

"""simple docstring"""



from ...configuration_utils import PretrainedConfig


SCREAMING_SNAKE_CASE_					:	Optional[Any]							  =						{
    'google/tapas-base-finetuned-sqa': (
        'https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'
    ),
    'google/tapas-base-finetuned-wtq': (
        'https://huggingface.co/google/tapas-base-finetuned-wtq/resolve/main/config.json'
    ),
    'google/tapas-base-finetuned-wikisql-supervised': (
        'https://huggingface.co/google/tapas-base-finetuned-wikisql-supervised/resolve/main/config.json'
    ),
    'google/tapas-base-finetuned-tabfact': (
        'https://huggingface.co/google/tapas-base-finetuned-tabfact/resolve/main/config.json'
    ),
}



class 					a						(       __lowerCamelCase				):



				"""simple docstring"""



				UpperCAmelCase						 =					"tapas"

				def __init__(     self: int    ,						UpperCamelCase: List[Any]=3_05_22    ,						UpperCamelCase: Dict=7_68    ,						UpperCamelCase: Optional[Any]=12    ,						UpperCamelCase: Optional[int]=12    ,						UpperCamelCase: str=30_72    ,						UpperCamelCase: int="gelu"    ,						UpperCamelCase: Optional[Any]=0.1    ,						UpperCamelCase: Dict=0.1    ,						UpperCamelCase: List[Any]=10_24    ,						UpperCamelCase: List[Any]=[3, 2_56, 2_56, 2, 2_56, 2_56, 10]    ,						UpperCamelCase: Any=0.02    ,						UpperCamelCase: Optional[Any]=1e-1_2    ,						UpperCamelCase: List[str]=0    ,						UpperCamelCase: str=10.0    ,						UpperCamelCase: Tuple=0    ,						UpperCamelCase: Any=1.0    ,						UpperCamelCase: Dict=None    ,						UpperCamelCase: List[Any]=1.0    ,						UpperCamelCase: Dict=False    ,						UpperCamelCase: List[Any]=None    ,						UpperCamelCase: Optional[Any]=1.0    ,						UpperCamelCase: Dict=1.0    ,						UpperCamelCase: Optional[Any]=False    ,						UpperCamelCase: Union[str, Any]=False    ,						UpperCamelCase: Optional[int]="ratio"    ,						UpperCamelCase: Any=None    ,						UpperCamelCase: Optional[int]=None    ,						UpperCamelCase: List[Any]=64    ,						UpperCamelCase: str=32    ,						UpperCamelCase: Dict=False    ,						UpperCamelCase: Optional[int]=True    ,						UpperCamelCase: Union[str, Any]=False    ,						UpperCamelCase: Optional[Any]=False    ,						UpperCamelCase: Any=True    ,						UpperCamelCase: List[str]=False    ,						UpperCamelCase: Any=None    ,						UpperCamelCase: List[Any]=None    ,						**UpperCamelCase: Optional[int]    ,						):






									"""simple docstring"""


									super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_    ,						**SCREAMING_SNAKE_CASE_       )

									# BERT hyperparameters (with updated max_position_embeddings and type_vocab_sizes)
									A__										=  vocab_size
									A__										=  hidden_size
									A__										=  num_hidden_layers
									A__										=  num_attention_heads
									A__										=  hidden_act
									A__										=  intermediate_size
									A__										=  hidden_dropout_prob
									A__										=  attention_probs_dropout_prob
									A__										=  max_position_embeddings
									A__										=  type_vocab_sizes
									A__										=  initializer_range
									A__										=  layer_norm_eps

									# Fine-tuning task hyperparameters
									A__										=  positive_label_weight
									A__										=  num_aggregation_labels
									A__										=  aggregation_loss_weight
									A__										=  use_answer_as_supervision
									A__										=  answer_loss_importance
									A__										=  use_normalized_answer_loss
									A__										=  huber_loss_delta
									A__										=  temperature
									A__										=  aggregation_temperature
									A__										=  use_gumbel_for_cells
									A__										=  use_gumbel_for_aggregation
									A__										=  average_approximation_function
									A__										=  cell_selection_preference
									A__										=  answer_loss_cutoff
									A__										=  max_num_rows
									A__										=  max_num_columns
									A__										=  average_logits_per_cell
									A__										=  select_one_column
									A__										=  allow_empty_column_selection
									A__										=  init_cell_selection_weights_to_zero
									A__										=  reset_position_index_per_cell
									A__										=  disable_per_token_loss

									# Aggregation hyperparameters
									A__										=  aggregation_labels
									A__										=  no_aggregation_label_index

									if isinstance(self.aggregation_labels    ,						SCREAMING_SNAKE_CASE_       ):
														A__										=  {int(SCREAMING_SNAKE_CASE_       ): v for k, v in aggregation_labels.items()}









"""simple docstring"""



from collections import defaultdict





def  _snake_case     (    UpperCAmelCase_  :					int			):
     A__										=  1
     A__										=  True
     for v in tree[start]:
          if v not in visited:
               ret += dfs(UpperCAmelCase_			)
     if ret % 2 == 0:
          cuts.append(UpperCAmelCase_			)
     return ret





def  _snake_case     (    ):
     dfs(1			)


if __name__ == "__main__":
 SCREAMING_SNAKE_CASE_  ,SCREAMING_SNAKE_CASE_					:	Any							  =						1_0, 9
 SCREAMING_SNAKE_CASE_					:	Any							  =						defaultdict(list)
 SCREAMING_SNAKE_CASE_					:	dict[int, bool]							  =						{}
 SCREAMING_SNAKE_CASE_					:	list[int]							  =						[]
 SCREAMING_SNAKE_CASE_					:	Optional[int]							  =						0
 SCREAMING_SNAKE_CASE_					:	Any							  =						[(2, 1), (3, 1), (4, 3), (5, 2), (6, 1), (7, 2), (8, 6), (9, 8), (1_0, 8)]
 for u, v in edges:
  tree[u].append(v)
  tree[v].append(u)
 even_tree()
 print(len(cuts) - 1)






