code: def __init__(self):
      super().__init__()
      self.conv = torch.nn.Conv2d(3, 5, 3)
      weight = torch.nn.Parameter(torch.ones(5, 5))
      self.weight1 = torch.nn.Parameter(torch.ones(5, 5))
      self.mymod = myMod(weight)
  
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 1 to create a new MyConvLinearModule object from inherited base classes: torch.nn with example: obj = MyConvLinearModule()