optimizer.py 文件源码

def __init__(self, params, defaults):
        self.defaults = defaults

        if isinstance(params, Variable) or torch.is_tensor(params):
            raise TypeError("params argument given to the optimizer should be "
                            "an iterable of Variables or dicts, but got " +
                            torch.typename(params))

        self.state = defaultdict(dict)
        self.param_groups = []

        param_groups = list(params)
        if len(param_groups) == 0:
            raise ValueError("optimizer got an empty parameter list")
        if not isinstance(param_groups[0], dict):
            param_groups = [{'params': param_groups}]

        for param_group in param_groups:
            self.add_param_group(param_group)