VPG playing BipedalWalker-v3 from https://github.com/sgoodfriend/rl-algo-impls/tree/2067e21d62fff5db60168687e7d9e89019a8bfc0
f0ac49c
| import gym | |
| import numpy as np | |
| from gym.wrappers.monitoring.video_recorder import VideoRecorder | |
| from typing import Tuple, Union | |
| from rl_algo_impls.wrappers.vectorable_wrapper import VecotarableWrapper | |
| ObsType = Union[np.ndarray, dict] | |
| ActType = Union[int, float, np.ndarray, dict] | |
| class EpisodeRecordVideo(VecotarableWrapper): | |
| def __init__( | |
| self, | |
| env: gym.Env, | |
| video_path_prefix: str, | |
| step_increment: int = 1, | |
| video_step_interval: int = 1_000_000, | |
| max_video_length: int = 3600, | |
| ) -> None: | |
| super().__init__(env) | |
| self.video_path_prefix = video_path_prefix | |
| self.step_increment = step_increment | |
| self.video_step_interval = video_step_interval | |
| self.max_video_length = max_video_length | |
| self.total_steps = 0 | |
| self.next_record_video_step = 0 | |
| self.video_recorder = None | |
| self.recorded_frames = 0 | |
| def step(self, action: ActType) -> Tuple[ObsType, float, bool, dict]: | |
| obs, rew, done, info = self.env.step(action) | |
| self.total_steps += self.step_increment | |
| # Using first env to record episodes | |
| if self.video_recorder: | |
| self.video_recorder.capture_frame() | |
| self.recorded_frames += 1 | |
| if info.get("episode"): | |
| episode_info = { | |
| k: v.item() if hasattr(v, "item") else v | |
| for k, v in info["episode"].items() | |
| } | |
| self.video_recorder.metadata["episode"] = episode_info | |
| if self.recorded_frames > self.max_video_length: | |
| self._close_video_recorder() | |
| return obs, rew, done, info | |
| def reset(self, **kwargs) -> ObsType: | |
| obs = self.env.reset(**kwargs) | |
| if self.video_recorder: | |
| self._close_video_recorder() | |
| elif self.total_steps >= self.next_record_video_step: | |
| self._start_video_recorder() | |
| return obs | |
| def _start_video_recorder(self) -> None: | |
| self._close_video_recorder() | |
| video_path = f"{self.video_path_prefix}-{self.next_record_video_step}" | |
| self.video_recorder = VideoRecorder( | |
| self.env, | |
| base_path=video_path, | |
| metadata={"step": self.total_steps}, | |
| ) | |
| self.video_recorder.capture_frame() | |
| self.recorded_frames = 1 | |
| self.next_record_video_step += self.video_step_interval | |
| def _close_video_recorder(self) -> None: | |
| if self.video_recorder: | |
| self.video_recorder.close() | |
| self.video_recorder = None | |
| self.recorded_frames = 0 | |