class_docstr: A connector used to mean-std-filter observations.
  
  Incoming observations are filtered such that the output of this filter is on
  average zero and has a standard deviation of 1. This filtering is applied
  separately per element of the observation space.
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docstr: Creates a new object with same state as self.
  
  This is a legacy Filter method that we need to keep around for now
  
  Returns:
      A copy of self.
docstr_tok: ["Creates","a","new","object","with","same","state","as","self",".","This","is","a","legacy","Filter","method","that","we","need","to","keep","around","for","now","Returns",":","A","copy","of","self","."]
code: def copy(self) -> "Filter":
      """Creates a new object with same state as self.
  
      This is a legacy Filter method that we need to keep around for now
  
      Returns:
          A copy of self.
      """
      # inline this as soon as we deprecate ordinary filter with non-connector
      # env_runner
      return self.filter.copy()
  
imports: from typing import Any, List
  from gymnasium.spaces import Discrete, MultiDiscrete
  import numpy
  import tree
  from ray.rllib.connectors.agent.synced_filter import SyncedFilterAgentConnector
  from ray.rllib.connectors.connector import AgentConnector
  from ray.rllib.connectors.connector import ConnectorContext
  from ray.rllib.connectors.registry import register_connector
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils.filter import Filter
  from ray.rllib.utils.filter import MeanStdFilter, ConcurrentMeanStdFilter
  from ray.rllib.utils.spaces.space_utils import get_base_struct_from_space
  from ray.rllib.utils.typing import AgentConnectorDataType
  from ray.util.annotations import PublicAPI
  from ray.rllib.utils.filter import RunningStat
label_desc: Use image node_id 7 for calling the MeanStdObservationFilterAgentConnector obj's underlying member method code with example usage: obj.copy() and returns: self