code: def test_output_value(self):
      with tf.compat.v1.variable_scope("MLP", reuse=True):
          h1_w = tf.compat.v1.get_variable("mlp1/hidden_0/kernel")
          h1_b = tf.compat.v1.get_variable("mlp1/hidden_0/bias")
          h2_w = tf.compat.v1.get_variable("mlp1/hidden_1/kernel")
          h2_b = tf.compat.v1.get_variable("mlp1/hidden_1/bias")
          out_w = tf.compat.v1.get_variable("mlp1/output/kernel")
          out_b = tf.compat.v1.get_variable("mlp1/output/bias")
  
      mlp_output = self.sess.run(
          self.mlp_f, feed_dict={self._input: self.obs_input}
      )
  
      # First layer
      h2_in = tf.matmul(self._input, h1_w) + h1_b
      h2_in = self.hidden_nonlinearity(h2_in)
  
      # Second layer
      h3_in = tf.matmul(h2_in, h2_w) + h2_b
      h3_in = self.hidden_nonlinearity(h3_in)
  
      # Output layer
      h3_out = tf.matmul(h3_in, out_w) + out_b
      out = self.sess.run(
          h3_out, feed_dict={self._input: self.obs_input}
      )
  
      np.testing.assert_array_equal(out, mlp_output)
  
file_path: garage/tests/garage/tf/models/test_mlp.py
imports: import numpy
  import tensorflow
  from garage.tf.models.mlp import mlp
  from tests.fixtures import TfGraphTestCase
label_desc: Use image node_id 5 for calling the TestMLP obj's underlying member method code with example usage: obj.test_output_value() without return types