code: def test_fill_mask(self):
      tokenizer = BigBirdTokenizer.from_pretrained(
          "google/bigbird-roberta-base"
      )
      model = BigBirdForMaskedLM.from_pretrained(
          "google/bigbird-roberta-base"
      )
      model.to(torch_device)
  
      input_ids = tokenizer(
          "The goal of life is [MASK] .", return_tensors="pt"
      ).input_ids.to(torch_device)
      logits = model(input_ids).logits
  
      # [MASK] is token at 6th position
      pred_token = tokenizer.decode(
          torch.argmax(logits[0, 6:7], axis=-1)
      )
      self.assertEqual(pred_token, "happiness")
  
imports: import unittest
  from transformers import BigBirdConfig, is_torch_available
  from transformers.models.auto import get_values
  from transformers.models.big_bird.tokenization_big_bird import BigBirdTokenizer
  from transformers.testing_utils import require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 8 for calling the BigBirdModelIntegrationTest obj's underlying member method code with example usage: obj.test_fill_mask() without return types