code: def __init__(self, config):
      super().__init__(config)
  
      self.embeddings = RobertaEmbeddings(config)
      self.init_weights()
  
file_path: transformers/examples/research_projects/deebert/src/modeling_highway_roberta.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  from torch import nn
  from torch.nn import CrossEntropyLoss, MSELoss
  from transformers import RobertaConfig
  from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
  from transformers.models.roberta.modeling_roberta import ROBERTA_INPUTS_DOCSTRING, ROBERTA_START_DOCSTRING, RobertaEmbeddings
  from .modeling_highway_bert import BertPreTrainedModel, DeeBertModel, HighwayException, entropy
label_desc: Use image node_id 1 to create a new DeeRobertaModel object from inherited base classes: DeeBertModel with example: obj = DeeRobertaModel(config)