
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping

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


_a   :      str       =				logging.get_logger(__name__)

_a   :      Dict       =				{
    """google/rembert""": """https://huggingface.co/google/rembert/resolve/main/config.json""",
    # See all RemBERT models at https://huggingface.co/models?filter=rembert
}






class   _UpperCAmelCase					(       _snake_case):
    __lowercase				:			int	=       """rembert"""
    def __init__(     self    ,     snake_case_=25_03_00    ,     snake_case_=11_52    ,     snake_case_=32    ,     snake_case_=18    ,     snake_case_=2_56    ,     snake_case_=16_64    ,     snake_case_=46_08    ,     snake_case_="gelu"    ,     snake_case_=0.0    ,     snake_case_=0.0    ,     snake_case_=0.1    ,     snake_case_=5_12    ,     snake_case_=2    ,     snake_case_=0.02    ,     snake_case_=1E-12    ,     snake_case_=True    ,     snake_case_=0    ,     snake_case_=3_12    ,     snake_case_=3_13    ,     **snake_case_    ,     ):
      super().__init__(pad_token_id=snake_case_    ,     bos_token_id=snake_case_    ,     eos_token_id=snake_case_    ,     **snake_case_  )

      _snake_case  :    Tuple            = vocab_size
      _snake_case  :    Optional[int]            = input_embedding_size
      _snake_case  :    Optional[Any]            = output_embedding_size
      _snake_case  :    Dict            = max_position_embeddings
      _snake_case  :    str            = hidden_size
      _snake_case  :    Any            = num_hidden_layers
      _snake_case  :    int            = num_attention_heads
      _snake_case  :    str            = intermediate_size
      _snake_case  :    Dict            = hidden_act
      _snake_case  :    Dict            = hidden_dropout_prob
      _snake_case  :    Tuple            = attention_probs_dropout_prob
      _snake_case  :    Optional[int]            = classifier_dropout_prob
      _snake_case  :    Optional[int]            = initializer_range
      _snake_case  :    int            = type_vocab_size
      _snake_case  :    Optional[int]            = layer_norm_eps
      _snake_case  :    List[Any]            = use_cache
      _snake_case  :    Optional[Any]            = False






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


    @property
    def        lowerCamelCase__						(     self  ):
      return 1E-4






from __future__ import annotations

class        _A			:



       def __init__(						self				:	str	,						__SCREAMING_SNAKE_CASE				:	int = 0):


           '''simple docstring'''

           __a					=							value
           __a					=							None
           __a					=							None





def 	__snake_case      (     _UpperCAmelCase  ,					_UpperCAmelCase							):
    if treea is None:
        return treea
    if treea is None:
        return treea

    __a					=							treea.value + treea.value
    __a					=							merge_two_binary_trees(treea.left  ,					treea.left							)
    __a					=							merge_two_binary_trees(treea.right  ,					treea.right							)
    return treea





def 	__snake_case      (     _UpperCAmelCase							):
    if root:
        print(root.value							)
        print_preorder(root.left							)
        print_preorder(root.right							)


if __name__ == "__main__":
 __snake_case		:List[Any] 						=	Node(1)
 __snake_case		:Optional[Any] 						=	Node(2)
 __snake_case		:Dict 						=	Node(3)
 __snake_case		:int 						=	Node(4)

 __snake_case		:List[str] 						=	Node(2)
 __snake_case		:List[str] 						=	Node(4)
 __snake_case		:Tuple 						=	Node(6)
 __snake_case		:str 						=	Node(9)
 __snake_case		:List[str] 						=	Node(5)

 print('''Tree1 is: ''')
 print_preorder(treea)
 print('''Tree2 is: ''')
 print_preorder(treea)
 __snake_case		:Union[str, Any] 						=	merge_two_binary_trees(treea, treea)
 print('''Merged Tree is: ''')
 print_preorder(merged_tree)





