docstr: Initialize the config which is the model configuration and transformer_config
  which is the config for the `transformer` base model.
docstr_tok: ["Initialize","the","config","which","is","the","model","configuration","and","transformer_config","which","is","the","config","for","the","`","transformer","`","base","model","."]
code: def __init__(self, config: Config):
      """Initialize the config which is the model configuration and transformer_config
      which is the config for the `transformer` base model.
      """
      super().__init__(config)
      self.config = config
  
imports: import logging
  from abc import ABC, abstractmethod
  from dataclasses import asdict, dataclass, field
  from typing import Any, Dict, List, NamedTuple, Optional, Tuple, Type
  from mmf.common.registry import registry
  from mmf.models import BaseModel
  from mmf.modules.encoders import IdentityEncoder
  from mmf.utils.modeling import get_bert_configured_parameters
  from omegaconf import MISSING, OmegaConf
  from torch import nn, Tensor
label_desc: Use image node_id 1 to create a new BaseTransformer object from inherited base classes: BaseModel with example: obj = BaseTransformer(config)