



"""simple docstring"""





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__  (       __snake_case ):







       '''simple docstring'''


       UpperCamelCase		=	['''image_processor''', '''tokenizer''']
       UpperCamelCase		=	'''BridgeTowerImageProcessor'''
       UpperCamelCase		=	('''RobertaTokenizer''', '''RobertaTokenizerFast''')



       def __init__(				self     :    int						,							_UpperCAmelCase     :    Tuple						,							_UpperCAmelCase     :    List[Any]       )					->		Union[str, Any]:


             '''simple docstring'''




             super().__init__(__lowerCamelCase						,							__lowerCamelCase       )



       def __call__(				self     :    Any						,							_UpperCAmelCase     :    Optional[int]						,							_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     :    Optional[bool] = None						,							_UpperCAmelCase     :    bool = False						,							_UpperCAmelCase     :    bool = False						,							_UpperCAmelCase     :    bool = False						,							_UpperCAmelCase     :    bool = False						,							_UpperCAmelCase     :    bool = True						,							_UpperCAmelCase     :    Optional[Union[str, TensorType]] = None						,							**_UpperCAmelCase     :    Dict						,							)					->		BatchEncoding:


             '''simple docstring'''




             UpperCAmelCase_     					=				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
             UpperCAmelCase_     					=				self.image_processor(
                 __lowerCamelCase						,							return_tensors=__lowerCamelCase						,							do_normalize=__lowerCamelCase						,							do_center_crop=__lowerCamelCase						,							**__lowerCamelCase       )
             encoding.update(__lowerCamelCase       )

             return encoding



       def 	lowercase__							(				self     :    Optional[Any]						,							*_UpperCAmelCase     :    Optional[int]						,							**_UpperCAmelCase     :    List[str]       )					->		str:


             '''simple docstring'''




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



       def 	lowercase__							(				self     :    Dict						,							*_UpperCAmelCase     :    Any						,							**_UpperCAmelCase     :    List[Any]       )					->		Optional[int]:


             '''simple docstring'''




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







       @property
       def 	lowercase__							(				self     :    List[Any]       )					->		Optional[int]:


             '''simple docstring'''




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








class 	__lowercase					:





      def __init__(		self    :       Optional[int]							)     -> int:






         """simple docstring"""







         UpperCAmelCase      					=  {}





      def 							_lowercase					(		self    :       str							)     -> None:






         """simple docstring"""







         print(self.vertex							)
         for i in self.vertex:
            print(__lowerCamelCase       ,							""" -> """       ,							""" -> """.join([str(__lowerCamelCase							) for j in self.vertex[i]]							)							)





      def 							_lowercase					(		self    :       Optional[Any]       ,							__lowerCamelCase    :       int       ,							__lowerCamelCase    :       int							)     -> None:






         """simple docstring"""







         if from_vertex in self.vertex:
            self.vertex[from_vertex].append(__lowerCamelCase							)
         else:
            # else make a new vertex
            UpperCAmelCase      					=  [to_vertex]





      def 							_lowercase					(		self    :       str							)     -> None:






         """simple docstring"""







         UpperCAmelCase      					=  [False] * len(self.vertex							)

         # call the recursive helper function
         for i in range(len(self.vertex							)							):
            if not visited[i]:
               self.dfs_recursive(__lowerCamelCase       ,							__lowerCamelCase							)





      def 							_lowercase					(		self    :       Optional[int]       ,							__lowerCamelCase    :       int       ,							__lowerCamelCase    :       list							)     -> None:






         """simple docstring"""







         UpperCAmelCase      					=  True

         print(__lowerCamelCase       ,							end=""" """							)

         # Recur for all the vertices that are adjacent to this node
         for i in self.vertex:
            if not visited[i]:
               self.dfs_recursive(__lowerCamelCase       ,							__lowerCamelCase							)


if __name__ == "__main__":
 __a	 =      Graph()
 g.add_edge(0, 1)
 g.add_edge(0, 2)
 g.add_edge(1, 2)
 g.add_edge(2, 0)
 g.add_edge(2, 3)
 g.add_edge(3, 3)

 g.print_graph()
 print("""DFS:""")
 g.dfs()

 # OUTPUT:
 # 0  ->  1 -> 2
 # 1  ->  2
 # 2  ->  0 -> 3
 # 3  ->  3
 # DFS:
 #  0 1 2 3



