, snake_case__ = 8    )						->				None:
       '''simple docstring'''





       UpperCAmelCase     :			str     	=0b0
       UpperCAmelCase     :			str     	=size
 def 						UpperCAmelCase__							(	self		, snake_case__    )						->				None:
       '''simple docstring'''





       UpperCAmelCase     :			Union[str, Any]     	=self.hash_(snake_case__    )
       self.bitarray |= h
 def 						UpperCAmelCase__							(	self		, snake_case__    )						->				bool:
       '''simple docstring'''





       UpperCAmelCase     :			List[Any]     	=self.hash_(snake_case__    )
       return (h & self.bitarray) == h
 def __contains__(	self		, snake_case__    )						->				bool:
       '''simple docstring'''





       return self.exists(snake_case__    )
 def 						UpperCAmelCase__							(	self		, snake_case__    )						->				str:
       '''simple docstring'''





       UpperCAmelCase     :			Dict     	=bin(snake_case__    )[2:]
       return res.zfill(self.size    )
 @property
 def 						UpperCAmelCase__							(	self    )						->				str:
       '''simple docstring'''





       return self.format_bin(self.bitarray    )
 def 						UpperCAmelCase__							(	self		, snake_case__    )						->				int:
       '''simple docstring'''





       UpperCAmelCase     :			Union[str, Any]     	=0b0
       for func in HASH_FUNCTIONS:
             UpperCAmelCase     :			Optional[Any]     	=(
                 int.from_bytes(func(value.encode()    ).digest()		, '''little'''    ) % self.size
             )
             res |= 2**position
       return res
 def 						UpperCAmelCase__							(	self		, snake_case__    )						->				str:
       '''simple docstring'''





       return self.format_bin(self.hash_(snake_case__    )    )






 @property
 def 						UpperCAmelCase__							(	self    )						->				float:
       '''simple docstring'''





       UpperCAmelCase     :			int     	=bin(self.bitarray    ).count('''1'''    )
       return (n_ones / self.size) ** len(snake_case__    )
