class_docstr: _FakePalettizationTensorHook is the class to assist in using CPU when we only want to utilize a certain percentage
  of the GPU memory.
docstr: Method that initialises un-packing and retrieving values from CPU.
docstr_tok: ["Method","that","initialises","un-packing","and","retrieving","values","from","CPU","."]
code: def init_unpack(self, x: _torch.Tensor):
      """
      Method that initialises un-packing and retrieving values from CPU.
      """
      if isinstance(x, int):
          idx = x
  
          assert self.tensor_list[idx] is not None
          self.tensor_list[idx] = self.tensor_list[idx].to(
              self.device_list[idx], non_blocking=True
          )
          return self.tensor_list[idx]
  
      return x
  
file_path: coremltools/coremltools/optimize/torch/palettization/_fake_palettizer_tensor_hook.py
imports: import torch
  import torch.nn.functional
label_desc: Use image node_id 3 for calling the _FakePalettizationTensorHook obj's underlying member method code with example usage: obj.init_unpack(x) and returns: x, self