def training_loop(batch1, output1, batch2, output2):
    with tf.GradientTape() as tape:
        predictions1 = model1(batch1)
        loss1 = your_loss_function1(predictions1, output1)

    gradients = tape.gradient(loss1 , model1.trainable_weights)
    loss_optimizer1.apply_gradients(zip(gradients, model1.trainable_weights))

    with tf.GradientTape() as tape:
        predictions2 = model1(batch2)
        loss2 = your_loss_function2(predictions2, output2)

    gradients = tape.gradient(loss2 , model2.trainable_weights)
    loss_optimizer2.apply_gradients(zip(gradients, model2.trainable_weights))

    return loss1, loss2