No, they are just variables. It’s actually not grad_in and grad_out, but input and output in the forward function.
You could also name them a and b. The important fact is, that register_forward_hook needs a function with a signature of getting two arguments. The first argument is the input to this layer, the second its output.
self.conv_output just saves the activation of the first sample in the batch and self.selected_filter.
It’s a member of your class to visualize the activation. Later you may call my_class.conv_output to visualize the activation map.