code: def testTfxModel(self):
      input_spec = {"input_0": lit_types.Scalar()}
      output_spec = {
          "output_0": lit_types.MulticlassPreds(
              vocab=["0", "1"], parent="input_0"
          )
      }
      config = tfx_model.TFXModelConfig(
          self._path, input_spec, output_spec
      )
      lit_model = tfx_model.TFXModel(config)
      result = list(lit_model.predict([{"input_0": 0.5}]))
      self.assertLen(result, 1)
      result = result[0]
      self.assertListEqual(list(result.keys()), ["output_0"])
      self.assertLen(result["output_0"], 2)
      self.assertIsInstance(result["output_0"][0], float)
      self.assertIsInstance(result["output_0"][1], float)
      self.assertDictEqual(lit_model.input_spec(), input_spec)
      self.assertDictEqual(lit_model.output_spec(), output_spec)
  
file_path: lit/lit_nlp/components/tfx_model_test.py
imports: import tempfile
  from lit_nlp.api import types
  from lit_nlp.components import tfx_model
  import tensorflow
label_desc: Use image node_id 2 for calling the TfxModelTest obj's underlying member method code with example usage: obj.testTfxModel() without return types