According to Keras documentation,
sample_weight can be used in order to give any sample in the training data a different importance in the loss.
I have googled around but have not found the answer to my question as follows:
sample weightstake part in the derivatives? In other words, does Keras use these weights to train the model or they just give rise to a different loss value? i.e., the derivatives are "still" computed w.r.t. to the "unweighted" loss?
Because the loss function is not actually defined based on the sample weights, its rather passed in (as an argument) to the
fit function in Keras.