
"""simple docstring"""





def 						_lowerCAmelCase				(				UpperCamelCase_				):
		if not isinstance(UpperCamelCase_  ,				UpperCamelCase_				):
				raise ValueError("""Input series is not valid, valid series - [2, 4, 6]"""				)
		if len(UpperCamelCase_				) == 0:
				raise ValueError("""Input list must be a non empty list"""				)
		if len(UpperCamelCase_				) == 1:
				return True
		__SCREAMING_SNAKE_CASE            = series[1] - series[0]
		for index in range(len(UpperCamelCase_				) - 1				):
				if series[index + 1] - series[index] != common_diff:
						return False
		return True



def 						_lowerCAmelCase				(				UpperCamelCase_				):
		if not isinstance(UpperCamelCase_  ,				UpperCamelCase_				):
				raise ValueError("""Input series is not valid, valid series - [2, 4, 6]"""				)
		if len(UpperCamelCase_				) == 0:
				raise ValueError("""Input list must be a non empty list"""				)
		__SCREAMING_SNAKE_CASE            = 0
		for val in series:
				answer += val
		return answer / len(UpperCamelCase_				)


if __name__ == "__main__":
							import doctest

							doctest.testmod()









"""simple docstring"""
from typing import TYPE_CHECKING

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


__a      =				{
    "configuration_mask2former": [
        "MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "Mask2FormerConfig",
    ],
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      =				["Mask2FormerImageProcessor"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      =				[
						    "MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "Mask2FormerForUniversalSegmentation",
						    "Mask2FormerModel",
						    "Mask2FormerPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_maskaformer import MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskaFormerConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .image_processing_maskaformer import MaskaFormerImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_maskaformer import (
												    MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    MaskaFormerForUniversalSegmentation,
												    MaskaFormerModel,
												    MaskaFormerPreTrainedModel,
												)


else:
						import sys

						__a      =				_LazyModule(__name__, globals()["__file__"], _import_structure)
