


"""simple docstring"""





class 						snake_case_:






     def __init__(		self     :    str    , UpperCamelCase_     :    Union[str, Any] ):
           lowerCAmelCase    :		List[Any]				=      val
           lowerCAmelCase    :		Dict				=      None
           lowerCAmelCase    :		Optional[int]				=      None






     def    lowerCamelCase__   (		self     :    Union[str, Any]    , UpperCamelCase_     :    List[str] ):
           if self.val:
                 if val < self.val:
                       if self.left is None:
                             lowerCAmelCase    :		Any				=      Node(UpperCamelCase_ )
                       else:
                             self.left.insert(UpperCamelCase_ )
                 elif val > self.val:
                       if self.right is None:
                             lowerCAmelCase    :		List[str]				=      Node(UpperCamelCase_ )
                       else:
                             self.right.insert(UpperCamelCase_ )
           else:
                 lowerCAmelCase    :		Dict				=      val



def    _snake_case  (  _snake_case :	List[str]       ,      _snake_case :	str	):
      # Recursive traversal
      if root:
            inorder(root.left       ,      _snake_case	)
            res.append(root.val	)
            inorder(root.right       ,      _snake_case	)


def    _snake_case  (  _snake_case :	Tuple	):
      # Build BST
      if len(_snake_case	) == 0:
            return arr
      lowerCAmelCase    :		Any				=      Node(arr[0]	)
      for i in range(1       ,      len(_snake_case	)	):
            root.insert(arr[i]	)
      # Traverse BST in order.
      lowerCAmelCase    :		str				=      []
      inorder(_snake_case       ,      _snake_case	)
      return res


if __name__ == "__main__":
 print(tree_sort([10, 1, 3, 2, 9, 14, 13]))









'''simple docstring'''







from collections import OrderedDict
from typing import Mapping

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


lowerCAmelCase_					:    int      	=			logging.get_logger(__name__)

lowerCAmelCase_					:    Tuple      	=			{
    'google/bigbird-roberta-base': 'https://huggingface.co/google/bigbird-roberta-base/resolve/main/config.json',
    'google/bigbird-roberta-large': 'https://huggingface.co/google/bigbird-roberta-large/resolve/main/config.json',
    'google/bigbird-base-trivia-itc': 'https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/config.json',
    # See all BigBird models at https://huggingface.co/models?filter=big_bird
}
class 				__SCREAMING_SNAKE_CASE  (lowerCamelCase_      ):






				"""simple docstring"""







				__a            ='big_bird'




				def __init__(  self     :					Optional[int]					,				__a     :					Dict=5_03_58					,				__a     :					str=7_68					,				__a     :					List[Any]=12					,				__a     :					List[str]=12					,				__a     :					Union[str, Any]=30_72					,				__a     :					str="gelu_new"					,				__a     :					Dict=0.1					,				__a     :					Union[str, Any]=0.1					,				__a     :					Any=40_96					,				__a     :					int=2					,				__a     :					Tuple=0.02					,				__a     :					List[Any]=1e-1_2					,				__a     :					int=True					,				__a     :					List[str]=0					,				__a     :					Tuple=1					,				__a     :					Optional[Any]=2					,				__a     :					Tuple=66					,				__a     :					str="block_sparse"					,				__a     :					Tuple=True					,				__a     :					Optional[int]=False					,				__a     :					str=64					,				__a     :					Tuple=3					,				__a     :					Any=None					,				**__a     :					Dict					,				):
								super().__init__(
								    pad_token_id=__a					,				bos_token_id=__a					,				eos_token_id=__a					,				sep_token_id=__a					,				**__a					,				)

								_a								= vocab_size
								_a								= max_position_embeddings
								_a								= hidden_size
								_a								= num_hidden_layers
								_a								= num_attention_heads
								_a								= intermediate_size
								_a								= hidden_act
								_a								= hidden_dropout_prob
								_a								= attention_probs_dropout_prob
								_a								= initializer_range
								_a								= type_vocab_size
								_a								= layer_norm_eps
								_a								= use_cache

								_a								= rescale_embeddings
								_a								= attention_type
								_a								= use_bias
								_a								= block_size
								_a								= num_random_blocks
								_a								= classifier_dropout


class 				__SCREAMING_SNAKE_CASE  (lowerCamelCase_      ):






				"""simple docstring"""







				@property
				def   UpperCamelCase__   (  self     :					Optional[int]					):
								if self.task == "multiple-choice":
												_a								= {0: "batch", 1: "choice", 2: "sequence"}
								else:
												_a								= {0: "batch", 1: "sequence"}
								return OrderedDict(
								    [
								        ("input_ids", dynamic_axis),
								        ("attention_mask", dynamic_axis),
								    ]					)
