Exemple #1
0
def load_demonstration(
    file_path: str,
) -> Tuple[BehaviorSpec, List[AgentInfoActionPairProto], int]:
    """
    Loads and parses a demonstration file.
    :param file_path: Location of demonstration file (.demo).
    :return: BrainParameter and list of AgentInfoActionPairProto containing demonstration data.
    """

    # First 32 bytes of file dedicated to meta-data.
    file_paths = get_demo_files(file_path)
    behavior_spec = None
    brain_param_proto = None
    info_action_pairs = []
    total_expected = 0
    for _file_path in file_paths:
        with open(_file_path, "rb") as fp:
            with hierarchical_timer("read_file"):
                data = fp.read()
            next_pos, pos, obs_decoded = 0, 0, 0
            while pos < len(data):
                next_pos, pos = _DecodeVarint32(data, pos)
                if obs_decoded == 0:
                    meta_data_proto = DemonstrationMetaProto()
                    meta_data_proto.ParseFromString(data[pos : pos + next_pos])
                    if (
                        meta_data_proto.api_version
                        not in SUPPORTED_DEMONSTRATION_VERSIONS
                    ):
                        raise RuntimeError(
                            f"Can't load Demonstration data from an unsupported version ({meta_data_proto.api_version})"
                        )
                    total_expected += meta_data_proto.number_steps
                    pos = INITIAL_POS
                if obs_decoded == 1:
                    brain_param_proto = BrainParametersProto()
                    brain_param_proto.ParseFromString(data[pos : pos + next_pos])
                    pos += next_pos
                if obs_decoded > 1:
                    agent_info_action = AgentInfoActionPairProto()
                    agent_info_action.ParseFromString(data[pos : pos + next_pos])
                    if behavior_spec is None:
                        behavior_spec = behavior_spec_from_proto(
                            brain_param_proto, agent_info_action.agent_info
                        )
                    info_action_pairs.append(agent_info_action)
                    if len(info_action_pairs) == total_expected:
                        break
                    pos += next_pos
                obs_decoded += 1
    if not behavior_spec:
        raise RuntimeError(
            f"No BrainParameters found in demonstration file at {file_path}."
        )
    return behavior_spec, info_action_pairs, total_expected
Exemple #2
0
def load_demonstration(
    file_path: str
) -> Tuple[BrainParameters, List[AgentInfoActionPairProto], int]:
    """
    Loads and parses a demonstration file.
    :param file_path: Location of demonstration file (.demo).
    :return: BrainParameter and list of AgentInfoActionPairProto containing demonstration data.
    """

    # First 32 bytes of file dedicated to meta-data.
    INITIAL_POS = 33
    file_paths = []
    if os.path.isdir(file_path):
        all_files = os.listdir(file_path)
        for _file in all_files:
            if _file.endswith(".demo"):
                file_paths.append(os.path.join(file_path, _file))
        if not all_files:
            raise ValueError("There are no '.demo' files in the provided directory.")
    elif os.path.isfile(file_path):
        file_paths.append(file_path)
        file_extension = pathlib.Path(file_path).suffix
        if file_extension != ".demo":
            raise ValueError(
                "The file is not a '.demo' file. Please provide a file with the "
                "correct extension."
            )
    else:
        raise FileNotFoundError(
            "The demonstration file or directory {} does not exist.".format(file_path)
        )

    brain_params = None
    brain_param_proto = None
    info_action_pairs = []
    total_expected = 0
    for _file_path in file_paths:
        with open(_file_path, "rb") as fp:
            with hierarchical_timer("read_file"):
                data = fp.read()
            next_pos, pos, obs_decoded = 0, 0, 0
            while pos < len(data):
                next_pos, pos = _DecodeVarint32(data, pos)
                if obs_decoded == 0:
                    meta_data_proto = DemonstrationMetaProto()
                    meta_data_proto.ParseFromString(data[pos : pos + next_pos])
                    total_expected += meta_data_proto.number_steps
                    pos = INITIAL_POS
                if obs_decoded == 1:
                    brain_param_proto = BrainParametersProto()
                    brain_param_proto.ParseFromString(data[pos : pos + next_pos])
                    pos += next_pos
                if obs_decoded > 1:
                    agent_info_action = AgentInfoActionPairProto()
                    agent_info_action.ParseFromString(data[pos : pos + next_pos])
                    if brain_params is None:
                        brain_params = BrainParameters.from_proto(
                            brain_param_proto, agent_info_action.agent_info
                        )
                    info_action_pairs.append(agent_info_action)
                    if len(info_action_pairs) == total_expected:
                        break
                    pos += next_pos
                obs_decoded += 1
    if not brain_params:
        raise RuntimeError(
            f"No BrainParameters found in demonstration file at {file_path}."
        )
    return brain_params, info_action_pairs, total_expected