class_docstr: T5 Finetuning model in the same format as MegatronGPTSFTModel 
class_docstr_tok: ["T5","Finetuning","model","in","the","same","format","as","MegatronGPTSFTModel"]
code: def __init__(self, cfg: DictConfig, trainer: Trainer):
      if not HAVE_APEX:
          raise ImportError(
              "Apex was not found. Please see the NeMo README for installation instructions: https://github.com/NVIDIA/NeMo#megatron-gpt."
          )
      super().__init__(cfg, trainer=trainer)
      self.val_metric = self.test_metric = None
      if hasattr(self.cfg.data, "validation_ds"):
          self.val_metric, self.val_metric_name = self.setup_metric(
              self.cfg.data.validation_ds
          )
          self.val_metric = (
              torch.nn.ModuleList(self.val_metric)
              if self.val_metric is not None
              else None
          )
      if hasattr(self.cfg.data, "test_ds"):
          self.test_metric, self.test_metric_name = self.setup_metric(
              self.cfg.data.test_ds
          )
          self.test_metric = (
              torch.nn.ModuleList(self.test_metric)
              if self.test_metric is not None
              else None
          )
  
imports: import itertools
  import json
  from typing import Dict, List
  import torch
  from omegaconf import DictConfig, ListConfig
  from pytorch_lightning.trainer.trainer import Trainer
  from nemo.collections.common.data import ConcatMapDataset
  from nemo.collections.common.metrics import MetricStringToTorchMetric
  from nemo.collections.common.metrics.classification_accuracy import ExactStringPerCategoryMatchMetric
  from nemo.collections.nlp.data.common.sequence_to_sequence_dataset import SequenceToSequenceDataset
  from nemo.collections.nlp.data.language_modeling.megatron.t5_sft_dataset import T5SFTDataset
  from nemo.collections.nlp.models.language_modeling.megatron_t5_model import MegatronT5Model, T5Sentinel
  from nemo.collections.nlp.modules.common.megatron.utils import get_iterator_k_split
  from nemo.collections.nlp.parts.mixins.nlp_adapter_mixins import NLPAdapterModelMixin
  from nemo.collections.nlp.parts.utils_funcs import get_last_rank
  from nemo.utils import AppState, logging
label_desc: Use image node_id 1 to create a new MegatronT5SFTModel object from inherited base classes: NLPAdapterModelMixin, MegatronT5Model with example: obj = MegatronT5SFTModel(cfg, trainer)