def METHOD_NAME(self):
    """VERIFY THAT ALL CHECKPOINTS ARE SAVED AND CONTAIN ALL THE EXPECTED KEYS"""
    trainer, model = self.get_classification_trainer(self.experiment_names[5])
    params = self.training_params.copy()
    params["save_ckpt_epoch_list"] = [1]
    trainer.train(model=model, training_params=params, train_loader=classification_test_dataloader(), valid_loader=classification_test_dataloader())
    ckpt_filename = ["ckpt_best.pth", "ckpt_latest.pth", "ckpt_epoch_1.pth"]
    ckpt_paths = [os.path.join(trainer.checkpoints_dir_path, suf) for suf in ckpt_filename]
    for ckpt_path in ckpt_paths:
        ckpt = torch.load(ckpt_path)
        self.assertListEqual(["net", "acc", "epoch", "optimizer_state_dict", "scaler_state_dict"], list(ckpt.keys()))
    trainer._save_checkpoint()
    weights_only = torch.load(os.path.join(trainer.checkpoints_dir_path, "ckpt_latest_weights_only.pth"))
    self.assertListEqual(["net"], list(weights_only.keys()))