code: def __init__(
      self,
      *,
      name: str,
      mode: ModeState,
      data_loader: torch.utils.data.DataLoader,
      inner_iterations: int,
      state_modules: List[StateModule],
      is_track_time: bool,
      step: Callable[[any, "BatchIndex"], None],
  ):
      self.is_track_time = is_track_time
      self.mode = mode
      self.name = name
      self.step = step
      self.state_modules = state_modules
      self.__iterable = None
      self.__states = [sm.create_state() for sm in self.state_modules]
      self.inner_iterations = inner_iterations
      self.data_loader = data_loader
      self._batch_index = BatchIndex(
          len(self.data_loader), self.inner_iterations
      )
  
imports: from typing import Optional, Dict, List, Callable, Any
  import torch.optim
  import torch.optim
  import torch.utils.data
  import torch.utils.data
  from torch import nn
  import labml.utils.pytorch
  from labml import tracker, monit
  from labml.configs import option, meta_config
  from .device import DeviceConfigs
  from .metrics import StateModule
  from .training_loop import TrainingLoopConfigs
label_desc: Use image node_id 1 to create a new Trainer object  with example: obj = Trainer()