




"""simple docstring"""






import warnings
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 lowerCAmelCase__	(     lowercase__						):






			'''simple docstring'''



			lowerCamelCase__      =			["""image_processor""", """tokenizer"""]
			lowerCamelCase__      =			"""ViltImageProcessor"""
			lowerCamelCase__      =			("""BertTokenizer""", """BertTokenizerFast""")
			def __init__(  self  ,      lowercase=None  ,      lowercase=None  ,      **lowercase  ):
							_lowerCamelCase     :			str    =    None
							if "feature_extractor" in kwargs:
											warnings.warn(
											    'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
											    ' instead.'  ,      __lowerCamelCase  ,      )
											_lowerCamelCase     :			Union[str, Any]    =    kwargs.pop('feature_extractor'  )

							_lowerCamelCase     :			Optional[Any]    =    image_processor if image_processor is not None else feature_extractor
							if image_processor is None:
											raise ValueError('You need to specify an `image_processor`.'  )
							if tokenizer is None:
											raise ValueError('You need to specify a `tokenizer`.'  )

							super().__init__(__lowerCamelCase  ,      __lowerCamelCase  )
							_lowerCamelCase     :			Any    =    self.image_processor
			def __call__(  self  ,      lowercase  ,      lowercase = None  ,      lowercase = True  ,      lowercase = False  ,      lowercase = None  ,      lowercase = None  ,      lowercase = 0  ,      lowercase = None  ,      lowercase = None  ,      lowercase = None  ,      lowercase = False  ,      lowercase = False  ,      lowercase = False  ,      lowercase = False  ,      lowercase = True  ,      lowercase = None  ,      **lowercase  ,      ):
							_lowerCamelCase     :			Optional[Any]    =    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
							_lowerCamelCase     :			str    =    self.image_processor(__lowerCamelCase  ,      return_tensors=__lowerCamelCase  )
							encoding.update(__lowerCamelCase  )

							return encoding
			def 					A_    (  self  ,      *lowercase  ,      **lowercase  ):
							return self.tokenizer.batch_decode(*__lowerCamelCase  ,      **__lowerCamelCase  )
			def 					A_    (  self  ,      *lowercase  ,      **lowercase  ):
							return self.tokenizer.decode(*__lowerCamelCase  ,      **__lowerCamelCase  )
			@property
			def 					A_    (  self  ):
							_lowerCamelCase     :			Optional[Any]    =    self.tokenizer.model_input_names
							_lowerCamelCase     :			str    =    self.image_processor.model_input_names
							return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names  )  )
			@property
			def 					A_    (  self  ):
							warnings.warn(
							    '`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'  ,      __lowerCamelCase  ,      )
							return self.image_processor_class






			@property
			def 					A_    (  self  ):
							warnings.warn(
							    '`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'  ,      __lowerCamelCase  ,      )
							return self.image_processor



from collections import defaultdict

def       lowercase_		(		_A			:    int						):

      """simple docstring"""




      lowerCamelCase__		:				Union[str, Any]    =  1
      lowerCamelCase__		:				Dict    =  True
      for v in tree[start]:
            if v not in visited:
                  ret += dfs(_A						)
      if ret % 2 == 0:
            cuts.append(_A						)
      return ret

def       lowercase_		(		):

      """simple docstring"""




      dfs(1						)


if __name__ == "__main__":
    A,  A      :    Tuple		=					10, 9
    A      :    int		=					defaultdict(list)
    A      :    dict[int, bool]		=					{}
    A      :    list[int]		=					[]
    A      :    List[str]		=					0
    A      :    Tuple		=					[(2, 1), (3, 1), (4, 3), (5, 2), (6, 1), (7, 2), (8, 6), (9, 8), (10, 8)]
    for u, v in edges:
        tree[u].append(v)
        tree[v].append(u)
    even_tree()
    print(len(cuts) - 1)


