code: def test_fp16_casting(self):
      pipe = pipeline(
          "fill-mask",
          model="hf-internal-testing/tiny-random-distilbert",
          device=torch_device,
          framework="pt",
      )
  
      # convert model to fp16
      pipe.model.half()
  
      response = pipe("Paris is the [MASK] of France.")
      # We actually don't care about the result, we just want to make sure
      # it works, meaning the float16 tensor got casted back to float32
      # for postprocessing.
      self.assertIsInstance(response, list)
  
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 4 for calling the FillMaskPipelineTests obj's underlying member method code with example usage: obj.test_fp16_casting() without return types