code: def __init__(self, args, encoder):
      super().__init__(args, encoder)
  
      self.classification_heads = nn.ModuleDict()
  
imports: import logging
  import torch
  import torch.nn
  import torch.nn.functional
  from fairseq import utils
  from fairseq.model_parallel.models.transformer import ModelParallelTransformerEncoder
  from fairseq.models import register_model, register_model_architecture
  from fairseq.models.roberta import roberta_base_architecture, roberta_prenorm_architecture, RobertaEncoder, RobertaModel
  from fairseq.modules import LayerNorm
label_desc: Use image node_id 1 to create a new ModelParallelRobertaModel object from inherited base classes: RobertaModel with example: obj = ModelParallelRobertaModel(args, encoder)