code: def from_pretrained(cls, model_name, *args, **kwargs):
      model = super().from_pretrained(model_name, *args, **kwargs)
      config = load_pretrained_model(model_name)["full_config"]
      OmegaConf.set_struct(config, True)
      if model_name == "mmbt.hateful_memes.images" or kwargs.get(
          "interface"
      ):
          return MMBTGridHMInterface(model, config)
      return model
  
imports: import os
  from copy import deepcopy
  from dataclasses import dataclass
  from typing import Dict, Optional, Union
  import torch
  from mmf.common.registry import registry
  from mmf.models.base_model import BaseModel
  from mmf.models.interfaces.mmbt import MMBTGridHMInterface
  from mmf.modules.encoders import EncoderFactory, ImageEncoderFactory, ImageEncoderTypes, MultiModalEncoderBase, ResNet152ImageEncoder, TextEncoderFactory, TextEncoderTypes, TransformerEncoder
  from mmf.modules.hf_layers import replace_with_jit
  from mmf.utils.checkpoint import load_pretrained_model
  from mmf.utils.configuration import get_mmf_cache_dir
  from mmf.utils.modeling import get_optimizer_parameters_for_bert
  from omegaconf import DictConfig, II, OmegaConf
  from torch import nn, Tensor
label_desc: Use image node_id 4 for calling the MMBT obj's underlying member method code with example usage: obj.from_pretrained(cls, model_name) and returns: model, MMBTGridHMInterface