oryx.experimental.nn.Relu

Parent abstract class for activation functions.

Inherits From: Activation, Layer, Module, Pytree

View aliases

Main aliases

oryx.experimental.nn.core.Relu

oryx.experimental.nn.Relu(
    layer_params, name=None
)

Attributes
info	Returns the info for this Layer.
params	Returns the parameters of this Layer.
state	Returns the state of this Layer.

Methods

call

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call(
    *args, **kwargs
)

Calls the Layer's call_and_update and returns the first result.

call_and_update

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call_and_update(
    *args, rng=None, **kwargs
)

Uses the layer_cau primitive to call `self._call_and_update.

flatten

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flatten()

Converts the Layer to a tuple suitable for PyTree.

initialize

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@classmethod
initialize(
    rng, in_shape
)

Initializes Activation Layer.

new

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@classmethod
new(
    layer_params, name=None
)

Creates Layer given a LayerParams namedtuple.

Args
layer_params	LayerParams namedtuple that defines the Layer.
name	a string name for the Layer.

Returns
A Layer object.

replace

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replace(
    params=None, state=None, info=None
)

Returns a copy of the layer with replaced properties.

spec

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@classmethod
spec(
    in_spec
)

unflatten

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@classmethod
unflatten(
    data, xs
)

Reconstruct the Layer from a flattened version.

update

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update(
    *args, **kwargs
)

Calls the Layer's call_and_update and returns the second result.

variables

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variables()

Returns the variables dictionary for this Layer.

__call__

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__call__(
    *args, **kwargs
) -> Any

Emulates a regular function call.

A Module's dunder call will ensure state is updated after the function call by calling assign on the updated state before returning the output of the function.

Args
*args	The arguments to the module.
**kwargs	The keyword arguments to the module.

Returns
The output of the module.