Typical Feed Forward Neural Networks require a fixed sized input and output. So when you have variable sized input, it seems to be common practice to pad the input with zero vectors.
Why does it not seem to be common practice to have a "is_padding" attribute? That way the network can easily distinguish between padding and actual data? Especially considering input is commonly centered around 0 by subtracting the mean and using unit variance.