I have a fairly elementary question but it is something that has caused me some trouble. So lets say we have a two layer convolutional network. In the first layer we have
Conv1 = Conv2d(1,2, stride = 1)
meaning that we have two filters for our input, producing two feature maps
in the second layer we have
Conv2 = Conv2d(2,2, stride = 1)
in this layer I would expect that we have two filters since the final output is two feature maps, but when i look into the weights we have 4 convolutional filters in the second convolutional layer. Why is this?