



"""simple docstring"""





from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass
@dataclass
class 				lowercase__       :







       '''simple docstring'''


       UpperCamelCase						=					42
       UpperCamelCase						=					None
       UpperCamelCase						=					None



lowerCamelCase       	=						namedtuple("""CoinsDistribResult""", """moves excess""")
def        a__     (				lowerCAmelCase__				):

      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				)

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

            UpperCAmelCase_      			=							1 - left_distrib_excess
            UpperCAmelCase_      			=							1 - right_distrib_excess

            UpperCAmelCase_      			=							(
                left_distrib_moves
                + right_distrib_moves
                + abs(lowerCAmelCase__				)
                + abs(lowerCAmelCase__				)
            )
            UpperCAmelCase_      			=							node.data - coins_to_left - coins_to_right

            return CoinsDistribResult(lowerCAmelCase__     ,      lowerCAmelCase__				)

      return get_distrib(lowerCAmelCase__				)[0]


if __name__ == "__main__":
  import doctest

  doctest.testmod()









"""simple docstring"""





# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase       	=						{
    """configuration_mgp_str""": ["""MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MgpstrConfig"""],
    """processing_mgp_str""": ["""MgpstrProcessor"""],
    """tokenization_mgp_str""": ["""MgpstrTokenizer"""],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase       	=						[
      """MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """MgpstrModel""",
      """MgpstrPreTrainedModel""",
      """MgpstrForSceneTextRecognition""",
  ]

if TYPE_CHECKING:
  from .configuration_mgp_str import MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP, MgpstrConfig
  from .processing_mgp_str import MgpstrProcessor
  from .tokenization_mgp_str import MgpstrTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_mgp_str import (
        MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST,
        MgpstrForSceneTextRecognition,
        MgpstrModel,
        MgpstrPreTrainedModel,
    )
else:
  import sys

  lowerCamelCase       	=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




