class_docstr: base trainer class.
  contains methods for training, validation, and writing output.
class_docstr_tok: ["base","trainer","class",".","contains","methods","for","training",",","validation",",","and","writing","output","."]
docstr: entrance of the whole training process
          
docstr_tok: ["entrance","of","the","whole","training","process"]
code: def train(self):
      """entrance of the whole training process"""
      max_epoch = int(
          math.ceil(1.0 * self.max_iter / len(self.train_loader))
      )
      for epoch in tqdm.trange(
          self.epoch, max_epoch, desc="Train", ncols=80
      ):
          self.epoch = epoch
          time.sleep(
              2
          )  # Prevent possible deadlock during epoch transition
          self.train_epoch()
          if self.iteration >= self.max_iter:
              break
  
file_path: ml-neuman/trainers/base_trainer.py
imports: import os
  import math
  import abc
  import time
  import tqdm
  from trainers import tensorboard_helper
  from options import options
label_desc: Use image node_id 7 for calling the BaseTrainer obj's underlying member method code with example usage: obj.train() without return types