code: def _load(path, model, input_sample=None, inplace=False):
      status = PytorchIPEXPUModel._load_status(path)
      checkpoint_path = path / status["checkpoint"]
      state_dict = torch.load(checkpoint_path, map_location="xpu")
      model.eval()
      model.load_state_dict(state_dict)
      return PytorchIPEXPUModel(
          model,
          thread_num=status["thread_num"],
          precision=status["precision"],
          use_ipex=status["use_ipex"],
      )
  
file_path: BigDL/python/nano/src/bigdl/nano/deps/ipex/ipex_inference_xpu_model.py
imports: from bigdl.nano.pytorch.model import AcceleratedLightningModule
  import torch
  import intel_extension_for_pytorch
  from bigdl.nano.utils.pytorch import apply_data_to_xpu, apply_data_to_half
  from bigdl.nano.pytorch.context_manager import generate_context_manager
  from bigdl.nano.utils.common import invalidInputError
  import warnings
label_desc: Use image node_id 5 for calling the PytorchIPEXPUModel obj's underlying member method code with example usage: obj._load(path, model, input_sample, inplace) and returns: PytorchIPEXPUModel