code: def test_TransformObservations(self) -> None:
      # Test that this is an identity transform
      means = np.array([3.0, 4.0])
      metric_names = ["a", "b"]
      covariance = np.array([[1.0, 2.0], [3.0, 4.0]])
      parameters = {"x": 1.0, "y": "cat"}
      arm_name = "armmy"
      observation = Observation(
          features=ObservationFeatures(
              parameters=parameters
          ),  # pyre-ignore
          data=ObservationData(
              metric_names=metric_names,
              means=means,
              covariance=covariance,
          ),
          arm_name=arm_name,
      )
      t = Transform(None, [])
      obs1 = t.transform_observations([deepcopy(observation)])[0]
      obs2 = t.untransform_observations([deepcopy(obs1)])[0]
      for obs in [obs1, obs2]:
          self.assertTrue(np.array_equal(obs.data.means, means))
          self.assertTrue(
              np.array_equal(obs.data.covariance, covariance)
          )
          self.assertEqual(obs.data.metric_names, metric_names)
          self.assertEqual(obs.features.parameters, parameters)
          self.assertEqual(obs.arm_name, arm_name)
  
file_path: Ax/ax/modelbridge/transforms/tests/test_base_transform.py
imports: from copy import deepcopy
  from unittest.mock import MagicMock
  import numpy
  from ax.core.observation import Observation, ObservationData, ObservationFeatures
  from ax.modelbridge.transforms.base import Transform
  from ax.utils.common.testutils import TestCase
label_desc: Use image node_id 2 for calling the TransformsTest obj's underlying member method code with example usage: obj.test_TransformObservations() without return types