


"""simple docstring"""





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 		snake_case_(       a__			):
     __UpperCamelCase  =					['''image_processor''', '''tokenizer''']
     __UpperCamelCase  =					'''BlipImageProcessor'''
     __UpperCamelCase  =					'''AutoTokenizer'''






     def __init__(	self  :					Optional[Any]					,				UpperCamelCase_  :					Any					,				UpperCamelCase_  :					Union[str, Any]					,				UpperCamelCase_  :					str				):
           super().__init__(UpperCamelCase_					,				UpperCamelCase_				)

           # add QFormer tokenizer
           lowerCAmelCase					:	str       =   qformer_tokenizer






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

           lowerCAmelCase					:	Optional[Any]       =   BatchFeature()

           if text is not None:
                 lowerCAmelCase					:	int       =   self.tokenizer(
                     text=UpperCamelCase_					,				add_special_tokens=UpperCamelCase_					,				padding=UpperCamelCase_					,				truncation=UpperCamelCase_					,				max_length=UpperCamelCase_					,				stride=UpperCamelCase_					,				pad_to_multiple_of=UpperCamelCase_					,				return_attention_mask=UpperCamelCase_					,				return_overflowing_tokens=UpperCamelCase_					,				return_special_tokens_mask=UpperCamelCase_					,				return_offsets_mapping=UpperCamelCase_					,				return_token_type_ids=UpperCamelCase_					,				return_length=UpperCamelCase_					,				verbose=UpperCamelCase_					,				return_tensors=UpperCamelCase_					,				**UpperCamelCase_					,				)
                 encoding.update(UpperCamelCase_				)
                 lowerCAmelCase					:	Optional[Any]       =   self.qformer_tokenizer(
                     text=UpperCamelCase_					,				add_special_tokens=UpperCamelCase_					,				padding=UpperCamelCase_					,				truncation=UpperCamelCase_					,				max_length=UpperCamelCase_					,				stride=UpperCamelCase_					,				pad_to_multiple_of=UpperCamelCase_					,				return_attention_mask=UpperCamelCase_					,				return_overflowing_tokens=UpperCamelCase_					,				return_special_tokens_mask=UpperCamelCase_					,				return_offsets_mapping=UpperCamelCase_					,				return_token_type_ids=UpperCamelCase_					,				return_length=UpperCamelCase_					,				verbose=UpperCamelCase_					,				return_tensors=UpperCamelCase_					,				**UpperCamelCase_					,				)
                 lowerCAmelCase					:	int       =   qformer_text_encoding.pop('''input_ids'''				)
                 lowerCAmelCase					:	List[Any]       =   qformer_text_encoding.pop('''attention_mask'''				)

           if images is not None:
                 lowerCAmelCase					:	str       =   self.image_processor(UpperCamelCase_					,				return_tensors=UpperCamelCase_				)
                 encoding.update(UpperCamelCase_				)

           return encoding






     def      lowerCamelCase__     (	self  :					Optional[int]					,				*UpperCamelCase_  :					List[str]					,				**UpperCamelCase_  :					Optional[Any]				):
           return self.tokenizer.batch_decode(*UpperCamelCase_					,				**UpperCamelCase_				)






     def      lowerCamelCase__     (	self  :					Dict					,				*UpperCamelCase_  :					Any					,				**UpperCamelCase_  :					List[str]				):
           return self.tokenizer.decode(*UpperCamelCase_					,				**UpperCamelCase_				)






     @property
     # Copied from transformers.models.blip.processing_blip.BlipProcessor.model_input_names
     def      lowerCamelCase__     (	self  :					Optional[int]				):
           lowerCAmelCase					:	Any       =   self.tokenizer.model_input_names
           lowerCAmelCase					:	List[Any]       =   self.image_processor.model_input_names
           return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names				)				)






     def      lowerCamelCase__     (	self  :					str					,				UpperCamelCase_  :					str					,				**UpperCamelCase_  :					Optional[int]				):
           if os.path.isfile(UpperCamelCase_				):
                 raise ValueError(F'''Provided path ({save_directory}) should be a directory, not a file'''				)
           os.makedirs(UpperCamelCase_					,				exist_ok=UpperCamelCase_				)
           lowerCAmelCase					:	Tuple       =   os.path.join(UpperCamelCase_					,				'''qformer_tokenizer'''				)
           self.qformer_tokenizer.save_pretrained(UpperCamelCase_				)
           return super().save_pretrained(UpperCamelCase_					,				**UpperCamelCase_				)






     @classmethod
     def      lowerCamelCase__     (	cls  :					Optional[Any]					,				UpperCamelCase_  :					str					,				**UpperCamelCase_  :					Union[str, Any]				):
           lowerCAmelCase					:	Any       =   AutoTokenizer.from_pretrained(UpperCamelCase_					,				subfolder='''qformer_tokenizer'''				)
           lowerCAmelCase					:	Union[str, Any]       =   cls._get_arguments_from_pretrained(UpperCamelCase_					,				**UpperCamelCase_				)
           args.append(UpperCamelCase_				)
           return cls(*UpperCamelCase_				)






"""simple docstring"""





class 		snake_case_:






     def __init__(	self  :					Union[str, Any]					,				UpperCamelCase_  :					str				):
           lowerCAmelCase					:	Dict       =   val
           lowerCAmelCase					:	str       =   None
           lowerCAmelCase					:	Dict       =   None






     def      lowerCamelCase__     (	self  :					Union[str, Any]					,				UpperCamelCase_  :					Dict				):
           if self.val:
                 if val < self.val:
                       if self.left is None:
                             lowerCAmelCase					:	int       =   Node(UpperCamelCase_				)
                       else:
                             self.left.insert(UpperCamelCase_				)
                 elif val > self.val:
                       if self.right is None:
                             lowerCAmelCase					:	Any       =   Node(UpperCamelCase_				)
                       else:
                             self.right.insert(UpperCamelCase_				)
           else:
                 lowerCAmelCase					:	Optional[Any]       =   val



def      _snake_case						(						_snake_case				:			Tuple ,   _snake_case				:			str			):
      # Recursive traversal
      if root:
            inorder(root.left ,   _snake_case			)
            res.append(root.val			)
            inorder(root.right ,   _snake_case			)


def      _snake_case						(						_snake_case				:			Optional[Any]			):
      # Build BST
      if len(_snake_case			) == 0:
            return arr
      lowerCAmelCase					:	Optional[Any]       =   Node(arr[0]			)
      for i in range(1 ,   len(_snake_case			)			):
            root.insert(arr[i]			)
      # Traverse BST in order.
      lowerCAmelCase					:	Optional[int]       =   []
      inorder(_snake_case ,   _snake_case			)
      return res


if __name__ == "__main__":
 print(tree_sort([10, 1, 3, 2, 9, 14, 13]))


