Week 2. Why we use K.mean here?


I don’t understand why we use K.mean in Contrastive Loss in class and don’t use in other places?
This is screen from video “Coding Contrastive Loss”

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It’s an interesting question. Notice that averaging is not being done in this fragment from the TensorFlow implementation…

return y_true * tf.math.square(y_pred) + (1.0 - y_true) * tf.math.square(
tf.math.maximum(margin - y_pred, 0.0)

It isn’t mentioned in the video?

The teacher skipped this line.

I did some research on this and it seems the instructor has mistaken that calculation with the RMSE calculation, seems to me. I will raise an issue in github so they can have a look at it as well.

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