training/evaluation mode, if they are affected, e.g. "Dropout",
      "BatchNorm", etc.
  Parameters:
     **mode** (*bool*) -- whether to set training mode ("True") or
     evaluation mode ("False"). Default: "True".

  Returns:
     self

  Return type:
     Module

type(dst_type)
  Casts all parameters and buffers to "dst_type".

  Note:

    This method modifies the module in-place.

  Parameters:
     **dst_type** (*type** or **string*) -- the desired type

  Returns:
     self

  Return type:
     Module

xpu(device=None)
  Moves all model parameters and buffers to the XPU.

  This also makes associated parameters and buffers different
  objects. So it should be called before constructing optimizer if
  the module will live on XPU while being optimized.

  Note:

    This method modifies the module in-place.

  Parameters:
     **device** (*int**, **optional*) -- if specified, all
