




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


UpperCAmelCase_									=	{
    'configuration_blip': [
        'BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BlipConfig',
        'BlipTextConfig',
        'BlipVisionConfig',
    ],
    'processing_blip': ['BlipProcessor'],
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase_									=	['BlipImageProcessor']


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase_									=	[
           'BLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
           'BlipModel',
           'BlipPreTrainedModel',
           'BlipForConditionalGeneration',
           'BlipForQuestionAnswering',
           'BlipVisionModel',
           'BlipTextModel',
           'BlipForImageTextRetrieval',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase_									=	[
           'TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
           'TFBlipModel',
           'TFBlipPreTrainedModel',
           'TFBlipForConditionalGeneration',
           'TFBlipForQuestionAnswering',
           'TFBlipVisionModel',
           'TFBlipTextModel',
           'TFBlipForImageTextRetrieval',
       ]

if TYPE_CHECKING:
       from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
       from .processing_blip import BlipProcessor

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .image_processing_blip import BlipImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_blip import (
                  BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  BlipForConditionalGeneration,
                  BlipForImageTextRetrieval,
                  BlipForQuestionAnswering,
                  BlipModel,
                  BlipPreTrainedModel,
                  BlipTextModel,
                  BlipVisionModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_blip import (
                  TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFBlipForConditionalGeneration,
                  TFBlipForImageTextRetrieval,
                  TFBlipForQuestionAnswering,
                  TFBlipModel,
                  TFBlipPreTrainedModel,
                  TFBlipTextModel,
                  TFBlipVisionModel,
              )

else:
       import sys

       UpperCAmelCase_									=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)







from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass





@dataclass
class     lowerCamelCase__:
      UpperCAmelCase__      :	int
      UpperCAmelCase__      :	TreeNode | None    		=   None
      UpperCAmelCase__      :	TreeNode | None    		=   None



UpperCAmelCase_									=	namedtuple('CoinsDistribResult', 'moves excess')




def 					lowerCamelCase__       (						A__       :					TreeNode | None	):





       '''simple docstring'''



       if root is None:
              return 0

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

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

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

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

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

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

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

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

              __lowerCamelCase   =						1 - left_distrib_excess
              __lowerCamelCase   =						1 - right_distrib_excess

              __lowerCamelCase   =						(
                  left_distrib_moves
                  + right_distrib_moves
                  + abs(A__	)
                  + abs(A__	)
              )
              __lowerCamelCase   =						node.data - coins_to_left - coins_to_right

              return CoinsDistribResult(A__  ,			A__	)

       return get_distrib(A__	)[0]


if __name__ == "__main__":
       import doctest

       doctest.testmod()

