Say I have a batch of examples, each examples represent a state:
[0.1, 0.2, 0.5] #1st example [0.4, 0.0, 0.3] #2nd example .......... [0.1, 0.1, 0.1] #16th example
I feed through the NN, and then the NN predict the following class:
[move up] #1st example [move down] #2nd example ........ [move left] #16th example
And then I take the square loss (which calculated to be 0.1 after taking average over 16 examples), and do backward propagation.
So, can I assume that each of these examples will assign (or contribute) to a 0.1 loss?