code: def test_lcm_onestep(self):
      pipe = LatentConsistencyModelPipeline.from_pretrained(
          "SimianLuo/LCM_Dreamshaper_v7", safety_checker=None
      )
      pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
      pipe = pipe.to(torch_device)
      pipe.set_progress_bar_config(disable=None)
  
      inputs = self.get_inputs(torch_device)
      inputs["num_inference_steps"] = 1
      image = pipe(**inputs).images
      assert image.shape == (1, 512, 512, 3)
  
      image_slice = image[0, -3:, -3:, -1].flatten()
      expected_slice = np.array(
          [
              0.1025,
              0.0911,
              0.0984,
              0.0981,
              0.0901,
              0.0918,
              0.1055,
              0.0940,
              0.0730,
          ]
      )
      assert np.abs(image_slice - expected_slice).max() < 1e-3
  
imports: import gc
  import inspect
  import unittest
  import numpy
  import torch
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, LatentConsistencyModelPipeline, LCMScheduler, UNet2DConditionModel
  from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
  from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
  from ..test_pipelines_common import PipelineLatentTesterMixin, PipelineTesterMixin
label_desc: Use image node_id 3 for calling the LatentConsistencyModelPipelineSlowTests obj's underlying member method code with example usage: obj.test_lcm_onestep() without return types