class_docstr: addcmul function takes a at::Scalar which results in a special TSData containing a Scalar rather than a Tensor.
code: def forward(self, a, b, c):
      return torch.addcmul(a, b, c, value=5)
  
imports: import unittest
  from torch._lazy.ts_backend import init
  from torch._lazy import config
  from torch._lazy.extract_compiled_graph import extract_compiled_graph
  import torch
  from torch import nn
  import dis
  import inspect
  from torch import fx
  import re
  from contextlib import contextmanager
  import copy
label_desc: Use image node_id 1 for calling the ModuleAddcmul obj's underlying member method code with example usage: obj.forward(a, b, c) and returns: torch