code: def test_stable_diffusion_panorama_k_lms(self):
      pipe = StableDiffusionPanoramaPipeline.from_pretrained(
          "stabilityai/stable-diffusion-2-base", safety_checker=None
      )
      pipe.scheduler = LMSDiscreteScheduler.from_config(
          pipe.scheduler.config
      )
      pipe.unet.set_default_attn_processor()
      pipe.to(torch_device)
      pipe.set_progress_bar_config(disable=None)
      pipe.enable_attention_slicing()
  
      inputs = self.get_inputs()
      image = pipe(**inputs).images
      image_slice = image[0, -3:, -3:, -1].flatten()
      assert image.shape == (1, 512, 2048, 3)
  
      expected_slice = np.array(
          [
              [
                  0.0,
                  0.0,
                  0.0,
                  0.0,
                  0.0,
                  0.0,
                  0.0,
                  0.0,
                  0.0,
              ]
          ]
      )
  
      assert np.abs(expected_slice - image_slice).max() < 1e-2
  
imports: import gc
  import unittest
  import numpy
  import torch
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, DDIMScheduler, EulerAncestralDiscreteScheduler, LMSDiscreteScheduler, PNDMScheduler, StableDiffusionPanoramaPipeline, UNet2DConditionModel
  from diffusers.utils.testing_utils import enable_full_determinism, nightly, require_torch_gpu, skip_mps, 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 4 for calling the StableDiffusionPanoramaNightlyTests obj's underlying member method code with example usage: obj.test_stable_diffusion_panorama_k_lms() without return types