class_docstr: Test that model classes can predict.
class_docstr_tok: ["Test","that","model","classes","can","predict","."]
code: def test_bertmlm(self):
      # Run prediction to ensure no failure.
      model_path = "https://storage.googleapis.com/what-if-tool-resources/lit-models/bert-base-uncased.tar.gz"
      model = pretrained_lms.BertMLM(model_path)
      model_in = [{"text": "test text", "tokens": ["test", "[MASK]"]}]
      model_out = list(model.predict(model_in))
  
      # Sanity-check entries exist in output.
      self.assertLen(model_out, 1)
      self.assertIn("pred_tokens", model_out[0])
      self.assertIn("cls_emb", model_out[0])
  
imports: from absl.testing import absltest
  from lit_nlp.examples.models import pretrained_lms
label_desc: Use image node_id 1 for calling the PretrainedLmsIntTest obj's underlying member method code with example usage: obj.test_bertmlm() without return types