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hardswish#

ivy.hardswish(x, /, *, complex_mode='jax', out=None)[source]#

Apply the hardswish activation function element-wise.

Parameters:

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

  • complex_mode (Literal['split', 'magnitude', 'jax'], default: 'jax') – optional specifier for how to handle complex data types. See ivy.func_wrapper.handle_complex_input for more detail.

  • 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 hardswish activation of each element in x.

Examples

With ivy.Array input:

>>> x = ivy.array([0., 0., 4.])
>>> y = ivy.hardswish(x)
>>> y
ivy.array([0., 0., 4.])

With ivy.Container input:

>>> x = ivy.Container(a=ivy.array([-3., 4., 5.]), b=ivy.array([0., 5.]))
>>> x = ivy.hardswish(x, out=x)
>>> x
{
    a: ivy.array([-0.,  4.,  5.]),
    b: ivy.array([0., 5.])
}
Array.hardswish(self, /, *, complex_mode='jax', out=None)[source]#

Apply the hardswish activation function element-wise.

Parameters:

  • x – input array

  • complex_mode (Literal['split', 'magnitude', 'jax'], default: 'jax') – optional specifier for how to handle complex data types. See ivy.func_wrapper.handle_complex_input for more detail.

  • 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 hardswish activation of each element in x.

Examples

With ivy.Array input:

>>> x = ivy.array([0., 0., 4.])
>>> y = ivy.hardswish(x)
>>> y
ivy.array([0., 0., 4.])

With ivy.Container input:

>>> x = ivy.Container(a=ivy.array([-3., 4., 5.]), b=ivy.array([0., 5.]))
>>> x = ivy.hardswish(x, out=x)
>>> x
{
    a: ivy.array([-0.,  4.,  5.]),
    b: ivy.array([0., 5.])
}
Container.hardswish(self, /, *, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, complex_mode='jax', out=None)[source]#

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

Parameters:

  • self (Container) – input container.

  • key_chains (Optional[Union[List[str], Dict[str, str], Container]], default: None) – The key-chains 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.

  • complex_mode (Literal['split', 'magnitude', 'jax'], default: 'jax') – optional specifier for how to handle complex data types. See ivy.func_wrapper.handle_complex_input for more detail.

  • 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 – a container with the hardswish activation function applied element-wise.

Examples

>>> x = ivy.Container(a=ivy.array([-3., 4., 5.]), b=ivy.array([0., 5.]))
>>> x = ivy.hardswish(x, out=x)
>>> x
{
    a: ivy.array([-0.,  4.,  5.]),
    b: ivy.array([0., 5.])
}
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