code: def _validate_no_observer_forward(self, model):
      quantize_forward_graph = model.quantize_forward.graph
      for n in quantize_forward_graph.nodes():
          if (n.kind() == "prim::CallMethod") and n.s(
              "name"
          ) == "forward":
              if OnDevicePTQUtils.is_value_type_observer(n.inputsAt(0)):
                  return False
      return True
  
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 3 for calling the TestOnDeviceDynamicPTQInsertQuantDequant obj's underlying member method code with example usage: obj._validate_no_observer_forward(model) and returns: True, False