SsdParameter - SsdTensorHandle is a property

gistfile1.txt

class SsdParameter(torch.nn.Parameter):
    @staticmethod
    def __new__(
        cls: SsdParameter, data: torch.Tensor, shape: Tuple[int, ...], dtype: torch.dtype, requires_grad: bool = False
    ) -> SsdParameter:
        if data is None:
            data = torch.tensor([])
            return torch.Tensor._make_subclass(cls, data, requires_grad)
        if type(data).__name__ == 'Tensor':
            return torch.Tensor._make_subclass(cls, data, requires_grad)
        else:
            # The wrapping tensor is just a meta tensor, so it
            # doesn't hold any memory (meta tensor is generally the preferred type
            # of tensor you want to make a subclass from)...
            p = torch.Tensor._make_subclass(cls, data.to("meta"), requires_grad)
            # ...the real tensor is held as an element on the tensor.
            p.wrapped = SsdTensorHandle._make_subclass(cls, torch.empty(data.shape, dtype=data.dtype), data.requires_grad)
            return p

    @classmethod
    def __torch_dispatch__(cls, func, types, args=(), kwargs=None):
        def unwrap(e):
            return e.wrapped if hasattr(e, 'wrapped') else e.wrapped

        return func(*tree_map(unwrap, args), **tree_map(unwrap, kwargs if kwargs else {}))