brainpy.optimizers.SGD
brainpy.optimizers.SGD#
- class brainpy.optimizers.SGD(lr, train_vars=None, name=None)[source]#
Stochastic gradient descent optimizer.
SGD performs a parameter update for training examples \(x\) and label \(y\):
\[\theta = \theta - \eta \cdot \nabla_\theta J(\theta; x; y)\]Methods
__init__
(lr[, train_vars, name])check_grads
(grads)load_states
(filename[, verbose])Load the model states.
nodes
([method, level, include_self])Collect all children nodes.
register_implicit_nodes
(nodes)register_implicit_vars
(variables)register_vars
([train_vars])save_states
(filename[, variables])Save the model states.
train_vars
([method, level, include_self])The shortcut for retrieving all trainable variables.
unique_name
([name, type_])Get the unique name for this object.
update
(grads)vars
([method, level, include_self])Collect all variables in this node and the children nodes.
Attributes
name