code: def setUp(self):
      super().setUp()
      self.init_mlmd()
  
      # We intentionally save a variable of each Examples/Model artifact so that
      # the tests are more readable.
      self.examples_1 = self.prepare_tfx_artifact(
          test_utils.Examples, properties={"span": 1, "version": 1}
      )
      self.examples_2 = self.prepare_tfx_artifact(
          test_utils.Examples, properties={"span": 2, "version": 1}
      )
      self.examples_3 = self.prepare_tfx_artifact(
          test_utils.Examples, properties={"span": 3, "version": 1}
      )
      self.examples_4 = self.prepare_tfx_artifact(
          test_utils.Examples, properties={"span": 4, "version": 1}
      )
      self.examples_5 = self.prepare_tfx_artifact(
          test_utils.Examples, properties={"span": 5, "version": 1}
      )
      self.examples_6 = self.prepare_tfx_artifact(
          test_utils.Examples, properties={"span": 6, "version": 1}
      )
      self.examples_7 = self.prepare_tfx_artifact(
          test_utils.Examples, properties={"span": 7, "version": 1}
      )
      self.examples_8 = self.prepare_tfx_artifact(
          test_utils.Examples, properties={"span": 8, "version": 1}
      )
      self.examples_9 = self.prepare_tfx_artifact(
          test_utils.Examples, properties={"span": 9, "version": 1}
      )
      self.examples_10 = self.prepare_tfx_artifact(
          test_utils.Examples, properties={"span": 10, "version": 1}
      )
      self.examples = [
          self.examples_1,
          self.examples_2,
          self.examples_3,
          self.examples_4,
          self.examples_5,
          self.examples_6,
          self.examples_7,
          self.examples_8,
          self.examples_9,
          self.examples_10,
      ]
  
      transform_graph = self.prepare_tfx_artifact(
          test_utils.TransformGraph
      )
  
      self.model_1 = self.prepare_tfx_artifact(test_utils.Model)
      self.model_2 = self.prepare_tfx_artifact(test_utils.Model)
      self.model_3 = self.prepare_tfx_artifact(test_utils.Model)
      self.model_4 = self.prepare_tfx_artifact(test_utils.Model)
      self.model_5 = self.prepare_tfx_artifact(test_utils.Model)
      self.models = [
          self.model_1,
          self.model_2,
          self.model_3,
          self.model_4,
          self.model_5,
      ]
  
      # Each Model will train on a rolling window of 2 Examples.
      for i, model in enumerate(self.models):
          self.train_on_examples(
              model, self.examples[i : i + 2], transform_graph
          )
  
imports: from typing import List, Optional
  import tensorflow
  from tfx import types
  from tfx.dsl.input_resolution.ops import ops
  from tfx.dsl.input_resolution.ops import ops_utils
  from tfx.dsl.input_resolution.ops import test_utils
  from tfx.orchestration.portable.input_resolution import exceptions
label_desc: Use image node_id 3 for calling the SpanDrivenEvaluatorInputsOpTest obj's underlying member method code with example usage: obj.setUp() without return types