
'''simple docstring'''







import random







def        SCREAMING_SNAKE_CASE__			(     __A    ,       __A			) ->			tuple:
	_snake_case		,				_snake_case		,				_snake_case     		=	[], [], []
	for element in data:
		if element < pivot:
			less.append(__A			)
		elif element > pivot:
			greater.append(__A			)
		else:
			equal.append(__A			)
	return less, equal, greater







def        SCREAMING_SNAKE_CASE__			(     __A    ,       __A			) ->			Tuple:
	# index = len(items) // 2 when trying to find the median
	#   (value of index when items is sorted)

	# invalid input
	if index >= len(__A			) or index < 0:
		return None

	_snake_case     		=	items[random.randint(0    ,       len(__A			) - 1			)]
	_snake_case     		=	0
	_snake_case		,				_snake_case		,				_snake_case     		=	_partition(__A    ,       __A			)
	_snake_case     		=	len(__A			)
	_snake_case     		=	len(__A			)

	# index is the pivot
	if m <= index < m + count:
		return pivot
	# must be in smaller
	elif m > index:
		return quick_select(__A    ,       __A			)
	# must be in larger
	else:
		return quick_select(__A    ,       index - (m + count)			)



'''simple docstring'''







from typing import TYPE_CHECKING

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


lowercase					:							int   =      {
    "configuration_mask2former": [
        "MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "Mask2FormerConfig",
    ],
}

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

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase					:							Optional[Any]   =      [
					    "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

					lowercase					:							int   =      _LazyModule(__name__, globals()["__file__"], _import_structure)

