I am trying to implement AlexNet with Keras and was inspecting the network design in MATLAB which is given as follows As could be seen, the second convolution layer has 256 filters of size 5x5, 48 channels and a padding of [ 2 2 2 2 ]. How could I specify padding of [ 2 2 2 2] with Keras? I went through the documentation of Conv2D. It accepts only 2 values for padding namely valid and same. I could not understand this. For what I know, valid would mean zero padding. How could I specify [2 2 2 2] padding with the second convolution layer? I created the first layer as: model.add(keras.layers.Conv2D(filters = 96, kernel_size = (11,11), strides = (4,4), padding = "valid", input_shape=(227,227,3))) Also, since in the second layer there are 48 channels, do I need to be explicit about it? Continue reading...
