




from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType



class 		_lowercase		(       UpperCAmelCase__	):
   _UpperCAmelCase     	=			['''image_processor''', '''tokenizer''']
   _UpperCAmelCase     	=			'''BridgeTowerImageProcessor'''
   _UpperCAmelCase     	=			('''RobertaTokenizer''', '''RobertaTokenizerFast''')

   def __init__(      self			:       Dict							,   __lowerCAmelCase			:       Union[str, Any]							,   __lowerCAmelCase			:       Any							)       ->				Optional[Any]:


    """simple docstring"""






    super().__init__(__lowerCAmelCase							,   __lowerCAmelCase							)

   def __call__(      self			:       Any							,   __lowerCAmelCase			:       Tuple							,   __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			:       Optional[bool] = None							,   __lowerCAmelCase			:       bool = False							,   __lowerCAmelCase			:       bool = False							,   __lowerCAmelCase			:       bool = False							,   __lowerCAmelCase			:       bool = False							,   __lowerCAmelCase			:       bool = True							,   __lowerCAmelCase			:       Optional[Union[str, TensorType]] = None							,   **__lowerCAmelCase			:       Any							,   )       ->				BatchEncoding:


    """simple docstring"""






    a						=		self.tokenizer(
        text=__lowerCAmelCase							,   add_special_tokens=__lowerCAmelCase							,   padding=__lowerCAmelCase							,   truncation=__lowerCAmelCase							,   max_length=__lowerCAmelCase							,   stride=__lowerCAmelCase							,   pad_to_multiple_of=__lowerCAmelCase							,   return_token_type_ids=__lowerCAmelCase							,   return_attention_mask=__lowerCAmelCase							,   return_overflowing_tokens=__lowerCAmelCase							,   return_special_tokens_mask=__lowerCAmelCase							,   return_offsets_mapping=__lowerCAmelCase							,   return_length=__lowerCAmelCase							,   verbose=__lowerCAmelCase							,   return_tensors=__lowerCAmelCase							,   **__lowerCAmelCase							,   )
    # add pixel_values + pixel_mask
    a						=		self.image_processor(
        __lowerCAmelCase							,   return_tensors=__lowerCAmelCase							,   do_normalize=__lowerCAmelCase							,   do_center_crop=__lowerCAmelCase							,   **__lowerCAmelCase							)
    encoding.update(__lowerCAmelCase							)

    return encoding

   def 		A							(      self			:       Optional[int]							,   *__lowerCAmelCase			:       Optional[int]							,   **__lowerCAmelCase			:       Optional[int]							)       ->				Dict:


    """simple docstring"""






    return self.tokenizer.batch_decode(*__lowerCAmelCase							,   **__lowerCAmelCase							)

   def 		A							(      self			:       str							,   *__lowerCAmelCase			:       int							,   **__lowerCAmelCase			:       Optional[int]							)       ->				Tuple:


    """simple docstring"""






    return self.tokenizer.decode(*__lowerCAmelCase							,   **__lowerCAmelCase							)




   @property
   def 		A							(      self			:       int							)       ->				Dict:


    """simple docstring"""






    a						=		self.tokenizer.model_input_names
    a						=		self.image_processor.model_input_names
    return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names							)							)






from __future__ import annotations

from collections.abc import Iterable, Iterator
from dataclasses import dataclass

A_		:     List[str]        =     (3, 9, -11, 0, 7, 5, 1, -1)
A_		:     Optional[int]        =     (4, 6, 2, 0, 8, 10, 3, -2)



@dataclass
class 		_lowercase		:
   _UpperCAmelCase     	=			42
   _UpperCAmelCase     	=			42



class 		_lowercase		:

   def __init__(      self			:       List[Any]							,   __lowerCAmelCase			:       Iterable[int]							)       ->				None:


    """simple docstring"""






    a						=		None
    for i in sorted(__lowerCAmelCase							,   reverse=__lowerCAmelCase							):
     a						=		Node(__lowerCAmelCase							,   self.head							)

   def __iter__(      self			:       Union[str, Any]							)       ->				Iterator[int]:


    """simple docstring"""






    a						=		self.head
    while node:
     yield node.data
     a						=		node.next_node

   def __len__(      self			:       Tuple							)       ->				int:


    """simple docstring"""






    return sum(1 for _ in self							)




   def __str__(      self			:       Union[str, Any]							)       ->				str:


    """simple docstring"""






    return " -> ".join([str(__lowerCAmelCase							) for node in self]							)


def 	UpperCAmelCase__      (      UpperCAmelCase__ :SortedLinkedList ,					UpperCAmelCase__ :SortedLinkedList					):






 '''simple docstring'''

 return SortedLinkedList(list(UpperCAmelCase__					) + list(UpperCAmelCase__					)					)


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     A_		:     Optional[Any]        =     SortedLinkedList
     print(merge_lists(SSL(test_data_odd), SSL(test_data_even)))

