Python LightningOptimizer.param_groups示例

示例#1

文件： test_lightning_optimizer.py 项目： oddeirikigland/pytorch-lightning

def test_state(tmpdir):
    model = torch.nn.Linear(3, 4)
    optimizer = torch.optim.Adam(model.parameters())
    lightning_optimizer = LightningOptimizer(optimizer)

    # test state
    assert optimizer.state == lightning_optimizer.state
    lightning_optimizer.state = optimizer.state
    assert optimizer.state == lightning_optimizer.state

    # test param_groups
    assert optimizer.param_groups == lightning_optimizer.param_groups
    lightning_optimizer.param_groups = optimizer.param_groups
    assert optimizer.param_groups == lightning_optimizer.param_groups

    # test defaults
    assert optimizer.defaults == lightning_optimizer.defaults
    lightning_optimizer.defaults = optimizer.defaults
    assert optimizer.defaults == lightning_optimizer.defaults

    assert isinstance(lightning_optimizer, LightningOptimizer)
    assert isinstance(lightning_optimizer, Adam)
    assert isinstance(lightning_optimizer, Optimizer)

    lightning_dict = {
        k: v
        for k, v in lightning_optimizer.__dict__.items()
        if k not in {"_optimizer", "_optimizer_idx", "_trainer"}
    }

    assert lightning_dict == optimizer.__dict__
    assert optimizer.state_dict() == lightning_optimizer.state_dict()
    assert optimizer.state == lightning_optimizer.state

示例#2

文件： test_lightning_optimizer.py 项目： tonywork/pytorch-lightning

def test_state(tmpdir):
    model = torch.nn.Linear(3, 4)
    optimizer = torch.optim.Adam(model.parameters())
    lightning_optimizer = LightningOptimizer(optimizer)

    # test state
    assert optimizer.state == lightning_optimizer.state
    lightning_optimizer.state = optimizer.state
    assert optimizer.state == lightning_optimizer.state

    # test param_groups
    assert optimizer.param_groups == lightning_optimizer.param_groups
    lightning_optimizer.param_groups = optimizer.param_groups
    assert optimizer.param_groups == lightning_optimizer.param_groups

    # test defaults
    assert optimizer.defaults == lightning_optimizer.defaults
    lightning_optimizer.defaults = optimizer.defaults
    assert optimizer.defaults == lightning_optimizer.defaults

    assert isinstance(lightning_optimizer, LightningOptimizer)
    assert isinstance(lightning_optimizer, Adam)
    assert isinstance(lightning_optimizer, Optimizer)
    lightning_dict = {}
    special_attrs = ["_accumulate_grad_batches", "_optimizer", "_optimizer_idx", "_support_closure",
                     "_trainer", "__getstate__", "__setstate__", "state_dict", "load_state_dict",
                     "zero_grad", "__setstate__", "add_param_group"]
    for k, v in lightning_optimizer.__dict__.items():
        if k not in special_attrs:
            lightning_dict[k] = v
    assert lightning_dict == optimizer.__dict__
    assert optimizer.state_dict() == lightning_optimizer.state_dict()
    assert optimizer.state == lightning_optimizer.state