code: def test_get_latent(self):
      obs_dim, action_dim, task_num, latent_dim = (2,), (2,), 5, 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
      )
  
      task_id = 3
      task_onehot = np.zeros(task_num)
      task_onehot[task_id] = 1
      latent, latent_info = policy.get_latent(task_onehot)
      assert latent.shape == (latent_dim,)
      assert latent_info["mean"].shape == (latent_dim,)
      assert latent_info["log_std"].shape == (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 2 for calling the TestGaussianMLPTaskEmbeddingPolicy obj's underlying member method code with example usage: obj.test_get_latent() without return types