
'''simple docstring'''






from typing import TYPE_CHECKING

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


__lowercase	=    {
    '''configuration_oneformer''': ['''ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''OneFormerConfig'''],
    '''processing_oneformer''': ['''OneFormerProcessor'''],
}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowercase	=    ['''OneFormerImageProcessor''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowercase	=    [
							    '''ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''OneFormerForUniversalSegmentation''',
							    '''OneFormerModel''',
							    '''OneFormerPreTrainedModel''',
							]

if TYPE_CHECKING:
							from .configuration_oneformer import ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, OneFormerConfig
							from .processing_oneformer import OneFormerProcessor

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .image_processing_oneformer import OneFormerImageProcessor
							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_oneformer import (
														    ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
														    OneFormerForUniversalSegmentation,
														    OneFormerModel,
														    OneFormerPreTrainedModel,
														)


else:
							import sys

							__lowercase	=    _LazyModule(__name__, globals()['''__file__'''], _import_structure)














from __future__ import annotations







def   snake_case		(				UpperCAmelCase						:							int,    UpperCAmelCase						:							list[int],    UpperCAmelCase						:							list[int],    UpperCAmelCase						:							int ):

				# Base Case
				if counter == 0 or capacity == 0:
								return 0

				# If weight of the nth item is more than Knapsack of capacity,
				#   then this item cannot be included in the optimal solution,
				# else return the maximum of two cases:
				#   (1) nth item included
				#   (2) not included
				if weights[counter - 1] > capacity:
								return knapsack(UpperCAmelCase,    UpperCAmelCase,    UpperCAmelCase,    counter - 1 )
				else:
								A									=   capacity - weights[counter - 1]
								A									=   values[counter - 1] + knapsack(
								    UpperCAmelCase,    UpperCAmelCase,    UpperCAmelCase,    counter - 1 )
								A									=   knapsack(UpperCAmelCase,    UpperCAmelCase,    UpperCAmelCase,    counter - 1 )
								return max(UpperCAmelCase,    UpperCAmelCase )


if __name__ == "__main__":
					import doctest

					doctest.testmod()





