in the model through qconfig_mapping
  # the following call will get the qconfig_mapping that works best for models
  # that target "fbgemm" backend
  qconfig_mapping = get_default_qconfig_mapping("fbgemm")

  # We can customize qconfig_mapping in different ways.
  # e.g. set the global qconfig, which means we will use the same qconfig for
  # all operators in the model, this can be overwritten by other settings
  # qconfig_mapping = QConfigMapping().set_global(qconfig)
  # e.g. quantize the linear submodule with a specific qconfig
  # qconfig_mapping = QConfigMapping().set_module_name("linear", qconfig)
  # e.g. quantize all nn.Linear modules with a specific qconfig
  # qconfig_mapping = QConfigMapping().set_object_type(torch.nn.Linear, qconfig)
  # for a more complete list, please see the docstring for :class:`torch.ao.quantization.QConfigMapping`
  # argument

  # example_inputs is a tuple of inputs, that is used to infer the type of the
