code: def testTarget(self):
      with self.test_session() as sess:
          # Target is projected KL between r_t + pcont_t atoms_t and
          # probabilities corresponding to logits_q_tm1 [ a_tm1 ].
          expected = np.array(
              [
                  [0.0, 0.0, 1.0],
                  [1 / 3, 1 / 3, 1 / 3],
                  [0.0, 0.0, 1.0],
                  [0.4, 0.6, 0.0],
                  [0.1, 0.5, 0.4],
              ]
          )
          self.assertAllClose(
              sess.run(self.qlearning.extra.target), expected, atol=1e-3
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow.compat.v1
  from trfl import dist_value_ops
label_desc: Use image node_id 4 for calling the CategoricalDistDoubleQLearningTest obj's underlying member method code with example usage: obj.testTarget() without return types