code: def train_step(self, data, return_loss_list=False):
      if self.precision == "fp32":
          loss, loss_list = self.train_step_fp32(data)
      elif self.precision == "fp16":
          loss, loss_list = self.train_step_fp16(data)
      self.runner.update_lr(loss)
      self.model.clear_gradients()
      if return_loss_list:
          return loss, loss_list
      else:
          return loss
  
file_path: PaddleSeg/contrib/PanopticSeg/paddlepanseg/core/launcher.py
imports: import abc
  import paddle
label_desc: Use image node_id 2 for calling the AMPLauncher obj's underlying member method code with example usage: obj.train_step(data, return_loss_list) and returns: loss,  loss_list, loss