brainpy.nn.nodes.RC.LinearReadout#

class brainpy.nn.nodes.RC.LinearReadout(num_unit, **kwargs)[source]#

Linear readout node. Different from Dense, this node has its own state.

Parameters

  • num_unit (int) – The number of output features. A positive integer.

  • weight_initializer (Initializer) – The weight initializer.

  • bias_initializer (Optional, Initializer) – The bias initializer.

  • trainable (bool) – Default is true.

__init__(num_unit, **kwargs)[source]#

Methods

__init__(num_unit, **kwargs)

copy([name, shallow])

Returns a copy of the Node.

feedback(ff_output, **shared_kwargs)

The feedback computation function of a node.

forward(ff[, fb])

The feedforward computation function of a node.

init_fb_conn()

Initialize the feedback connections.

init_fb_output([num_batch])

Set the initial node feedback state.

init_ff_conn()

Initialize the feedforward connections.

init_state([num_batch])

Set the initial node state.

initialize([num_batch])

Initialize the node.

load_states(filename[, verbose])

Load the model states.

nodes([method, level, include_self])

Collect all children nodes.

offline_fit(targets, ffs[, fbs])

The offline training interface for the Dense node.

online_fit(target, ff[, fb])

Online training fitting interface.

online_init()

Online training initialization interface.

register_implicit_nodes(nodes)

register_implicit_vars(variables)

save_states(filename[, variables])

Save the model states.

set_fb_output(state)

Safely set the feedback state of the node.

set_feedback_shapes(fb_shapes)

set_feedforward_shapes(feedforward_shapes)

set_output_shape(shape)

set_state(state)

Safely set the state of the node.

train_vars([method, level, include_self])

The shortcut for retrieving all trainable variables.

unique_name([name, type_])

Get the unique name for this object.

vars([method, level, include_self])

Collect all variables in this node and the children nodes.

Attributes

data_pass

Offline fitting method.

fb_output

rtype

Optional[TypeVar(Tensor, JaxArray, ndarray)]

feedback_shapes

Output data size.

feedforward_shapes

Input data size.

is_feedback_input_supported

is_feedback_supported

is_initialized

rtype

bool

name

output_shape

Output data size.

state

Node current internal state.

trainable

Returns if the Node can be trained.