




'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase_						:      Union[str, Any]       =						{'''configuration_plbart''': ['''PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PLBartConfig''']}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCamelCase_						:      Optional[int]       =						['''PLBartTokenizer''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCamelCase_						:      int       =						[
       '''PLBART_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''PLBartForCausalLM''',
       '''PLBartForConditionalGeneration''',
       '''PLBartForSequenceClassification''',
       '''PLBartModel''',
       '''PLBartPreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_plbart import PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP, PLBartConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_plbart import PLBartTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_plbart import (
          PLBART_PRETRAINED_MODEL_ARCHIVE_LIST,
          PLBartForCausalLM,
          PLBartForConditionalGeneration,
          PLBartForSequenceClassification,
          PLBartModel,
          PLBartPreTrainedModel,
      )


else:
   import sys

   UpperCamelCase_						:      str       =						_LazyModule(__name__, globals()['''__file__'''], _import_structure)








'''simple docstring'''





from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass

@dataclass
class        _a    :
     SCREAMING_SNAKE_CASE_							:   int
     SCREAMING_SNAKE_CASE_							:   TreeNode | None       =						None
     SCREAMING_SNAKE_CASE_							:   TreeNode | None       =						None







UpperCamelCase_						:      Any       =						namedtuple('''CoinsDistribResult''', '''moves excess''')





def      __a     (       _UpperCamelCase:   TreeNode | None   )						->			int:

     """simple docstring"""




     if root is None:
          return 0

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

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

     def count_coins(_UpperCamelCase:   TreeNode | None   ) -> int:
          if node is None:
               return 0

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

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

     # Main calculation
     def get_distrib(_UpperCamelCase:   TreeNode | None   ) -> CoinsDistribResult:

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

          _snake_case							, _snake_case							=				get_distrib(node.left   )
          _snake_case							, _snake_case							=				get_distrib(node.right   )

          _snake_case							=				1 - left_distrib_excess
          _snake_case							=				1 - right_distrib_excess

          _snake_case							=				(
              left_distrib_moves
              + right_distrib_moves
              + abs(_UpperCamelCase   )
              + abs(_UpperCamelCase   )
          )
          _snake_case							=				node.data - coins_to_left - coins_to_right

          return CoinsDistribResult(_UpperCamelCase ,						_UpperCamelCase   )

     return get_distrib(_UpperCamelCase   )[0]


if __name__ == "__main__":
   import doctest

   doctest.testmod()


