code: def build_fc(
      self,
      input_dim: int,
      output_dim: int,
      q_noise: float,
      qn_block_size: int,
  ) -> Union[nn.Module, nn.Linear, nn.Embedding, nn.Conv2d]:
      return quant_noise(
          nn.Linear(input_dim, output_dim), q_noise, qn_block_size
      )
  
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 GraphormerGraphEncoderLayer obj's underlying member method code with example usage: obj.build_fc(input_dim, output_dim, q_noise, qn_block_size) and returns: quant_noise