transformed_env_constructor

torchrl.trainers.helpers.transformed_env_constructor(cfg: DictConfig, video_tag: str = '', logger: Optional[Logger] = None, stats: Optional[dict] = None, norm_obs_only: bool = False, use_env_creator: bool = False, custom_env_maker: Optional[Callable] = None, custom_env: Optional[EnvBase] = None, return_transformed_envs: bool = True, action_dim_gsde: Optional[int] = None, state_dim_gsde: Optional[int] = None, batch_dims: Optional[int] = 0, obs_norm_state_dict: Optional[dict] = None) → Union[Callable, EnvCreator]

Returns an environment creator from an argparse.Namespace built with the appropriate parser constructor.

Parameters:

• cfg (DictConfig) – a DictConfig containing the arguments of the script.

• video_tag (str, optional) – video tag to be passed to the Logger object

• logger (Logger, optional) – logger associated with the script

• stats (dict, optional) – a dictionary containing the loc and scale for the ObservationNorm transform

• norm_obs_only (bool, optional) – If True and VecNorm is used, the reward won’t be normalized online. Default is False.

• use_env_creator (bool, optional) – wheter the EnvCreator class should be used. By using EnvCreator, one can make sure that running statistics will be put in shared memory and accessible for all workers when using a VecNorm transform. Default is True.

• custom_env_maker (callable, optional) – if your env maker is not part of torchrl env wrappers, a custom callable can be passed instead. In this case it will override the constructor retrieved from args.

• custom_env (EnvBase, optional) – if an existing environment needs to be transformed_in, it can be passed directly to this helper. custom_env_maker and custom_env are exclusive features.

• return_transformed_envs (bool, optional) – if True, a transformed_in environment is returned.

• action_dim_gsde (int, Optional) – if gSDE is used, this can present the action dim to initialize the noise. Make sure this is indicated in environment executed in parallel.

• state_dim_gsde – if gSDE is used, this can present the state dim to initialize the noise. Make sure this is indicated in environment executed in parallel.

• batch_dims (int, optional) – number of dimensions of a batch of data. If a single env is used, it should be 0 (default). If multiple envs are being transformed in parallel, it should be set to 1 (or the number of dims of the batch).

• obs_norm_state_dict (dict, optional) – the state_dict of the ObservationNorm transform to be loaded into the environment