class_docstr: Dummy tf_policy with mismatched dtypes and a list action_spec.
class_docstr_tok: ["Dummy","tf_policy","with","mismatched","dtypes","and","a","list","action_spec","."]
code: def __init__(self):
      observation_spec = tensor_spec.TensorSpec([2, 2], tf.float32)
      time_step_spec = ts.time_step_spec(observation_spec)
      action_spec = [
          tensor_spec.BoundedTensorSpec([1], tf.int64, 0, 1),
          tensor_spec.BoundedTensorSpec([1], tf.int32, 0, 1),
      ]
      super(TFPolicyMismatchedDtypesListAction, self).__init__(
          time_step_spec, action_spec
      )
  
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 1 to create a new TFPolicyMismatchedDtypesListAction object from inherited base classes: tf_policy with example: obj = TFPolicyMismatchedDtypesListAction()