Reduce grad back to target_shape by summing over broadcast axes.

Used in the backward pass of any binary op that broadcast one operand against the other. The gradient initially has the broadcast (output) shape; this helper walks the trailing dimensions and sums along any axis where target_shape is size 1 or absent, so the result matches the original input shape ready to be accumulated into .grad.

Math

For each output index i,