class_docstr: Dummy policy with constant probability distribution.
class_docstr_tok: ["Dummy","policy","with","constant","probability","distribution","."]
code: def _distribution(self, time_step, policy_state):
      action_spec = cast(
          tensor_spec.BoundedTensorSpec, self.action_spec
      )
      probs = tf.constant(
          0.2, shape=[action_spec.maximum - action_spec.minimum]
      )
      action_distribution = tf.nest.map_structure(
          lambda obs: tfp.distributions.Categorical(probs=probs),
          time_step.observation,
      )
      step = policy_step.PolicyStep(action_distribution)
      return step
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import cast
  from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.policies import tf_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.utils import common
  from tf_agents.utils import test_utils
label_desc: Use image node_id 2 for calling the TfEmitLogProbsPolicy obj's underlying member method code with example usage: obj._distribution(time_step, policy_state) and returns: step