code: def __init__(self, in_features: int, out_features: int):
      super().__init__()
      self._weight = nn.Parameter(
          torch.randn(out_features, in_features)
      )
      self._bias = nn.Parameter(torch.randn(out_features))
  
file_path: opacus/opacus/tests/utils.py
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new CustomLinearModule object from inherited base classes: nn with example: obj = CustomLinearModule(in_features, out_features)