class_docstr: Connector base class.
  
  A connector is a step of transformation, of either envrionment data before they
  get to a policy, or policy output before it is sent back to the environment.
  
  Connectors may be training-aware, for example, behave slightly differently
  during training and inference.
  
  All connectors are required to be serializable and implement to_state().
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docstr: De-serialize a JSON params back into a Connector.
  
  from_state is required, so that all Connectors are serializable.
  
  Args:
      ctx: Context for constructing this connector.
      params: Serialized states of the connector to be recovered.
  
  Returns:
      De-serialized connector.
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code: def from_state(
      self, ctx: ConnectorContext, params: Any
  ) -> "Connector":
      """De-serialize a JSON params back into a Connector.
  
      from_state is required, so that all Connectors are serializable.
  
      Args:
          ctx: Context for constructing this connector.
          params: Serialized states of the connector to be recovered.
  
      Returns:
          De-serialized connector.
      """
      # Must implement by each connector.
      return NotImplementedError
  
imports: import abc
  import logging
  from typing import TYPE_CHECKING, Any, Dict, List, Tuple, Union
  import gymnasium
  from ray.rllib.policy.view_requirement import ViewRequirement
  from ray.rllib.utils.typing import ActionConnectorDataType, AgentConnectorDataType, AlgorithmConfigDict, TensorType
  from ray.util.annotations import PublicAPI
label_desc: Use image node_id 6 for calling the Connector obj's underlying member method code with example usage: obj.from_state(ctx, params) and returns: NotImplementedError