
Add self.param to x
Pass x through self.submodule. Here we would need to consider the steps happening in that submodule. I’m just going to use dummy operation names for illustration:
    I. submodule.op_1
    II. submodule.op_2
Apply the clamp operation

So even if we point at this one line, the question then is: “For which step do we want to extract the output?”.
FX is a core PyTorch toolkit that (oversimplifying) does the unravelling I just mentioned. It does something called “symbolic tracing”, which means the Python code is interpreted and stepped through, operation-by-operation, using some dummy proxy for a real input. Introducing some nomenclature, each step as described above is considered a “node”, and consecutive nodes are connected to one another to form a “graph” (not unlike the common mathematical notion of a graph). Here are the “steps” above translated to this concept of a graph.
