class_docstr: Base class for distributed RL-style data collection from an environment.
  
  The EnvRunner API's core functionalities can be summarized as:
  - Gets configured via passing a AlgorithmConfig object to the constructor.
  Normally, subclasses of EnvRunner then construct their own environment (possibly
  vectorized) copies and RLModules/Policies and use the latter to step through the
  environment in order to collect training data.
  - Clients of EnvRunner can use the `sample()` method to collect data for training
  from the environment(s).
  - EnvRunner offers parallelism via creating n remote Ray Actors based on this class.
  Use `ray.remote([resources])(EnvRunner)` method to create the corresponding Ray
  remote class. Then instantiate n Actors using the Ray `[ctor].remote(...)` syntax.
  - EnvRunner clients can get information about the server/node on which the
  individual Actors are running.
docstr: Returns experiences (of any form) sampled from this EnvRunner.
  
  The exact nature and size of collected data are defined via the EnvRunner's
  config and may be overridden by the given arguments.
  
  Args:
      **kwargs: Forward compatibility kwargs.
  
  Returns:
      The collected experience in any form.
docstr_tok: ["Returns","experiences","(","of","any","form",")","sampled","from","this","EnvRunner",".","The","exact","nature","and","size","of","collected","data","are","defined","via","the","EnvRunner's","config","and","may","be","overridden","by","the","given","arguments",".","Args",":","*","*","kwargs",":","Forward","compatibility","kwargs",".","Returns",":","The","collected","experience","in","any","form","."]
code: def sample(self, **kwargs) -> Any:
      """Returns experiences (of any form) sampled from this EnvRunner.
  
      The exact nature and size of collected data are defined via the EnvRunner's
      config and may be overridden by the given arguments.
  
      Args:
          **kwargs: Forward compatibility kwargs.
  
      Returns:
          The collected experience in any form.
      """
  
file_path: ray/python/ray/rllib/env/env_runner.py
imports: import abc
  from typing import Any, Dict, TYPE_CHECKING
  from ray.rllib.utils.actor_manager import FaultAwareApply
  from ray.rllib.utils.annotations import ExperimentalAPI
  from ray.rllib.utils.framework import try_import_tf
label_desc: Use image node_id 3 for calling the EnvRunner obj's underlying member method code with example usage: obj.sample() without return types