quantax.nn.Sequential

class quantax.nn.Sequential(layers: Sequence[Callable], holomorphic: bool = False)

Bases: Sequential

A sequence of equinox.Module applied in order similar to Sequential in Equinox.

Note

Functions can be added as a layer by wrapping them in equinox.nn.Lambda.

__init__(layers: Sequence[Callable], holomorphic: bool = False)

Parameters:

• layers – A sequence of equinox.Module.

• holomorphic – Whether the whole network is a complex holomorphic function, default to False.

Note

The users are responsible to ensure the given holomorphic argument is correct.

rescale(maximum: Array) → Sequential

Generate a new network in which all layers are rescaled. This is often used when a Theta0Layer is included as a layer.

Parameters:

maximum – The maximum output obtained from this network.

Returns:

The rescaled network

Note

This method generates a new network while doesn’t modify the existing network.

Attributes

layers
holomorphic