code: def print_mdnrnn_losses(minibatch, model_index, losses) -> None:
      logger.info(
          f"{minibatch}-th minibatch {model_index}-th model: \n"
          f'loss={losses["loss"]}, bce={losses["bce"]}, '
          f'gmm={losses["gmm"]}, mse={losses["mse"]}\n'
      )
  
file_path: ReAgent/reagent/training/cem_trainer.py
imports: import logging
  from typing import List
  import reagent.core.types
  import torch.nn
  from reagent.core.parameters import CEMTrainerParameters
  from reagent.models.cem_planner import CEMPlannerNetwork
  from reagent.training.reagent_lightning_module import ReAgentLightningModule
  from reagent.training.world_model.mdnrnn_trainer import MDNRNNTrainer
label_desc: Use image node_id 1 for calling a global function with example usage: print_mdnrnn_losses(minibatch, model_index, losses) without return types