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)
