code: def to(self, *args, **kwargs):
      (
          device,
          dtype,
          non_blocking,
          convert_to_format,
      ) = torch._C._nn._parse_to(*args, **kwargs)
      if device is None:
          return super().to(*args, **kwargs)
      elif device.type == "xpu":
          if convert_to_format is not None and self.dim() in (4, 5):
              return super().to(
                  "cpu",
                  dtype,
                  non_blocking,
                  memory_format=convert_to_format,
              )
          return super().to("cpu", dtype, non_blocking)
      return super().to(*args, **kwargs)
  
file_path: BigDL/python/llm/src/bigdl/llm/transformers/embedding.py
imports: import torch
  from torch import Tensor
  from torch.nn import functional
  from torch.nn import Parameter
  from typing import Optional
label_desc: Use image node_id 1 for calling the CPUPinnedParam obj's underlying member method code with example usage: obj.to() and returns: super, super, super, super