code: def __init__(self, workers, maml_steps, metric_gen, use_meta_env):
      self.workers = workers
      self.maml_optimizer_steps = maml_steps
      self.metric_gen = metric_gen
      self.use_meta_env = use_meta_env
  
imports: import logging
  from typing import Optional, Type
  import numpy
  from ray.rllib.algorithms.algorithm import Algorithm
  from ray.rllib.algorithms.algorithm_config import AlgorithmConfig, NotProvided
  from ray.rllib.evaluation.metrics import collect_metrics, get_learner_stats
  from ray.rllib.evaluation.worker_set import WorkerSet
  from ray.rllib.execution.common import STEPS_SAMPLED_COUNTER, STEPS_TRAINED_COUNTER, STEPS_TRAINED_THIS_ITER_COUNTER, _get_shared_metrics
  from ray.rllib.execution.metric_ops import CollectMetrics
  from ray.rllib.policy.policy import Policy
  from ray.rllib.policy.sample_batch import concat_samples, convert_ma_batch_to_sample_batch
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.deprecation import DEPRECATED_VALUE
  from ray.rllib.utils.metrics.learner_info import LEARNER_INFO
  from ray.rllib.utils.sgd import standardized
  from ray.util.iter import LocalIterator, from_actors
label_desc: Use image node_id 1 to create a new MetaUpdate object  with example: obj = MetaUpdate(workers, maml_steps, metric_gen, use_meta_env)