
import math


class 							lowercase   :



		def __init__(					self							, A_							, A_							, A_			)    ->   Tuple:
				"""simple docstring"""
				UpperCamelCase            =	x
				UpperCamelCase            =	y
				UpperCamelCase            =	z



		def __repr__(					self			)    ->   str:
				"""simple docstring"""
				return F'''Point({self.x}, {self.y}, {self.z})'''






def  A			(   lowercase       ,			lowercase					)  ->    float:
		'''simple docstring'''

		return math.sqrt(abs((b.x - a.x) ** 2 + (b.y - a.y) ** 2 + (b.z - a.z) ** 2					)					)


if __name__ == "__main__":
					import doctest

					doctest.testmod()


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_UpperCAmelCase   :					int    =			{"configuration_levit": ["LEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LevitConfig", "LevitOnnxConfig"]}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase   :					Optional[Any]    =			["LevitFeatureExtractor"]
					_UpperCAmelCase   :					Optional[int]    =			["LevitImageProcessor"]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase   :					Optional[int]    =			[
					    "LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "LevitForImageClassification",
					    "LevitForImageClassificationWithTeacher",
					    "LevitModel",
					    "LevitPreTrainedModel",
					]


if TYPE_CHECKING:
					from .configuration_levit import LEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, LevitConfig, LevitOnnxConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_levit import LevitFeatureExtractor
										from .image_processing_levit import LevitImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_levit import (
										    LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    LevitForImageClassification,
										    LevitForImageClassificationWithTeacher,
										    LevitModel,
										    LevitPreTrainedModel,
										)
else:
					import sys

					_UpperCAmelCase   :					Optional[Any]    =			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
