code: def test_output_normalized(self, output_dim):
      model = CategoricalMLPModel(output_dim=output_dim)
      obs_ph = tf.compat.v1.placeholder(
          tf.float32, shape=(None, output_dim)
      )
      obs = np.ones((1, output_dim))
      dist = model.build(obs_ph).dist
      probs = tf.compat.v1.get_default_session().run(
          tf.reduce_sum(dist.probs), feed_dict={obs_ph: obs}
      )
      assert np.isclose(probs, 1.0)
  
file_path: garage/tests/garage/tf/models/test_categorical_mlp_model.py
imports: import pickle
  import numpy
  import pytest
  import tensorflow
  import tensorflow_probability
  from garage.tf.models import CategoricalMLPModel
  from tests.fixtures import TfGraphTestCase
label_desc: Use image node_id 3 for calling the TestCategoricalMLPModel obj's underlying member method code with example usage: obj.test_output_normalized(output_dim) without return types