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hardshrink#

ivy.hardshrink(x, /, *, lambd=0.5, out=None)[source]#

Apply the hardshrink function element-wise.

Parameters:

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

  • lambd (float, default: 0.5) – the value for the Hardshrink formulation.

  • 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:

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

Examples

With ivy.Array input: >>> x = ivy.array([-1.0, 1.0, 2.0]) >>> y = ivy.hardshrink(x) >>> print(y) ivy.array([-1., 1., 2.]) >>> x = ivy.array([-1.0, 1.0, 2.0]) >>> y = x.hardshrink() >>> print(y) ivy.array([-1., 1., 2.]) >>> x = ivy.array([[-1.3, 3.8, 2.1], [1.7, 4.2, -6.6]]) >>> y = ivy.hardshrink(x) >>> print(y) ivy.array([[-1.29999995, 3.79999995, 2.0999999 ],

[ 1.70000005, 4.19999981, -6.5999999 ]])

Array.hardshrink(self, /, *, lambd=0.5, out=None)[source]#

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

Parameters:

  • self (Array) – input array.

  • lambd (float, default: 0.5) – the lambd value for the Hardshrink formulation

  • 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:

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

Examples

>>> x = ivy.array([-1., 0., 1.])
>>> y = x.hardshrink()
>>> print(y)
ivy.array([-1.,  0.,  1.])
>>> x = ivy.array([-1., 0., 1.])
>>> y = x.hardshrink(lambd=1.0)
>>> print(y)
ivy.array([0., 0., 0.])
Container.hardshrink(self, /, *, lambd=0.5, key_chains=None, to_apply=False, prune_unapplied=True, map_sequences=False, out=None)[source]#

Apply the hard shrinkage function element-wise.

Parameters:

  • self (Container) – Input container.

  • lambd (Container, default: 0.5) – Lambda value for hard shrinkage calculation.

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

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

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

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

  • 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:

ret – Container with hard shrinkage applied to the leaves.

Examples

>>> x = ivy.Container(a=ivy.array([1., -2.]), b=ivy.array([0.4, -0.2]))
>>> y = ivy.Container.hardshrink(x)
>>> print(y)
{
    a: ivy.array([1., -2.]),
    b: ivy.array([0., 0.])
}
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