






"""simple docstring"""







def        SCREAMING_SNAKE_CASE       (      lowerCamelCase_):
					a__          =  len(lowerCamelCase_)
					a__          =  sum(lowerCamelCase_)

					a__          =  [[False for x in range(s + 1)] for y in range(n + 1)]

					for i in range(1 ,     n + 1):
										a__          =  True

					for i in range(1 ,     s + 1):
										a__          =  False

					for i in range(1 ,     n + 1):
										for j in range(1 ,     s + 1):
															a__          =  dp[i][j - 1]

															if arr[i - 1] <= j:
																				a__          =  dp[i][j] or dp[i - 1][j - arr[i - 1]]

					for j in range(int(s / 2) ,     -1 ,     -1):
										if dp[n][j] is True:
															a__          =  s - 2 * j
															break

					return diff










"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


__a       :	str             = {
    'configuration_swiftformer': [
        'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SwiftFormerConfig',
        'SwiftFormerOnnxConfig',
    ]
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__a       :	int             = [
	    'SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'SwiftFormerForImageClassification',
	    'SwiftFormerModel',
	    'SwiftFormerPreTrainedModel',
	]

if TYPE_CHECKING:
	from .configuration_swiftformer import (
	    SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    SwiftFormerConfig,
	    SwiftFormerOnnxConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_swiftformer import (
		    SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    SwiftFormerForImageClassification,
		    SwiftFormerModel,
		    SwiftFormerPreTrainedModel,
		)

else:
	import sys

	__a       :	Dict             = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


