02ef279b852bad53771e02435d0caa0a64d17343,baseline/tf/classify/training/distributed.py,ClassifyTrainerDistributedTf,__init__,#ClassifyTrainerDistributedTf#Any#,36

Before Change

                                                             directory=checkpoint_dir,
                                                             max_to_keep=5)
        devices = ["/device:GPU:{}".format(i) for i in range(self.gpus)]
        self.strategy = tf.distribute.MirroredStrategy(devices)


    def _train(self, loader, steps=0, **kwargs):
        Train an epoch of data using either the input loader or using `tf.dataset`

After Change

                                                             max_to_keep=5)
        strategy_type = kwargs.get("strategy_type", "mirror")
        self.eval_device = kwargs.get("eval_device", "/device:GPU:0")
        if strategy_type == "tpu":
            self.eval_device = "/device:CPU:0"
            gpus = 0
        else:
            gpus = int(kwargs.get("gpus", 1))
        endpoint = kwargs.get("endpoint")
        self.strategy = create_distribute_strategy(strategy_type, gpus, endpoint)

    def reset_strategy_to_eval(self):

Instances