class_docstr: MegatronGPTInfusedAdapterModel is a model that combines a base model (GPTModel) with a "Infused Adapter that can Inhibiting and Amplify Inner Activations", known as IA3.
  This class supports the addition of IA3 into a transformer based LM as described in Liu et al. (https://arxiv.org/pdf/2205.05638.pdf)
  
  Three adapter's are inserted into each Transformer layer in the base GPT Model. Each adapter is basically a vector that simply scales the key, value or ffn hidden representations.
  
  It is assumed that these set of adapters will then be trained for a specific task.
  Once trained, the adapter weights will be saved and can be re-loaded 
  and infused into the same GPT Model for inference. 
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code: def list_available_models(cls):
      pass
  
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 9 for calling the MegatronT5InfusedAdapterModel obj's underlying member method code with example usage: obj.list_available_models(cls) without return types