optim.py 文件源码

def sgd_momentum(w, dw, config=None):
    '''
    Performs stochastic gradient descent with momentum.

    config format:
    - learning_rate: Scalar learning rate.
    - momentum: Scalar between 0 and 1 giving the momentum value.
      Setting momentum = 0 reduces to sgd.
    - velocity: A numpy array of the same shape as w and dw used to store a moving
      average of the gradients.
    '''
    if config is None:
        config = {}
    config.setdefault('learning_rate', 1e-2)
    config.setdefault('momentum', 0.9)
    v = config.get('velocity', np.zeros_like(w))

    next_w = None
    v = config['momentum'] * v + config['learning_rate'] * dw
    next_w = w - v
    config['velocity'] = v

    return next_w, config