code: def params_cls() -> Type[TrainerParams]:
      return TrainerParams
  
imports: import logging
  import os
  from typing import Type
  from tfaip.data.pipeline.datapipeline import RawDataPipeline
  from tfaip.data.pipeline.definitions import PipelineMode
  from tfaip.trainer.callbacks.logger_callback import LoggerCallback
  from tfaip.trainer.callbacks.tensor_board_callback import TensorBoardCallback
  from tfaip.trainer.callbacks.train_params_logger import TrainerCheckpointsCallback
  from tfaip.trainer.trainer import Trainer
  from tfaip.trainer.warmstart.warmstarter import WarmStarter
  from calamari_ocr.ocr import Codec, SavedCalamariModel
  from calamari_ocr.ocr.dataset.data import Data
  from calamari_ocr.ocr.dataset.imageprocessors.augmentation import AugmentationProcessorParams
  from calamari_ocr.ocr.model.params import ModelParams
  from calamari_ocr.ocr.training.params import TrainerParams
  from calamari_ocr.ocr.training.pipeline_params import CalamariTrainOnlyPipelineParams
  from calamari_ocr.ocr.training.warmstart import WarmStarterWithCodecAdaption
  from calamari_ocr.utils import checkpoint_path
label_desc: Use image node_id 1 for calling the Trainer obj's underlying member method code with example usage: obj.params_cls() and returns: TrainerParams