def test_linear_are_4bit(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 and the class type of the linear layers of the converted models
        """
        self.model_fp16.get_memory_footprint()
        self.model_4bit.get_memory_footprint()

        for name, module in self.model_4bit.named_modules():
            if isinstance(module, torch.nn.Linear):
                if name not in ["proj_out"]:
                    # 4-bit parameters are packed in uint8 variables
                    self.assertTrue(module.weight.dtype == torch.uint8)

        A simple test to check if the model conversion has been done correctly by checking on the
        memory footprint of the converted model and the class type of the linear layers of the converted models
        
tests/quantization/bnb/test_4bit.py