code: def __init__(self, tape):
      self.tape = tape
  
imports: import functools
  import logging
  import os
  import threading
  from typing import Dict, List, Optional, Tuple, Union
  import tree
  from ray.rllib.evaluation.episode import Episode
  from ray.rllib.models.catalog import ModelCatalog
  from ray.rllib.models.repeated_values import RepeatedValues
  from ray.rllib.policy.policy import Policy, PolicyState
  from ray.rllib.policy.rnn_sequencing import pad_batch_to_sequences_of_same_size
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils import add_mixins, force_list
  from ray.rllib.utils.annotations import override, DeveloperAPI
  from ray.rllib.utils.deprecation import DEPRECATED_VALUE, deprecation_warning
  from ray.rllib.utils.error import ERR_MSG_TF_POLICY_CANNOT_SAVE_KERAS_MODEL
  from ray.rllib.utils.framework import try_import_tf
  from ray.rllib.utils.metrics import DIFF_NUM_GRAD_UPDATES_VS_SAMPLER_POLICY, NUM_AGENT_STEPS_TRAINED, NUM_GRAD_UPDATES_LIFETIME
  from ray.rllib.utils.metrics.learner_info import LEARNER_STATS_KEY
  from ray.rllib.utils.numpy import convert_to_numpy
  from ray.rllib.utils.spaces.space_utils import normalize_action
  from ray.rllib.utils.tf_utils import get_gpu_devices
  from ray.rllib.utils.threading import with_lock
  from ray.rllib.utils.typing import LocalOptimizer, ModelGradients, TensorType, TensorStructType
  from ray.util.debug import log_once
label_desc: Use image node_id 1 to create a new _OptimizerWrapper object  with example: obj = _OptimizerWrapper(tape)