



from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass






@dataclass
class SCREAMING_SNAKE_CASE__     :




    '''simple docstring'''






    __lowerCamelCase			: int
    __lowerCamelCase			: TreeNode | None					=      None
    __lowerCamelCase			: TreeNode | None					=      None


SCREAMING_SNAKE_CASE_:Optional[int]             =						namedtuple("""CoinsDistribResult""", """moves excess""")




def 	__UpperCamelCase	(  _lowerCAmelCase		)       ->  int:



    """simple docstring"""






    if root is None:
        return 0

    # Validation
    def count_nodes(_lowerCAmelCase		) -> int:
        if node is None:
            return 0

        return count_nodes(node.left		) + count_nodes(node.right		) + 1

    def count_coins(_lowerCAmelCase		) -> int:
        if node is None:
            return 0

        return count_coins(node.left		) + count_coins(node.right		) + node.data

    if count_nodes(_lowerCAmelCase		) != count_coins(_lowerCAmelCase		):
        raise ValueError("""The nodes number should be same as the number of coins"""		)

    # Main calculation
    def get_distrib(_lowerCAmelCase		) -> CoinsDistribResult:

        if node is None:
            return CoinsDistribResult(0      ,     1		)

        A     ,							A :       Any          =   get_distrib(node.left		)
        A     ,							A :       int          =   get_distrib(node.right		)

        A :       Optional[Any]          =   1 - left_distrib_excess
        A :       Optional[Any]          =   1 - right_distrib_excess

        A :       Optional[Any]          =   (
            left_distrib_moves
            + right_distrib_moves
            + abs(_lowerCAmelCase		)
            + abs(_lowerCAmelCase		)
        )
        A :       Dict          =   node.data - coins_to_left - coins_to_right

        return CoinsDistribResult(_lowerCAmelCase      ,     _lowerCAmelCase		)

    return get_distrib(_lowerCAmelCase		)[0]


if __name__ == "__main__":
     import doctest

     doctest.testmod()







from collections import OrderedDict
from typing import Mapping

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


SCREAMING_SNAKE_CASE_:Any             =						logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_:Dict             =						{
    """facebook/xmod-base""": """https://huggingface.co/facebook/xmod-base/resolve/main/config.json""",
    """facebook/xmod-large-prenorm""": """https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json""",
    """facebook/xmod-base-13-125k""": """https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json""",
    """facebook/xmod-base-30-125k""": """https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json""",
    """facebook/xmod-base-30-195k""": """https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json""",
    """facebook/xmod-base-60-125k""": """https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json""",
    """facebook/xmod-base-60-265k""": """https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json""",
    """facebook/xmod-base-75-125k""": """https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json""",
    """facebook/xmod-base-75-269k""": """https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json""",
}






class SCREAMING_SNAKE_CASE__     (		SCREAMING_SNAKE_CASE__    ):




    '''simple docstring'''






    __lowerCamelCase			: Dict					=      "xmod"






    def __init__(       self,		lowerCamelCase__=3_0522,		lowerCamelCase__=768,		lowerCamelCase__=12,		lowerCamelCase__=12,		lowerCamelCase__=3072,		lowerCamelCase__="gelu",		lowerCamelCase__=0.1,		lowerCamelCase__=0.1,		lowerCamelCase__=512,		lowerCamelCase__=2,		lowerCamelCase__=0.02,		lowerCamelCase__=1e-12,		lowerCamelCase__=1,		lowerCamelCase__=0,		lowerCamelCase__=2,		lowerCamelCase__="absolute",		lowerCamelCase__=True,		lowerCamelCase__=None,		lowerCamelCase__=False,		lowerCamelCase__=2,		lowerCamelCase__=False,		lowerCamelCase__=True,		lowerCamelCase__=True,		lowerCamelCase__=("en_XX",),		lowerCamelCase__=None,		**lowerCamelCase__,		):
        super().__init__(pad_token_id=lowerCamelCase__,		bos_token_id=lowerCamelCase__,		eos_token_id=lowerCamelCase__,		**lowerCamelCase__		)

        A :       int          =   vocab_size
        A :       int          =   hidden_size
        A :       str          =   num_hidden_layers
        A :       List[str]          =   num_attention_heads
        A :       List[str]          =   hidden_act
        A :       Dict          =   intermediate_size
        A :       Optional[int]          =   hidden_dropout_prob
        A :       Union[str, Any]          =   attention_probs_dropout_prob
        A :       int          =   max_position_embeddings
        A :       Tuple          =   type_vocab_size
        A :       List[Any]          =   initializer_range
        A :       str          =   layer_norm_eps
        A :       Union[str, Any]          =   position_embedding_type
        A :       Any          =   use_cache
        A :       int          =   classifier_dropout
        A :       int          =   pre_norm
        A :       List[str]          =   adapter_reduction_factor
        A :       Any          =   adapter_layer_norm
        A :       Any          =   adapter_reuse_layer_norm
        A :       str          =   ln_before_adapter
        A :       Dict          =   list(lowerCamelCase__		)
        A :       Union[str, Any]          =   default_language






class SCREAMING_SNAKE_CASE__     (		SCREAMING_SNAKE_CASE__    ):




    '''simple docstring'''






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


