code: def run_pipeline_test(self, fill_masker, examples):
      tokenizer = fill_masker.tokenizer
      model = fill_masker.model
  
      outputs = fill_masker(
          f"This is a {tokenizer.mask_token}",
      )
      self.assertEqual(
          outputs,
          [
              {
                  "sequence": ANY(str),
                  "score": ANY(float),
                  "token": ANY(int),
                  "token_str": ANY(str),
              },
              {
                  "sequence": ANY(str),
                  "score": ANY(float),
                  "token": ANY(int),
                  "token_str": ANY(str),
              },
              {
                  "sequence": ANY(str),
                  "score": ANY(float),
                  "token": ANY(int),
                  "token_str": ANY(str),
              },
              {
                  "sequence": ANY(str),
                  "score": ANY(float),
                  "token": ANY(int),
                  "token_str": ANY(str),
              },
              {
                  "sequence": ANY(str),
                  "score": ANY(float),
                  "token": ANY(int),
                  "token_str": ANY(str),
              },
          ],
      )
  
      outputs = fill_masker([f"This is a {tokenizer.mask_token}"])
      self.assertEqual(
          outputs,
          [
              {
                  "sequence": ANY(str),
                  "score": ANY(float),
                  "token": ANY(int),
                  "token_str": ANY(str),
              },
              {
                  "sequence": ANY(str),
                  "score": ANY(float),
                  "token": ANY(int),
                  "token_str": ANY(str),
              },
              {
                  "sequence": ANY(str),
                  "score": ANY(float),
                  "token": ANY(int),
                  "token_str": ANY(str),
              },
              {
                  "sequence": ANY(str),
                  "score": ANY(float),
                  "token": ANY(int),
                  "token_str": ANY(str),
              },
              {
                  "sequence": ANY(str),
                  "score": ANY(float),
                  "token": ANY(int),
                  "token_str": ANY(str),
              },
          ],
      )
  
      outputs = fill_masker(
          [
              f"This is a {tokenizer.mask_token}",
              f"Another {tokenizer.mask_token} great test.",
          ]
      )
      self.assertEqual(
          outputs,
          [
              [
                  {
                      "sequence": ANY(str),
                      "score": ANY(float),
                      "token": ANY(int),
                      "token_str": ANY(str),
                  },
                  {
                      "sequence": ANY(str),
                      "score": ANY(float),
                      "token": ANY(int),
                      "token_str": ANY(str),
                  },
                  {
                      "sequence": ANY(str),
                      "score": ANY(float),
                      "token": ANY(int),
                      "token_str": ANY(str),
                  },
                  {
                      "sequence": ANY(str),
                      "score": ANY(float),
                      "token": ANY(int),
                      "token_str": ANY(str),
                  },
                  {
                      "sequence": ANY(str),
                      "score": ANY(float),
                      "token": ANY(int),
                      "token_str": ANY(str),
                  },
              ],
              [
                  {
                      "sequence": ANY(str),
                      "score": ANY(float),
                      "token": ANY(int),
                      "token_str": ANY(str),
                  },
                  {
                      "sequence": ANY(str),
                      "score": ANY(float),
                      "token": ANY(int),
                      "token_str": ANY(str),
                  },
                  {
                      "sequence": ANY(str),
                      "score": ANY(float),
                      "token": ANY(int),
                      "token_str": ANY(str),
                  },
                  {
                      "sequence": ANY(str),
                      "score": ANY(float),
                      "token": ANY(int),
                      "token_str": ANY(str),
                  },
                  {
                      "sequence": ANY(str),
                      "score": ANY(float),
                      "token": ANY(int),
                      "token_str": ANY(str),
                  },
              ],
          ],
      )
  
      with self.assertRaises(ValueError):
          fill_masker([None])
      # No mask_token is not supported
      with self.assertRaises(PipelineException):
          fill_masker("This is")
  
      self.run_test_top_k(model, tokenizer)
      self.run_test_targets(model, tokenizer)
      self.run_test_top_k_targets(model, tokenizer)
      self.fill_mask_with_duplicate_targets_and_top_k(model, tokenizer)
      self.fill_mask_with_multiple_masks(model, tokenizer)
  
imports: import gc
  import unittest
  from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
  from transformers.pipelines import PipelineException
  from transformers.testing_utils import backend_empty_cache, is_pipeline_test, is_torch_available, nested_simplify, require_tf, require_torch, require_torch_accelerator, slow, torch_device
  from .test_pipelines_common import ANY
label_desc: Use image node_id 11 for calling the FillMaskPipelineTests obj's underlying member method code with example usage: obj.run_pipeline_test(fill_masker, examples) without return types