code: def test_image_reproducibility(self, model_arch: str):
      pipeline = self.ORTMODEL_CLASS.from_pretrained(
          MODEL_NAMES[model_arch], export=True
      )
      inputs = _generate_inputs()
      height, width = 64, 32
      np.random.seed(0)
      ort_outputs_1 = pipeline(**inputs, height=height, width=width)
      np.random.seed(0)
      ort_outputs_2 = pipeline(**inputs, height=height, width=width)
      ort_outputs_3 = pipeline(**inputs, height=height, width=width)
      # Compare model outputs
      self.assertTrue(
          np.array_equal(
              ort_outputs_1.images[0], ort_outputs_2.images[0]
          )
      )
      self.assertFalse(
          np.array_equal(
              ort_outputs_1.images[0], ort_outputs_3.images[0]
          )
      )
  
imports: import random
  import unittest
  from typing import Dict
  import numpy
  import PIL
  import pytest
  import torch
  from diffusers import OnnxStableDiffusionImg2ImgPipeline, StableDiffusionPipeline, StableDiffusionXLPipeline
  from diffusers.utils import load_image
  from diffusers.utils.testing_utils import floats_tensor
  from packaging.version import Version, parse
  from parameterized import parameterized
  from transformers.testing_utils import require_torch_gpu
  from utils_onnxruntime_tests import MODEL_NAMES, SEED, ORTModelTestMixin
  from optimum.onnxruntime import ORTLatentConsistencyModelPipeline, ORTStableDiffusionImg2ImgPipeline, ORTStableDiffusionInpaintPipeline, ORTStableDiffusionPipeline, ORTStableDiffusionXLImg2ImgPipeline, ORTStableDiffusionXLPipeline
  from optimum.onnxruntime.modeling_diffusion import ORTModelTextEncoder, ORTModelUnet, ORTModelVaeDecoder, ORTModelVaeEncoder
  from optimum.pipelines.diffusers.pipeline_utils import VaeImageProcessor
  from optimum.utils.import_utils import _diffusers_version
  from optimum.utils.testing_utils import grid_parameters, require_diffusers, require_ort_rocm
label_desc: Use image node_id 2 for calling the ORTStableDiffusionPipelineTest obj's underlying member method code with example usage: obj.test_image_reproducibility(model_arch) without return types