


'''simple docstring'''



from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import torch

from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available






@dataclass
class 	UpperCamelCase__(       lowerCAmelCase	):
				__magic_name__    :				Union[List[np.ndarray], torch.FloatTensor]


try:
	if not (is_transformers_available() and is_torch_available()):
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
	from .pipeline_text_to_video_synth import TextToVideoSDPipeline
	from .pipeline_text_to_video_synth_imgaimg import VideoToVideoSDPipeline  # noqa: F401
	from .pipeline_text_to_video_zero import TextToVideoZeroPipeline









'''simple docstring'''



from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass






@dataclass
class 	UpperCamelCase__:
				__magic_name__    :				int
				__magic_name__    :				TreeNode | None  		=	None
				__magic_name__    :				TreeNode | None  		=	None







_lowercase      :      Tuple            =					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					)

												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(A					)
												    + abs(A					)
												)
												UpperCAmelCase					    =     node.data - coins_to_left - coins_to_right

												return CoinsDistribResult(A				,       A					)

						return get_distrib(A					)[0]


if __name__ == "__main__":
	import doctest

	doctest.testmod()





