code: def __init__(self, device: torch.device):
      super().__init__()
      self.l = nn.Linear(100, 100, device=device)
      self.u1 = UnitModule(device)
      self.u2 = UnitModule(device)
      self.p = nn.Parameter(torch.randn((100, 100), device=device))
  
imports: from typing import Tuple
  import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new CompositeParamModel object from inherited base classes: nn with example: obj = CompositeParamModel(device)