def save_checkpoint(self): save_checkpoint(checkpoint_dir=self.config.checkpoint_dir, current_epoch=self.current_epoch, global_step=self.current_step, best_score=self.best_score, exe=self.exe, main_program=self.main_program)
def save_checkpoint(self): model_saved_dir = os.path.join(self.config.checkpoint_dir, "step_%d" % self.current_step) logger.info("Saving model checkpoint to {}".format(model_saved_dir)) self.save_inference_model(dirname=model_saved_dir) save_checkpoint(checkpoint_dir=self.config.checkpoint_dir, current_epoch=self.current_epoch, global_step=self.current_step, best_score=self.best_score, exe=self.exe, main_program=self.main_program)
def save_checkpoint(self): """ save the program of the last step in training """ model_saved_dir = os.path.join(self.config.checkpoint_dir, "step_%d" % self.current_step) logger.info("Saving model checkpoint to {}".format(model_saved_dir)) # to resume traning by loading ckpt, it must be save program (save_persistables) fluid.io.save_persistables(self.exe, dirname=model_saved_dir, main_program=self.main_program) save_checkpoint(checkpoint_dir=self.config.checkpoint_dir, current_epoch=self.current_epoch, global_step=self.current_step, best_score=self.best_score, exe=self.exe, main_program=self.main_program)