





def       lowerCAmelCase__(	lowercase       :    float				) ->    float:
  return -num if num < 0 else num







def       lowerCAmelCase__(	lowercase       :    list[int]				) ->    int:
  if len(lowercase				) == 0:
    raise ValueError("abs_min() arg is an empty sequence"				)
  __snake_case   :				List[Any]        =       x[0]
  for i in x:
    if abs_val(lowercase				) < abs_val(lowercase				):
      __snake_case   :				Any        =       i
  return j







def       lowerCAmelCase__(	lowercase       :    list[int]				) ->    int:
  if len(lowercase				) == 0:
    raise ValueError("abs_max() arg is an empty sequence"				)
  __snake_case   :				Any        =       x[0]
  for i in x:
    if abs(lowercase				) > abs(lowercase				):
      __snake_case   :				Any        =       i
  return j







def       lowerCAmelCase__(	lowercase       :    list[int]				) ->    int:
  if len(lowercase				) == 0:
    raise ValueError("abs_max_sort() arg is an empty sequence"				)
  return sorted(lowercase   ,     key=lowercase				)[-1]







def       lowerCAmelCase__(	) ->    List[Any]:
  assert abs_val(0				) == 0
  assert abs_val(34				) == 34
  assert abs_val(-1000_0000_0000				) == 1000_0000_0000

  __snake_case   :				int        =       [-3, -1, 2, -11]
  assert abs_max(lowercase				) == -11
  assert abs_max_sort(lowercase				) == -11
  assert abs_min(lowercase				) == -1


if __name__ == "__main__":
     import doctest

     doctest.testmod()

     test_abs_val()
     print(abs_val(-34))  # --> 34








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCamelCase       = {'''configuration_nat''': ['''NAT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NatConfig''']}


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase       = [
         '''NAT_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''NatForImageClassification''',
         '''NatModel''',
         '''NatPreTrainedModel''',
         '''NatBackbone''',
     ]

if TYPE_CHECKING:
     from .configuration_nat import NAT_PRETRAINED_CONFIG_ARCHIVE_MAP, NatConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_nat import (
              NAT_PRETRAINED_MODEL_ARCHIVE_LIST,
              NatBackbone,
              NatForImageClassification,
              NatModel,
              NatPreTrainedModel,
          )

else:
     import sys

     _UpperCamelCase       = _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

