docstr: Collect experience by running `n_steps` in the environment.
  Note: if this is a `VecEnv`, the total number of steps will
  be `n_steps * n_envs`.
  
  :param env: (Union[gym.Env, VecEnv]) The environment to learn from
  :param model: (BaseRLModel) The model to learn
  :param n_steps: (int) The number of steps to run for each environment
docstr_tok: ["Collect","experience","by","running","`","n_steps","`","in","the","environment",".","Note",":","if","this","is","a","`","VecEnv","`",",","the","total","number","of","steps","will","be","`","n_steps","*","n_envs","`",".",":","param","env",":","(","Union","[","gym.Env",",","VecEnv","]",")","The","environment","to","learn","from",":","param","model",":","(","BaseRLModel",")","The","model","to","learn",":","param","n_steps",":","(","int",")","The","number","of","steps","to","run","for","each","environment"]
code: def __init__(
      self,
      *,
      env: Union[gym.Env, VecEnv],
      model: "BaseRLModel",
      n_steps: int,
  ):
      """
      Collect experience by running `n_steps` in the environment.
      Note: if this is a `VecEnv`, the total number of steps will
      be `n_steps * n_envs`.
  
      :param env: (Union[gym.Env, VecEnv]) The environment to learn from
      :param model: (BaseRLModel) The model to learn
      :param n_steps: (int) The number of steps to run for each environment
      """
      self.env = env
      self.model = model
      n_envs = env.num_envs
      self.batch_ob_shape = (
          n_envs * n_steps,
      ) + env.observation_space.shape
      self.obs = np.zeros(
          (n_envs,) + env.observation_space.shape,
          dtype=env.observation_space.dtype.name,
      )
      self.obs[:] = env.reset()
      self.n_steps = n_steps
      self.states = (
          model.initial_state
      )  # pytype: disable=attribute-error
      self.dones = [False for _ in range(n_envs)]
      self.callback = None  # type: Optional[BaseCallback]
      self.continue_training = True
      self.n_envs = n_envs
  
file_path: stable-baselines/stable_baselines/common/runners.py
imports: from abc import ABC, abstractmethod
  import typing
  from typing import Union, Optional, Any
  import gym
  import numpy
  from stable_baselines.common.callbacks import BaseCallback
  from stable_baselines.common.vec_env import VecEnv
label_desc: Use image node_id 1 to create a new AbstractEnvRunner object from inherited base classes: ABC with example: obj = AbstractEnvRunner()