docstr: A simple test to check if the model conversion has been done correctly by checking on the
  memory footprint of the converted model
docstr_tok: ["A","simple","test","to","check","if","the","model","conversion","has","been","done","correctly","by","checking","on","the","memory","footprint","of","the","converted","model"]
code: def test_memory_footprint(self):
      r"""
      A simple test to check if the model conversion has been done correctly by checking on the
      memory footprint of the converted model
      """
  
      mem_quantized = self.quantized_model.get_memory_footprint()
  
      self.assertAlmostEqual(
          self.mem_fp16 / mem_quantized,
          self.EXPECTED_RELATIVE_DIFFERENCE,
      )
  
imports: import tempfile
  import unittest
  import pytest
  from transformers import AutoModelForCausalLM, AutoTokenizer, GPTQConfig
  from transformers.testing_utils import is_torch_available, require_accelerate, require_auto_gptq, require_optimum, require_torch_gpu, require_torch_multi_gpu, slow
label_desc: Use image node_id 2 for calling the GPTQTest obj's underlying member method code with example usage: obj.test_memory_footprint() without return types