code: def test_auxiliary(self):
      obs_dim, action_dim, task_num, latent_dim = (2,), (2,), 2, 2
      env = GymEnv(DummyBoxEnv(obs_dim=obs_dim, action_dim=action_dim))
      embedding_spec = InOutSpec(
          input_space=akro.Box(
              low=np.zeros(task_num), high=np.ones(task_num)
          ),
          output_space=akro.Box(
              low=np.zeros(latent_dim), high=np.ones(latent_dim)
          ),
      )
      encoder = GaussianMLPEncoder(embedding_spec)
      policy = GaussianMLPTaskEmbeddingPolicy(
          env_spec=env.spec, encoder=encoder
      )
      obs_input = tf.compat.v1.placeholder(
          tf.float32, shape=(None, None, 2)
      )
      task_input = tf.compat.v1.placeholder(
          tf.float32, shape=(None, None, 2)
      )
      networks = policy.build(obs_input, task_input)
      dist = networks[0].dist
      encoder_dist = networks[1].dist
  
      assert (
          dist.loc.get_shape().as_list()[-1]
          == env.action_space.flat_dim
      )
      assert policy.encoder == encoder
      assert policy.latent_space.flat_dim == latent_dim
      assert policy.task_space.flat_dim == task_num
      assert (
          policy.augmented_observation_space.flat_dim
          == env.observation_space.flat_dim + task_num
      )
      assert encoder_dist.loc.get_shape().as_list()[-1] == latent_dim
  
imports: from itertools import chain
  import pickle
  from unittest import mock
  import akro
  import numpy
  import pytest
  import tensorflow
  from garage import InOutSpec
  from garage.envs import GymEnv
  from garage.tf.embeddings import GaussianMLPEncoder
  from garage.tf.policies import GaussianMLPTaskEmbeddingPolicy
  from tests.fixtures import TfGraphTestCase
  from tests.fixtures.envs.dummy import DummyBoxEnv
label_desc: Use image node_id 3 for calling the TestGaussianMLPTaskEmbeddingPolicy obj's underlying member method code with example usage: obj.test_auxiliary() without return types