有没有一种方法可以在keras中编写自定义损失函数？

import keras.backend as K
from keras.losses import Loss

class CustomLoss(Loss):
    def __init__(self, param1, param2):
        super(CustomLoss, self).__init__()
        self.param1 = param1
        self.param2 = param2
        
    def call(self, y_true, y_pred):
        # 自定义损失函数的计算逻辑
        loss = ...
        return loss

class CustomLoss(Loss):
    def __init__(self, weight):
        super(CustomLoss, self).__init__()
        self.weight = weight
        
    def call(self, y_true, y_pred):
        loss = K.mean(K.square(y_true - y_pred) * self.weight)
        return loss

model.compile(loss=CustomLoss(weight=0.5), optimizer='adam')