code: def undo(self):
      self.Linear_forward = patches.undo(
          __name__, torch.nn.Linear, "forward"
      )
      self.Linear_load_state_dict = patches.undo(
          __name__, torch.nn.Linear, "_load_from_state_dict"
      )
      self.Conv2d_forward = patches.undo(
          __name__, torch.nn.Conv2d, "forward"
      )
      self.Conv2d_load_state_dict = patches.undo(
          __name__, torch.nn.Conv2d, "_load_from_state_dict"
      )
      self.GroupNorm_forward = patches.undo(
          __name__, torch.nn.GroupNorm, "forward"
      )
      self.GroupNorm_load_state_dict = patches.undo(
          __name__, torch.nn.GroupNorm, "_load_from_state_dict"
      )
      self.LayerNorm_forward = patches.undo(
          __name__, torch.nn.LayerNorm, "forward"
      )
      self.LayerNorm_load_state_dict = patches.undo(
          __name__, torch.nn.LayerNorm, "_load_from_state_dict"
      )
      self.MultiheadAttention_forward = patches.undo(
          __name__, torch.nn.MultiheadAttention, "forward"
      )
      self.MultiheadAttention_load_state_dict = patches.undo(
          __name__, torch.nn.MultiheadAttention, "_load_from_state_dict"
      )
  
imports: import torch
  import networks
  from modules import patches
label_desc: Use image node_id 2 for calling the LoraPatches obj's underlying member method code with example usage: obj.undo() without return types