code: def run_safety_checker(self, image: np.ndarray):
      if self.safety_checker is None:
          has_nsfw_concept = None
      else:
          feature_extractor_input = self.image_processor.numpy_to_pil(
              image
          )
          safety_checker_input = self.feature_extractor(
              feature_extractor_input, return_tensors="np"
          ).pixel_values.astype(image.dtype)
          images, has_nsfw_concept = [], []
          for i in range(image.shape[0]):
              image_i, has_nsfw_concept_i = self.safety_checker(
                  clip_input=safety_checker_input[i : i + 1],
                  images=image[i : i + 1],
              )
              images.append(image_i)
              has_nsfw_concept.append(has_nsfw_concept_i[0])
          image = np.concatenate(images)
  
      return image, has_nsfw_concept
  
file_path: optimum/optimum/pipelines/diffusers/pipeline_stable_diffusion.py
imports: import inspect
  import logging
  from typing import Callable, List, Optional, Union
  import numpy
  import torch
  from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
  from .pipeline_utils import DiffusionPipelineMixin, rescale_noise_cfg
label_desc: Use image node_id 5 for calling the StableDiffusionPipelineMixin obj's underlying member method code with example usage: obj.run_safety_checker(image) and returns: image,  has_nsfw_concept