



from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass






@dataclass
class 		lowercase						:






	"""simple docstring"""


	a__				: int
	a__				: TreeNode | None		       =							None
	a__				: TreeNode | None		       =							None

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



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






						'''simple docstring'''



						if root is None:
												return 0

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

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

						def count_coins(lowerCAmelCase_       : TreeNode | None    ) -> 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_       : TreeNode | None    ) -> 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()





from typing import TYPE_CHECKING

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


__A       =						{
    '''configuration_clip''': [
        '''CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''CLIPConfig''',
        '''CLIPOnnxConfig''',
        '''CLIPTextConfig''',
        '''CLIPVisionConfig''',
    ],
    '''processing_clip''': ['''CLIPProcessor'''],
    '''tokenization_clip''': ['''CLIPTokenizer'''],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__A       =						['''CLIPTokenizerFast''']

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__A       =						['''CLIPFeatureExtractor''']
	__A       =						['''CLIPImageProcessor''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__A       =						[
	    '''CLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''CLIPModel''',
	    '''CLIPPreTrainedModel''',
	    '''CLIPTextModel''',
	    '''CLIPTextModelWithProjection''',
	    '''CLIPVisionModel''',
	    '''CLIPVisionModelWithProjection''',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__A       =						[
	    '''TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TFCLIPModel''',
	    '''TFCLIPPreTrainedModel''',
	    '''TFCLIPTextModel''',
	    '''TFCLIPVisionModel''',
	]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__A       =						[
	    '''FlaxCLIPModel''',
	    '''FlaxCLIPPreTrainedModel''',
	    '''FlaxCLIPTextModel''',
	    '''FlaxCLIPTextPreTrainedModel''',
	    '''FlaxCLIPVisionModel''',
	    '''FlaxCLIPVisionPreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_clip import (
	    CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    CLIPConfig,
	    CLIPOnnxConfig,
	    CLIPTextConfig,
	    CLIPVisionConfig,
	)
	from .processing_clip import CLIPProcessor
	from .tokenization_clip import CLIPTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_clip_fast import CLIPTokenizerFast

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_clip import CLIPFeatureExtractor
		from .image_processing_clip import CLIPImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_clip import (
		    CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
		    CLIPModel,
		    CLIPPreTrainedModel,
		    CLIPTextModel,
		    CLIPTextModelWithProjection,
		    CLIPVisionModel,
		    CLIPVisionModelWithProjection,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_clip import (
		    TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFCLIPModel,
		    TFCLIPPreTrainedModel,
		    TFCLIPTextModel,
		    TFCLIPVisionModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_clip import (
		    FlaxCLIPModel,
		    FlaxCLIPPreTrainedModel,
		    FlaxCLIPTextModel,
		    FlaxCLIPTextPreTrainedModel,
		    FlaxCLIPVisionModel,
		    FlaxCLIPVisionPreTrainedModel,
		)


else:
	import sys

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




