def test_simple_inference_with_text_denoiser_lora_unfused_torch_compile(self):
        """
        Tests a simple inference with lora attached to text encoder and unet, then unloads the lora weights
        and makes sure it works as expected
        """
        for scheduler_cls in self.scheduler_classes:
            components, text_lora_config, denoiser_lora_config = self.get_dummy_components(scheduler_cls)
            pipe = self.pipeline_class(**components)
            pipe = pipe.to(torch_device)
            pipe.set_progress_bar_config(disable=None)
            _, _, inputs = self.get_dummy_inputs(with_generator=False)

            pipe, _ = self.check_if_adapters_added_correctly(pipe, text_lora_config, denoiser_lora_config)

            pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
            pipe.text_encoder = torch.compile(pipe.text_encoder, mode="reduce-overhead", fullgraph=True)

            if self.has_two_text_encoders or self.has_three_text_encoders:
                pipe.text_encoder_2 = torch.compile(pipe.text_encoder_2, mode="reduce-overhead", fullgraph=True)

            # Just makes sure it works..
            _ = pipe(**inputs, generator=torch.manual_seed(0))[0]

        Tests a simple inference with lora attached to text encoder and unet, then unloads the lora weights
        and makes sure it works as expected
        
tests/lora/utils.py