#ssd

An SSD-style class predictor is a $3 \times 3$ convolution with padding 1, applied to a feature map of shape $1 \times 256 \times 10 \times 10$. Each spatial position is the center of $a = 4$ anchor boxes, and there are $q = 5$ object classes plus background. What is the shape of the class predictor's output?