celu#
- ivy.celu(x, /, *, alpha=1.0, complex_mode='jax', out=None)[source]#
Apply the Continuously Differentiable Exponential Linear Unit (CELU) activation function to each element of the input.
- Parameters:
x (
Union
[Array
,NativeArray
]) – Input array.alpha (
float
, default:1.0
) – The alpha value (negative slope) for the CELU formulation. Default is1.0
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:
- Returns:
ret – The input array with celu applied element-wise.
Examples
With
ivy.Array
input:>>> x = ivy.array([0.39, -0.85]) >>> y = ivy.celu(x) >>> y ivy.array([ 0.39, -0.57])
With
ivy.Container
input:>>> x = ivy.Container(a=ivy.array([0.39, -0.85]), b=ivy.array([1., -0.2])) >>> y = ivy.celu(x) >>> y { a: ivy.array([0.38999999, -0.57]), b: ivy.array([1., -0.18]) }
- Array.celu(self, /, *, alpha=1.0, complex_mode='jax', out=None)[source]#
ivy.Array instance method variant of ivy.celu. This method simply wraps the function, and so the docstring for ivy.celu also applies to this method with minimal changes.
- Parameters:
self (
Array
) – input array.alpha (
float
, default:1.0
) – the alpha (negative slope) value for CELU formulation.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 with the celu activation function applied element-wise.
Examples
>>> x = ivy.array([0.39, -0.85]) >>> y = x.celu() >>> print(y) ivy.array([ 0.39, -0.57])
- Container.celu(self, /, *, alpha=1.0, 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.leaky_relu. This method simply wraps the function, and so the docstring for ivy.leaky_relu also applies to this method with minimal changes.
- Parameters:
self (
Container
) – input container.alpha (
Container
, default:1.0
) – array or scalar specifying alpha (negative slope) value for CELU formulation.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 celu unit function applied element-wise.
Examples
>>> x = ivy.Container(a=ivy.array([0.39, -0.85]), b=ivy.array([1., -0.2])) >>> y = x.celu() >>> print(y) { a: ivy.array([0.38999999, -0.57]), b: ivy.array([1., -0.18]) }