code: def forward(
      self,
      input_ids,
      dec_input,
      enc_mask,
      dec_mask,
      position_ids,
      taskname_ids,
      labels=None,
      inference=False,
  ):
      # Call forward on T5 model with preprocessed embeddings
      if self.autocast_dtype == torch.float32:
          output = self.frozen_model.enc_dec_model(
              enc_input_ids=input_ids,
              enc_attn_mask=enc_mask,
              dec_input_ids=dec_input,
              dec_attn_mask=dec_mask,
              token_type_ids=None,
              labels=labels,
              output_enc_hidden_only=False,
              enc_input=None,
          )
      else:
          with torch.autocast(
              device_type="cuda", dtype=self.autocast_dtype
          ):
              output = self.frozen_model.enc_dec_model(
                  enc_input_ids=input_ids,
                  enc_attn_mask=enc_mask,
                  dec_input_ids=dec_input,
                  dec_attn_mask=dec_mask,
                  token_type_ids=None,
                  labels=labels,
                  output_enc_hidden_only=False,
                  enc_input=None,
              )
  
      return output, None
  
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 2 for calling the MegatronT5BaseAdapterModel obj's underlying member method code with example usage: obj.forward(input_ids, dec_input, enc_mask, dec_mask, position_ids, taskname_ids, labels, inference) and returns: output,  None