问题描述
我正在将下面url中的学生-教师模型转换为keras一个.
I'm converting student-teacher model in below url to keras one.
https://github.com/chengshengchan/model_compression/blob/master/teacher-student.py
我怎样才能给两种模型(学生，老师)提供输入，而仅从喀拉拉邦的学生那里获得一种输出?我将trainable = false设置为老师的所有张量，并将损失函数设置为学生和老师的输出之间的差异，如下所示:
How can I give input to two model(student, teacher) and get one output from only student in keras?I'll set teacher's all tensors with trainable=false, and loss function as difference between student and teacher's output like below :
tf_loss = tf.nn.l2_loss(teacher - student)/batch_size
据我所知，在定义model.fit时，可以仅向一个模型提供输入.但是在这种情况下，我应该同时采用教师和学生模式.
As I know, it is possible to give input to only one model when defining model.fit. But in this cases, I should it to both of teacher and student model.
提前谢谢！
推荐答案
我在Keras中看到的唯一实现包括构建2个单独的函数，这些函数可以扩大或加深教师模型的权重层，作为学生模型的初始权重.我不确定是否正是Hinton等人. (2015)升格说老实，但它是师生. https://github.com/fchollet/keras/issues/3491
The only implementation I have seen in Keras involves building 2 separate functions which either widen or deepen weight layers from the teacher model as initial weights for the student model.I am not sure if it is precisely that Hinton et al. (2015) distillation to be honest, but it is teacher-student.https://github.com/fchollet/keras/issues/3491
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