code: def testEntropyLoss(self, probs, weights):
      probs = tf.convert_to_tensor(probs)
      distribution = tfp.distributions.Categorical(probs=probs)
      shape = probs.shape.as_list()
      action_spec = tensor_spec.TensorSpec(shape[2:-1], dtype=tf.int32)
      expected = tf.reduce_mean(
          -tf.reduce_mean(distribution.entropy()) * weights
      )
      actual = reinforce_agent._entropy_loss(
          distribution, action_spec, weights
      )
      self.assertAlmostEqual(
          self.evaluate(actual), self.evaluate(expected), places=4
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  from absl.testing.absltest import mock
  import tensorflow
  import tensorflow_probability
  from tf_agents.agents.reinforce import reinforce_agent
  from tf_agents.networks import actor_distribution_rnn_network
  from tf_agents.networks import network
  from tf_agents.networks import utils
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
  from tf_agents.utils import common
  from tf_agents.utils import nest_utils
label_desc: Use image node_id 10 for calling the ReinforceAgentTest obj's underlying member method code with example usage: obj.testEntropyLoss(probs, weights) without return types