code: def test_observe_multiple_dimensions(self):
      observer = action_metrics.ContinuousActionObserver()
      observer.observe_first(env=_FAKE_ENV, timestep=_TIMESTEP)
      observer.observe(
          env=_FAKE_ENV,
          timestep=_TIMESTEP,
          action=np.array([[1, 2], [3, 4]]),
      )
      np.testing.assert_equal(
          {
              "action[0, 0]_max": 1,
              "action[0, 0]_min": 1,
              "action[0, 0]_mean": 1,
              "action[0, 0]_p50": 1,
              "action[0, 1]_max": 2,
              "action[0, 1]_min": 2,
              "action[0, 1]_mean": 2,
              "action[0, 1]_p50": 2,
              "action[1, 0]_max": 3,
              "action[1, 0]_min": 3,
              "action[1, 0]_mean": 3,
              "action[1, 0]_p50": 3,
              "action[1, 1]_max": 4,
              "action[1, 1]_min": 4,
              "action[1, 1]_mean": 4,
              "action[1, 1]_p50": 4,
          },
          observer.get_metrics(),
      )
  
file_path: acme/acme/utils/observers/action_metrics_test.py
imports: from acme import specs
  from acme.testing import fakes
  from acme.utils.observers import action_metrics
  import dm_env
  import numpy
  from absl.testing import absltest
label_desc: Use image node_id 6 for calling the ActionMetricsTest obj's underlying member method code with example usage: obj.test_observe_multiple_dimensions() without return types