class_docstr: This class specifies the configurations for PaddleHub to finetune 
class_docstr_tok: ["This","class","specifies","the","configurations","for","PaddleHub","to","finetune"]
docstr: Construct finetune Config 
docstr_tok: ["Construct","finetune","Config"]
code: def __init__(
      self,
      log_interval: int = 10,
      eval_interval: int = 100,
      use_data_parallel: bool = True,
      save_ckpt_interval: int = None,
      use_cuda: bool = True,
      checkpoint_dir: str = None,
      num_epoch: int = 1,
      batch_size: int = 32,
      strategy: Callable = None,
  ):
      """Construct finetune Config"""
      self.log_interval = log_interval
      self.eval_interval = eval_interval
      self.save_ckpt_interval = save_ckpt_interval
      self.use_cuda = use_cuda
      self.num_epoch = num_epoch
      self.batch_size = batch_size
      self.use_data_parallel = use_data_parallel
  
      if checkpoint_dir is None:
          now = int(time.time())
          time_str = time.strftime("%Y%m%d%H%M%S", time.localtime(now))
          self.checkpoint_dir = "ckpt_" + time_str
      else:
          self.checkpoint_dir = checkpoint_dir
  
imports: import time
  from typing import Callable
label_desc: Use image node_id 1 to create a new RunConfig object from inherited base classes: object with example: obj = RunConfig(log_interval, eval_interval, use_data_parallel, save_ckpt_interval, use_cuda, checkpoint_dir, num_epoch, batch_size, strategy)