code: def __init__(
      self,
      pad_token_id=1,
      bos_token_id=0,
      eos_token_id=2,
      project_dim=512,
      pooler_fn="cls",
      learn_encoder=False,
      **kwargs,
  ):
      super().__init__(
          pad_token_id=pad_token_id,
          bos_token_id=bos_token_id,
          eos_token_id=eos_token_id,
          **kwargs,
      )
      self.project_dim = project_dim
      self.pooler_fn = pooler_fn
      self.learn_encoder = learn_encoder
  
file_path: stable-diffusion-webui/modules/xlmr_m18.py
imports: from transformers import BertPreTrainedModel, BertConfig
  import torch.nn
  import torch
  from transformers.models.xlm_roberta.configuration_xlm_roberta import XLMRobertaConfig
  from transformers import XLMRobertaModel, XLMRobertaTokenizer
  from typing import Optional
label_desc: Use image node_id 1 to create a new RobertaSeriesConfig object from inherited base classes: XLMRobertaConfig with example: obj = RobertaSeriesConfig(pad_token_id, bos_token_id, eos_token_id, project_dim, pooler_fn, learn_encoder)