




from collections.abc import Callable

class   __a:






    """simple docstring"""





    def __init__(				self       ,_SCREAMING_SNAKE_CASE = None  )			->		None:
         # Stores actual heap items.
         UpperCAmelCase_      :							list       =      []
         # Stores indexes of each item for supporting updates and deletion.
         UpperCAmelCase_      :							dict       =      {}
         # Stores current size of heap.
         UpperCAmelCase_      :							Tuple       =      0
         # Stores function used to evaluate the score of an item on which basis ordering
         # will be done.
         UpperCAmelCase_      :							List[Any]       =      key or (lambda _SCREAMING_SNAKE_CASE  : x)





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE  )			->		int | None:
         return int((i - 1) / 2  ) if i > 0 else None





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE  )			->		int | None:
         UpperCAmelCase_      :							Dict       =      int(2 * i + 1  )
         return left if 0 < left < self.size else None





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE  )			->		int | None:
         UpperCAmelCase_      :							List[Any]       =      int(2 * i + 2  )
         return right if 0 < right < self.size else None





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE  )			->		None:
         UpperCAmelCase_,   UpperCAmelCase_      :							Union[str, Any]       =      (
             self.pos_map[self.arr[j][0]],
             self.pos_map[self.arr[i][0]],
         )
         # Then swap the items in the list.
         UpperCAmelCase_,   UpperCAmelCase_      :							Any       =      self.arr[j], self.arr[i]





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE  )			->		bool:
         return self.arr[i][1] < self.arr[j][1]





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE  )			->		int:
         UpperCAmelCase_      :							int       =      self._left(_SCREAMING_SNAKE_CASE  )
         UpperCAmelCase_      :							Union[str, Any]       =      self._right(_SCREAMING_SNAKE_CASE  )
         UpperCAmelCase_      :							Union[str, Any]       =      i

         if left is not None and not self._cmp(_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE  ):
              UpperCAmelCase_      :							List[Any]       =      left
         if right is not None and not self._cmp(_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE  ):
              UpperCAmelCase_      :							str       =      right

         return valid_parent





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE  )			->		None:
         UpperCAmelCase_      :							List[Any]       =      self._parent(_SCREAMING_SNAKE_CASE  )
         while parent is not None and not self._cmp(_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE  ):
              self._swap(_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE  )
              UpperCAmelCase_,   UpperCAmelCase_      :							Optional[Any]       =      parent, self._parent(_SCREAMING_SNAKE_CASE  )





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE  )			->		None:
         UpperCAmelCase_      :							Tuple       =      self._get_valid_parent(_SCREAMING_SNAKE_CASE  )
         while valid_parent != index:
              self._swap(_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE  )
              UpperCAmelCase_,   UpperCAmelCase_      :							int       =      valid_parent, self._get_valid_parent(_SCREAMING_SNAKE_CASE  )





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE  )			->		None:
         if item not in self.pos_map:
              return
         UpperCAmelCase_      :							Any       =      self.pos_map[item]
         UpperCAmelCase_      :							Optional[int]       =      [item, self.key(_SCREAMING_SNAKE_CASE  )]
         # Make sure heap is right in both up and down direction.
         # Ideally only one of them will make any change.
         self._heapify_up(_SCREAMING_SNAKE_CASE  )
         self._heapify_down(_SCREAMING_SNAKE_CASE  )





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE  )			->		None:
         if item not in self.pos_map:
              return
         UpperCAmelCase_      :							str       =      self.pos_map[item]
         del self.pos_map[item]
         UpperCAmelCase_      :							Union[str, Any]       =      self.arr[self.size - 1]
         UpperCAmelCase_      :							List[str]       =      index
         self.size -= 1
         # Make sure heap is right in both up and down direction. Ideally only one
         # of them will make any change- so no performance loss in calling both.
         if self.size > index:
              self._heapify_up(_SCREAMING_SNAKE_CASE  )
              self._heapify_down(_SCREAMING_SNAKE_CASE  )





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE  )			->		None:
         UpperCAmelCase_      :							Dict       =      len(self.arr  )
         if arr_len == self.size:
              self.arr.append([item, self.key(_SCREAMING_SNAKE_CASE  )]  )
         else:
              UpperCAmelCase_      :							List[Any]       =      [item, self.key(_SCREAMING_SNAKE_CASE  )]
         UpperCAmelCase_      :							List[str]       =      self.size
         self.size += 1
         self._heapify_up(self.size - 1  )





    def 							a__				(				self  )			->		tuple | None:
         return self.arr[0] if self.size else None





    def 							a__				(				self  )			->		tuple | None:
         UpperCAmelCase_      :							Optional[int]       =      self.get_top()
         if top_item_tuple:
              self.delete_item(top_item_tuple[0]  )
         return top_item_tuple







def lowerCamelCase__       (      ):

     '''simple docstring'''




if __name__ == "__main__":
     import doctest

     doctest.testmod()





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, BlipaProcessor, BlipImageProcessor, GPTaTokenizer, PreTrainedTokenizerFast

@require_vision
class   __a(					unittest.TestCase       ):






    """simple docstring"""





    def 							a__				(				self  )			->		Optional[int]:
         UpperCAmelCase_      :							Optional[int]       =      tempfile.mkdtemp()

         UpperCAmelCase_      :							str       =      BlipImageProcessor()
         UpperCAmelCase_      :							Dict       =      GPTaTokenizer.from_pretrained('''hf-internal-testing/tiny-random-GPT2Model'''  )

         UpperCAmelCase_      :							Optional[Any]       =      BlipaProcessor(_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE  )

         processor.save_pretrained(self.tmpdirname  )





    def 							a__				(				self       ,**_SCREAMING_SNAKE_CASE  )			->		Optional[int]:
         return AutoProcessor.from_pretrained(self.tmpdirname       ,**_SCREAMING_SNAKE_CASE  ).tokenizer





    def 							a__				(				self       ,**_SCREAMING_SNAKE_CASE  )			->		Dict:
         return AutoProcessor.from_pretrained(self.tmpdirname       ,**_SCREAMING_SNAKE_CASE  ).image_processor





    def 							a__				(				self  )			->		List[Any]:
         shutil.rmtree(self.tmpdirname  )





    def 							a__				(				self  )			->		Tuple:
         UpperCAmelCase_      :							Tuple       =      [np.random.randint(255       ,size=(3, 30, 400)       ,dtype=np.uinta  )]

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

         return image_inputs





    def 							a__				(				self  )			->		List[str]:
         UpperCAmelCase_      :							Dict       =      BlipaProcessor(tokenizer=self.get_tokenizer()       ,image_processor=self.get_image_processor()  )
         processor.save_pretrained(self.tmpdirname  )

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

         UpperCAmelCase_      :							Union[str, Any]       =      BlipaProcessor.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 							a__				(				self  )			->		Any:
         UpperCAmelCase_      :							Dict       =      self.get_image_processor()
         UpperCAmelCase_      :							Any       =      self.get_tokenizer()

         UpperCAmelCase_      :							str       =      BlipaProcessor(tokenizer=_SCREAMING_SNAKE_CASE       ,image_processor=_SCREAMING_SNAKE_CASE  )

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

         UpperCAmelCase_      :							Optional[Any]       =      image_processor(_SCREAMING_SNAKE_CASE       ,return_tensors='''np'''  )
         UpperCAmelCase_      :							int       =      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 							a__				(				self  )			->		int:
         UpperCAmelCase_      :							str       =      self.get_image_processor()
         UpperCAmelCase_      :							List[Any]       =      self.get_tokenizer()

         UpperCAmelCase_      :							Any       =      BlipaProcessor(tokenizer=_SCREAMING_SNAKE_CASE       ,image_processor=_SCREAMING_SNAKE_CASE  )

         UpperCAmelCase_      :							Tuple       =      '''lower newer'''

         UpperCAmelCase_      :							Optional[int]       =      processor(text=_SCREAMING_SNAKE_CASE  )

         UpperCAmelCase_      :							int       =      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 							a__				(				self  )			->		Optional[int]:
         UpperCAmelCase_      :							str       =      self.get_image_processor()
         UpperCAmelCase_      :							List[Any]       =      self.get_tokenizer()

         UpperCAmelCase_      :							Tuple       =      BlipaProcessor(tokenizer=_SCREAMING_SNAKE_CASE       ,image_processor=_SCREAMING_SNAKE_CASE  )

         UpperCAmelCase_      :							int       =      '''lower newer'''
         UpperCAmelCase_      :							int       =      self.prepare_image_inputs()

         UpperCAmelCase_      :							List[str]       =      processor(text=_SCREAMING_SNAKE_CASE       ,images=_SCREAMING_SNAKE_CASE  )

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

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





    def 							a__				(				self  )			->		Optional[int]:
         UpperCAmelCase_      :							Tuple       =      self.get_image_processor()
         UpperCAmelCase_      :							Dict       =      self.get_tokenizer()

         UpperCAmelCase_      :							List[str]       =      BlipaProcessor(tokenizer=_SCREAMING_SNAKE_CASE       ,image_processor=_SCREAMING_SNAKE_CASE  )

         UpperCAmelCase_      :							Optional[Any]       =      [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

         UpperCAmelCase_      :							List[str]       =      processor.batch_decode(_SCREAMING_SNAKE_CASE  )
         UpperCAmelCase_      :							Union[str, Any]       =      tokenizer.batch_decode(_SCREAMING_SNAKE_CASE  )

         self.assertListEqual(_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE  )





    def 							a__				(				self  )			->		str:
         UpperCAmelCase_      :							Union[str, Any]       =      self.get_image_processor()
         UpperCAmelCase_      :							int       =      self.get_tokenizer()

         UpperCAmelCase_      :							Any       =      BlipaProcessor(tokenizer=_SCREAMING_SNAKE_CASE       ,image_processor=_SCREAMING_SNAKE_CASE  )

         UpperCAmelCase_      :							Dict       =      '''lower newer'''
         UpperCAmelCase_      :							Union[str, Any]       =      self.prepare_image_inputs()

         UpperCAmelCase_      :							Any       =      processor(text=_SCREAMING_SNAKE_CASE       ,images=_SCREAMING_SNAKE_CASE  )

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