softplus#

ivy.softplus(x, /, *, beta=None, threshold=None, out=None)[source]#

Apply the softplus function element-wise.

Parameters:

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

  • beta (Optional[Union[int, float]]) – The beta value for the softplus formation. Default: None. (default: None)

  • threshold (Optional[Union[int, float]]) – values above this revert to a linear function. Default: None. (default: None)

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

Return type:

Array

Returns:

ret – an array containing the softplus activation of each element in x.

Functional Examples

With ivy.Array input:

>>> x = ivy.array([-0.3461, -0.6491])
>>> y = ivy.softplus(x)
>>> print(y)
ivy.array([0.535,0.42])

>>> x = ivy.array([-0.3461, -0.6491])
>>> y = ivy.softplus(x, beta=0.5)
>>> print(y)
ivy.array([1.22, 1.09])

>>> x = ivy.array([1., 2., 3.])
>>> y = ivy.softplus(x, threshold=2)
>>> print(y)
ivy.array([1.31, 2.13, 3.  ])
Array.softplus(self, /, *, beta=None, threshold=None, out=None)#

ivy.Array instance method variant of ivy.softplus. This method simply wraps the function, and so the docstring for ivy.softplus also applies to this method with minimal changes.

Parameters:

  • self (Array) – input array.

  • beta (Optional[Union[int, float]]) – the beta parameter of the softplus function. (default: None)

  • threshold (Optional[Union[int, float]]) – the threshold parameter of the softplus function. (default: None)

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

Return type:

Array

Returns:

ret – an array with the softplus activation function applied element-wise.

Examples

>>> x = ivy.array([-0.3461, -0.6491])
>>> y = x.softplus()
>>> print(y)
ivy.array([0.535,0.42])

>>> x = ivy.array([-0.3461, -0.6491])
>>> y = x.softplus(beta=0.5)
>>> print(y)
ivy.array([1.22, 1.09])

>>> x = ivy.array([1.31, 2., 2.])
>>> y = x.softplus(threshold=2, out=x)
>>> print(x)
ivy.array([1.55, 2.13, 2.13])
Container.softplus(self, /, *, beta=None, threshold=None, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, out=None)#

ivy.Container instance method variant of ivy.softplus. This method simply wraps the function, and so the docstring for ivy.softplus also applies to this method with minimal changes.

Parameters:

  • self (Container) – input container.

  • beta (Optional[Union[int, float]]) – The beta value for the softplus formation. Default: None. (default: None)

  • threshold (Optional[Union[int, float]]) – values above this revert to a linear function. Default: None. (default: None)

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

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

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

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

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

Return type:

Container

Returns:

ret – a container with the softplus unit function applied element-wise.

Examples

>>> x = ivy.Container(a=ivy.array([-0.3461, -0.6491]))
>>> y = x.softplus()
>>> print(y)
{
    a: ivy.array([0.535, 0.42])
}

>>> x = ivy.Container(a=ivy.array([-1., 2., 4.]))
>>> y = x.softplus(beta=0.5, threshold=2)
>>> print(y)
{
    a: ivy.array([0.948, 2.63, 4.25])
}