SGD# class brainpy.optim.SGD(lr, train_vars=None, weight_decay=None, name=None)[source]# Stochastic gradient descent optimizer. SGD performs a parameter update for training examples \(x\) and label \(y\): \[\theta = \theta - \eta \cdot \nabla_\theta J(\theta; x; y)\] Parameters: lr (float, Scheduler) – learning rate.
