code: def testMixturePolicyInconsistentSpecs(self):
      context_dim = 11
      observation_spec = tensor_spec.TensorSpec(
          [context_dim], tf.float32
      )
      time_step_spec = ts.time_step_spec(observation_spec)
      action_spec = tensor_spec.BoundedTensorSpec(
          shape=(), dtype=tf.int32, minimum=0, maximum=9, name="action"
      )
      sub_policies = [
          ConstantPolicy(action_spec, time_step_spec, i)
          for i in range(9)
      ]
      wrong_obs_spec = tensor_spec.TensorSpec(
          [context_dim + 1], tf.float32
      )
      wrong_time_step_spec = ts.time_step_spec(wrong_obs_spec)
      wrong_policy = ConstantPolicy(
          action_spec, wrong_time_step_spec, 9
      )
      sub_policies.append(wrong_policy)
      weights = [0, 0, 0.2, 0, 0, -0.3, 0, 0, 0.5, 0]
      dist = tfd.Categorical(probs=weights)
      with self.assertRaisesRegexp(
          AssertionError, "Inconsistent time step specs"
      ):
          mixture_policy.MixturePolicy(dist, sub_policies)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import tensorflow
  import tensorflow_probability
  from tf_agents.bandits.policies import mixture_policy
  from tf_agents.policies import policy_saver
  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 test_utils
label_desc: Use image node_id 1 for calling the MixturePolicyTest obj's underlying member method code with example usage: obj.testMixturePolicyInconsistentSpecs() without return types