AdamTrainer.py 文件源码

def __init__(self, rng, batchsize, epochs=100, alpha=0.001, beta1=0.9, beta2=0.999, eps=1e-08, gamma=0.1, cost='mse'):
        self.alpha = alpha
        self.beta1 = beta1
        self.beta2 = beta2
        self.eps = eps
        self.gamma = gamma
        self.rng = rng
        self.theano_rng = RandomStreams(rng.randint(2 ** 30))
        self.epochs = epochs
        self.batchsize = batchsize
        if   cost == 'mse':
            self.cost = lambda network, x, y: T.mean((network(x) - y)**2)
        elif cost == 'cross_entropy':
            self.cost = lambda network, x, y: T.nnet.binary_crossentropy(network(x), y).mean()
        else:
            self.cost = cost