relu6#
- ivy.relu6(x, /, *, complex_mode='jax', out=None)[source]#
Apply the rectified linear unit 6 function element-wise.
- Parameters:
x (
Union
[Array
,NativeArray
]) – input arraycomplex_mode (
Literal
['split'
,'magnitude'
,'jax'
], default:'jax'
) – optional specifier for how to handle complex data types. Seeivy.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:
- Returns:
ret – an array containing the rectified linear unit 6 activation of each element in
x
.
Examples
With
ivy.Array
input:>>> x = ivy.array([-1., 0., 1., 2., 3., 4., 5., 6., 7.]) >>> y = ivy.relu6(x) >>> print(y) ivy.array([0., 0., 1., 2., 3., 4., 5., 6., 6.])
>>> x = ivy.array([-1., 0., 1., 2., 3., 4., 5., 6., 7.]) >>> y = ivy.zeros(9) >>> ivy.relu6(x, out = y) >>> print(y) ivy.array([0., 0., 1., 2., 3., 4., 5., 6., 6.])
- Array.relu6(self, /, *, complex_mode='jax', out=None)[source]#
Apply the rectified linear unit 6 function element-wise.
- Parameters:
self – input array
complex_mode (
Literal
['split'
,'magnitude'
,'jax'
], default:'jax'
) – optional specifier for how to handle complex data types. Seeivy.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 rectified linear unit 6 activation of each element in input.
Examples
With
ivy.Array
input:>>> x = ivy.array([-1., 0., 1., 2., 3., 4., 5., 6., 7.]) >>> y = ivy.relu6(x) >>> print(y) ivy.array([0., 0., 1., 2., 3., 4., 5., 6., 6.])
>>> x = ivy.array([-1., 0., 1., 2., 3., 4., 5., 6., 7.]) >>> y = ivy.zeros(9) >>> ivy.relu6(x, out = y) >>> print(y) ivy.array([0., 0., 1., 2., 3., 4., 5., 6., 6.])
- Container.relu6(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.relu6. This method simply wraps the function, and so the docstring for ivy.relu6 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 isNone
.to_apply (
Union
[bool
,Container
], default:True
) – If True, the method will be applied to key_chains, otherwise key_chains will be skipped. Default isTrue
.prune_unapplied (
Union
[bool
,Container
], default:False
) – Whether to prune key_chains for which the function was not applied. Default isFalse
.map_sequences (
Union
[bool
,Container
], default:False
) – Whether to also map method to sequences (lists, tuples). Default isFalse
.complex_mode (
Literal
['split'
,'magnitude'
,'jax'
], default:'jax'
) – optional specifier for how to handle complex data types. Seeivy.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 rectified linear 6 activation unit function applied element-wise.
Examples
>>> x = ivy.Container(a = ivy.array([-3., -2., -1., 0., 1., 2., 3., 4., 5.]), ... b= ivy.array([1., 2., 3., 4., 5., 6., 7., 8., 9.])) >>> y = x.relu() >>> print(y) { a: ivy.array([0., 0., 0., 0., 1., 2., 3., 4., 5.]), b: ivy.array([1., 2., 3., 4., 5., 6., 7., 8., 9.]) }