docstr: Full training logic
docstr_tok: ["Full","training","logic"]
code: def train(self):
      """
      Full training logic
      """
      for epoch in range(self.start_epoch + 1, self.epochs + 1):
          self.epoch_result = self._train_epoch(epoch)
          self._on_epoch_finish()
      if paddle.distributed.get_rank() == 0 and self.visualdl_enable:
          self.writer.close()
      self._on_train_finish()
  
imports: import os
  import pathlib
  import shutil
  from pprint import pformat
  import anyconfig
  import paddle
  import numpy
  import random
  from paddle.jit import to_static
  from paddle.static import InputSpec
  from utils import setup_logger
label_desc: Use image node_id 3 for calling the BaseTrainer obj's underlying member method code with example usage: obj.train() without return types