code: def forward(
      self, input_nodes: torch.Tensor, **unused
  ) -> torch.Tensor:
      input_nodes = self.classifier(input_nodes)
      input_nodes = input_nodes + self.lm_output_learned_bias
      return input_nodes
  
imports: import math
  from typing import Iterable, Iterator, List, Optional, Tuple, Union
  import torch
  import torch.nn
  from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
  from ...activations import ACT2FN
  from ...modeling_outputs import BaseModelOutputWithNoAttention, SequenceClassifierOutput
  from ...modeling_utils import PreTrainedModel
  from ...utils import logging
  from .configuration_graphormer import GraphormerConfig
label_desc: Use image node_id 2 for calling the GraphormerDecoderHead obj's underlying member method code with example usage: obj.forward(input_nodes) and returns: input_nodes