 This reconstruction loss is scaled down by 0.0005 so that it does not dominate the margin loss during training.The first convolutional layers perform feature extraction.For the 28x28 pixel MNIST image test an initial 256 9x9 pixel convolutional kernels (using stride 1 and rectified linear unit (ReLU) activation, defining 20x20 receptive fields) convert the pixel input into 1D feature activations and induce nonlinearity.