code: def __init__(
      self,
      model=None,
      data_loader=None,
      train_times=1000,
      alpha=0.5,
      use_gpu=True,
      opt_method="sgd",
      save_steps=None,
      checkpoint_dir=None,
  ):
      self.work_threads = 8
      self.train_times = train_times
  
      self.opt_method = opt_method
      self.optimizer = None
      self.lr_decay = 0
      self.weight_decay = 0
      self.alpha = alpha
  
      self.model = model
      self.data_loader = data_loader
      self.use_gpu = use_gpu
      self.save_steps = save_steps
      self.checkpoint_dir = checkpoint_dir
  
imports: import torch
  import torch.nn
  from torch.autograd import Variable
  import torch.optim
  import os
  import time
  import sys
  import datetime
  import ctypes
  import json
  import numpy
  import copy
  from tqdm import tqdm
label_desc: Use image node_id 1 to create a new Trainer object from inherited base classes: object with example: obj = Trainer(model, data_loader, train_times, alpha, use_gpu, opt_method, save_steps, checkpoint_dir)