class_docstr: A Linear layer that can be used with LoRA.
code: def forward(
      self, hidden_states: torch.Tensor, scale: float = 1.0
  ) -> torch.Tensor:
      if self.lora_layer is None:
          out = super().forward(hidden_states)
          return out
      else:
          out = super().forward(hidden_states) + (
              scale * self.lora_layer(hidden_states)
          )
          return out
  
imports: from typing import Optional, Tuple, Union
  import torch
  import torch.nn.functional
  from torch import nn
  from ..utils import logging
  from ..utils.import_utils import is_transformers_available
label_desc: Use image node_id 5 for calling the LoRACompatibleLinear obj's underlying member method code with example usage: obj.forward(hidden_states, scale) and returns: out, out