code: def test_without_std_share_network_shapes(
      self, output_dim, hidden_sizes
  ):
      model = GaussianMLPModel(
          output_dim=output_dim,
          hidden_sizes=hidden_sizes,
          std_share_network=False,
          adaptive_std=False,
      )
      model.build(self.input_var)
      with tf.compat.v1.variable_scope(model.name, reuse=True):
          mean_output_weights = tf.compat.v1.get_variable(
              "dist_params/mean_network/output/kernel"
          )
          mean_output_bias = tf.compat.v1.get_variable(
              "dist_params/mean_network/output/bias"
          )
          log_std_output_weights = tf.compat.v1.get_variable(
              "dist_params/log_std_network/parameter"
          )
      assert mean_output_weights.shape[1] == output_dim
      assert mean_output_bias.shape == output_dim
      assert log_std_output_weights.shape == output_dim
  
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 6 for calling the TestGaussianMLPModel obj's underlying member method code with example usage: obj.test_without_std_share_network_shapes(output_dim, hidden_sizes) without return types