

import os
from typing import List, Optional, Union

from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
from ..auto import AutoTokenizer





class 			_SCREAMING_SNAKE_CASE (   __snake_case		):







   '''simple docstring'''




   lowerCamelCase__				=      ["image_processor", "tokenizer"]
   lowerCamelCase__				=      "BlipImageProcessor"
   lowerCamelCase__				=      "AutoTokenizer"





   def __init__(       self					:			Tuple     , __lowerCamelCase					:			Optional[int]     , __lowerCamelCase					:			Dict     , __lowerCamelCase					:			Any			):
       super().__init__(__lowerCamelCase     , __lowerCamelCase			)

       # add QFormer tokenizer
       SCREAMING_SNAKE_CASE										=   qformer_tokenizer





   def __call__(       self					:			List[str]     , __lowerCamelCase					:			ImageInput = None     , __lowerCamelCase					:			Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None     , __lowerCamelCase					:			bool = True     , __lowerCamelCase					:			Union[bool, str, PaddingStrategy] = False     , __lowerCamelCase					:			Union[bool, str, TruncationStrategy] = None     , __lowerCamelCase					:			Optional[int] = None     , __lowerCamelCase					:			int = 0     , __lowerCamelCase					:			Optional[int] = None     , __lowerCamelCase					:			Optional[bool] = None     , __lowerCamelCase					:			bool = False     , __lowerCamelCase					:			bool = False     , __lowerCamelCase					:			bool = False     , __lowerCamelCase					:			bool = False     , __lowerCamelCase					:			bool = False     , __lowerCamelCase					:			bool = True     , __lowerCamelCase					:			Optional[Union[str, TensorType]] = None     , **__lowerCamelCase					:			Dict     , ):
       if images is None and text is None:
           raise ValueError("You have to specify at least images or text."			)

       SCREAMING_SNAKE_CASE										=   BatchFeature()

       if text is not None:
           SCREAMING_SNAKE_CASE										=   self.tokenizer(
               text=__lowerCamelCase     , add_special_tokens=__lowerCamelCase     , padding=__lowerCamelCase     , truncation=__lowerCamelCase     , max_length=__lowerCamelCase     , stride=__lowerCamelCase     , pad_to_multiple_of=__lowerCamelCase     , return_attention_mask=__lowerCamelCase     , return_overflowing_tokens=__lowerCamelCase     , return_special_tokens_mask=__lowerCamelCase     , return_offsets_mapping=__lowerCamelCase     , return_token_type_ids=__lowerCamelCase     , return_length=__lowerCamelCase     , verbose=__lowerCamelCase     , return_tensors=__lowerCamelCase     , **__lowerCamelCase     , )
           encoding.update(__lowerCamelCase			)
           SCREAMING_SNAKE_CASE										=   self.qformer_tokenizer(
               text=__lowerCamelCase     , add_special_tokens=__lowerCamelCase     , padding=__lowerCamelCase     , truncation=__lowerCamelCase     , max_length=__lowerCamelCase     , stride=__lowerCamelCase     , pad_to_multiple_of=__lowerCamelCase     , return_attention_mask=__lowerCamelCase     , return_overflowing_tokens=__lowerCamelCase     , return_special_tokens_mask=__lowerCamelCase     , return_offsets_mapping=__lowerCamelCase     , return_token_type_ids=__lowerCamelCase     , return_length=__lowerCamelCase     , verbose=__lowerCamelCase     , return_tensors=__lowerCamelCase     , **__lowerCamelCase     , )
           SCREAMING_SNAKE_CASE										=   qformer_text_encoding.pop("input_ids"			)
           SCREAMING_SNAKE_CASE										=   qformer_text_encoding.pop("attention_mask"			)

       if images is not None:
           SCREAMING_SNAKE_CASE										=   self.image_processor(__lowerCamelCase     , return_tensors=__lowerCamelCase			)
           encoding.update(__lowerCamelCase			)

       return encoding





   def      _snake_case		(       self					:			List[str]     , *__lowerCamelCase					:			Union[str, Any]     , **__lowerCamelCase					:			Union[str, Any]			):
       return self.tokenizer.batch_decode(*__lowerCamelCase     , **__lowerCamelCase			)





   def      _snake_case		(       self					:			Union[str, Any]     , *__lowerCamelCase					:			Union[str, Any]     , **__lowerCamelCase					:			Any			):
       return self.tokenizer.decode(*__lowerCamelCase     , **__lowerCamelCase			)





   @property
   # Copied from transformers.models.blip.processing_blip.BlipProcessor.model_input_names
   def      _snake_case		(       self					:			Union[str, Any]			):
       SCREAMING_SNAKE_CASE										=   self.tokenizer.model_input_names
       SCREAMING_SNAKE_CASE										=   self.image_processor.model_input_names
       return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names			)			)





   def      _snake_case		(       self					:			str     , __lowerCamelCase					:			Union[str, Any]     , **__lowerCamelCase					:			Optional[int]			):
       if os.path.isfile(__lowerCamelCase			):
           raise ValueError(f"Provided path ({save_directory}) should be a directory, not a file"			)
       os.makedirs(__lowerCamelCase     , exist_ok=__lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   os.path.join(__lowerCamelCase     , "qformer_tokenizer"			)
       self.qformer_tokenizer.save_pretrained(__lowerCamelCase			)
       return super().save_pretrained(__lowerCamelCase     , **__lowerCamelCase			)





   @classmethod
   def      _snake_case		(       cls					:			Union[str, Any]     , __lowerCamelCase					:			Tuple     , **__lowerCamelCase					:			Optional[Any]			):
       SCREAMING_SNAKE_CASE										=   AutoTokenizer.from_pretrained(__lowerCamelCase     , subfolder="qformer_tokenizer"			)
       SCREAMING_SNAKE_CASE										=   cls._get_arguments_from_pretrained(__lowerCamelCase     , **__lowerCamelCase			)
       args.append(__lowerCamelCase			)
       return cls(*__lowerCamelCase			)



'''simple docstring'''






from collections.abc import Callable






class   __snake_case			:







    """simple docstring"""



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

    def __lowercase  (  self       :    Optional[Any]       ,		lowerCamelCase       :    int						)  ->    int | None:
      return int((i - 1) / 2						) if i > 0 else None

    def __lowercase  (  self       :    Union[str, Any]       ,		lowerCamelCase       :    int						)  ->    int | None:
      lowerCAmelCase_     : List[str]     =  int(2 * i + 1						)
      return left if 0 < left < self.size else None

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

    def __lowercase  (  self       :    List[str]       ,		lowerCamelCase       :    int       ,		lowerCamelCase       :    int						)  ->    None:
      lowerCAmelCase_,				lowerCAmelCase_     : Union[str, Any]     =  (
          self.pos_map[self.arr[j][0]],
          self.pos_map[self.arr[i][0]],
      )
      # Then swap the items in the list.
      lowerCAmelCase_,				lowerCAmelCase_     : List[Any]     =  self.arr[j], self.arr[i]

    def __lowercase  (  self       :    Tuple       ,		lowerCamelCase       :    int       ,		lowerCamelCase       :    int						)  ->    bool:
      return self.arr[i][1] < self.arr[j][1]

    def __lowercase  (  self       :    int       ,		lowerCamelCase       :    int						)  ->    int:
      lowerCAmelCase_     : List[str]     =  self._left(lowerCamelCase						)
      lowerCAmelCase_     : Optional[Any]     =  self._right(lowerCamelCase						)
      lowerCAmelCase_     : Tuple     =  i

      if left is not None and not self._cmp(lowerCamelCase       ,		lowerCamelCase						):
        lowerCAmelCase_     : int     =  left
      if right is not None and not self._cmp(lowerCamelCase       ,		lowerCamelCase						):
        lowerCAmelCase_     : Optional[Any]     =  right

      return valid_parent

    def __lowercase  (  self       :    List[Any]       ,		lowerCamelCase       :    int						)  ->    None:
      lowerCAmelCase_     : Tuple     =  self._parent(lowerCamelCase						)
      while parent is not None and not self._cmp(lowerCamelCase       ,		lowerCamelCase						):
        self._swap(lowerCamelCase       ,		lowerCamelCase						)
        lowerCAmelCase_,				lowerCAmelCase_     : str     =  parent, self._parent(lowerCamelCase						)

    def __lowercase  (  self       :    Tuple       ,		lowerCamelCase       :    int						)  ->    None:
      lowerCAmelCase_     : Optional[Any]     =  self._get_valid_parent(lowerCamelCase						)
      while valid_parent != index:
        self._swap(lowerCamelCase       ,		lowerCamelCase						)
        lowerCAmelCase_,				lowerCAmelCase_     : int     =  valid_parent, self._get_valid_parent(lowerCamelCase						)

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

    def __lowercase  (  self       :    int       ,		lowerCamelCase       :    int						)  ->    None:
      if item not in self.pos_map:
        return
      lowerCAmelCase_     : List[str]     =  self.pos_map[item]
      del self.pos_map[item]
      lowerCAmelCase_     : Tuple     =  self.arr[self.size - 1]
      lowerCAmelCase_     : 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(lowerCamelCase						)
        self._heapify_down(lowerCamelCase						)

    def __lowercase  (  self       :    List[Any]       ,		lowerCamelCase       :    int       ,		lowerCamelCase       :    int						)  ->    None:
      lowerCAmelCase_     : Any     =  len(self.arr						)
      if arr_len == self.size:
        self.arr.append([item, self.key(lowerCamelCase						)]						)
      else:
        lowerCAmelCase_     : str     =  [item, self.key(lowerCamelCase						)]
      lowerCAmelCase_     : Optional[Any]     =  self.size
      self.size += 1
      self._heapify_up(self.size - 1						)

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





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







def 							UpperCamelCase_     (       ):
  '''simple docstring'''







if __name__ == "__main__":
  import doctest

  doctest.testmod()



