code: def get_linear_packed_param_fp_weight(node):
      weight = node.inputsAt(0).node()
      if (
          weight.kind() != "aten::quantize_per_tensor"
          and weight.kind() != "aten::quantize_per_channel"
      ):
          raise ValueError("Quantized weight must be produced.")
      fp_weight = weight.inputsAt(0).node()
      assert (
          fp_weight.kind() == "prim::GetAttr"
      ), "Weight must be an attribute of the module."
      fp_weight_name = fp_weight.s("name")
      return fp_weight_name
  
imports: import torch
  import torch._C
  from torch.ao.quantization import default_dynamic_qconfig, per_channel_dynamic_qconfig
  from torch.ao.quantization.quantize_jit import prepare_dynamic_jit, convert_dynamic_jit, _prepare_ondevice_dynamic_jit, _quantize_ondevice_dynamic_jit
  from torch.testing._internal.common_utils import TestCase
  from torch.testing._internal.common_quantization import get_script_module, LinearAddModel
  from torch.jit.mobile import _load_for_lite_interpreter, LiteScriptModule
  from torch.testing import FileCheck
  from torch.utils import bundled_inputs
  import io
  from typing import Dict
label_desc: Use image node_id 6 for calling the OnDevicePTQUtils obj's underlying member method code with example usage: obj.get_linear_packed_param_fp_weight(node) and returns: fp_weight_name