The problem is:
I have LFW data set which contains about 2000 persons’ face, that is to say about 2000 classes. And each person contains about 2 images.
I use triple loss to train the net.but the problem is:

We need to contain almost all the classes in the minibatch to train a good model right ?(I’m not sure).that is to say at least 4000 images in a minibatch.is possible in practice?Typically I with 64/32 as mini batch that’s wierd.