def get_model(model_checkpoint_path): checkpoint_dict = Trainer.load_checkpoint_from_path(model_checkpoint_path) model_state = checkpoint_dict["model_state_dict"] model = ResNet18(None) model.conv1 = nn.Conv2d(1, 64, kernel_size=7, stride=1, padding=3, bias=False) model.load_state_dict(model_state) return model
def test_load_checkpoint_from_path(ray_start_2_cpus, tmpdir): config = TestConfig() checkpoint_strategy = CheckpointStrategy(checkpoint_score_attribute="loss", checkpoint_score_order="min") def train_func_checkpoint(): train.save_checkpoint(loss=3) train.save_checkpoint(loss=7) trainer = Trainer(config, num_workers=2, logdir=tmpdir) trainer.start() trainer.run(train_func_checkpoint, checkpoint_strategy=checkpoint_strategy) assert trainer.best_checkpoint["loss"] == 3 assert (Trainer.load_checkpoint_from_path( trainer.best_checkpoint_path) == trainer.best_checkpoint)