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| """Contains methods for step compatibility, from old-to-new and new-to-old API.""" | |
| from typing import Tuple, Union | |
| import numpy as np | |
| from gym.core import ObsType | |
| DoneStepType = Tuple[ | |
| Union[ObsType, np.ndarray], | |
| Union[float, np.ndarray], | |
| Union[bool, np.ndarray], | |
| Union[dict, list], | |
| ] | |
| TerminatedTruncatedStepType = Tuple[ | |
| Union[ObsType, np.ndarray], | |
| Union[float, np.ndarray], | |
| Union[bool, np.ndarray], | |
| Union[bool, np.ndarray], | |
| Union[dict, list], | |
| ] | |
| def convert_to_terminated_truncated_step_api( | |
| step_returns: Union[DoneStepType, TerminatedTruncatedStepType], is_vector_env=False | |
| ) -> TerminatedTruncatedStepType: | |
| """Function to transform step returns to new step API irrespective of input API. | |
| Args: | |
| step_returns (tuple): Items returned by step(). Can be (obs, rew, done, info) or (obs, rew, terminated, truncated, info) | |
| is_vector_env (bool): Whether the step_returns are from a vector environment | |
| """ | |
| if len(step_returns) == 5: | |
| return step_returns | |
| else: | |
| assert len(step_returns) == 4 | |
| observations, rewards, dones, infos = step_returns | |
| # Cases to handle - info single env / info vector env (list) / info vector env (dict) | |
| if is_vector_env is False: | |
| truncated = infos.pop("TimeLimit.truncated", False) | |
| return ( | |
| observations, | |
| rewards, | |
| dones and not truncated, | |
| dones and truncated, | |
| infos, | |
| ) | |
| elif isinstance(infos, list): | |
| truncated = np.array( | |
| [info.pop("TimeLimit.truncated", False) for info in infos] | |
| ) | |
| return ( | |
| observations, | |
| rewards, | |
| np.logical_and(dones, np.logical_not(truncated)), | |
| np.logical_and(dones, truncated), | |
| infos, | |
| ) | |
| elif isinstance(infos, dict): | |
| num_envs = len(dones) | |
| truncated = infos.pop("TimeLimit.truncated", np.zeros(num_envs, dtype=bool)) | |
| return ( | |
| observations, | |
| rewards, | |
| np.logical_and(dones, np.logical_not(truncated)), | |
| np.logical_and(dones, truncated), | |
| infos, | |
| ) | |
| else: | |
| raise TypeError( | |
| f"Unexpected value of infos, as is_vector_envs=False, expects `info` to be a list or dict, actual type: {type(infos)}" | |
| ) | |
| def convert_to_done_step_api( | |
| step_returns: Union[TerminatedTruncatedStepType, DoneStepType], | |
| is_vector_env: bool = False, | |
| ) -> DoneStepType: | |
| """Function to transform step returns to old step API irrespective of input API. | |
| Args: | |
| step_returns (tuple): Items returned by step(). Can be (obs, rew, done, info) or (obs, rew, terminated, truncated, info) | |
| is_vector_env (bool): Whether the step_returns are from a vector environment | |
| """ | |
| if len(step_returns) == 4: | |
| return step_returns | |
| else: | |
| assert len(step_returns) == 5 | |
| observations, rewards, terminated, truncated, infos = step_returns | |
| # Cases to handle - info single env / info vector env (list) / info vector env (dict) | |
| if is_vector_env is False: | |
| if truncated or terminated: | |
| infos["TimeLimit.truncated"] = truncated and not terminated | |
| return ( | |
| observations, | |
| rewards, | |
| terminated or truncated, | |
| infos, | |
| ) | |
| elif isinstance(infos, list): | |
| for info, env_truncated, env_terminated in zip( | |
| infos, truncated, terminated | |
| ): | |
| if env_truncated or env_terminated: | |
| info["TimeLimit.truncated"] = env_truncated and not env_terminated | |
| return ( | |
| observations, | |
| rewards, | |
| np.logical_or(terminated, truncated), | |
| infos, | |
| ) | |
| elif isinstance(infos, dict): | |
| if np.logical_or(np.any(truncated), np.any(terminated)): | |
| infos["TimeLimit.truncated"] = np.logical_and( | |
| truncated, np.logical_not(terminated) | |
| ) | |
| return ( | |
| observations, | |
| rewards, | |
| np.logical_or(terminated, truncated), | |
| infos, | |
| ) | |
| else: | |
| raise TypeError( | |
| f"Unexpected value of infos, as is_vector_envs=False, expects `info` to be a list or dict, actual type: {type(infos)}" | |
| ) | |
| def step_api_compatibility( | |
| step_returns: Union[TerminatedTruncatedStepType, DoneStepType], | |
| output_truncation_bool: bool = True, | |
| is_vector_env: bool = False, | |
| ) -> Union[TerminatedTruncatedStepType, DoneStepType]: | |
| """Function to transform step returns to the API specified by `output_truncation_bool` bool. | |
| Done (old) step API refers to step() method returning (observation, reward, done, info) | |
| Terminated Truncated (new) step API refers to step() method returning (observation, reward, terminated, truncated, info) | |
| (Refer to docs for details on the API change) | |
| Args: | |
| step_returns (tuple): Items returned by step(). Can be (obs, rew, done, info) or (obs, rew, terminated, truncated, info) | |
| output_truncation_bool (bool): Whether the output should return two booleans (new API) or one (old) (True by default) | |
| is_vector_env (bool): Whether the step_returns are from a vector environment | |
| Returns: | |
| step_returns (tuple): Depending on `output_truncation_bool` bool, it can return (obs, rew, done, info) or (obs, rew, terminated, truncated, info) | |
| Examples: | |
| This function can be used to ensure compatibility in step interfaces with conflicting API. Eg. if env is written in old API, | |
| wrapper is written in new API, and the final step output is desired to be in old API. | |
| >>> obs, rew, done, info = step_api_compatibility(env.step(action), output_truncation_bool=False) | |
| >>> obs, rew, terminated, truncated, info = step_api_compatibility(env.step(action), output_truncation_bool=True) | |
| >>> observations, rewards, dones, infos = step_api_compatibility(vec_env.step(action), is_vector_env=True) | |
| """ | |
| if output_truncation_bool: | |
| return convert_to_terminated_truncated_step_api(step_returns, is_vector_env) | |
| else: | |
| return convert_to_done_step_api(step_returns, is_vector_env) | |