code: def is_pinned(self, tensor):
      if tensor.is_pinned(device=self.current_device_name()):
          return True
      else:
          for begin, end in self.aligned_tensors:
              if (
                  begin <= tensor.data_ptr()
                  and tensor.data_ptr() <= end
              ):
                  return True
      return False
  
imports: import torch
  from deepspeed.accelerator.abstract_accelerator import DeepSpeedAccelerator
  import intel_extension_for_pytorch
  import oneccl_bindings_for_pytorch
label_desc: Use image node_id 56 for calling the XPU_Accelerator obj's underlying member method code with example usage: obj.is_pinned(tensor) and returns: False, True, True