Margin Ranking

• Creates a criterion that measures the loss given inputs x1x1x1 , x2x2x2 , two 1D mini-batch Tensors, and a label 1D mini-batch tensor yyy (containing 1 or -1).
• If y=1y = 1y=1 then it assumed the first input should be ranked higher (have a larger value) than the second input, and vice-versa for y=−1y = -1y=−1 .
• take avg

$\frac{1}{\mathrm{length}\left(y\right)}\cdot \mathrm{sum}\left(\max \left(0,\left(-y\right)\cdot x1-x2+margin\right)\right)$