code: def test_without_std_share_network_shapes(
      self, output_dim, hidden_dim
  ):
      model = GaussianGRUModel(
          output_dim=output_dim,
          hidden_dim=hidden_dim,
          std_share_network=False,
          hidden_nonlinearity=None,
          recurrent_nonlinearity=None,
          hidden_w_init=self.default_initializer,
          recurrent_w_init=self.default_initializer,
          output_w_init=self.default_initializer,
      )
      step_hidden_var = tf.compat.v1.placeholder(
          shape=(self.batch_size, hidden_dim),
          name="step_hidden",
          dtype=tf.float32,
      )
      model.build(self.input_var, self.step_input_var, step_hidden_var)
  
      # output layer is a tf.keras.layers.Dense object,
      # which cannot be access by tf.compat.v1.variable_scope.
      # A workaround is to access in tf.compat.v1.global_variables()
      for var in tf.compat.v1.global_variables():
          if "output_layer/kernel" in var.name:
              std_share_output_weights = var
          if "output_layer/bias" in var.name:
              std_share_output_bias = var
          if "log_std_param/parameter" in var.name:
              log_std_param = var
      assert std_share_output_weights.shape[1] == output_dim
      assert std_share_output_bias.shape == output_dim
      assert log_std_param.shape == output_dim
  
file_path: garage/tests/garage/tf/models/test_gaussian_gru_model.py
imports: import pickle
  from unittest import mock
  import numpy
  import pytest
  import tensorflow
  import tensorflow_probability
  from garage.tf.models import GaussianGRUModel
  from tests.fixtures import TfGraphTestCase
  from tests.helpers import recurrent_step_gru
label_desc: Use image node_id 6 for calling the TestGaussianGRUModel obj's underlying member method code with example usage: obj.test_without_std_share_network_shapes(output_dim, hidden_dim) without return types