code: def __init__(self, config):
      super().__init__(config)
      self.bert = MMBertModel(config)
      self.videomlp = VideoTokenMLP(config)
      # we do not use `BertGenerationOnlyLMHead`
      # because we can reuse pretraining.
      self.cls = BertOnlyMLMHead(config)
      self.hidden_size = config.hidden_size
      self.init_weights()
  
file_path: fairseq/examples/MMPT/mmpt/models/mmfusionnlg.py
imports: import torch
  from torch.nn import functional
  from typing import Optional, Iterable
  from .mmfusion import MMFusion
  from .transformermodel import MMBertModel
  from ..modules import VideoTokenMLP
label_desc: Use image node_id 1 to create a new MMBertForNLG object from inherited base classes: BertPreTrainedModel with example: obj = MMBertForNLG(config)