HubAndSpokes

Bases: tf.keras.Model

__init__(tau, hub_name, hub_units, spoke_names, spoke_units)

Hub-and-spokes model.

See Rogers et. al., 2004 for more details.

Parameters:

Name	Type	Description	Default
tau	float	Time constant of the time-averaging.	required
hub_name	str	Name of the hub layer.	required
hub_units	int	Number of units in the hub layer.	required
spoke_names	List[str]	Names of the spoke layers.	required
spoke_units	List[int]	Number of units in each spoke layer. Must be the same length as spoke_names.	required

call(inputs, return_internals=False)

Forward pass.

The number of time steps is determined by axis 1 in the inputs.

Parameters:

Name	Type	Description	Default
inputs	Dict[str, tf.Tensor]	Inputs to the spokes (name as key). Assumes input is 0 if not given.	required
return_internals	bool	Whether to return intermediate inputs to each connection.	False

Returns:

Type	Description
Dict[str, tf.Tensor]	Dict[str, tf.Tensor]: Activations of the hub and spokes, with layer names as keys. If return_internals is True, also returns intermediate inputs to each connection.

train_step(data)

Train the model for one step.

Loss is cumulated over all y_train items.

Parameters:

Name	Type	Description	Default
data	Tuple[Dict[str, tf.Tensor]]	Tuple of (x_train, y_train).	required

Returns:

Type	Description
Dict[str, tf.Tensor]	Dict[str, tf.Tensor]: metrics.