Reward classifier and training (#528)
Co-authored-by: Daniel Ritchie <daniel@brainwavecollective.ai> Co-authored-by: resolver101757 <kelster101757@hotmail.com> Co-authored-by: Jannik Grothusen <56967823+J4nn1K@users.noreply.github.com> Co-authored-by: Remi <re.cadene@gmail.com> Co-authored-by: Michel Aractingi <michel.aractingi@huggingface.co>
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@@ -191,6 +191,7 @@ def record(
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single_task: str,
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pretrained_policy_name_or_path: str | None = None,
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policy_overrides: List[str] | None = None,
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assign_rewards: bool = False,
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fps: int | None = None,
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warmup_time_s: int | float = 2,
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episode_time_s: int | float = 10,
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@@ -214,6 +215,9 @@ def record(
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policy = None
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device = None
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use_amp = None
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extra_features = (
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{"next.reward": {"dtype": "int64", "shape": (1,), "names": None}} if assign_rewards else None
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)
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if single_task:
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task = single_task
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@@ -254,12 +258,12 @@ def record(
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use_videos=video,
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image_writer_processes=num_image_writer_processes,
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image_writer_threads=num_image_writer_threads_per_camera * len(robot.cameras),
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features=extra_features,
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)
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if not robot.is_connected:
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robot.connect()
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listener, events = init_keyboard_listener()
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listener, events = init_keyboard_listener(assign_rewards=assign_rewards)
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# Execute a few seconds without recording to:
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# 1. teleoperate the robot to move it in starting position if no policy provided,
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@@ -469,12 +473,12 @@ if __name__ == "__main__":
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default=1,
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help="Upload dataset to Hugging Face hub.",
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)
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parser_record.add_argument(
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"--tags",
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type=str,
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nargs="*",
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help="Add tags to your dataset on the hub.",
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)
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# parser_record.add_argument(
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# "--tags",
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# type=str,
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# nargs="*",
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# help="Add tags to your dataset on the hub.",
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# )
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parser_record.add_argument(
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"--num-image-writer-processes",
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type=int,
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@@ -517,6 +521,12 @@ if __name__ == "__main__":
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nargs="*",
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help="Any key=value arguments to override config values (use dots for.nested=overrides)",
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)
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parser_record.add_argument(
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"--assign-rewards",
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type=int,
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default=0,
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help="Enables the assignation of rewards to frames (by default no assignation). When enabled, assign a 0 reward to frames until the space bar is pressed which assign a 1 reward. Press the space bar a second time to assign a 0 reward. The reward assigned is reset to 0 when the episode ends.",
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)
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parser_replay = subparsers.add_parser("replay", parents=[base_parser])
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parser_replay.add_argument(
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