def KL(pred, target, temperature=5, verbose=False):
""" 计算pred和target的KL散度
[IN] pred: numpy.ndarray, 预测值
target: numpy.ndarray, 目标值
temperature: int, 温度参数T
verbose: boolean, true则展示除以T, softmax后的pred和target的输出
[OUT] loss: float, KL散度结果
"""
#logging.info("pred before: {}".format(pred.numpy()[:2]))
pred = L.softmax(pred / temperature)
if verbose:
logging.info("pred: {}".format(pred.numpy()[:2]))
pred = L.log(pred)
#logging.info("target before: {}".format(target.numpy()[:2]))
target = L.softmax(target / temperature)
if verbose:
logging.info("target: {}".format(target.numpy()[:2]))
loss = L.kldiv_loss(pred, target)
if verbose:
logging.info("kl loss: {}".format(loss.numpy()))
return loss
def KL(pred, target):
pred = L.log(L.softmax(pred))
target = L.softmax(target)
loss = L.kldiv_loss(pred, target)
return loss