code: def get_dummy_train_state(
      dataloader: Optional[Iterable[object]] = None,
  ) -> State:
      return State(
          entry_point=EntryPoint.TRAIN,
          train_state=PhaseState(
              dataloader=dataloader or [1, 2, 3, 4],
              max_epochs=1,
              max_steps=1,
              max_steps_per_epoch=1,
          ),
          timer=None,
      )
  
imports: from typing import Iterable, Iterator, Optional, Tuple
  import torch
  from torch import nn, Tensor
  from torch.utils.data import DataLoader, Dataset, IterableDataset, TensorDataset
  from torchtnt.framework.auto_unit import AutoUnit
  from torchtnt.framework.state import EntryPoint, PhaseState, State
  from torchtnt.framework.unit import EvalUnit, PredictUnit, TrainUnit
  from torchtnt.utils.lr_scheduler import TLRScheduler
label_desc: Use image node_id 1 for calling a global function with example usage: get_dummy_train_state(dataloader) and returns: State