class_docstr: Mixin for TFPolicy that adds entropy coeff decay.
code: def __init__(self, entropy_coeff, entropy_coeff_schedule):
      self._entropy_coeff_schedule = None
      # Disable any scheduling behavior related to learning if Learner API is active.
      # Schedules are handled by Learner class.
      if entropy_coeff_schedule is None or (
          self.config.get("_enable_new_api_stack", False)
      ):
          self.entropy_coeff = get_variable(
              entropy_coeff,
              framework="tf",
              tf_name="entropy_coeff",
              trainable=False,
          )
      else:
          # Allows for custom schedule similar to lr_schedule format
          if isinstance(entropy_coeff_schedule, list):
              self._entropy_coeff_schedule = PiecewiseSchedule(
                  entropy_coeff_schedule,
                  outside_value=entropy_coeff_schedule[-1][-1],
                  framework=None,
              )
          else:
              # Implements previous version but enforces outside_value
              self._entropy_coeff_schedule = PiecewiseSchedule(
                  [[0, entropy_coeff], [entropy_coeff_schedule, 0.0]],
                  outside_value=0.0,
                  framework=None,
              )
  
          self.entropy_coeff = get_variable(
              self._entropy_coeff_schedule.value(0),
              framework="tf",
              tf_name="entropy_coeff",
              trainable=False,
          )
          if self.framework == "tf":
              self._entropy_coeff_placeholder = tf1.placeholder(
                  dtype=tf.float32, name="entropy_coeff"
              )
              self._entropy_coeff_update = self.entropy_coeff.assign(
                  self._entropy_coeff_placeholder, read_value=False
              )
  
imports: import logging
  from typing import Dict, List
  import numpy
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.policy.eager_tf_policy import EagerTFPolicy
  from ray.rllib.policy.eager_tf_policy_v2 import EagerTFPolicyV2
  from ray.rllib.policy.policy import Policy, PolicyState
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.policy.tf_policy import TFPolicy
  from ray.rllib.utils.annotations import DeveloperAPI, override
  from ray.rllib.utils.framework import get_variable, try_import_tf
  from ray.rllib.utils.schedules import PiecewiseSchedule
  from ray.rllib.utils.tf_utils import make_tf_callable
  from ray.rllib.utils.typing import AlgorithmConfigDict, LocalOptimizer, ModelGradients, TensorType
label_desc: Use image node_id 1 to create a new EntropyCoeffSchedule object  with example: obj = EntropyCoeffSchedule(entropy_coeff, entropy_coeff_schedule)