如何将tensorflow内置的logits自定义损失函数转换为keras？

import tensorflow as tf
from tensorflow import keras

def custom_loss(y_true, y_pred):
    loss = tf.nn.sigmoid_cross_entropy_with_logits(labels=y_true, logits=y_pred)
    return tf.reduce_mean(loss)

model = tf.keras.models.Sequential()
model.add(tf.keras.layers.Dense(units=10, activation='relu', input_shape=(input_dim,)))
model.add(tf.keras.layers.Dense(units=1, activation='sigmoid'))

model.compile(optimizer='adam', loss=custom_loss, metrics=['accuracy'])