code: def test_without_std_share_network_output_values(
      self, output_dim, hidden_sizes
  ):
      model = GaussianMLPModel(
          output_dim=output_dim,
          hidden_sizes=hidden_sizes,
          init_std=2,
          std_share_network=False,
          adaptive_std=False,
          hidden_nonlinearity=None,
          hidden_w_init=tf.ones_initializer(),
          output_w_init=tf.ones_initializer(),
      )
      dist = model.build(self.input_var).dist
  
      mean, log_std = self.sess.run(
          [dist.loc, tf.math.log(dist.stddev())],
          feed_dict={self.input_var: self.obs},
      )
  
      expected_mean = np.full(
          [1, 1, output_dim], 5 * np.prod(hidden_sizes)
      )
      expected_log_std = np.full([1, 1, output_dim], np.log(2.0))
      assert np.array_equal(mean, expected_mean)
      assert np.allclose(log_std, expected_log_std)
  
imports: import pickle
  import numpy
  import pytest
  import tensorflow
  import tensorflow_probability
  from garage.tf.models import GaussianMLPModel
  from tests.fixtures import TfGraphTestCase
label_desc: Use image node_id 5 for calling the TestGaussianMLPModel obj's underlying member method code with example usage: obj.test_without_std_share_network_output_values(output_dim, hidden_sizes) without return types