code: def _build_logger(self, log_file):
      import os
  
      log_folder = os.path.split(log_file)[0]
      if not os.path.exists(log_file):
          os.makedirs(log_folder)
      self.logger = get_log(log_file)
  
imports: import numpy
  import torch
  import torch.optim
  from torch.utils.data import DataLoader
  from graph4nlp.pytorch.datasets.jobs import JobsDataset
  from graph4nlp.pytorch.models.graph2seq_loss import Graph2SeqLoss
  from graph4nlp.pytorch.modules.utils.copy_utils import prepare_ext_vocab
  from args import get_args
  from build_model import get_model
  from evaluation import ExpressionAccuracy
  from utils import get_log, wordid2str
label_desc: Use image node_id 3 for calling the Jobs obj's underlying member method code with example usage: obj._build_logger(log_file) without return types