code: def test_load_local(self):
      controlnet = ControlNetModel.from_pretrained(
          "lllyasviel/control_v11p_sd15_canny"
      )
      pipe_1 = StableDiffusionControlNetPipeline.from_pretrained(
          "runwayml/stable-diffusion-v1-5",
          safety_checker=None,
          controlnet=controlnet,
      )
  
      controlnet = ControlNetModel.from_single_file(
          "https://huggingface.co/lllyasviel/ControlNet-v1-1/blob/main/control_v11p_sd15_canny.pth"
      )
      pipe_2 = StableDiffusionControlNetPipeline.from_single_file(
          "https://huggingface.co/runwayml/stable-diffusion-v1-5/blob/main/v1-5-pruned-emaonly.safetensors",
          safety_checker=None,
          controlnet=controlnet,
      )
      pipes = [pipe_1, pipe_2]
      images = []
  
      for pipe in pipes:
          pipe.enable_model_cpu_offload()
          pipe.set_progress_bar_config(disable=None)
  
          generator = torch.Generator(device="cpu").manual_seed(0)
          prompt = "bird"
          image = load_image(
              "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/bird_canny.png"
          )
  
          output = pipe(
              prompt,
              image,
              generator=generator,
              output_type="np",
              num_inference_steps=3,
          )
          images.append(output.images[0])
  
          del pipe
          gc.collect()
          torch.cuda.empty_cache()
  
      assert np.abs(images[0] - images[1]).max() < 1e-3
  
imports: import gc
  import tempfile
  import traceback
  import unittest
  import numpy
  import torch
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, ControlNetModel, DDIMScheduler, EulerDiscreteScheduler, StableDiffusionControlNetPipeline, UNet2DConditionModel
  from diffusers.pipelines.controlnet.pipeline_controlnet import MultiControlNetModel
  from diffusers.utils.import_utils import is_xformers_available
  from diffusers.utils.testing_utils import enable_full_determinism, load_image, load_numpy, require_python39_or_higher, require_torch_2, require_torch_gpu, run_test_in_subprocess, slow, torch_device
  from diffusers.utils.torch_utils import randn_tensor
  from ..pipeline_params import IMAGE_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
  from ..test_pipelines_common import PipelineKarrasSchedulerTesterMixin, PipelineLatentTesterMixin, PipelineTesterMixin
label_desc: Use image node_id 15 for calling the ControlNetPipelineSlowTests obj's underlying member method code with example usage: obj.test_load_local() without return types