Confusion in contrastive loss

#3
by gkmeng - opened

Hi, thank you for the interesting application. However I have some questions regarding the way keras-io do the labelling and the eqn of contrastive loss.
In the original pair, similar pairs are assigned as 0 and dissimilar pairs are assigned as 1, and the equation used are as follows:

loss = [(1 - y ) x D] + [(y) X max(margin-D, 0)]

However in the example given by Keras (https://keras.io/examples/vision/siamese_contrastive/), the labelling method are reversed, and the same equation of contrastive loss are still used. Any reason why keras did so? Thank you.

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