code: def test_large_model_pt(self):
      pipe = pipeline("image-to-text", model="ydshieh/vit-gpt2-coco-en")
      image = "./tests/fixtures/tests_samples/COCO/000000039769.png"
  
      outputs = pipe(image)
      self.assertEqual(
          outputs,
          [
              {
                  "generated_text": "a cat laying on a blanket next to a cat laying on a bed "
              }
          ],
      )
  
      outputs = pipe([image, image])
      self.assertEqual(
          outputs,
          [
              [
                  {
                      "generated_text": "a cat laying on a blanket next to a cat laying on a bed "
                  }
              ],
              [
                  {
                      "generated_text": "a cat laying on a blanket next to a cat laying on a bed "
                  }
              ],
          ],
      )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/pipelines/test_pipelines_image_to_text.py
imports: import unittest
  from transformers import MODEL_FOR_VISION_2_SEQ_MAPPING, TF_MODEL_FOR_VISION_2_SEQ_MAPPING, is_vision_available
  from transformers.pipelines import pipeline
  from transformers.testing_utils import require_tf, require_torch, require_vision, slow
  from .test_pipelines_common import ANY, PipelineTestCaseMeta
label_desc: Use image node_id 5 for calling the ImageToTextPipelineTests obj's underlying member method code with example usage: obj.test_large_model_pt() without return types