hardsilu#

ivy.hardsilu(x, /, *, out=None)[source]#

Apply the hardsilu/hardswish function element-wise.

Parameters:
  • x (Union[Array, NativeArray]) – input array

  • out (Optional[Array], default: None) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

Array

Returns:

an array containing the output of the hardsilu/hardswish function applied to each element in x.

Examples

With ivy.Array input:

>>> x = ivy.array([1., 2., 3.])
>>> y = ivy.hardsilu(x)
>>> print(y)
ivy.array([0.66666669, 1.66666663, 3.        ])
>>> x = ivy.array([-2.1241, 1.4897, 4.4090])
>>> y = ivy.zeros(3)
>>> ivy.hardsilu(x, out=y)
>>> print(y)
ivy.array([-0.31008321,  1.1147176 ,  4.40899992])

With ivy.Container input:

>>> x = ivy.Container(a=ivy.array([-0.5, -1, 0]), b=ivy.array([0.5, 1., 2]))
>>> y = ivy.hardsilu(x)
>>> print(y)
{
    a: ivy.array([-0.20833333, -0.33333334, 0.]),
    b: ivy.array([0.29166666, 0.66666669, 1.66666663])
}
Array.hardsilu(self, out=None)[source]#

ivy.Array instance method which acts as a wrapper for ivy.hardsilu.

Parameters:
  • self – input array

  • out (Optional[Array], default: None) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

Array

Returns:

  • an array containing the output of the hardsilu/hardswish function applied

  • to each element in x.

Examples

>>> x = ivy.array([1., 2., 3.])
>>> y = x.hardsilu()
>>> print(y)
ivy.array([0.66666667, 1.66666667, 3.])
Container.hardsilu(self, /, *, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, out=None)[source]#

ivy.Container instance method which acts as a wrapper for ivy.hardsilu.

Parameters:
  • self – input container

  • key_chains (Optional[Union[List[str], Dict[str, str], Container]], default: None) – The keychains to apply or not apply the method to. Default is None.

  • to_apply (Union[bool, Container], default: True) – If True, the method will be applied to key_chains, otherwise key_chains will be skipped. Default is True.

  • prune_unapplied (Union[bool, Container], default: False) – Whether to prune key_chains for which the function was not applied. Default is False.

  • map_sequences (Union[bool, Container], default: False) – Whether to also map method to sequences (lists, tuples). Default is False.

  • out (Optional[Container], default: None) – optional output container, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

Container

Returns:

  • a container containing the output of the hardsilu/hardswish function applied

  • to each element in the input container.

Examples

>>> x = ivy.Container(a=ivy.array([-0.5, -1, 0]), b=ivy.array([0.5, 1., 2]))
>>> y = x.hardsilu()
>>> print(y)
{
    a: ivy.array([-0.20833333, -0.33333334, 0.]),
    b: ivy.array([0.29166666, 0.66666669, 1.66666663])
}