figure deep learning for computer vision valid locat ions of patches in input feat ure map if you want to get an output feature map with the same spatial dimensions as the inputyou can use padding padding consists of adding an appropriate number of rows and columns on each side of the input feature map so as to make it possible to fit center convolution windows around every input tile for windowyou add one column on the rightone column on the leftone row at the topand one row at the bottom for windowyou add two rows (see figure etc figure padding input in order be able extract patches in conv layerspadding is configurable via the padding argumentwhich takes two values"valid"which means no padding (only valid window locations will be used)and "same"which means "pad in such way as to have an output with the same width and height as the input the padding argument defaults to "validlicensed to