



from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__UpperCAmelCase			  =			logging.get_logger(__name__)

__UpperCAmelCase			  =			{
    '''hustvl/yolos-small''': '''https://huggingface.co/hustvl/yolos-small/resolve/main/config.json''',
    # See all YOLOS models at https://huggingface.co/models?filter=yolos
}



class 							lowerCAmelCase_						(    a__				):
       UpperCAmelCase__							:   Any  	=    "yolos"
       def __init__(     self,     SCREAMING_SNAKE_CASE_=768,     SCREAMING_SNAKE_CASE_=12,     SCREAMING_SNAKE_CASE_=12,     SCREAMING_SNAKE_CASE_=3072,     SCREAMING_SNAKE_CASE_="gelu",     SCREAMING_SNAKE_CASE_=0.0,     SCREAMING_SNAKE_CASE_=0.0,     SCREAMING_SNAKE_CASE_=0.02,     SCREAMING_SNAKE_CASE_=1e-12,     SCREAMING_SNAKE_CASE_=[512, 864],     SCREAMING_SNAKE_CASE_=16,     SCREAMING_SNAKE_CASE_=3,     SCREAMING_SNAKE_CASE_=True,     SCREAMING_SNAKE_CASE_=100,     SCREAMING_SNAKE_CASE_=True,     SCREAMING_SNAKE_CASE_=False,     SCREAMING_SNAKE_CASE_=1,     SCREAMING_SNAKE_CASE_=5,     SCREAMING_SNAKE_CASE_=2,     SCREAMING_SNAKE_CASE_=5,     SCREAMING_SNAKE_CASE_=2,     SCREAMING_SNAKE_CASE_=0.1,     **SCREAMING_SNAKE_CASE_,     )	->						Optional[int]:
          super().__init__(**SCREAMING_SNAKE_CASE_			)

          UpperCamelCase       :    str		      =      hidden_size
          UpperCamelCase       :    Union[str, Any]		      =      num_hidden_layers
          UpperCamelCase       :    Tuple		      =      num_attention_heads
          UpperCamelCase       :    Optional[Any]		      =      intermediate_size
          UpperCamelCase       :    Any		      =      hidden_act
          UpperCamelCase       :    List[Any]		      =      hidden_dropout_prob
          UpperCamelCase       :    Union[str, Any]		      =      attention_probs_dropout_prob
          UpperCamelCase       :    Optional[int]		      =      initializer_range
          UpperCamelCase       :    Tuple		      =      layer_norm_eps
          UpperCamelCase       :    Tuple		      =      image_size
          UpperCamelCase       :    int		      =      patch_size
          UpperCamelCase       :    List[str]		      =      num_channels
          UpperCamelCase       :    List[str]		      =      qkv_bias
          UpperCamelCase       :    Tuple		      =      num_detection_tokens
          UpperCamelCase       :    Tuple		      =      use_mid_position_embeddings
          UpperCamelCase       :    Tuple		      =      auxiliary_loss
          # Hungarian matcher
          UpperCamelCase       :    Any		      =      class_cost
          UpperCamelCase       :    Optional[int]		      =      bbox_cost
          UpperCamelCase       :    str		      =      giou_cost
          # Loss coefficients
          UpperCamelCase       :    List[str]		      =      bbox_loss_coefficient
          UpperCamelCase       :    Optional[int]		      =      giou_loss_coefficient
          UpperCamelCase       :    Optional[int]		      =      eos_coefficient






class 							lowerCAmelCase_						(    a__				):
       UpperCAmelCase__							:   List[Any]  	=    version.parse("1.11"				)
       @property
       def    snake_case_			(     self			)	->						Mapping[str, Mapping[int, str]]:
          return OrderedDict(
              [
                  ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
              ]			)
       @property
       def    snake_case_			(     self			)	->						float:
          return 1e-4






       @property
       def    snake_case_			(     self			)	->						int:
          return 12









from collections import defaultdict





def 				A__ (snake_case   :		int				)     ->						int:
					__UpperCamelCase					:	Optional[int]             =      1
					__UpperCamelCase					:	Tuple             =      True
					for v in tree[start]:
										if v not in visited:
															ret += dfs(snake_case				)
					if ret % 2 == 0:
										cuts.append(snake_case				)
					return ret





def 				A__ ()     ->						str:
					dfs(1				)


if __name__ == "__main__":
	a__     ,							a__		     =     10, 9
	a__		     =     defaultdict(list)
	a__		     =     {}
	a__		     =     []
	a__		     =     0
	a__		     =     [(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)






