code: def from_pretrained(self, pretrained_mlp):
      self.user_embedding.weight.data.copy_(
          pretrained_mlp.user_embedding.weight
      )
      self.item_embedding.weight.data.copy_(
          pretrained_mlp.item_embedding.weight
      )
      for layer, pretrained_layer in zip(
          self.mlp_model, pretrained_mlp.mlp_model
      ):
          if isinstance(layer, nn.Linear) and isinstance(
              pretrained_layer, nn.Linear
          ):
              layer.weight.data.copy_(pretrained_layer.weight)
              layer.bias.data.copy_(pretrained_layer.bias)
      self.logit.weight.data.copy_(pretrained_mlp.logit.weight)
      self.logit.bias.data.copy_(pretrained_mlp.logit.bias)
  
imports: import torch
  import torch.nn
label_desc: Use image node_id 3 for calling the MLP obj's underlying member method code with example usage: obj.from_pretrained(pretrained_mlp) without return types