code: def fill_mask_with_multiple_masks(self, model, tokenizer):
      fill_masker = FillMaskPipeline(model=model, tokenizer=tokenizer)
  
      outputs = fill_masker(
          f"This is a {tokenizer.mask_token} {tokenizer.mask_token} {tokenizer.mask_token}",
          top_k=2,
      )
      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),
                  },
              ],
          ],
      )
  
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 16 for calling the FillMaskPipelineTests obj's underlying member method code with example usage: obj.fill_mask_with_multiple_masks(model, tokenizer) without return types