code: def test_std_share_network_is_pickleable(
      self, mock_normal, output_dim, hidden_sizes
  ):
      mock_normal.return_value = 0.5
      input_var = tf.compat.v1.placeholder(
          tf.float32, shape=(None, 10, 10, 3)
      )
      model = GaussianCNNModel(
          input_dim=self.input_dim,
          filters=((3, (3, 3)), (6, (3, 3))),
          strides=[1, 1],
          padding="SAME",
          hidden_sizes=hidden_sizes,
          output_dim=output_dim,
          std_share_network=True,
      )
      outputs = model.build(input_var).outputs
  
      # get output bias
      with tf.compat.v1.variable_scope("GaussianCNNModel", reuse=True):
          bias = tf.compat.v1.get_variable(
              "dist_params/mean_std_network/output/bias"
          )
      # assign it to all ones
      bias.load(tf.ones_like(bias).eval())
  
      output1 = self.sess.run(
          outputs[:-1], feed_dict={input_var: self.obs}
      )
  
      h = pickle.dumps(model)
      with tf.compat.v1.Session(graph=tf.Graph()) as sess:
          input_var = tf.compat.v1.placeholder(
              tf.float32, shape=(None, 10, 10, 3)
          )
          model_pickled = pickle.loads(h)
          outputs = model_pickled.build(input_var).outputs
          output2 = sess.run(
              outputs[:-1], feed_dict={input_var: self.obs}
          )
  
          assert np.array_equal(output1, output2)
  
imports: import pickle
  from unittest import mock
  import numpy
  import pytest
  import tensorflow
  from garage.tf.models import GaussianCNNModel
  from tests.fixtures import TfGraphTestCase
label_desc: Use image node_id 8 for calling the TestGaussianCNNModel obj's underlying member method code with example usage: obj.test_std_share_network_is_pickleable(mock_normal, output_dim, hidden_sizes) without return types