class_docstr: RoBERTa encoder.
class_docstr_tok: ["RoBERTa","encoder","."]
code: def __init__(self, args, dictionary):
      super().__init__(args, dictionary)
      assert not self.args.untie_weights_roberta
  
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 ModelParallelRobertaEncoder object from inherited base classes: RobertaEncoder with example: obj = ModelParallelRobertaEncoder(args, dictionary)