code: def test_output_values(self, output_dim, hidden_dim):
      model = GRUModel(
          output_dim=output_dim,
          hidden_dim=hidden_dim,
          hidden_nonlinearity=None,
          recurrent_nonlinearity=None,
          hidden_w_init=tf.constant_initializer(1),
          recurrent_w_init=tf.constant_initializer(1),
          output_w_init=tf.constant_initializer(1),
      )
  
      step_hidden_var = tf.compat.v1.placeholder(
          shape=(self.batch_size, hidden_dim),
          name="step_hidden",
          dtype=tf.float32,
      )
  
      outputs = model.build(
          self.input_var, self.step_input_var, step_hidden_var
      ).outputs
      output = self.sess.run(
          outputs[0], feed_dict={self.input_var: self.obs_inputs}
      )
      expected_output = np.full(
          [self.batch_size, self.time_step, output_dim], hidden_dim * -2
      )
      assert np.array_equal(output, expected_output)
  
file_path: garage/tests/garage/tf/models/test_gru_model.py
imports: import pickle
  import numpy
  import pytest
  import tensorflow
  from garage.tf.models import GRUModel
  from tests.fixtures import TfGraphTestCase
label_desc: Use image node_id 2 for calling the TestGRUModel obj's underlying member method code with example usage: obj.test_output_values(output_dim, hidden_dim) without return types