brainpy.nn.nodes.base.Dense
brainpy.nn.nodes.base.Dense#
- class brainpy.nn.nodes.base.Dense(num_unit, weight_initializer=XavierNormal(scale=1.0, mode=fan_avg, in_axis=- 2, out_axis=- 1, distribution=truncated_normal, seed=None), bias_initializer=ZeroInit, **kwargs)[source]#
A linear transformation.
Different from
GeneralDense
, this class only supports 2D input data.Mathematically, this node can be defined as:
\[y = x \cdot W+ b\]- Parameters
num_unit (int) – The number of the output features. A positive integer.
weight_initializer (optional, Initializer) – The weight initialization.
bias_initializer (optional, Initializer) – The bias initialization.
trainable (bool) – Enable training this node or not. (default True)
- __init__(num_unit, weight_initializer=XavierNormal(scale=1.0, mode=fan_avg, in_axis=- 2, out_axis=- 1, distribution=truncated_normal, seed=None), bias_initializer=ZeroInit, **kwargs)[source]#
Methods
__init__
(num_unit[, weight_initializer, ...])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
feedback_shapes
Output data size.
feedforward_shapes
Input data size.
is_feedback_input_supported
is_feedback_supported
is_initialized
- rtype
name
output_shape
Output data size.
state
Node current internal state.
trainable
Returns if the Node can be trained.