docstr: Test that the model builds using a config using either model_params or
  model_name and calls fx graph mode quantization apis
docstr_tok: ["Test","that","the","model","builds","using","a","config","using","either","model_params","or","model_name","and","calls","fx","graph","mode","quantization","apis"]
code: def test_quantize_model(self, config):
      """
      Test that the model builds using a config using either model_params or
      model_name and calls fx graph mode quantization apis
      """
      if get_torch_version() < [1, 13]:
          self.skipTest(
              "This test is using a new api of FX Graph Mode Quantization which is only available after 1.13"
          )
      import torch.ao.quantization as tq
      from torch.ao.quantization.quantize_fx import (
          convert_fx,
          prepare_fx,
      )
  
      model = build_model(config)
      assert isinstance(model, RegNet)
      model.eval()
      example_inputs = (torch.rand(1, 3, 3, 3),)
      model.stem = prepare_fx(
          model.stem, {"": tq.default_qconfig}, example_inputs
      )
      model.stem = convert_fx(model.stem)
  
imports: import copy
  import logging
  import unittest
  import torch
  import torch.nn
  from classy_vision.generic.util import get_torch_version
  from classy_vision.models import build_model, RegNet
  from parameterized import parameterized
label_desc: Use image node_id 2 for calling the TestRegNetModelBuild obj's underlying member method code with example usage: obj.test_quantize_model(config) without return types