






def       a__						(  A					):
   return -num if num < 0 else num
def       a__						(  A					):
   if len(A					) == 0:
      raise ValueError("""abs_min() arg is an empty sequence"""					)
   lowercase__						:	Tuple         = x[0]
   for i in x:
      if abs_val(A					) < abs_val(A					):
         lowercase__						:	str         = i
   return j
def       a__						(  A					):
   if len(A					) == 0:
      raise ValueError("""abs_max() arg is an empty sequence"""					)
   lowercase__						:	List[str]         = x[0]
   for i in x:
      if abs(A					) > abs(A					):
         lowercase__						:	Any         = i
   return j
def       a__						(  A					):
   if len(A					) == 0:
      raise ValueError("""abs_max_sort() arg is an empty sequence"""					)
   return sorted(A		,				key=A					)[-1]
def       a__						(  ):
   assert abs_val(0					) == 0
   assert abs_val(34					) == 34
   assert abs_val(-100_000_000_000					) == 100_000_000_000

   lowercase__						:	List[str]         = [-3, -1, 2, -11]
   assert abs_max(A					) == -11
   assert abs_max_sort(A					) == -11
   assert abs_min(A					) == -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


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


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a    =       [
     '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

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


