can be used.
forward(*x)
  Return type:
     *Tensor*

add(x, y)
  Return type:
     *Tensor*

add_scalar(x, y)
  Return type:
     *Tensor*

mul(x, y)
  Return type:
     *Tensor*

mul_scalar(x, y)
  Return type:
     *Tensor*

cat(x, dim=0)
  Return type:
     *Tensor*

add_relu(x, y)
  Return type:
     *Tensor*

torch.ao.ns._numeric_suite.prepare_model_with_stubs(float_module, q_module, module_swap_list, logger_cls)
Prepare the model by attaching the float module to its matching
   quantized module as the shadow if the float module type is in
   module_swap_list.
Example usage:
  prepare_model_with_stubs(float_model, q_model, module_swap_list, Logger)
  q_model(data)
  ob_dict = get_logger_dict(q_model)

Parameters:
      * float_module (Module) -- float module used to generate
        the q_module
  * **q_module** (*Module*) -- module quantized from float_module
