Triplet-Loss | Apply triplet loss to face recognition， adding new loss | Machine Learning library

I have a ResNet based siamese network which uses the idea that you try to minimize the l-2 distance between 2 images and then apply a sigmoid so that it gives you {0:'same',1:'different'} output and based on how far the prediction is, you just flow the gradients back to network but there is a problem that updation of gradients is too little as we're changing the distance between {0,1} so I thought of using the same architecture but based on Triplet Loss.

As much as I know that Triplet Loss is a Loss Function which decrease the distance between anchor and positive but decrease between anchor and negative. Also, there is a margin added to it.

So for EXAMPLE LEt us Suppose: a Siamese Network, which gives embeddings:

I am trying to replicate the lossless tripler loss, but using the "K." syntax, like in my triplet loss below:

My code