




def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	List[str]:



       """simple docstring"""

       A__							=   len(lowercase_						)
       A__							=   sum(lowercase_						)

       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








from typing import TYPE_CHECKING

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


_lowerCamelCase     :		Union[str, Any]								=       {
    """configuration_swiftformer""": [
        """SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SwiftFormerConfig""",
        """SwiftFormerOnnxConfig""",
    ]
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase     :		Union[str, Any]								=       [
      """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

  _lowerCamelCase     :		str								=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


