tf-keras-skeleton.py 文件源码

def get_gradients(self, loss, params):
        grads = K.gradients(loss, params)
        if hasattr(self, 'clipnorm') and self.clipnorm > 0:
          norm = K.sqrt(sum([K.sum(K.square(g)) for g in grads]))
          grads = [clip_norm(g, self.clipnorm, norm) for g in grads]
        if hasattr(self, 'clipvalue') and self.clipvalue > 0:
          grads = [K.clip(g, -self.clipvalue, self.clipvalue) for g in grads]
        return grads