code: def __init__(self, cfg: DictConfig, trainer: Trainer):
      super().__init__(cfg, trainer)
      self.adapter_name_keys = []
  
imports: import itertools
  from typing import Any
  import torch
  from omegaconf.dictconfig import DictConfig
  from omegaconf.omegaconf import open_dict
  from pytorch_lightning.trainer.trainer import Trainer
  from nemo.collections.common.parts.adapter_modules import LinearAdapterConfig
  from nemo.collections.nlp.models.language_modeling.megatron_t5_model import MegatronT5Model
  from nemo.collections.nlp.models.language_modeling.megatron_t5_prompt_learning_model import MegatronT5PromptLearningModel
  from nemo.collections.nlp.models.language_modeling.megatron_t5_sft_model import MegatronT5SFTModel
  from nemo.collections.nlp.modules.common import VirtualPromptStyle
  from nemo.collections.nlp.modules.common.megatron.adapters.parallel_adapters import AdapterName, InfusedAdapterConfig, LoraKQVAdapterConfig, LoraKVAdapterConfig, LoraQAdapterConfig, MLPInfusedAdapterConfig, ParallelLinearAdapterConfig
  from nemo.collections.nlp.parts.utils_funcs import get_last_rank
  from nemo.core.classes.mixins import adapter_mixins
  from nemo.utils import logging, model_utils
label_desc: Use image node_id 1 to create a new MegatronT5BaseAdapterModel object from inherited base classes: MegatronT5PromptLearningModel with example: obj = MegatronT5BaseAdapterModel(cfg, trainer)