It also looks like there is script::Module::dump() which will print something like this, you can toggle it to include the sections that are relevant to you:
  void dump(
      bool print_method_bodies,  // you probably want this to be `false` for a summary
      bool print_attr_values,
      bool print_param_values) const;

module __torch__.M {
  parameters {
  }
  attributes {
    training = True
  }
  methods {
    method forward {
      graph(%self : ClassType<M>,
            %x.1 : Tensor):
        %3 : Tensor = prim::CallMethod[name="other_fn"](%self, %x.1) # ../test.py:36:15
        return (%3)
  
    }
    method other_fn {
      graph(%self : ClassType<M>,
            %x.1 : Tensor):
        %4 : int = prim::Constant[value=1]()
        %3 : int = prim::Constant[value=10]() # ../test.py:33:19
        %5 : Tensor = aten::add(%x.1, %3, %4) # ../test.py:33:15
        return (%5)
  
    }
  }
  submodules {
  }
}